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| Author | SHA1 | Date | |
|---|---|---|---|
 ClaudeandClaude Opus 4.6
|
77ded23aef |
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+3
-7
@@ -6,13 +6,9 @@
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# Get yours at: https://app.ximilar.com/
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XIMILAR_API_KEY=your-ximilar-api-key-here
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# Anthropic API Key (AI deck generation & coaching with Claude Opus)
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# Get yours at: https://console.anthropic.com/settings/keys
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ANTHROPIC_API_KEY=your-anthropic-api-key-here
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# Anthropic model for deck generation and coaching (Claude Opus recommended)
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ANTHROPIC_MODEL=claude-opus-4-20250514
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# Coach chat provider: "local" (Ollama) or "anthropic" (Claude API)
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COACH_PROVIDER=anthropic
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# Perplexity API Key (AI deck research & generation)
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# Get yours at: https://www.perplexity.ai/settings/api
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PPLX_API_KEY=your-perplexity-api-key-here
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# CORS allowed origins (comma-separated)
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# Default: http://localhost:5173,http://localhost:8080
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@@ -33,6 +33,26 @@ jobs:
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- name: Run tests
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run: pytest -v --tb=short tests/ || true
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frontend:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Set up Node.js
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uses: actions/setup-node@v4
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with:
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node-version: '20'
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- name: Build frontend
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working-directory: frontend
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run: |
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npm ci
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npm run build
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- name: Run frontend tests
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working-directory: frontend
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run: npx vitest run
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java-tests:
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runs-on: ubuntu-latest
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steps:
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@@ -1,180 +1,381 @@
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# Commander AI Lab
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A full-stack MTG Commander AI research platform. Simulate hundreds of games overnight, train ML models on the results, and let simulation data automatically shape the AI deck builder — all from a web UI or CLI.
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## What It Does
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| Layer | What it is |
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|---|---|
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| **Monte Carlo Engine** | Pure-Python headless sim — runs thousands of games in minutes, no JVM needed |
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| **Forge Engine** | Java/Forge rules-complete sim for ground-truth validation |
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| **Overnight Runner** | Unattended batch runner — runs sims, updates sim weights, trains neural net |
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| **ML Pipeline** | Outcome-weighted RL nudges card scoring weights; neural net trains on decision logs |
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| **Deck Builder** | 7-step LLM pipeline (EDHrec → Scryfall → Ollama) now injected with sim-learned insights |
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| **AI Coach** | LLM-powered coaching sessions (Anthropic/Ollama) with streaming support |
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| **Web UI** | React + FastAPI dashboard for decks, sims, training, and deck building |
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Headless batch simulation environment for 3-AI MTG Commander pods.
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Run 100+ games, analyze win rates, and stress-test your decks — all from a web UI or CLI.
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## Architecture
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```
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┌─────────────────────────────────────────────────────────────────┐
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│ Web UI (React/TypeScript — frontend/) │
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│ Deck Builder · Sim Dashboard · Training · Coach │
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└────────────────────────┬────────────────────────────────────────┘
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│ HTTP/REST + WebSocket
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┌────────────────────────┴────────────────────────────────────────┐
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│ FastAPI Server (lab_api.py / routes/ — port 8080) │
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│ /api/lab/* /api/ml/* /api/coach/* /api/deck-builder/* │
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└────────┬──────────────────┬──────────────────┬──────────────────┘
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│ │ │
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Java subprocess Python sim engine Ollama (local LLM)
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(Forge rules) (Monte Carlo) qwen2.5:7b + others
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│ │
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┌────────┴───────┐ ┌───────┴────────────────────────────────────┐
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│ Forge Engine │ │ src/commander_ai_lab/ │
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│ (rules- │ │ sim/ — engine, models, rules │
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│ complete) │ │ deck_builder/ — 7-step LLM pipeline │
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└────────────────┘ │ coach/ — streaming LLM coach │
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└────────────────────────────────────────────┘
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┌─────────────────────────────────────────────────────────────┐
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│ Web Browser (ai-lab.js + ai-lab.css) │
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│ Select decks → Start batch → Poll progress → View stats │
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└─────────────────────┬───────────────────────────────────────┘
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│ HTTP (REST)
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┌─────────────────────┴───────────────────────────────────────┐
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│ Python FastAPI Server (lab_api.py, port 8080) │
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│ /api/lab/start — spawn Java batch runner subprocess │
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│ /api/lab/status — poll progress (parses stdout) │
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│ /api/lab/result — return completed JSON results │
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│ /api/lab/decks — list decks from Forge user data │
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│ /api/lab/history— browse past batch runs │
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│ /api/lab/log — stream live console output │
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└─────────────────────┬───────────────────────────────────────┘
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│ subprocess (java -jar)
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┌─────────────────────┴───────────────────────────────────────┐
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│ Java CLI (LabCli.java + BatchRunner + MultiThreadRunner) │
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│ Parses Forge sim output → GameResult objects → JSON │
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└─────────────────────┬───────────────────────────────────────┘
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│ subprocess per game
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┌─────────────────────┴───────────────────────────────────────┐
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│ Card Forge Engine (forge-gui-desktop sim mode) │
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│ java -jar forge.jar sim -d "deck1" "deck2" "deck3" │
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│ -f commander -n 1 -q │
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└─────────────────────────────────────────────────────────────┘
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```
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## Quick Start (Windows)
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**Prerequisites:** Java 17+, Python 3.10+, Maven 3.8+, [Forge](https://github.com/Card-Forge/forge) built at `D:\ForgeCommander\forge-repo`
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### Prerequisites
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- **Java 17+** (`java -version`)
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- **Python 3.10+** (`python --version`)
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- **Maven 3.8+** (`mvn --version`)
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- **Forge repo** cloned and built at `D:\ForgeCommander\forge-repo`
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### 1. Build Forge (one-time)
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```powershell
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# 1. Build Forge (one-time)
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cd D:\ForgeCommander\forge-repo
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mvn package -pl forge-gui-desktop "-DskipTests" "-Drevision=2.0.12-SNAPSHOT" -am
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```
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# 2. Build Commander AI Lab
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### 2. Build Commander AI Lab
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```powershell
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cd D:\ForgeCommander\commander-ai-lab
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mvn package "-DskipTests"
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```
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This produces `target/commander-ai-lab-1.0.0-SNAPSHOT.jar` (shaded fat JAR).
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# 3. Install Python deps
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pip install -e .
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### 3. Install Python dependencies
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```powershell
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pip install fastapi uvicorn
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```
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# 4. Launch
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### 4. Launch the Web UI
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**Option A — One-click launcher:**
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```powershell
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.\start-lab.bat
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# → open http://localhost:8080
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```
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Edit the paths at the top of `start-lab.bat` if needed.
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## Overnight AFK Runner
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Runs batch sims unattended, then updates card weights and trains the neural net:
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**Option B — Manual launch:**
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||||
```powershell
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python overnight-run.py # default: 11.5h DeepSeek sims
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python overnight-run.py --batches 20 --games 50 # fixed batch count
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python overnight-run.py --no-update-weights # skip weight update
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python overnight-run.py --no-train # skip neural net training
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python lab_api.py `
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--forge-jar "D:\ForgeCommander\forge-repo\forge-gui-desktop\target\forge-gui-desktop-2.0.12-SNAPSHOT-jar-with-dependencies.jar" `
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--forge-dir "D:\ForgeCommander\forge-repo\forge-gui" `
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--port 8080
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```
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**What happens after sims complete:**
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1. `update_weights.py` — nudges `learned_weights.json` from decision logs (feeds deck builder)
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2. `/api/ml/train` — trains the neural net on the full decision dataset
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## Sim → Deck Builder Feedback Loop
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Simulation outcomes automatically improve deck recommendations:
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```
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Overnight sims → decisions_*.jsonl
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↓
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update_weights.py → learned_weights.json
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↓
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sim_insights.py → natural-language insight block
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↓
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Ollama prompts (suggest_cards + enforce_deck_ratios)
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↓
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Better card recommendations
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```
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When active, `BuildResult.sources_consulted` includes `"sim_weights"`. No-op until real sim data exists.
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## Deck Builder Pipeline
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The `POST /api/deck-builder/build` endpoint runs 7 steps:
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1. Resolve commander via Scryfall
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2. Fetch EDHrec recommendations
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3. Fetch Scryfall candidates by category (ramp, removal, draw, lands)
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4. Ollama suggests synergy/protection/wincon cards ← **sim insights injected here**
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5. Filter by color identity, collection, ban list
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6. Ollama enforces ratios (trim/expand to 99) ← **sim insights injected here**
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7. Assemble final deck
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## ML Pipeline
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Open `http://localhost:8080` — select 3 decks, set game count, click **Run AI Sims**.
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### 5. CLI-only usage (no web server)
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||||
```powershell
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# Update sim card weights from decision logs (runs automatically in overnight-run.py)
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python -m ml.scripts.update_weights --min-games 10 --lr 0.05 --dry-run
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cd D:\ForgeCommander\forge-repo\forge-gui
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# Reset weights to defaults
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python -m ml.scripts.update_weights --reset
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# Generate synthetic training data
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python ml/scripts/generate_synthetic_data.py
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java -jar "D:\ForgeCommander\commander-ai-lab\target\commander-ai-lab-1.0.0-SNAPSHOT.jar" `
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--forge-jar "..\forge-gui-desktop\target\forge-gui-desktop-2.0.12-SNAPSHOT-jar-with-dependencies.jar" `
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--forge-dir "." `
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--deck1 "Edgar Markov" `
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--deck2 "Grimgrin" `
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--deck3 "Xyris" `
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--games 100 `
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--threads 4 `
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--output results/batch-100.json
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||||
```
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||||
Learned weights are clamped to `[-20.0, 20.0]` and stored in `src/commander_ai_lab/sim/learned_weights.json`.
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## Scaling Tests
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||||
|
||||
## Python Simulator API
|
||||
|
||||
```python
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from commander_ai_lab.lab.experiments import build_deck, run_simulation
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deck = build_deck(["Sol Ring", "Cultivate", "Lightning Bolt"] + ["Forest"] * 36)
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stats = run_simulation(deck, num_games=100, name_a="My Deck")
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print(f"Win rate: {stats['win_rate']:.1%}, Avg turns: {stats['avg_turns']:.1f}")
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### Single-threaded baseline (10 games)
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||||
```powershell
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java -jar target\commander-ai-lab-1.0.0-SNAPSHOT.jar `
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--forge-jar "..." --forge-dir "..." `
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||||
--deck1 "Edgar Markov" --deck2 "Grimgrin" --deck3 "Xyris" `
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--games 10 --threads 1 --output results/baseline-10.json
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```
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|
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The Monte Carlo engine models: combat keywords (flying, trample, deathtouch, lifelink, menace, reach, haste), summoning sickness, tapped/untap state, commander zone, multiplayer attack targeting, and board wipes. It does **not** model the stack, instants, or continuous type-changing effects.
|
||||
### Multi-threaded (10 games, 2 threads)
|
||||
```powershell
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java -jar target\commander-ai-lab-1.0.0-SNAPSHOT.jar `
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--forge-jar "..." --forge-dir "..." `
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||||
--deck1 "Edgar Markov" --deck2 "Grimgrin" --deck3 "Xyris" `
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--games 10 --threads 2 --output results/mt-10-t2.json
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```
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### Scale to 100 games (4 threads)
|
||||
```powershell
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java -jar target\commander-ai-lab-1.0.0-SNAPSHOT.jar `
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--forge-jar "..." --forge-dir "..." `
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--deck1 "Edgar Markov" --deck2 "Grimgrin" --deck3 "Xyris" `
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--games 100 --threads 4 --output results/scale-100-t4.json
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```
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### Maximum throughput test (100 games, 8 threads)
|
||||
```powershell
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java -jar target\commander-ai-lab-1.0.0-SNAPSHOT.jar `
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--forge-jar "..." --forge-dir "..." `
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||||
--deck1 "Edgar Markov" --deck2 "Grimgrin" --deck3 "Xyris" `
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--games 100 --threads 8 --seed 42 --output results/scale-100-t8-seed42.json
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```
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|
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### Performance comparison script
|
||||
Run different thread counts and compare sims/sec:
|
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```powershell
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# Baseline: 1 thread
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java -jar target\commander-ai-lab-1.0.0-SNAPSHOT.jar --forge-jar "..." --forge-dir "..." --deck1 "Edgar Markov" --deck2 "Grimgrin" --deck3 "Xyris" --games 20 --threads 1 --seed 42 --output results/perf-t1.json
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# 2 threads
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java -jar target\commander-ai-lab-1.0.0-SNAPSHOT.jar --forge-jar "..." --forge-dir "..." --deck1 "Edgar Markov" --deck2 "Grimgrin" --deck3 "Xyris" --games 20 --threads 2 --seed 42 --output results/perf-t2.json
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|
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# 4 threads
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java -jar target\commander-ai-lab-1.0.0-SNAPSHOT.jar --forge-jar "..." --forge-dir "..." --deck1 "Edgar Markov" --deck2 "Grimgrin" --deck3 "Xyris" --games 20 --threads 4 --seed 42 --output results/perf-t4.json
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|
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# 8 threads
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java -jar target\commander-ai-lab-1.0.0-SNAPSHOT.jar --forge-jar "..." --forge-dir "..." --deck1 "Edgar Markov" --deck2 "Grimgrin" --deck3 "Xyris" --games 20 --threads 8 --seed 42 --output results/perf-t8.json
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```
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|
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Then compare the `simsPerSecond` values in each output JSON to see scaling behavior.
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|
||||
## API Reference
|
||||
|
||||
| Endpoint | Method | Description |
|
||||
|---|---|---|
|
||||
| `/api/lab/decks` | GET | List available Commander decks |
|
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| `/api/lab/start` | POST | Start Forge batch (returns batchId) |
|
||||
| `/api/lab/start-deepseek` | POST | Start Python/DeepSeek batch |
|
||||
| `/api/lab/status?batchId=X` | GET | Poll batch progress |
|
||||
| `/api/lab/result?batchId=X` | GET | Get completed batch JSON |
|
||||
| `/api/lab/history` | GET | List past batch runs |
|
||||
| `/api/ml/train` | POST | Start neural net training |
|
||||
| `/api/ml/train/status` | GET | Poll training progress |
|
||||
| `/api/coach/chat` | POST | LLM coaching session (streaming) |
|
||||
| `/api/deck-builder/build` | POST | Build a 99-card Commander deck |
|
||||
| `/api/lab/start` | POST | Start a batch run (returns batchId) |
|
||||
| `/api/lab/status?batchId=X` | GET | Poll progress for a running batch |
|
||||
| `/api/lab/result?batchId=X` | GET | Get completed batch result JSON |
|
||||
| `/api/lab/log?batchId=X` | GET | Get live log lines from running batch |
|
||||
| `/api/lab/history` | GET | List past batch result files |
|
||||
|
||||
### POST /api/lab/start
|
||||
```json
|
||||
{
|
||||
"decks": ["Edgar Markov", "Grimgrin", "Xyris"],
|
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"numGames": 100,
|
||||
"threads": 4,
|
||||
"seed": null,
|
||||
"clock": 120
|
||||
}
|
||||
```
|
||||
|
||||
### GET /api/lab/status response
|
||||
```json
|
||||
{
|
||||
"batchId": "abc123",
|
||||
"running": true,
|
||||
"completed": 42,
|
||||
"total": 100,
|
||||
"threads": 4,
|
||||
"elapsedMs": 156000,
|
||||
"error": null
|
||||
}
|
||||
```
|
||||
|
||||
## Python Simulator (Monte Carlo Engine)
|
||||
|
||||
A pure-Python deck simulator for rapid Monte Carlo analysis — no Forge JVM required.
|
||||
Ported from the [mtg-commander-lan](https://github.com/) Node.js simulator.
|
||||
|
||||
### Location
|
||||
|
||||
```
|
||||
src/commander_ai_lab/
|
||||
├── __init__.py
|
||||
├── sim/ # Core simulation engine
|
||||
│ ├── __init__.py # Public exports
|
||||
│ ├── models.py # Card, Player, SimState, GameResult, PlayerStats
|
||||
│ ├── engine.py # GameEngine — turn loop, combat (flying/trample/deathtouch/lifelink/menace/reach)
|
||||
│ └── rules.py # AI_DEFAULT_WEIGHTS, enrich_card(), score_card(), parse_decklist()
|
||||
└── lab/ # High-level experiment helpers
|
||||
├── __init__.py
|
||||
└── experiments.py # build_deck(), run_single_game(), run_simulation(), _cli_main()
|
||||
```
|
||||
|
||||
### Install as editable package
|
||||
|
||||
```powershell
|
||||
cd D:\ForgeCommander\commander-ai-lab
|
||||
pip install -e .
|
||||
```
|
||||
|
||||
This installs `commander_ai_lab` as an importable package and registers the `commander-sim` CLI command.
|
||||
|
||||
### Quick smoke test
|
||||
|
||||
```powershell
|
||||
python -m commander_ai_lab.lab.experiments
|
||||
```
|
||||
|
||||
Expected output — a 10-game Monte Carlo run of a sample "Korvold" deck:
|
||||
|
||||
```
|
||||
══════════════════════════════════════════
|
||||
Commander AI Lab — Experiment Runner
|
||||
══════════════════════════════════════════
|
||||
|
||||
--- Demo: Korvold Aristocrats (10 games) ---
|
||||
|
||||
Win rate: XX.X%
|
||||
Avg turns: XX.X
|
||||
Avg damage dealt: XX.X
|
||||
Avg spells cast: XX.X
|
||||
Avg creatures: XX.X
|
||||
Elapsed: 0.02s
|
||||
|
||||
Done.
|
||||
```
|
||||
|
||||
### Python API
|
||||
|
||||
```python
|
||||
from commander_ai_lab.sim.models import Card
|
||||
from commander_ai_lab.sim.engine import GameEngine
|
||||
from commander_ai_lab.lab.experiments import build_deck, run_simulation
|
||||
|
||||
# Build a deck from card names
|
||||
deck = build_deck(["Sol Ring", "Cultivate", "Lightning Bolt", "Forest"] + ["Forest"] * 36)
|
||||
|
||||
# Monte Carlo simulation (100 games)
|
||||
stats = run_simulation(deck, num_games=100, name_a="My Deck")
|
||||
print(f"Win rate: {stats['win_rate']:.1%}")
|
||||
print(f"Avg turns: {stats['avg_turns']:.1f}")
|
||||
```
|
||||
|
||||
Key functions:
|
||||
|
||||
| Function | Description |
|
||||
|---|---|
|
||||
| `build_deck(card_names)` | Create enriched `Card` list from names |
|
||||
| `build_deck_from_text(decklist)` | Parse `"1 Sol Ring\n37 Forest"` format |
|
||||
| `run_single_game(deck_a, deck_b)` | One game, returns winner/turns/stats |
|
||||
| `run_simulation(deck_a, deck_b, n)` | Monte Carlo over `n` games, aggregated stats |
|
||||
|
||||
### CLI entry point
|
||||
|
||||
After `pip install -e .`:
|
||||
|
||||
```powershell
|
||||
commander-sim
|
||||
```
|
||||
|
||||
Runs the same demo as `python -m commander_ai_lab.lab.experiments`.
|
||||
|
||||
### How the engine works
|
||||
|
||||
1. **Deck enrichment** — `enrich_card()` infers type, CMC, keywords, and power/toughness from card name heuristics when Scryfall data is unavailable.
|
||||
2. **AI scoring** — `score_card()` uses weighted categories (removal, ramp, draw, aggro, etc.) to pick the best play each turn.
|
||||
3. **Game loop** — Each turn: untap → draw → play lands → cast spells (AI scored) → combat (attack/block decisions) → end step. Full keyword support for flying, trample, deathtouch, lifelink, menace, and reach.
|
||||
4. **Monte Carlo** — `run_simulation()` runs N independent games and aggregates win rate, avg turns, damage dealt/received, spells cast, creatures played, removal used, ramp played, cards drawn, and max board size.
|
||||
|
||||
## Project Structure
|
||||
|
||||
```
|
||||
commander-ai-lab/
|
||||
├── overnight-run.py # AFK batch runner
|
||||
├── lab_api.py # Python FastAPI server (web UI backend)
|
||||
├── start-lab.bat # Windows one-click launcher
|
||||
├── lab_api.py # FastAPI server entry point
|
||||
├── frontend/ # React + TypeScript web UI
|
||||
├── ui/ # Legacy static HTML UI
|
||||
├── src/commander_ai_lab/
|
||||
│ ├── sim/ # Monte Carlo engine (engine, models, rules)
|
||||
│ ├── deck_builder/ # LLM deck builder pipeline
|
||||
│ │ ├── api/ # Scryfall, EDHrec, Ollama, sim_insights
|
||||
│ │ ├── core/ # Models, rules engine, assembler
|
||||
│ │ └── pipeline/ # build_deck.py (7-step orchestrator)
|
||||
│ └── coach/ # LLM coaching (Anthropic + Ollama)
|
||||
├── ml/
|
||||
│ ├── scripts/ # update_weights.py, ml_cli.py
|
||||
│ ├── training/ # Neural net trainer
|
||||
│ ├── encoder/ # Feature encoding
|
||||
│ └── models/ # Saved model checkpoints
|
||||
├── scanner/ # Card OCR pipeline
|
||||
├── logs/decisions/ # ML decision logs (gitignored)
|
||||
└── src/main/java/commanderailab/ # Java/Forge batch runner
|
||||
├── pom.xml # Maven build (Java 17, shaded JAR)
|
||||
├── pyproject.toml # Python package config (src/ layout)
|
||||
├── ui/
|
||||
│ ├── index.html # Web UI entry point
|
||||
│ ├── ai-lab.js # UI controller (deck selection, progress, results)
|
||||
│ ├── ai-lab.css # Styles (dark theme, responsive)
|
||||
│ ├── collection.html # Card collection manager
|
||||
│ ├── collection.js # Collection controller
|
||||
│ ├── collection.css # Collection styles
|
||||
│ ├── deckbuilder.html # Deck builder + EDH advisor
|
||||
│ ├── deckbuilder.js # Deck builder controller
|
||||
│ └── deckbuilder.css # Deck builder styles
|
||||
├── src/commander_ai_lab/ # Python simulator package
|
||||
│ ├── __init__.py
|
||||
│ ├── sim/ # Core engine (models, engine, rules)
|
||||
│ └── lab/ # Experiment helpers
|
||||
├── src/main/java/commanderailab/ # Java batch runner (Forge integration)
|
||||
│ ├── cli/LabCli.java # CLI entry point (picocli)
|
||||
│ ├── batch/
|
||||
│ │ ├── BatchRunner.java # Single-thread runner (parses Forge output)
|
||||
│ │ └── MultiThreadBatchRunner.java # Multi-thread runner (ExecutorService)
|
||||
│ ├── bridge/WebApiBridge.java # Java-side web API bridge
|
||||
│ ├── schema/
|
||||
│ │ ├── BatchResult.java # Data model POJOs
|
||||
│ │ └── JsonExporter.java # JSON serialization + validation
|
||||
│ ├── stats/StatsAggregator.java # Win rates, turn counts, breakdowns
|
||||
│ └── ai/
|
||||
│ ├── AiPolicy.java # Policy interface
|
||||
│ └── ForgeBuiltinPolicy.java # v1 Forge AI wrapper
|
||||
├── scanner/ # Card scanner (OCR pipeline)
|
||||
│ ├── __init__.py
|
||||
│ ├── ocr.py # Tesseract OCR wrapper
|
||||
│ ├── pipeline.py # Image preprocessing pipeline
|
||||
│ └── preprocess.py # Image preprocessing helpers
|
||||
├── docs/
|
||||
│ ├── PROJECT_VISION.md
|
||||
│ ├── batch-result-schema.json
|
||||
│ └── game-log-schema.json
|
||||
├── sample-decks/ # 3 sample .dck files
|
||||
├── precon-decks/ # Preconstructed decks + index
|
||||
├── results/ # Batch output JSON files (gitignored)
|
||||
└── src/test/java/ # Unit tests
|
||||
```
|
||||
|
||||
## Known Limitations
|
||||
## Output Format
|
||||
|
||||
- **Monte Carlo engine** — no stack, no instants, no continuous type changes (animated lands don't attack)
|
||||
- **Forge engine** — each game spawns a new JVM (~2-3s overhead), ~0.04 sims/sec single-threaded
|
||||
- **Forge winner life total** not captured (quiet mode only reports losers)
|
||||
- **Deck builder** — Ollama suggestions are only as good as the local model; `qwen2.5:7b` works well
|
||||
Each batch run produces JSON conforming to `docs/batch-result-schema.json`:
|
||||
```json
|
||||
{
|
||||
"metadata": {
|
||||
"schemaVersion": "1.0.0",
|
||||
"batchId": "uuid",
|
||||
"timestamp": "2026-03-06T...",
|
||||
"totalGames": 100,
|
||||
"completedGames": 100,
|
||||
"format": "commander",
|
||||
"podSize": 3,
|
||||
"engineVersion": "forge-2.0.12-SNAPSHOT",
|
||||
"masterSeed": 42,
|
||||
"threads": 4,
|
||||
"elapsedMs": 260000
|
||||
},
|
||||
"decks": [...],
|
||||
"games": [...],
|
||||
"summary": {
|
||||
"perDeck": [
|
||||
{ "deckName": "Edgar Markov", "winRate": 0.60, "wins": 60, ... }
|
||||
],
|
||||
"avgGameTurns": 12.3,
|
||||
"simsPerSecond": 0.38
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Frontend Development
|
||||
|
||||
The UI is a React + TypeScript SPA in the `frontend/` directory.
|
||||
|
||||
### Dev server (with hot reload)
|
||||
```bash
|
||||
cd frontend
|
||||
npm install
|
||||
npm run dev
|
||||
```
|
||||
Vite proxies `/api` and `/ws` to `localhost:8000`, so start the FastAPI backend first.
|
||||
|
||||
### Production build
|
||||
```bash
|
||||
cd frontend
|
||||
npm run build
|
||||
```
|
||||
FastAPI serves the built assets from `frontend/dist/`.
|
||||
|
||||
## Known Limitations
|
||||
- Winner's life total not captured (Forge quiet mode only reports losers)
|
||||
- Win condition classification is heuristic-based on Forge loss reason strings
|
||||
- Each game spawns a new JVM process (~2-3s overhead per game)
|
||||
- Max throughput ~0.04 sims/sec single-threaded (Forge sim is CPU-heavy)
|
||||
- Multithreading spawns parallel subprocesses — throughput scales linearly with threads up to CPU core count
|
||||
@@ -1 +1 @@
|
||||
# Coach clients — Anthropic Claude, LM Studio
|
||||
# Coach clients — Perplexity, LM Studio
|
||||
@@ -1,401 +0,0 @@
|
||||
"""
|
||||
Commander AI Lab — Anthropic Claude Structured Output Client
|
||||
════════════════════════════════════════════════════════════
|
||||
Uses the anthropic SDK to call Claude's messages endpoint
|
||||
with structured JSON output enforced via system prompt.
|
||||
Supports both sync and native async operation.
|
||||
|
||||
All substantive calls use .messages.stream() to avoid the SDK's
|
||||
10-minute non-streaming timeout restriction on large max_tokens.
|
||||
"""
|
||||
import json
|
||||
import logging
|
||||
import re
|
||||
from typing import Optional
|
||||
|
||||
import anthropic
|
||||
|
||||
logger = logging.getLogger("coach.anthropic")
|
||||
|
||||
# ── Anthropic Models ───────────────────────────────────────────
|
||||
CLAUDE_OPUS = "claude-opus-4-0-20250514"
|
||||
CLAUDE_SONNET = "claude-sonnet-4-5"
|
||||
CLAUDE_HAIKU = "claude-haiku-4-5"
|
||||
|
||||
|
||||
class AnthropicResponse:
|
||||
"""Parsed response container from Anthropic API.
|
||||
|
||||
Drop-in replacement for PerplexityResponse — same attribute shape
|
||||
so all existing call-sites work without changes.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
content: str,
|
||||
parsed_json: Optional[dict],
|
||||
prompt_tokens: int,
|
||||
completion_tokens: int,
|
||||
model: str,
|
||||
citations: list[str] = None,
|
||||
):
|
||||
self.content = content
|
||||
self.parsed_json = parsed_json
|
||||
self.prompt_tokens = prompt_tokens
|
||||
self.completion_tokens = completion_tokens
|
||||
self.model = model
|
||||
self.citations = citations or [] # Anthropic has no citations; kept for compat
|
||||
|
||||
@property
|
||||
def ok(self) -> bool:
|
||||
return self.parsed_json is not None
|
||||
|
||||
|
||||
class AnthropicClient:
|
||||
"""
|
||||
Anthropic Claude API client.
|
||||
|
||||
Drop-in replacement for PerplexityClient.
|
||||
All substantive calls use .messages.stream() so the SDK never
|
||||
enforces the 10-minute non-streaming timeout.
|
||||
|
||||
Usage:
|
||||
client = AnthropicClient(api_key="sk-ant-...")
|
||||
resp = client.chat_structured(
|
||||
system_prompt="You are a deck builder.",
|
||||
user_prompt="Build a deck for...",
|
||||
json_schema=deck_schema,
|
||||
schema_name="DeckList",
|
||||
)
|
||||
if resp.ok:
|
||||
deck = resp.parsed_json
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
api_key: str,
|
||||
model: str = CLAUDE_OPUS,
|
||||
timeout: int = 120,
|
||||
base_url: str = None,
|
||||
):
|
||||
if not api_key:
|
||||
raise ValueError("Anthropic API key is required")
|
||||
self.api_key = api_key
|
||||
self.model = model
|
||||
self.timeout = timeout
|
||||
self._client = anthropic.Anthropic(
|
||||
api_key=api_key,
|
||||
base_url=base_url,
|
||||
timeout=float(timeout),
|
||||
)
|
||||
self._async_client = anthropic.AsyncAnthropic(
|
||||
api_key=api_key,
|
||||
base_url=base_url,
|
||||
timeout=float(timeout),
|
||||
)
|
||||
|
||||
def chat_structured(
|
||||
self,
|
||||
system_prompt: str,
|
||||
user_prompt: str,
|
||||
json_schema: dict = None,
|
||||
schema_name: str = "response",
|
||||
model: str = None,
|
||||
temperature: float = 0.2,
|
||||
max_tokens: int = 8192,
|
||||
) -> AnthropicResponse:
|
||||
"""
|
||||
Send a chat request expecting JSON output.
|
||||
Uses streaming to avoid the Anthropic SDK 10-minute timeout restriction.
|
||||
"""
|
||||
use_model = model or self.model
|
||||
effective_system = self._build_system(system_prompt, json_schema, schema_name)
|
||||
|
||||
try:
|
||||
with self._client.messages.stream(
|
||||
model=use_model,
|
||||
system=effective_system,
|
||||
messages=[{"role": "user", "content": user_prompt}],
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
) as stream:
|
||||
content = stream.get_final_text()
|
||||
final_msg = stream.get_final_message()
|
||||
return self._parse_streamed(content, final_msg, use_model)
|
||||
except Exception as e:
|
||||
logger.error("[anthropic] chat_structured failed: %s", e)
|
||||
raise
|
||||
|
||||
def chat_plain(
|
||||
self,
|
||||
system_prompt: str,
|
||||
user_prompt: str,
|
||||
model: str = None,
|
||||
temperature: float = 0.2,
|
||||
max_tokens: int = 4096,
|
||||
) -> AnthropicResponse:
|
||||
"""
|
||||
Send a plain chat request without strict structured output.
|
||||
Uses streaming to avoid the Anthropic SDK 10-minute timeout restriction.
|
||||
"""
|
||||
use_model = model or self.model
|
||||
|
||||
try:
|
||||
with self._client.messages.stream(
|
||||
model=use_model,
|
||||
system=system_prompt,
|
||||
messages=[{"role": "user", "content": user_prompt}],
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
) as stream:
|
||||
content = stream.get_final_text()
|
||||
final_msg = stream.get_final_message()
|
||||
return self._parse_streamed(content, final_msg, use_model)
|
||||
except Exception as e:
|
||||
logger.error("[anthropic] chat_plain failed: %s", e)
|
||||
raise
|
||||
|
||||
async def achat_structured(
|
||||
self,
|
||||
system_prompt: str,
|
||||
user_prompt: str,
|
||||
json_schema: dict = None,
|
||||
schema_name: str = "response",
|
||||
model: str = None,
|
||||
temperature: float = 0.2,
|
||||
max_tokens: int = 8192,
|
||||
) -> AnthropicResponse:
|
||||
"""Native async structured chat using streaming."""
|
||||
use_model = model or self.model
|
||||
effective_system = self._build_system(system_prompt, json_schema, schema_name)
|
||||
|
||||
try:
|
||||
async with self._async_client.messages.stream(
|
||||
model=use_model,
|
||||
system=effective_system,
|
||||
messages=[{"role": "user", "content": user_prompt}],
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
) as stream:
|
||||
content = await stream.get_final_text()
|
||||
final_msg = await stream.get_final_message()
|
||||
return self._parse_streamed(content, final_msg, use_model)
|
||||
except Exception as e:
|
||||
logger.error("[anthropic] achat_structured failed: %s", e)
|
||||
raise
|
||||
|
||||
async def achat_plain(
|
||||
self,
|
||||
system_prompt: str,
|
||||
user_prompt: str,
|
||||
model: str = None,
|
||||
temperature: float = 0.2,
|
||||
max_tokens: int = 4096,
|
||||
) -> AnthropicResponse:
|
||||
"""Native async plain chat using streaming."""
|
||||
use_model = model or self.model
|
||||
|
||||
try:
|
||||
async with self._async_client.messages.stream(
|
||||
model=use_model,
|
||||
system=system_prompt,
|
||||
messages=[{"role": "user", "content": user_prompt}],
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
) as stream:
|
||||
content = await stream.get_final_text()
|
||||
final_msg = await stream.get_final_message()
|
||||
return self._parse_streamed(content, final_msg, use_model)
|
||||
except Exception as e:
|
||||
logger.error("[anthropic] achat_plain failed: %s", e)
|
||||
raise
|
||||
|
||||
def check_status(self) -> dict:
|
||||
"""
|
||||
Quick health check — tiny max_tokens=10 call, safe to use non-streaming
|
||||
since it will never approach the 10-minute threshold.
|
||||
"""
|
||||
try:
|
||||
response = self._client.messages.create(
|
||||
model=self.model,
|
||||
system="Reply with the word OK.",
|
||||
messages=[{"role": "user", "content": "Status check."}],
|
||||
max_tokens=10,
|
||||
)
|
||||
content = response.content[0].text if response.content else ""
|
||||
return {
|
||||
"connected": True,
|
||||
"model": self.model,
|
||||
"response": content,
|
||||
}
|
||||
except Exception as e:
|
||||
return {
|
||||
"connected": False,
|
||||
"model": self.model,
|
||||
"error": str(e),
|
||||
}
|
||||
|
||||
# ── Internal helpers ──────────────────────────────────────────
|
||||
|
||||
@staticmethod
|
||||
def _build_system(system_prompt: str, json_schema: dict, schema_name: str) -> str:
|
||||
"""Append JSON schema hint to system prompt when a schema is provided."""
|
||||
if not json_schema:
|
||||
return system_prompt
|
||||
schema_str = json.dumps(json_schema, indent=2)
|
||||
return (
|
||||
f"{system_prompt}\n\n"
|
||||
f"You MUST respond with valid JSON only — no markdown fences, no prose.\n"
|
||||
f"The response must conform to the following JSON schema ({schema_name}):\n"
|
||||
f"{schema_str}"
|
||||
)
|
||||
|
||||
def _parse_streamed(self, content: str, final_msg, use_model: str) -> AnthropicResponse:
|
||||
"""Build an AnthropicResponse from streamed text + final message metadata."""
|
||||
usage = getattr(final_msg, "usage", None)
|
||||
prompt_tokens = usage.input_tokens if usage else 0
|
||||
completion_tokens = usage.output_tokens if usage else 0
|
||||
|
||||
parsed = None
|
||||
try:
|
||||
parsed = json.loads(content)
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
parsed = self._extract_json(content)
|
||||
|
||||
logger.info(
|
||||
"[anthropic] model=%s tokens=(%d in, %d out) parsed=%s",
|
||||
use_model,
|
||||
prompt_tokens,
|
||||
completion_tokens,
|
||||
"yes" if parsed else "no",
|
||||
)
|
||||
|
||||
return AnthropicResponse(
|
||||
content=content,
|
||||
parsed_json=parsed,
|
||||
prompt_tokens=prompt_tokens,
|
||||
completion_tokens=completion_tokens,
|
||||
model=use_model,
|
||||
citations=[],
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _extract_json(text: str) -> Optional[dict]:
|
||||
"""Best-effort JSON extraction from possibly noisy text."""
|
||||
try:
|
||||
return json.loads(text.strip())
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
pass
|
||||
|
||||
# Markdown fences
|
||||
fence_match = re.search(r'```(?:json)?\s*([\s\S]*?)```', text)
|
||||
if fence_match:
|
||||
try:
|
||||
return json.loads(fence_match.group(1).strip())
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
pass
|
||||
|
||||
# Brace counting
|
||||
start = text.find('{')
|
||||
if start == -1:
|
||||
return None
|
||||
depth = 0
|
||||
in_string = False
|
||||
escape_next = False
|
||||
for i in range(start, len(text)):
|
||||
ch = text[i]
|
||||
if escape_next:
|
||||
escape_next = False
|
||||
continue
|
||||
if ch == '\\' and in_string:
|
||||
escape_next = True
|
||||
continue
|
||||
if ch == '"':
|
||||
in_string = not in_string
|
||||
continue
|
||||
if in_string:
|
||||
continue
|
||||
if ch == '{':
|
||||
depth += 1
|
||||
elif ch == '}':
|
||||
depth -= 1
|
||||
if depth == 0:
|
||||
try:
|
||||
return json.loads(text[start:i + 1])
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
return None
|
||||
|
||||
# Truncated JSON — attempt repair
|
||||
return AnthropicClient._repair_truncated_json(text[start:])
|
||||
|
||||
@staticmethod
|
||||
def _repair_truncated_json(text: str) -> Optional[dict]:
|
||||
"""
|
||||
Attempt to repair truncated JSON from max_tokens cutoff.
|
||||
Strategy: find the last complete nested object, then close
|
||||
all open brackets/braces.
|
||||
"""
|
||||
logger.info("Attempting truncated JSON repair (%d chars)...", len(text))
|
||||
last_good = -1
|
||||
depth = 0
|
||||
in_string = False
|
||||
escape_next = False
|
||||
for i in range(len(text)):
|
||||
ch = text[i]
|
||||
if escape_next:
|
||||
escape_next = False
|
||||
continue
|
||||
if ch == '\\' and in_string:
|
||||
escape_next = True
|
||||
continue
|
||||
if ch == '"':
|
||||
in_string = not in_string
|
||||
continue
|
||||
if in_string:
|
||||
continue
|
||||
if ch == '{':
|
||||
depth += 1
|
||||
elif ch == '}':
|
||||
depth -= 1
|
||||
if depth >= 1:
|
||||
last_good = i
|
||||
|
||||
if last_good == -1:
|
||||
return None
|
||||
|
||||
truncated = text[:last_good + 1]
|
||||
close_depth = 0
|
||||
in_arr = 0
|
||||
in_str = False
|
||||
esc = False
|
||||
for ch in truncated:
|
||||
if esc:
|
||||
esc = False
|
||||
continue
|
||||
if ch == '\\' and in_str:
|
||||
esc = True
|
||||
continue
|
||||
if ch == '"':
|
||||
in_str = not in_str
|
||||
continue
|
||||
if in_str:
|
||||
continue
|
||||
if ch == '{':
|
||||
close_depth += 1
|
||||
elif ch == '}':
|
||||
close_depth -= 1
|
||||
elif ch == '[':
|
||||
in_arr += 1
|
||||
elif ch == ']':
|
||||
in_arr -= 1
|
||||
|
||||
suffix = ']' * in_arr + '}' * close_depth
|
||||
repaired = truncated + suffix
|
||||
try:
|
||||
result = json.loads(repaired)
|
||||
card_count = len(result.get('cards', []))
|
||||
logger.info("JSON repair succeeded: recovered %d cards", card_count)
|
||||
return result
|
||||
except (json.JSONDecodeError, TypeError) as e:
|
||||
logger.warning("JSON repair failed: %s", e)
|
||||
return None
|
||||
+51
-343
@@ -9,8 +9,6 @@ calls the LLM, parses responses, and persists coaching sessions.
|
||||
import json
|
||||
import logging
|
||||
import uuid
|
||||
import os
|
||||
import re
|
||||
from datetime import datetime, timezone
|
||||
from pathlib import Path
|
||||
from typing import Optional, List, Dict
|
||||
@@ -18,16 +16,11 @@ from typing import Optional, List, Dict
|
||||
from .config import (
|
||||
DECK_REPORTS_DIR, COACH_SESSIONS_DIR,
|
||||
MAX_UNDERPERFORMERS, MAX_CANDIDATES_PER_UNDERPERFORMER,
|
||||
COACH_PROVIDER, ANTHROPIC_API_KEY, ANTHROPIC_MODEL,
|
||||
UNDERPERFORMER_IMPACT_THRESHOLD, DEFAULT_MAX_TOKENS, ensure_dirs,
|
||||
UNDERPERFORMER_IMPACT_THRESHOLD, ensure_dirs,
|
||||
)
|
||||
from .models import (
|
||||
DeckReport, CoachGoals, CoachSession,
|
||||
SuggestedCut, SuggestedAdd, CoachStatus,
|
||||
UpgradePriorityItem, CommanderDependency, MulliganAnalysis,
|
||||
RemovalCoverage, RampQuality, DrawEngineProfile,
|
||||
WinCondition, AntiSynergyFlag,
|
||||
PodPresence, TempoAssessment, MetaMatchup,
|
||||
)
|
||||
from .llm_client import LLMClient
|
||||
from .embeddings import MTGEmbeddingIndex
|
||||
@@ -35,18 +28,6 @@ from .prompt_template import build_system_prompt, build_user_prompt
|
||||
|
||||
logger = logging.getLogger("coach.service")
|
||||
|
||||
# SQLite persistence for coach sessions
|
||||
try:
|
||||
from services.database import (
|
||||
save_coach_session as _db_save_session,
|
||||
load_coach_session as _db_load_session,
|
||||
list_coach_sessions as _db_list_sessions,
|
||||
delete_coach_session as _db_delete_session,
|
||||
)
|
||||
_DB_AVAILABLE = True
|
||||
except ImportError:
|
||||
_DB_AVAILABLE = False
|
||||
|
||||
|
||||
class CoachService:
|
||||
"""
|
||||
@@ -65,19 +46,23 @@ class CoachService:
|
||||
self.embeddings = embeddings
|
||||
ensure_dirs()
|
||||
|
||||
# ── Deck Report I/O ────────────────────────────────────
|
||||
# ── Deck Report I/O ────────────────────────────────────────
|
||||
|
||||
def load_deck_report(self, deck_id: str) -> Optional[DeckReport]:
|
||||
"""Load a deck report from disk."""
|
||||
# Try exact filename first, then case-insensitive search
|
||||
report_path = DECK_REPORTS_DIR / f"{deck_id}.json"
|
||||
if not report_path.exists():
|
||||
# Try case-insensitive match
|
||||
for f in DECK_REPORTS_DIR.glob("*.json"):
|
||||
if re.sub(r'[^a-z0-9]', '', f.stem.lower()) == re.sub(r'[^a-z0-9]', '', deck_id.lower()):
|
||||
if f.stem.lower() == deck_id.lower():
|
||||
report_path = f
|
||||
break
|
||||
|
||||
if not report_path.exists():
|
||||
logger.warning("Deck report not found: %s", deck_id)
|
||||
return None
|
||||
|
||||
try:
|
||||
with open(report_path, "r") as f:
|
||||
data = json.load(f)
|
||||
@@ -92,60 +77,18 @@ class CoachService:
|
||||
return []
|
||||
return [f.stem for f in DECK_REPORTS_DIR.glob("*.json")]
|
||||
|
||||
# ── Coach Session I/O ──────────────────────────────
|
||||
# ── Coach Session I/O ──────────────────────────────────────
|
||||
|
||||
def save_session(self, session: CoachSession) -> Path:
|
||||
"""Persist a coaching session to disk and SQLite."""
|
||||
"""Persist a coaching session to disk."""
|
||||
COACH_SESSIONS_DIR.mkdir(parents=True, exist_ok=True)
|
||||
path = COACH_SESSIONS_DIR / f"{session.sessionId}.json"
|
||||
with open(path, "w") as f:
|
||||
f.write(session.model_dump_json(indent=2))
|
||||
if _DB_AVAILABLE:
|
||||
try:
|
||||
_db_save_session({
|
||||
"session_id": session.sessionId,
|
||||
"deck_id": session.deckId,
|
||||
"timestamp": session.timestamp,
|
||||
"model_used": session.modelUsed or "",
|
||||
"prompt_tokens": session.promptTokens or 0,
|
||||
"completion_tokens": session.completionTokens or 0,
|
||||
"summary": session.summary or "",
|
||||
"goals_json": json.dumps(session.goals.model_dump() if session.goals else {}),
|
||||
"cuts_json": json.dumps([c.model_dump() for c in session.suggestedCuts]),
|
||||
"adds_json": json.dumps([a.model_dump() for a in session.suggestedAdds]),
|
||||
"heuristic_hints_json": json.dumps(session.heuristicHints or []),
|
||||
"mana_base_advice": session.manaBaseAdvice or "",
|
||||
"raw_text": session.rawTextExplanation or "",
|
||||
})
|
||||
logger.info("Coach session persisted to SQLite: %s", session.sessionId)
|
||||
except Exception as e:
|
||||
logger.warning("Failed to persist session to SQLite: %s", e)
|
||||
return path
|
||||
|
||||
def load_session(self, session_id: str) -> Optional[CoachSession]:
|
||||
"""Load a coaching session from SQLite, falling back to disk."""
|
||||
if _DB_AVAILABLE:
|
||||
try:
|
||||
row = _db_load_session(session_id)
|
||||
if row:
|
||||
data = dict(row)
|
||||
return CoachSession(
|
||||
sessionId=data["session_id"],
|
||||
deckId=data["deck_id"],
|
||||
timestamp=data["timestamp"],
|
||||
modelUsed=data.get("model_used", ""),
|
||||
promptTokens=data.get("prompt_tokens", 0),
|
||||
completionTokens=data.get("completion_tokens", 0),
|
||||
summary=data.get("summary", ""),
|
||||
goals=json.loads(data["goals_json"]) if data.get("goals_json") and data["goals_json"] != "{}" else None,
|
||||
suggestedCuts=[SuggestedCut(**c) for c in json.loads(data.get("cuts_json", "[]"))],
|
||||
suggestedAdds=[SuggestedAdd(**a) for a in json.loads(data.get("adds_json", "[]"))],
|
||||
heuristicHints=json.loads(data.get("heuristic_hints_json", "[]")),
|
||||
manaBaseAdvice=data.get("mana_base_advice", ""),
|
||||
rawTextExplanation=data.get("raw_text", ""),
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning("SQLite load failed for %s: %s", session_id, e)
|
||||
"""Load a coaching session from disk."""
|
||||
path = COACH_SESSIONS_DIR / f"{session_id}.json"
|
||||
if not path.exists():
|
||||
return None
|
||||
@@ -158,14 +101,7 @@ class CoachService:
|
||||
return None
|
||||
|
||||
def list_sessions(self, deck_id: str = None) -> List[dict]:
|
||||
"""List coaching sessions from SQLite, falling back to disk."""
|
||||
if _DB_AVAILABLE:
|
||||
try:
|
||||
rows = _db_list_sessions(deck_id)
|
||||
if rows is not None:
|
||||
return rows
|
||||
except Exception as e:
|
||||
logger.warning("SQLite list_sessions failed: %s", e)
|
||||
"""List all coaching sessions, optionally filtered by deck."""
|
||||
if not COACH_SESSIONS_DIR.exists():
|
||||
return []
|
||||
sessions = []
|
||||
@@ -187,24 +123,23 @@ class CoachService:
|
||||
continue
|
||||
return sessions
|
||||
|
||||
# ── Main Coaching Pipeline ───────────────────────────────
|
||||
# ── Main Coaching Pipeline ─────────────────────────────────
|
||||
|
||||
async def run_coaching_session(
|
||||
self,
|
||||
deck_id: str,
|
||||
goals: Optional[CoachGoals] = None,
|
||||
fallback_report: Optional[DeckReport] = None,
|
||||
) -> CoachSession:
|
||||
async def run_coaching_session(self, deck_id: str,
|
||||
goals: Optional[CoachGoals] = None,
|
||||
fallback_report: Optional[DeckReport] = None,
|
||||
) -> CoachSession:
|
||||
"""
|
||||
Full coaching pipeline:
|
||||
1. Load deck report (or use fallback from DB card list)
|
||||
2. Identify underperformers
|
||||
3. Find replacement candidates via embeddings
|
||||
4. Build prompt
|
||||
5. Call LLM (streaming for Anthropic to avoid 10-min SDK timeout)
|
||||
5. Call LLM
|
||||
6. Parse response
|
||||
7. Persist session
|
||||
"""
|
||||
# 0. Auto-load embeddings if not loaded
|
||||
if not self.embeddings.loaded:
|
||||
logger.info("Embeddings not loaded — attempting auto-load...")
|
||||
try:
|
||||
@@ -216,6 +151,7 @@ class CoachService:
|
||||
except Exception as e:
|
||||
logger.warning("Embeddings auto-load failed: %s", e)
|
||||
|
||||
# 1. Load deck report — try simulation report first, then fallback
|
||||
report = self.load_deck_report(deck_id)
|
||||
if report is None and fallback_report is not None:
|
||||
report = fallback_report
|
||||
@@ -223,18 +159,25 @@ class CoachService:
|
||||
if report is None:
|
||||
raise ValueError(f"Deck report not found for: {deck_id}")
|
||||
|
||||
# 2. Get deck card names (for exclusion from candidates)
|
||||
deck_card_names = [c.name for c in report.cards]
|
||||
|
||||
# 3. Find replacement candidates for underperformers
|
||||
candidates: Dict[str, List[dict]] = {}
|
||||
|
||||
underperformers = report.underperformers[:MAX_UNDERPERFORMERS]
|
||||
if not underperformers:
|
||||
# If no explicit underperformers, pick lowest impact cards
|
||||
sorted_cards = sorted(report.cards, key=lambda c: c.impactScore)
|
||||
underperformers = [
|
||||
c.name for c in sorted_cards[:MAX_UNDERPERFORMERS]
|
||||
if c.impactScore < UNDERPERFORMER_IMPACT_THRESHOLD
|
||||
]
|
||||
|
||||
# If still no underperformers and we have cards, pick bottom N by impact
|
||||
if not underperformers and report.cards:
|
||||
sorted_cards = sorted(report.cards, key=lambda c: c.impactScore)
|
||||
# Take the bottom 5 non-land cards as candidates for cuts
|
||||
underperformers = [
|
||||
c.name for c in sorted_cards[:5]
|
||||
if not any(t in (c.tags or []) for t in [])
|
||||
@@ -252,61 +195,18 @@ class CoachService:
|
||||
candidates[card_name] = [m.to_dict() for m in matches]
|
||||
else:
|
||||
logger.warning("Embeddings not loaded — skipping candidate search")
|
||||
# Phase 3: RAG vector search for additional card context
|
||||
rag_cards: List[dict] = []
|
||||
try:
|
||||
from services.rag_store import query_cards
|
||||
query_text = f"{report.commander} {' '.join(report.colorIdentity)} commander deck"
|
||||
rag_cards = query_cards(query_text, n_results=15, color_identity=report.colorIdentity)
|
||||
logger.info("RAG returned %d cards for '%s'", len(rag_cards), deck_id)
|
||||
except Exception as e:
|
||||
logger.warning("RAG query failed (non-fatal): %s", e)
|
||||
|
||||
|
||||
# 4. Build prompts
|
||||
system_prompt = build_system_prompt(report, goals)
|
||||
user_prompt = build_user_prompt(report, candidates, rag_cards=rag_cards)
|
||||
user_prompt = build_user_prompt(report, candidates)
|
||||
|
||||
logger.info("Calling LLM for deck: %s (provider=%s)", deck_id, COACH_PROVIDER)
|
||||
|
||||
if COACH_PROVIDER == "anthropic":
|
||||
import anthropic as _anthropic
|
||||
anthropic_key = ANTHROPIC_API_KEY
|
||||
if not anthropic_key:
|
||||
raise ConnectionError("Anthropic API key not configured. Set ANTHROPIC_API_KEY env var.")
|
||||
aclient = _anthropic.AsyncAnthropic(api_key=anthropic_key)
|
||||
async with aclient.messages.stream(
|
||||
model=ANTHROPIC_MODEL,
|
||||
system=system_prompt,
|
||||
messages=[{"role": "user", "content": user_prompt}],
|
||||
max_tokens=DEFAULT_MAX_TOKENS,
|
||||
temperature=0.7,
|
||||
) as stream:
|
||||
content = await stream.get_final_text()
|
||||
final_msg = await stream.get_final_message()
|
||||
usage = getattr(final_msg, "usage", None)
|
||||
from types import SimpleNamespace
|
||||
llm_response = SimpleNamespace(
|
||||
content=content,
|
||||
model=final_msg.model,
|
||||
prompt_tokens=usage.input_tokens if usage else 0,
|
||||
completion_tokens=usage.output_tokens if usage else 0,
|
||||
parsed_json=None,
|
||||
)
|
||||
try:
|
||||
cleaned = re.sub(r'^```(?:json)?\s*', '', content.strip())
|
||||
cleaned = re.sub(r'\s*```$', '', cleaned.strip())
|
||||
llm_response.parsed_json = json.loads(cleaned)
|
||||
except (json.JSONDecodeError, ValueError):
|
||||
match = re.search(r'\{[\s\S]*\}', content)
|
||||
if match:
|
||||
try:
|
||||
llm_response.parsed_json = json.loads(match.group(0))
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
else:
|
||||
llm_response = await self.llm.chat(system_prompt, user_prompt)
|
||||
# 5. Call LLM
|
||||
logger.info("Calling LLM for deck: %s", deck_id)
|
||||
llm_response = await self.llm.chat(system_prompt, user_prompt)
|
||||
|
||||
# 6. Parse response into CoachSession
|
||||
session_id = f"sess-{datetime.now(timezone.utc).strftime('%Y%m%d-%H%M%S')}-{uuid.uuid4().hex[:6]}"
|
||||
|
||||
session = CoachSession(
|
||||
sessionId=session_id,
|
||||
deckId=deck_id,
|
||||
@@ -320,111 +220,27 @@ class CoachService:
|
||||
if llm_response.parsed_json:
|
||||
self._populate_session_from_json(session, llm_response.parsed_json)
|
||||
else:
|
||||
# Fallback: store raw text
|
||||
session.rawTextExplanation = llm_response.content
|
||||
session.summary = "LLM returned non-JSON response. See raw explanation."
|
||||
|
||||
# 7. Persist
|
||||
self.save_session(session)
|
||||
logger.info("Coaching session saved: %s", session_id)
|
||||
|
||||
return session
|
||||
|
||||
# ── Quick Digest ──────────────────────────────────────────
|
||||
|
||||
async def run_quick_digest(
|
||||
self,
|
||||
deck_id: str,
|
||||
goals: Optional[CoachGoals] = None,
|
||||
fallback_report: Optional[DeckReport] = None,
|
||||
) -> CoachSession:
|
||||
"""Fast ~400-600 token call: summary + top 3 upgradePriority + commanderDependency."""
|
||||
report = self.load_deck_report(deck_id)
|
||||
if report is None and fallback_report is not None:
|
||||
report = fallback_report
|
||||
if report is None:
|
||||
raise ValueError(f"Deck report not found for: {deck_id}")
|
||||
|
||||
# Phase 3: light RAG query for quick digest too
|
||||
rag_cards: List[dict] = []
|
||||
try:
|
||||
from services.rag_store import query_cards
|
||||
query_text = f"{report.commander} {' '.join(report.colorIdentity)}"
|
||||
rag_cards = query_cards(query_text, n_results=8, color_identity=report.colorIdentity)
|
||||
except Exception:
|
||||
pass
|
||||
from .prompt_template import build_quick_system_prompt, build_user_prompt
|
||||
system_prompt = build_quick_system_prompt(report, goals)
|
||||
user_prompt = build_user_prompt(report, {}, rag_cards=rag_cards) # RAG-enriched quick digest # no candidates for speed
|
||||
|
||||
logger.info("Quick digest for deck: %s (provider=%s)", deck_id, COACH_PROVIDER)
|
||||
|
||||
if COACH_PROVIDER == "anthropic":
|
||||
import anthropic as _anthropic
|
||||
anthropic_key = ANTHROPIC_API_KEY
|
||||
if not anthropic_key:
|
||||
raise ConnectionError("Anthropic API key not configured.")
|
||||
aclient = _anthropic.AsyncAnthropic(api_key=anthropic_key)
|
||||
async with aclient.messages.stream(
|
||||
model=ANTHROPIC_MODEL,
|
||||
system=system_prompt,
|
||||
messages=[{"role": "user", "content": user_prompt}],
|
||||
max_tokens=1024,
|
||||
temperature=0.5,
|
||||
) as stream:
|
||||
content = await stream.get_final_text()
|
||||
final_msg = await stream.get_final_message()
|
||||
usage = getattr(final_msg, "usage", None)
|
||||
from types import SimpleNamespace
|
||||
llm_response = SimpleNamespace(
|
||||
content=content,
|
||||
model=final_msg.model,
|
||||
prompt_tokens=usage.input_tokens if usage else 0,
|
||||
completion_tokens=usage.output_tokens if usage else 0,
|
||||
parsed_json=None,
|
||||
)
|
||||
try:
|
||||
cleaned = re.sub(r'^```(?:json)?\s*', '', content.strip())
|
||||
cleaned = re.sub(r'\s*```$', '', cleaned.strip())
|
||||
llm_response.parsed_json = json.loads(cleaned)
|
||||
except (json.JSONDecodeError, ValueError):
|
||||
match = re.search(r'\{[\s\S]*\}', content)
|
||||
if match:
|
||||
try:
|
||||
llm_response.parsed_json = json.loads(match.group(0))
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
else:
|
||||
llm_response = await self.llm.chat(system_prompt, user_prompt)
|
||||
|
||||
session_id = f"quick-{datetime.now(timezone.utc).strftime('%Y%m%d-%H%M%S')}-{uuid.uuid4().hex[:6]}"
|
||||
session = CoachSession(
|
||||
sessionId=session_id,
|
||||
deckId=deck_id,
|
||||
timestamp=datetime.now(timezone.utc).isoformat(),
|
||||
modelUsed=llm_response.model,
|
||||
promptTokens=llm_response.prompt_tokens,
|
||||
completionTokens=llm_response.completion_tokens,
|
||||
goals=goals,
|
||||
isQuickDigest=True,
|
||||
)
|
||||
if llm_response.parsed_json:
|
||||
self._populate_session_from_json(session, llm_response.parsed_json)
|
||||
else:
|
||||
session.rawTextExplanation = llm_response.content
|
||||
session.summary = "Quick digest returned non-JSON. See raw explanation."
|
||||
|
||||
self.save_session(session)
|
||||
return session
|
||||
|
||||
# ── JSON Parser ───────────────────────────────────────────
|
||||
|
||||
def _populate_session_from_json(self, session: CoachSession, data: dict):
|
||||
"""Parse LLM JSON response into CoachSession fields."""
|
||||
session.summary = data.get("summary", "")
|
||||
session.rawTextExplanation = data.get("rawTextExplanation", "")
|
||||
session.manaBaseAdvice = data.get("manaBaseAdvice")
|
||||
|
||||
# Heuristic hints
|
||||
hints = data.get("heuristicHints", [])
|
||||
session.heuristicHints = hints if isinstance(hints, list) else [str(hints)]
|
||||
|
||||
# Suggested cuts
|
||||
for cut_data in data.get("suggestedCuts", []):
|
||||
if isinstance(cut_data, dict):
|
||||
session.suggestedCuts.append(SuggestedCut(
|
||||
@@ -433,6 +249,7 @@ class CoachService:
|
||||
replacementOptions=cut_data.get("replacementOptions", []),
|
||||
))
|
||||
|
||||
# Suggested adds
|
||||
for add_data in data.get("suggestedAdds", []):
|
||||
if isinstance(add_data, dict):
|
||||
session.suggestedAdds.append(SuggestedAdd(
|
||||
@@ -442,134 +259,25 @@ class CoachService:
|
||||
synergyWith=add_data.get("synergyWith", []),
|
||||
))
|
||||
|
||||
# Phase 2
|
||||
for item in data.get("upgradePriority", []):
|
||||
if isinstance(item, dict):
|
||||
session.upgradePriority.append(UpgradePriorityItem(
|
||||
rank=item.get("rank", 0),
|
||||
cut=item.get("cut", ""),
|
||||
add=item.get("add", ""),
|
||||
reasoning=item.get("reasoning", ""),
|
||||
expectedImpact=item.get("expectedImpact", ""),
|
||||
))
|
||||
|
||||
cd = data.get("commanderDependency")
|
||||
if isinstance(cd, dict):
|
||||
session.commanderDependency = CommanderDependency(
|
||||
score=cd.get("score", 5),
|
||||
dependentCards=cd.get("dependentCards", []),
|
||||
recoveryPlan=cd.get("recoveryPlan", ""),
|
||||
)
|
||||
|
||||
ma = data.get("mulliganAnalysis")
|
||||
if isinstance(ma, dict):
|
||||
session.mulliganAnalysis = MulliganAnalysis(
|
||||
estimatedKeepRate=ma.get("estimatedKeepRate", ""),
|
||||
worstOffenders=ma.get("worstOffenders", []),
|
||||
recommendation=ma.get("recommendation", ""),
|
||||
)
|
||||
|
||||
# Phase 3: Removal coverage
|
||||
rc = data.get("removalCoverage")
|
||||
if isinstance(rc, dict):
|
||||
session.removalCoverage = RemovalCoverage(**{
|
||||
k: rc.get(k, "" if k != "gaps" else [])
|
||||
for k in ["creatures", "artifacts", "enchantments", "planeswalkers", "lands", "massRemoval", "gaps"]
|
||||
})
|
||||
|
||||
# Phase 3: Ramp quality
|
||||
rq = data.get("rampQuality")
|
||||
if isinstance(rq, dict):
|
||||
session.rampQuality = RampQuality(**{
|
||||
k: rq.get(k, "") for k in ["manaRocks", "landFetch", "manaDorks", "costReducers", "fragility", "canReachFourByTurnThree"]
|
||||
})
|
||||
|
||||
# Phase 3: Draw engine profile
|
||||
dep = data.get("drawEngineProfile")
|
||||
if isinstance(dep, dict):
|
||||
session.drawEngineProfile = DrawEngineProfile(
|
||||
burstDraw=dep.get("burstDraw", []),
|
||||
repeatableEngines=dep.get("repeatableEngines", []),
|
||||
assessment=dep.get("assessment", ""),
|
||||
sustainability=dep.get("sustainability", ""),
|
||||
)
|
||||
|
||||
# Phase 3: Win conditions
|
||||
for wc in data.get("winConditions", []):
|
||||
if isinstance(wc, dict):
|
||||
session.winConditions.append(WinCondition(
|
||||
name=wc.get("name", ""),
|
||||
cards=wc.get("cards", []),
|
||||
independence=wc.get("independence", ""),
|
||||
description=wc.get("description", ""),
|
||||
))
|
||||
|
||||
# Phase 3: Anti-synergy flags
|
||||
for af in data.get("antiSynergyFlags", []):
|
||||
if isinstance(af, dict):
|
||||
session.antiSynergyFlags.append(AntiSynergyFlag(
|
||||
cards=af.get("cards", []),
|
||||
conflict=af.get("conflict", ""),
|
||||
severity=af.get("severity", ""),
|
||||
))
|
||||
|
||||
# Phase 5: Pod presence
|
||||
pp = data.get("podPresence")
|
||||
if isinstance(pp, dict):
|
||||
session.podPresence = PodPresence(
|
||||
threatLevel=pp.get("threatLevel", ""),
|
||||
politicalTools=pp.get("politicalTools", []),
|
||||
adversarialRating=pp.get("adversarialRating", ""),
|
||||
recommendation=pp.get("recommendation", ""),
|
||||
)
|
||||
|
||||
# Phase 5: Tempo assessment
|
||||
ta = data.get("tempoAssessment")
|
||||
if isinstance(ta, dict):
|
||||
session.tempoAssessment = TempoAssessment(
|
||||
peakTurn=ta.get("peakTurn", 0),
|
||||
profile=ta.get("profile", ""),
|
||||
survivalWindow=ta.get("survivalWindow", ""),
|
||||
assessment=ta.get("assessment", ""),
|
||||
)
|
||||
|
||||
# Phase 5: Meta matchups
|
||||
for mm in data.get("metaMatchups", []):
|
||||
if isinstance(mm, dict):
|
||||
session.metaMatchups.append(MetaMatchup(
|
||||
archetype=mm.get("archetype", ""),
|
||||
assessment=mm.get("assessment", ""),
|
||||
keyThreats=mm.get("keyThreats", []),
|
||||
keyAnswers=mm.get("keyAnswers", []),
|
||||
overallRating=mm.get("overallRating", ""),
|
||||
))
|
||||
|
||||
# ── Status Check ─────────────────────────────────────────
|
||||
# ── Status Check ───────────────────────────────────────────
|
||||
|
||||
def get_status(self) -> CoachStatus:
|
||||
"""Check the health of all coach subsystems."""
|
||||
status = CoachStatus()
|
||||
|
||||
if COACH_PROVIDER == "anthropic":
|
||||
anthropic_key = ANTHROPIC_API_KEY
|
||||
if anthropic_key:
|
||||
status.llmConnected = True
|
||||
status.llmModel = f"Claude Opus ({ANTHROPIC_MODEL})"
|
||||
status.llmModels = [ANTHROPIC_MODEL]
|
||||
else:
|
||||
status.llmConnected = False
|
||||
status.llmModel = None
|
||||
status.llmModels = []
|
||||
status.error = "Anthropic API key not configured. Set ANTHROPIC_API_KEY env var."
|
||||
else:
|
||||
llm_status = self.llm.check_connection()
|
||||
status.llmConnected = llm_status.get("connected", False)
|
||||
status.llmModel = llm_status.get("active_model")
|
||||
status.llmModels = llm_status.get("models", [])
|
||||
if not status.llmConnected:
|
||||
status.error = llm_status.get("error", "Local LLM not reachable")
|
||||
# Check LLM
|
||||
llm_status = self.llm.check_connection()
|
||||
status.llmConnected = llm_status.get("connected", False)
|
||||
status.llmModel = llm_status.get("active_model")
|
||||
status.llmModels = llm_status.get("models", [])
|
||||
if not status.llmConnected:
|
||||
status.error = llm_status.get("error", "LM Studio not reachable")
|
||||
|
||||
# Check embeddings
|
||||
status.embeddingsLoaded = self.embeddings.loaded
|
||||
status.embeddingCards = self.embeddings.card_count
|
||||
|
||||
# Check deck reports
|
||||
status.deckReportsAvailable = len(self.list_deck_reports())
|
||||
|
||||
return status
|
||||
+27
-30
@@ -1,6 +1,6 @@
|
||||
"""
|
||||
Commander AI Lab — Coach Configuration
|
||||
────────────────────────────────────────
|
||||
═══════════════════════════════════════
|
||||
Central config for Ollama, embeddings, and coach service paths.
|
||||
All paths are relative to the commander-ai-lab root directory.
|
||||
"""
|
||||
@@ -8,60 +8,57 @@ All paths are relative to the commander-ai-lab root directory.
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
# ── Base Paths ───────────────────────────────────────────────────────
|
||||
# ── Base Paths ──────────────────────────────────────────────
|
||||
# Resolve relative to wherever the lab is installed
|
||||
LAB_ROOT = Path(os.environ.get("COMMANDER_LAB_ROOT", Path(__file__).parent.parent))
|
||||
|
||||
# ── Ollama (OpenAI-compatible API) ────────────────────────────
|
||||
LLM_URL = os.environ.get("LLM_URL", "http://localhost:11434/v1")
|
||||
# ── Ollama (OpenAI-compatible API) ──────────────────────
|
||||
LLM_URL = os.environ.get("LLM_URL", "http://192.168.0.240:11434/v1")
|
||||
LLM_MODEL = os.environ.get("LLM_MODEL", "gpt-oss:20b")
|
||||
LLM_TIMEOUT = int(os.environ.get("LLM_TIMEOUT", "360")) # seconds
|
||||
LLM_MAX_RETRIES = 3
|
||||
|
||||
# ── Embeddings ───────────────────────────────────────────────────
|
||||
# ── Embeddings ─────────────────────────────────────────────
|
||||
EMBEDDINGS_DIR = LAB_ROOT / "data"
|
||||
EMBEDDINGS_NPZ = EMBEDDINGS_DIR / "mtg-embeddings.npz"
|
||||
EMBEDDINGS_PARQUET = EMBEDDINGS_DIR / "mtg-embeddings.parquet"
|
||||
|
||||
# ── Deck Reports ────────────────────────────────────────────────
|
||||
# ── Deck Reports ───────────────────────────────────────────
|
||||
DECK_REPORTS_DIR = LAB_ROOT / "deck-reports"
|
||||
COACH_SESSIONS_DIR = LAB_ROOT / "coach-sessions"
|
||||
|
||||
# ── Prompt Limits ───────────────────────────────────────────────
|
||||
# ── Prompt Limits ──────────────────────────────────────────
|
||||
MAX_PROMPT_TOKENS = 2048
|
||||
MAX_CANDIDATES_PER_UNDERPERFORMER = 8
|
||||
MAX_UNDERPERFORMERS = 8
|
||||
MAX_CANDIDATES_PER_UNDERPERFORMER = 5
|
||||
MAX_UNDERPERFORMERS = 4
|
||||
UNDERPERFORMER_IMPACT_THRESHOLD = -0.05 # impactScore below this = underperformer
|
||||
|
||||
# ── LLM Generation Settings (Coach — Ollama fallback) ─────────────
|
||||
# ── LLM Generation Settings (Coach — Ollama) ──────────────
|
||||
DEFAULT_TEMPERATURE = 0.7
|
||||
DEFAULT_MAX_TOKENS = 16384
|
||||
# DeepSeek-R1 uses <think> reasoning tokens before the JSON output,
|
||||
# so we need a generous limit to avoid truncation
|
||||
DEFAULT_MAX_TOKENS = 8192
|
||||
|
||||
# ── Anthropic Claude Deck Generation Settings ──────────────────────
|
||||
# Provider for deck generation: "anthropic" (Claude) or "local" (Ollama)
|
||||
DECK_GEN_PROVIDER = os.environ.get("DECK_GEN_PROVIDER", "anthropic")
|
||||
# Model used when DECK_GEN_PROVIDER="anthropic"
|
||||
DECK_GEN_MODEL = os.environ.get("DECK_GEN_MODEL", "claude-opus-4-20250514")
|
||||
# Anthropic API key
|
||||
ANTHROPIC_API_KEY = os.environ.get("ANTHROPIC_API_KEY", "")
|
||||
# Anthropic model for deck generation and coaching
|
||||
ANTHROPIC_MODEL = os.environ.get("ANTHROPIC_MODEL", "claude-opus-4-20250514")
|
||||
# Coach chat provider: "anthropic" (Claude API) or "local" (Ollama)
|
||||
COACH_PROVIDER = os.environ.get("COACH_PROVIDER", "anthropic")
|
||||
DECK_GEN_BASE_URL = os.environ.get("DECK_GEN_BASE_URL", "http://localhost:11434/v1")
|
||||
# ── Perplexity Deck Generation Settings ───────────────────────
|
||||
# Provider for deck generation: "perplexity" (V3) or "local" (V2 collection-based)
|
||||
DECK_GEN_PROVIDER = os.environ.get("DECK_GEN_PROVIDER", "local")
|
||||
# Model for deck generation (sonar = fast/$0.004, sonar-pro = deep/$0.04)
|
||||
DECK_GEN_MODEL = os.environ.get("DECK_GEN_MODEL", "gpt-oss:20b")
|
||||
DECK_GEN_BASE_URL = os.environ.get("DECK_GEN_BASE_URL", "http://192.168.0.240:11434/v1")
|
||||
DECK_GEN_TEMPERATURE = float(os.environ.get("DECK_GEN_TEMPERATURE", "0.2"))
|
||||
DECK_GEN_MAX_TOKENS = int(os.environ.get("DECK_GEN_MAX_TOKENS", "16384"))
|
||||
|
||||
# ── Smart Substitution Settings ───────────────────────────────────
|
||||
# Minimum embedding similarity to accept a substitute without Anthropic fallback
|
||||
# ── Smart Substitution Settings ───────────────────────────────
|
||||
# Minimum embedding similarity to accept a substitute without Perplexity fallback
|
||||
SUBSTITUTION_MIN_SIMILARITY = float(os.environ.get("SUBSTITUTION_MIN_SIMILARITY", "0.75"))
|
||||
# Maximum number of alternatives to suggest per missing card
|
||||
SUBSTITUTION_MAX_ALTERNATIVES = int(os.environ.get("SUBSTITUTION_MAX_ALTERNATIVES", "5"))
|
||||
# Model for substitution fallback (claude-haiku-4-5 is fast + cheap for focused queries)
|
||||
SUBSTITUTION_MODEL = os.environ.get("SUBSTITUTION_MODEL", "claude-haiku-4-5")
|
||||
# Enable Anthropic fallback for low-confidence embedding matches
|
||||
SUBSTITUTION_USE_ANTHROPIC_FALLBACK = os.environ.get("SUBSTITUTION_USE_ANTHROPIC_FALLBACK", "true").lower() == "true"
|
||||
# Model for substitution fallback (sonar is fine — small focused queries)
|
||||
SUBSTITUTION_MODEL = os.environ.get("SUBSTITUTION_MODEL", "gpt-oss:20b")
|
||||
# Enable Perplexity fallback for low-confidence embedding matches
|
||||
SUBSTITUTION_USE_PPLX_FALLBACK = os.environ.get("SUBSTITUTION_USE_PPLX_FALLBACK", "true").lower() == "true"
|
||||
|
||||
# ── Ensure directories exist ─────────────────────────────────────
|
||||
# ── Ensure directories exist ───────────────────────────────
|
||||
def ensure_dirs():
|
||||
"""Create required directories if they don't exist."""
|
||||
EMBEDDINGS_DIR.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
+41
-229
@@ -9,11 +9,6 @@ Data source: https://huggingface.co/datasets/minimaxir/mtg-embeddings
|
||||
Format: Parquet with 768-dim float32 embeddings per card (~32K cards)
|
||||
Model: Alibaba-NLP/gte-modernbert-base
|
||||
|
||||
Unknown cards (e.g. newly printed sets) are fetched from Scryfall,
|
||||
embedded on-the-fly using the same model, and persisted to a local
|
||||
custom cache (embeddings/mtg_embeddings_custom.npz) so they survive
|
||||
restarts without re-hitting Scryfall.
|
||||
|
||||
Uses NumPy brute-force cosine similarity — fast enough for ~32K cards (<100ms).
|
||||
"""
|
||||
|
||||
@@ -24,11 +19,9 @@ import os
|
||||
from pathlib import Path
|
||||
from typing import List, Optional, Tuple
|
||||
from urllib.request import urlopen, Request
|
||||
from urllib.parse import quote
|
||||
|
||||
import numpy as np
|
||||
|
||||
from services.card_text import build_card_text
|
||||
from .config import EMBEDDINGS_DIR, EMBEDDINGS_NPZ, EMBEDDINGS_PARQUET
|
||||
|
||||
logger = logging.getLogger("coach.embeddings")
|
||||
@@ -39,16 +32,8 @@ HF_PARQUET_URL = (
|
||||
"resolve/main/mtg_embeddings.parquet"
|
||||
)
|
||||
|
||||
# ── Scryfall API ───────────────────────────────────────────
|
||||
SCRYFALL_NAMED_URL = "https://api.scryfall.com/cards/named?fuzzy={}"
|
||||
|
||||
# ── Custom cache for on-the-fly embedded cards ─────────────
|
||||
CUSTOM_CACHE_PATH = EMBEDDINGS_DIR / "mtg_embeddings_custom.npz"
|
||||
|
||||
# ── Embedding model (same as minimaxir/mtg-embeddings) ─────
|
||||
EMBEDDING_MODEL = "Alibaba-NLP/gte-modernbert-base"
|
||||
|
||||
# ── Color identity parsing ─────────────────────────────────
|
||||
# Maps mana symbols like {W}, {U}, {B}, {R}, {G} to color letters
|
||||
MANA_SYMBOL_COLORS = {
|
||||
"W": "W", "U": "U", "B": "B", "R": "R", "G": "G"
|
||||
}
|
||||
@@ -61,6 +46,7 @@ def _parse_color_identity(mana_cost: str) -> str:
|
||||
colors = set()
|
||||
for match in re.finditer(r'\{([WUBRG])\}', mana_cost or ""):
|
||||
colors.add(match.group(1))
|
||||
# Sort in WUBRG order
|
||||
order = "WUBRG"
|
||||
return "".join(c for c in order if c in colors)
|
||||
|
||||
@@ -75,11 +61,12 @@ def _parse_mana_value(mana_cost: str) -> float:
|
||||
if symbol in MANA_SYMBOL_COLORS:
|
||||
total += 1.0
|
||||
elif symbol == "X":
|
||||
pass
|
||||
pass # X = 0 for CMC purposes
|
||||
else:
|
||||
try:
|
||||
total += float(symbol)
|
||||
except ValueError:
|
||||
# Hybrid/phyrexian symbols count as 1
|
||||
total += 1.0
|
||||
return total
|
||||
|
||||
@@ -88,35 +75,7 @@ def _is_color_subset(card_colors: str, deck_colors: List[str]) -> bool:
|
||||
"""Check if card's color identity is within deck's color identity."""
|
||||
deck_set = set(deck_colors)
|
||||
card_set = set(card_colors)
|
||||
return card_set.issubset(deck_set) or len(card_set) == 0
|
||||
|
||||
|
||||
def _fetch_scryfall_card(card_name: str) -> Optional[dict]:
|
||||
"""Fetch card data from Scryfall by fuzzy name match.
|
||||
|
||||
Returns a dict with keys: name, mana_cost, type_line, oracle_text,
|
||||
color_identity. Returns None on any error.
|
||||
"""
|
||||
url = SCRYFALL_NAMED_URL.format(quote(card_name))
|
||||
try:
|
||||
req = Request(url, headers={"User-Agent": "commander-ai-lab/1.0"})
|
||||
with urlopen(req, timeout=10) as resp:
|
||||
data = json.loads(resp.read().decode("utf-8"))
|
||||
return {
|
||||
"name": data.get("name", card_name),
|
||||
"mana_cost": data.get("mana_cost", ""),
|
||||
"type_line": data.get("type_line", ""),
|
||||
"oracle_text": data.get("oracle_text", ""),
|
||||
"color_identity": "".join(data.get("color_identity", [])),
|
||||
}
|
||||
except Exception as e:
|
||||
logger.warning("Scryfall lookup failed for '%s': %s", card_name, e)
|
||||
return None
|
||||
|
||||
|
||||
def _build_card_text(card: dict) -> str:
|
||||
"""Delegate to shared build_card_text() -- see services/card_text.py."""
|
||||
return build_card_text(card)
|
||||
return card_set.issubset(deck_set) or len(card_set) == 0 # colorless always allowed
|
||||
|
||||
|
||||
class CardMatch:
|
||||
@@ -155,17 +114,15 @@ class MTGEmbeddingIndex:
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
self.names: np.ndarray = None
|
||||
self.colors: np.ndarray = None
|
||||
self.mana_values: np.ndarray = None
|
||||
self.types: np.ndarray = None
|
||||
self.mana_costs: np.ndarray = None
|
||||
self.texts: np.ndarray = None
|
||||
self.vectors: np.ndarray = None
|
||||
self.names: np.ndarray = None # (N,) string array
|
||||
self.colors: np.ndarray = None # (N,) string array (e.g., "WU", "BRG")
|
||||
self.mana_values: np.ndarray = None # (N,) float array
|
||||
self.types: np.ndarray = None # (N,) string array
|
||||
self.mana_costs: np.ndarray = None # (N,) string array
|
||||
self.texts: np.ndarray = None # (N,) string array
|
||||
self.vectors: np.ndarray = None # (N, 768) float32, L2-normalized
|
||||
self._name_to_idx: dict = {}
|
||||
self._loaded = False
|
||||
self._sentence_model = None # lazy-loaded only when needed
|
||||
self._custom_dirty = False # tracks whether custom cache needs saving
|
||||
|
||||
@property
|
||||
def loaded(self) -> bool:
|
||||
@@ -195,7 +152,10 @@ class MTGEmbeddingIndex:
|
||||
return EMBEDDINGS_PARQUET
|
||||
|
||||
def convert_parquet_to_npz(self) -> Path:
|
||||
"""Convert the Parquet file to a compact NPZ for fast loading."""
|
||||
"""
|
||||
Convert the Parquet file to a compact NPZ for fast loading.
|
||||
Requires pandas and pyarrow.
|
||||
"""
|
||||
try:
|
||||
import pandas as pd
|
||||
except ImportError:
|
||||
@@ -209,11 +169,14 @@ class MTGEmbeddingIndex:
|
||||
types = df["type"].fillna("").values.astype(str)
|
||||
texts = df["text"].fillna("").values.astype(str)
|
||||
|
||||
# Parse color identities from mana costs
|
||||
colors = np.array([_parse_color_identity(mc) for mc in mana_costs])
|
||||
mana_values = np.array([_parse_mana_value(mc) for mc in mana_costs], dtype=np.float32)
|
||||
|
||||
# Extract embedding vectors
|
||||
embeddings = np.vstack(df["embedding"].to_numpy()).astype(np.float32)
|
||||
|
||||
# L2 normalize for cosine similarity via dot product
|
||||
norms = np.linalg.norm(embeddings, axis=1, keepdims=True)
|
||||
norms[norms == 0] = 1.0
|
||||
embeddings = embeddings / norms
|
||||
@@ -235,27 +198,25 @@ class MTGEmbeddingIndex:
|
||||
return EMBEDDINGS_NPZ
|
||||
|
||||
def load(self, force_download: bool = False) -> bool:
|
||||
"""Load embeddings from NPZ (fast) or fall back to downloading
|
||||
"""
|
||||
Load embeddings from NPZ (fast) or fall back to downloading
|
||||
and converting from Parquet.
|
||||
"""
|
||||
if self._loaded and not force_download:
|
||||
return True
|
||||
|
||||
# Try NPZ first (fast path)
|
||||
if EMBEDDINGS_NPZ.exists() and not force_download:
|
||||
ok = self._load_npz()
|
||||
else:
|
||||
try:
|
||||
self.download_parquet(force=force_download)
|
||||
self.convert_parquet_to_npz()
|
||||
ok = self._load_npz()
|
||||
except Exception as e:
|
||||
logger.error("Failed to load embeddings: %s", e)
|
||||
return False
|
||||
return self._load_npz()
|
||||
|
||||
if ok:
|
||||
self._load_custom_cache()
|
||||
|
||||
return ok
|
||||
# Download and convert
|
||||
try:
|
||||
self.download_parquet(force=force_download)
|
||||
self.convert_parquet_to_npz()
|
||||
return self._load_npz()
|
||||
except Exception as e:
|
||||
logger.error("Failed to load embeddings: %s", e)
|
||||
return False
|
||||
|
||||
def _load_npz(self) -> bool:
|
||||
"""Load from pre-built NPZ file."""
|
||||
@@ -269,6 +230,7 @@ class MTGEmbeddingIndex:
|
||||
self.texts = data.get("texts", np.array([""] * len(self.names)))
|
||||
self.vectors = data["vectors"]
|
||||
|
||||
# Build name lookup
|
||||
self._name_to_idx = {
|
||||
name.lower(): i for i, name in enumerate(self.names)
|
||||
}
|
||||
@@ -279,168 +241,12 @@ class MTGEmbeddingIndex:
|
||||
logger.error("Failed to load NPZ: %s", e)
|
||||
return False
|
||||
|
||||
# ── Custom cache ──────────────────────────────────────────
|
||||
|
||||
def _load_custom_cache(self) -> None:
|
||||
"""Merge on-the-fly embedded cards from the custom cache into the index."""
|
||||
if not CUSTOM_CACHE_PATH.exists():
|
||||
return
|
||||
try:
|
||||
data = np.load(str(CUSTOM_CACHE_PATH), allow_pickle=True)
|
||||
c_names = data["names"]
|
||||
# Only add cards that aren't already in the main index
|
||||
new_mask = np.array(
|
||||
[n.lower() not in self._name_to_idx for n in c_names]
|
||||
)
|
||||
if not new_mask.any():
|
||||
return
|
||||
self._append_cards(
|
||||
c_names[new_mask],
|
||||
data["colors"][new_mask],
|
||||
data["mana_values"][new_mask],
|
||||
data["types"][new_mask],
|
||||
data["mana_costs"][new_mask],
|
||||
data["texts"][new_mask],
|
||||
data["vectors"][new_mask],
|
||||
)
|
||||
logger.info("Loaded %d custom-cached card embeddings", new_mask.sum())
|
||||
except Exception as e:
|
||||
logger.warning("Failed to load custom embedding cache: %s", e)
|
||||
|
||||
def _save_custom_cache(self) -> None:
|
||||
"""Persist the custom cache NPZ (only cards not in the base dataset)."""
|
||||
if not self._custom_dirty:
|
||||
return
|
||||
try:
|
||||
EMBEDDINGS_DIR.mkdir(parents=True, exist_ok=True)
|
||||
# Collect indices that correspond to custom-added cards
|
||||
# We track these by loading the base count at load time — simpler:
|
||||
# just re-save the full custom cache from CUSTOM_CACHE_PATH if it
|
||||
# exists, merging with any new cards we've added this session.
|
||||
existing_names: set = set()
|
||||
existing: dict = {}
|
||||
if CUSTOM_CACHE_PATH.exists():
|
||||
try:
|
||||
d = np.load(str(CUSTOM_CACHE_PATH), allow_pickle=True)
|
||||
for n in d["names"]:
|
||||
existing_names.add(n.lower())
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# Find names in our live index that aren't in the base NPZ
|
||||
base_data = np.load(str(EMBEDDINGS_NPZ), allow_pickle=True)
|
||||
base_names = set(n.lower() for n in base_data["names"])
|
||||
custom_mask = np.array(
|
||||
[n.lower() not in base_names for n in self.names]
|
||||
)
|
||||
if not custom_mask.any():
|
||||
return
|
||||
|
||||
np.savez_compressed(
|
||||
str(CUSTOM_CACHE_PATH),
|
||||
names=self.names[custom_mask],
|
||||
colors=self.colors[custom_mask],
|
||||
mana_values=self.mana_values[custom_mask],
|
||||
types=self.types[custom_mask],
|
||||
mana_costs=self.mana_costs[custom_mask],
|
||||
texts=self.texts[custom_mask],
|
||||
vectors=self.vectors[custom_mask],
|
||||
)
|
||||
self._custom_dirty = False
|
||||
logger.info("Saved custom embedding cache: %d cards", custom_mask.sum())
|
||||
except Exception as e:
|
||||
logger.warning("Failed to save custom embedding cache: %s", e)
|
||||
|
||||
def _append_cards(
|
||||
self,
|
||||
names: np.ndarray,
|
||||
colors: np.ndarray,
|
||||
mana_values: np.ndarray,
|
||||
types: np.ndarray,
|
||||
mana_costs: np.ndarray,
|
||||
texts: np.ndarray,
|
||||
vectors: np.ndarray,
|
||||
) -> None:
|
||||
"""Append new card arrays to the live in-memory index."""
|
||||
start_idx = len(self.names)
|
||||
self.names = np.concatenate([self.names, names])
|
||||
self.colors = np.concatenate([self.colors, colors])
|
||||
self.mana_values = np.concatenate([self.mana_values, mana_values])
|
||||
self.types = np.concatenate([self.types, types])
|
||||
self.mana_costs = np.concatenate([self.mana_costs, mana_costs])
|
||||
self.texts = np.concatenate([self.texts, texts])
|
||||
self.vectors = np.concatenate([self.vectors, vectors], axis=0)
|
||||
for i, name in enumerate(names):
|
||||
self._name_to_idx[name.lower()] = start_idx + i
|
||||
|
||||
# ── Sentence model (lazy) ─────────────────────────────────
|
||||
|
||||
def _get_sentence_model(self):
|
||||
"""Lazy-load the sentence-transformers model on first cache miss."""
|
||||
if self._sentence_model is None:
|
||||
try:
|
||||
from sentence_transformers import SentenceTransformer
|
||||
logger.info("Loading embedding model %s (first cache miss)...", EMBEDDING_MODEL)
|
||||
self._sentence_model = SentenceTransformer(EMBEDDING_MODEL)
|
||||
logger.info("Embedding model loaded.")
|
||||
except Exception as e:
|
||||
logger.error("Failed to load SentenceTransformer: %s", e)
|
||||
return None
|
||||
return self._sentence_model
|
||||
|
||||
# ── On-the-fly Scryfall fallback ──────────────────────────
|
||||
|
||||
def _fetch_and_embed_card(self, card_name: str) -> Optional[np.ndarray]:
|
||||
"""Fetch card from Scryfall, embed it, append to index, persist to cache.
|
||||
|
||||
Returns the L2-normalized embedding vector on success, None on failure.
|
||||
"""
|
||||
logger.info("Fetching unknown card from Scryfall: '%s'", card_name)
|
||||
card_data = _fetch_scryfall_card(card_name)
|
||||
if card_data is None:
|
||||
return None
|
||||
|
||||
model = self._get_sentence_model()
|
||||
if model is None:
|
||||
return None
|
||||
|
||||
text = _build_card_text(card_data)
|
||||
vec = model.encode(text, normalize_embeddings=True).astype(np.float32)
|
||||
# Ensure shape (1, 768)
|
||||
vec = vec.reshape(1, -1)
|
||||
|
||||
resolved_name = card_data["name"]
|
||||
mana_cost = card_data.get("mana_cost", "")
|
||||
color_identity = card_data.get("color_identity", "") or _parse_color_identity(mana_cost)
|
||||
|
||||
self._append_cards(
|
||||
names=np.array([resolved_name]),
|
||||
colors=np.array([color_identity]),
|
||||
mana_values=np.array([_parse_mana_value(mana_cost)], dtype=np.float32),
|
||||
types=np.array([card_data.get("type_line", "")]),
|
||||
mana_costs=np.array([mana_cost]),
|
||||
texts=np.array([card_data.get("oracle_text", "")]),
|
||||
vectors=vec,
|
||||
)
|
||||
|
||||
self._custom_dirty = True
|
||||
self._save_custom_cache()
|
||||
logger.info("Embedded and cached new card: '%s'", resolved_name)
|
||||
return self.vectors[self._name_to_idx[resolved_name.lower()]]
|
||||
|
||||
# ── Public API ────────────────────────────────────────────
|
||||
|
||||
def get_card_vector(self, card_name: str) -> Optional[np.ndarray]:
|
||||
"""Get the embedding vector for a card by name (case-insensitive).
|
||||
|
||||
On a cache miss, fetches from Scryfall and embeds on the fly.
|
||||
"""
|
||||
"""Get the embedding vector for a card by name (case-insensitive)."""
|
||||
idx = self._name_to_idx.get(card_name.lower())
|
||||
if idx is not None:
|
||||
return self.vectors[idx]
|
||||
|
||||
# Cache miss — try Scryfall fallback
|
||||
return self._fetch_and_embed_card(card_name)
|
||||
return None
|
||||
|
||||
def search_similar(self, query_card: str,
|
||||
color_filter: List[str] = None,
|
||||
@@ -468,32 +274,38 @@ class MTGEmbeddingIndex:
|
||||
|
||||
query_vec = self.get_card_vector(query_card)
|
||||
if query_vec is None:
|
||||
logger.warning("Card not found in embeddings and Scryfall fallback failed: %s", query_card)
|
||||
logger.warning("Card not found in embeddings: %s", query_card)
|
||||
return []
|
||||
|
||||
# Compute similarities (dot product on normalized vectors = cosine similarity)
|
||||
similarities = self.vectors @ query_vec
|
||||
|
||||
# Build exclusion set
|
||||
exclude_set = set()
|
||||
exclude_set.add(query_card.lower())
|
||||
if exclude_cards:
|
||||
exclude_set.update(name.lower() for name in exclude_cards)
|
||||
|
||||
# Filter and collect results
|
||||
results = []
|
||||
for idx in np.argsort(similarities)[::-1]:
|
||||
name = str(self.names[idx])
|
||||
if name.lower() in exclude_set:
|
||||
continue
|
||||
|
||||
# Color filter
|
||||
if color_filter:
|
||||
card_colors = str(self.colors[idx])
|
||||
if not _is_color_subset(card_colors, color_filter):
|
||||
continue
|
||||
|
||||
# Type filter
|
||||
if type_filter:
|
||||
card_type = str(self.types[idx])
|
||||
if type_filter.lower() not in card_type.lower():
|
||||
continue
|
||||
|
||||
# Mana value range filter
|
||||
if mana_range:
|
||||
mv = float(self.mana_values[idx])
|
||||
if mv < mana_range[0] or mv > mana_range[1]:
|
||||
|
||||
+130
-127
@@ -1,25 +1,22 @@
|
||||
"""
|
||||
Commander AI Lab — Ollama LLM Client
|
||||
Commander AI Lab — Ollama Client
|
||||
════════════════════════════════════
|
||||
Fully async HTTP client targeting Ollama's OpenAI-compatible
|
||||
/v1/chat/completions endpoint. Every network call uses
|
||||
httpx.AsyncClient so it NEVER blocks the FastAPI event loop.
|
||||
Async HTTP client targeting Ollama's OpenAI-compatible
|
||||
/v1/chat/completions endpoint. Includes retry logic for
|
||||
non-JSON responses and configurable timeout.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import asyncio
|
||||
from typing import Optional
|
||||
|
||||
import httpx
|
||||
from urllib.request import urlopen, Request
|
||||
from urllib.error import URLError
|
||||
|
||||
from .config import (
|
||||
LLM_URL,
|
||||
LLM_MODEL,
|
||||
LLM_TIMEOUT,
|
||||
LLM_MAX_RETRIES,
|
||||
DEFAULT_TEMPERATURE,
|
||||
DEFAULT_MAX_TOKENS,
|
||||
LLM_URL, LLM_MODEL,
|
||||
LLM_TIMEOUT, LLM_MAX_RETRIES,
|
||||
DEFAULT_TEMPERATURE, DEFAULT_MAX_TOKENS,
|
||||
)
|
||||
|
||||
logger = logging.getLogger("coach.llm")
|
||||
@@ -27,15 +24,9 @@ logger = logging.getLogger("coach.llm")
|
||||
|
||||
class LLMResponse:
|
||||
"""Parsed LLM response container."""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
content: str,
|
||||
parsed_json: Optional[dict],
|
||||
prompt_tokens: int,
|
||||
completion_tokens: int,
|
||||
model: str,
|
||||
):
|
||||
def __init__(self, content: str, parsed_json: Optional[dict],
|
||||
prompt_tokens: int, completion_tokens: int,
|
||||
model: str):
|
||||
self.content = content
|
||||
self.parsed_json = parsed_json
|
||||
self.prompt_tokens = prompt_tokens
|
||||
@@ -45,7 +36,7 @@ class LLMResponse:
|
||||
|
||||
class LLMClient:
|
||||
"""
|
||||
Fully async client for Ollama's OpenAI-compatible API.
|
||||
Client for Ollama's OpenAI-compatible API.
|
||||
|
||||
Usage:
|
||||
client = LLMClient()
|
||||
@@ -54,25 +45,19 @@ class LLMClient:
|
||||
suggestions = response.parsed_json
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
base_url: str = None,
|
||||
model: str = None,
|
||||
timeout: int = None,
|
||||
):
|
||||
def __init__(self, base_url: str = None, model: str = None,
|
||||
timeout: int = None):
|
||||
self.base_url = (base_url or LLM_URL).rstrip("/")
|
||||
self.model = model or LLM_MODEL
|
||||
self.timeout = timeout or LLM_TIMEOUT
|
||||
self._resolved_model: Optional[str] = None
|
||||
self._resolved_model = None # actual model name from /models endpoint
|
||||
|
||||
# ── Model resolution ───────────────────────────────────────
|
||||
|
||||
async def _resolve_model(self) -> str:
|
||||
def _resolve_model(self) -> str:
|
||||
"""Get the actual loaded model name from Ollama /models endpoint."""
|
||||
if self._resolved_model:
|
||||
return self._resolved_model
|
||||
try:
|
||||
status = await self.check_connection()
|
||||
status = self.check_connection()
|
||||
if status.get("connected") and status.get("active_model"):
|
||||
self._resolved_model = status["active_model"]
|
||||
logger.info("Resolved Ollama model: %s", self._resolved_model)
|
||||
@@ -81,18 +66,11 @@ class LLMClient:
|
||||
pass
|
||||
return self.model
|
||||
|
||||
# ── Request building ──────────────────────────────────────
|
||||
|
||||
async def _build_request_body(
|
||||
self,
|
||||
system_prompt: str,
|
||||
user_prompt: str,
|
||||
temperature: float,
|
||||
max_tokens: int,
|
||||
force_json: bool,
|
||||
) -> dict:
|
||||
model_name = await self._resolve_model()
|
||||
body: dict = {
|
||||
def _build_request_body(self, system_prompt: str, user_prompt: str,
|
||||
temperature: float, max_tokens: int,
|
||||
force_json: bool) -> dict:
|
||||
model_name = self._resolve_model()
|
||||
body = {
|
||||
"model": model_name,
|
||||
"messages": [
|
||||
{"role": "system", "content": system_prompt},
|
||||
@@ -101,27 +79,32 @@ class LLMClient:
|
||||
"temperature": temperature,
|
||||
"max_tokens": max_tokens,
|
||||
}
|
||||
# Only request JSON format if using a model that supports it
|
||||
# Some models (esp. smaller ones) don't support response_format
|
||||
if force_json:
|
||||
body["response_format"] = {"type": "json_object"}
|
||||
return body
|
||||
|
||||
# ── Response parsing ──────────────────────────────────────
|
||||
|
||||
@staticmethod
|
||||
def _strip_think_tags(text: str) -> str:
|
||||
"""Remove DeepSeek-R1 <think>...</think> reasoning blocks."""
|
||||
"""Remove DeepSeek-R1 <think>...</think> reasoning blocks from LLM output."""
|
||||
import re
|
||||
return re.sub(r'<think>.*?</think>', '', text, flags=re.DOTALL).strip()
|
||||
# Remove all <think>...</think> blocks (greedy, handles multiline)
|
||||
cleaned = re.sub(r'<think>.*?</think>', '', text, flags=re.DOTALL)
|
||||
return cleaned.strip()
|
||||
|
||||
@staticmethod
|
||||
def _extract_json_object(text: str) -> Optional[dict]:
|
||||
"""Find and parse the first complete JSON object via brace-counting."""
|
||||
"""Find and parse the first complete JSON object in text.
|
||||
Uses brace-counting to handle nested objects reliably."""
|
||||
start = text.find('{')
|
||||
if start == -1:
|
||||
return None
|
||||
|
||||
depth = 0
|
||||
in_string = False
|
||||
escape_next = False
|
||||
|
||||
for i in range(start, len(text)):
|
||||
ch = text[i]
|
||||
if escape_next:
|
||||
@@ -141,56 +124,66 @@ class LLMClient:
|
||||
elif ch == '}':
|
||||
depth -= 1
|
||||
if depth == 0:
|
||||
candidate = text[start : i + 1]
|
||||
candidate = text[start:i+1]
|
||||
try:
|
||||
return json.loads(candidate)
|
||||
except (json.JSONDecodeError, ValueError):
|
||||
# Malformed — try next opening brace
|
||||
next_start = text.find('{', start + 1)
|
||||
if next_start != -1 and next_start < i:
|
||||
start = next_start
|
||||
depth = 1
|
||||
return None
|
||||
depth = 1 # we're already past this brace
|
||||
return None
|
||||
return None
|
||||
|
||||
def _parse_response(self, raw: dict) -> LLMResponse:
|
||||
"""Extract content and usage from an OpenAI-format response."""
|
||||
"""Extract content and usage from OpenAI-format response.
|
||||
Handles DeepSeek-R1 <think> tags, markdown fences, and raw JSON."""
|
||||
choice = raw.get("choices", [{}])[0]
|
||||
content = choice.get("message", {}).get("content", "")
|
||||
usage = raw.get("usage", {})
|
||||
|
||||
# Step 1: Strip <think>...</think> blocks (DeepSeek-R1)
|
||||
cleaned = self._strip_think_tags(content)
|
||||
parsed: Optional[dict] = None
|
||||
# 1. Direct JSON parse
|
||||
|
||||
# Step 2: Try direct JSON parse on cleaned content
|
||||
parsed = None
|
||||
try:
|
||||
parsed = json.loads(cleaned)
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
pass
|
||||
# 2. Markdown fences
|
||||
|
||||
# Step 3: Try extracting from markdown fences
|
||||
if parsed is None and "```json" in cleaned:
|
||||
try:
|
||||
s = cleaned.index("```json") + 7
|
||||
e = cleaned.index("```", s)
|
||||
parsed = json.loads(cleaned[s:e].strip())
|
||||
start = cleaned.index("```json") + 7
|
||||
end = cleaned.index("```", start)
|
||||
parsed = json.loads(cleaned[start:end].strip())
|
||||
except (json.JSONDecodeError, ValueError, IndexError):
|
||||
pass
|
||||
if parsed is None and "```" in cleaned:
|
||||
try:
|
||||
s = cleaned.index("```") + 3
|
||||
e = cleaned.index("```", s)
|
||||
parsed = json.loads(cleaned[s:e].strip())
|
||||
start = cleaned.index("```") + 3
|
||||
end = cleaned.index("```", start)
|
||||
parsed = json.loads(cleaned[start:end].strip())
|
||||
except (json.JSONDecodeError, ValueError, IndexError):
|
||||
pass
|
||||
# 3. Brace-counting extraction
|
||||
|
||||
# Step 4: Brute-force — find the first valid JSON object in the text
|
||||
if parsed is None:
|
||||
parsed = self._extract_json_object(cleaned)
|
||||
# 4. Fallback on original content
|
||||
|
||||
# Step 5: If still nothing, try on the original content (in case
|
||||
# think-tag stripping was too aggressive)
|
||||
if parsed is None and content != cleaned:
|
||||
parsed = self._extract_json_object(content)
|
||||
|
||||
if parsed is not None:
|
||||
logger.info("Successfully parsed JSON from LLM response")
|
||||
else:
|
||||
logger.warning(
|
||||
"Could not extract JSON from LLM response (%d chars)", len(content)
|
||||
)
|
||||
logger.warning("Could not extract JSON from LLM response (%d chars)",
|
||||
len(content))
|
||||
|
||||
return LLMResponse(
|
||||
content=content,
|
||||
parsed_json=parsed,
|
||||
@@ -199,84 +192,94 @@ class LLMClient:
|
||||
model=raw.get("model", self.model),
|
||||
)
|
||||
|
||||
# ── Public API ─────────────────────────────────────────────
|
||||
|
||||
async def chat(
|
||||
self,
|
||||
system_prompt: str,
|
||||
user_prompt: str,
|
||||
temperature: float = None,
|
||||
max_tokens: int = None,
|
||||
force_json: bool = True,
|
||||
) -> LLMResponse:
|
||||
def chat_sync(self, system_prompt: str, user_prompt: str,
|
||||
temperature: float = None, max_tokens: int = None,
|
||||
force_json: bool = True) -> LLMResponse:
|
||||
"""
|
||||
Async chat call to Ollama. Retries up to LLM_MAX_RETRIES.
|
||||
Never blocks the event loop — uses httpx.AsyncClient throughout.
|
||||
Synchronous chat call to Ollama.
|
||||
Retries up to LLM_MAX_RETRIES on failure or non-JSON response.
|
||||
"""
|
||||
temp = temperature if temperature is not None else DEFAULT_TEMPERATURE
|
||||
tokens = max_tokens if max_tokens is not None else DEFAULT_MAX_TOKENS
|
||||
body = await self._build_request_body(
|
||||
system_prompt, user_prompt, temp, tokens, force_json
|
||||
)
|
||||
last_error: Optional[Exception] = None
|
||||
body = self._build_request_body(system_prompt, user_prompt,
|
||||
temp, tokens, force_json)
|
||||
|
||||
last_error = None
|
||||
for attempt in range(1, LLM_MAX_RETRIES + 1):
|
||||
try:
|
||||
logger.info("LLM call attempt %d/%d", attempt, LLM_MAX_RETRIES)
|
||||
async with httpx.AsyncClient(
|
||||
timeout=httpx.Timeout(float(self.timeout))
|
||||
) as client:
|
||||
resp = await client.post(
|
||||
f"{self.base_url}/chat/completions",
|
||||
json=body,
|
||||
headers={"Content-Type": "application/json"},
|
||||
)
|
||||
resp.raise_for_status()
|
||||
raw = resp.json()
|
||||
req = Request(
|
||||
f"{self.base_url}/chat/completions",
|
||||
data=json.dumps(body).encode("utf-8"),
|
||||
headers={"Content-Type": "application/json"},
|
||||
method="POST",
|
||||
)
|
||||
with urlopen(req, timeout=self.timeout) as resp:
|
||||
raw = json.loads(resp.read().decode("utf-8"))
|
||||
|
||||
result = self._parse_response(raw)
|
||||
|
||||
# If we need JSON and didn't get it, retry
|
||||
if force_json and result.parsed_json is None:
|
||||
logger.warning(
|
||||
"Attempt %d: LLM returned non-JSON, retrying", attempt
|
||||
)
|
||||
logger.warning("Attempt %d: LLM returned non-JSON, retrying", attempt)
|
||||
last_error = ValueError("Non-JSON response from LLM")
|
||||
continue
|
||||
|
||||
return result
|
||||
except httpx.HTTPStatusError as e:
|
||||
logger.warning("Attempt %d HTTP error %s", attempt, e.response.status_code)
|
||||
last_error = e
|
||||
# 400 with json format → retry without response_format constraint
|
||||
if e.response.status_code == 400 and force_json:
|
||||
logger.warning("Got 400 — retrying without response_format")
|
||||
force_json = False
|
||||
body = await self._build_request_body(
|
||||
system_prompt, user_prompt, temp, tokens, False
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.warning("Attempt %d failed: %s", attempt, e)
|
||||
last_error = e
|
||||
if attempt < LLM_MAX_RETRIES:
|
||||
import asyncio
|
||||
await asyncio.sleep(2 * attempt)
|
||||
|
||||
# If 400 and we used json response_format, retry without it
|
||||
error_str = str(e)
|
||||
if "400" in error_str and force_json:
|
||||
logger.warning("Got 400 — retrying without response_format constraint")
|
||||
force_json = False
|
||||
body = self._build_request_body(
|
||||
system_prompt, user_prompt, temp, tokens, False)
|
||||
|
||||
if attempt < LLM_MAX_RETRIES:
|
||||
import time
|
||||
time.sleep(2 * attempt) # Simple backoff
|
||||
|
||||
raise ConnectionError(
|
||||
f"LLM call failed after {LLM_MAX_RETRIES} attempts: {last_error}"
|
||||
)
|
||||
|
||||
async def check_connection(self) -> dict:
|
||||
"""Check if Ollama is reachable. Returns status dict."""
|
||||
async def chat(self, system_prompt: str, user_prompt: str,
|
||||
temperature: float = None, max_tokens: int = None,
|
||||
force_json: bool = True) -> LLMResponse:
|
||||
"""
|
||||
Async chat call — runs the sync call in a thread executor
|
||||
so it doesn't block the FastAPI event loop.
|
||||
"""
|
||||
loop = asyncio.get_event_loop()
|
||||
return await loop.run_in_executor(
|
||||
None,
|
||||
lambda: self.chat_sync(system_prompt, user_prompt,
|
||||
temperature, max_tokens, force_json)
|
||||
)
|
||||
|
||||
def check_connection(self) -> dict:
|
||||
"""
|
||||
Check if Ollama is reachable. Returns status dict.
|
||||
"""
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=httpx.Timeout(5.0)) as client:
|
||||
resp = await client.get(
|
||||
f"{self.base_url}/models",
|
||||
headers={"Content-Type": "application/json"},
|
||||
)
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
models = data.get("data", [])
|
||||
model_ids = [m.get("id", "unknown") for m in models]
|
||||
return {
|
||||
"connected": True,
|
||||
"models": model_ids,
|
||||
"active_model": model_ids[0] if model_ids else self.model,
|
||||
}
|
||||
req = Request(
|
||||
f"{self.base_url}/models",
|
||||
headers={"Content-Type": "application/json"},
|
||||
method="GET",
|
||||
)
|
||||
with urlopen(req, timeout=5) as resp:
|
||||
data = json.loads(resp.read().decode("utf-8"))
|
||||
models = data.get("data", [])
|
||||
model_ids = [m.get("id", "unknown") for m in models]
|
||||
return {
|
||||
"connected": True,
|
||||
"models": model_ids,
|
||||
"active_model": model_ids[0] if model_ids else self.model,
|
||||
}
|
||||
except Exception as e:
|
||||
return {
|
||||
"connected": False,
|
||||
|
||||
+17
-140
@@ -4,9 +4,12 @@ Commander AI Lab — Coach Data Models
|
||||
Pydantic v2 models for deck reports, coach requests/responses,
|
||||
and coaching session persistence.
|
||||
"""
|
||||
|
||||
from datetime import datetime
|
||||
from typing import List, Optional, Dict
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Deck Report Models (mirrors Java DeckReport)
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
@@ -14,16 +17,16 @@ from pydantic import BaseModel, Field
|
||||
class CardPerformance(BaseModel):
|
||||
"""Per-card aggregated stats from simulation data."""
|
||||
name: str
|
||||
drawnRate: float = 0.0
|
||||
castRate: float = 0.0
|
||||
drawnRate: float = 0.0 # Fraction of games where card was drawn
|
||||
castRate: float = 0.0 # Fraction of games where drawn AND cast
|
||||
keptInOpeningHandRate: float = 0.0
|
||||
deadCardRate: float = 0.0
|
||||
impactScore: float = 0.0
|
||||
synergyScore: float = 0.0
|
||||
clunkinessScore: float = 0.0
|
||||
deadCardRate: float = 0.0 # Drawn but never cast/used
|
||||
impactScore: float = 0.0 # (winRateWhenCast - overallWinRate) * castRate
|
||||
synergyScore: float = 0.0 # Co-occurrence uplift with other deck cards
|
||||
clunkinessScore: float = 0.0 # deadCardRate * (1 - castRate)
|
||||
avgTurnCast: Optional[float] = None
|
||||
avgDamageDealt: float = 0.0
|
||||
tags: List[str] = Field(default_factory=list)
|
||||
tags: List[str] = Field(default_factory=list) # ramp, draw, removal, etc.
|
||||
|
||||
|
||||
class MatchupRecord(BaseModel):
|
||||
@@ -45,7 +48,7 @@ class DeckMeta(BaseModel):
|
||||
class DeckStructure(BaseModel):
|
||||
"""Deck composition breakdown."""
|
||||
landCount: int = 0
|
||||
curveBuckets: List[int] = Field(default_factory=lambda: [0]*8)
|
||||
curveBuckets: List[int] = Field(default_factory=lambda: [0]*8) # CMC 0-7+
|
||||
cardTypeCounts: Dict[str, int] = Field(default_factory=dict)
|
||||
functionalCounts: Dict[str, int] = Field(default_factory=dict)
|
||||
|
||||
@@ -54,7 +57,7 @@ class ComboRecord(BaseModel):
|
||||
"""Known combo with performance data."""
|
||||
cardNames: List[str]
|
||||
winRateWhenAssembled: float = 0.0
|
||||
assemblyRate: float = 0.0
|
||||
assemblyRate: float = 0.0 # Fraction of games where all pieces drawn
|
||||
|
||||
|
||||
class DeckReport(BaseModel):
|
||||
@@ -81,10 +84,10 @@ class DeckReport(BaseModel):
|
||||
|
||||
class CoachGoals(BaseModel):
|
||||
"""User-specified coaching goals."""
|
||||
targetPowerLevel: Optional[int] = None
|
||||
metaFocus: Optional[str] = None
|
||||
budget: Optional[str] = None
|
||||
focusAreas: List[str] = Field(default_factory=list)
|
||||
targetPowerLevel: Optional[int] = None # 1-10
|
||||
metaFocus: Optional[str] = None # aggro, control, combo, midrange, stax
|
||||
budget: Optional[str] = None # budget, medium, no-limit
|
||||
focusAreas: List[str] = Field(default_factory=list) # e.g., ["ramp", "card draw"]
|
||||
|
||||
|
||||
class CoachRequest(BaseModel):
|
||||
@@ -104,120 +107,12 @@ class SuggestedCut(BaseModel):
|
||||
class SuggestedAdd(BaseModel):
|
||||
"""A card the coach suggests adding."""
|
||||
cardName: str
|
||||
role: str = ""
|
||||
role: str = "" # ramp, draw, removal, finisher, etc.
|
||||
reason: str = ""
|
||||
synergyWith: List[str] = Field(default_factory=list)
|
||||
estimatedManaValue: Optional[float] = None
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Phase 2: Structured Analysis Models
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class UpgradePriorityItem(BaseModel):
|
||||
"""A single prioritized cut/add swap ranked by expected impact."""
|
||||
rank: int
|
||||
cut: str
|
||||
add: str
|
||||
reasoning: str = ""
|
||||
expectedImpact: str = ""
|
||||
|
||||
|
||||
class CommanderDependency(BaseModel):
|
||||
"""How reliant the deck is on having the commander in play."""
|
||||
score: int = 5
|
||||
dependentCards: List[str] = Field(default_factory=list)
|
||||
recoveryPlan: str = ""
|
||||
|
||||
|
||||
class MulliganAnalysis(BaseModel):
|
||||
"""Opening hand keepability assessment."""
|
||||
estimatedKeepRate: str = ""
|
||||
worstOffenders: List[str] = Field(default_factory=list)
|
||||
recommendation: str = ""
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Phase 3: Qualitative Analysis Models
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class RemovalCoverage(BaseModel):
|
||||
"""Categorized removal package by permanent type."""
|
||||
creatures: str = ""
|
||||
artifacts: str = ""
|
||||
enchantments: str = ""
|
||||
planeswalkers: str = ""
|
||||
lands: str = ""
|
||||
massRemoval: str = ""
|
||||
gaps: List[str] = Field(default_factory=list)
|
||||
|
||||
|
||||
class RampQuality(BaseModel):
|
||||
"""Ramp package breakdown by subtype and fragility."""
|
||||
manaRocks: str = ""
|
||||
landFetch: str = ""
|
||||
manaDorks: str = ""
|
||||
costReducers: str = ""
|
||||
fragility: str = ""
|
||||
canReachFourByTurnThree: str = ""
|
||||
|
||||
|
||||
class DrawEngineProfile(BaseModel):
|
||||
"""Card draw sustainability analysis."""
|
||||
burstDraw: List[str] = Field(default_factory=list)
|
||||
repeatableEngines: List[str] = Field(default_factory=list)
|
||||
assessment: str = ""
|
||||
sustainability: str = ""
|
||||
|
||||
|
||||
class WinCondition(BaseModel):
|
||||
"""A named win condition with independence rating."""
|
||||
name: str
|
||||
cards: List[str] = Field(default_factory=list)
|
||||
independence: str = ""
|
||||
description: str = ""
|
||||
|
||||
|
||||
class AntiSynergyFlag(BaseModel):
|
||||
"""An internal conflict between cards in the deck."""
|
||||
cards: List[str] = Field(default_factory=list)
|
||||
conflict: str = ""
|
||||
severity: str = ""
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Phase 5: Pod Politics & Meta Awareness Models
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class PodPresence(BaseModel):
|
||||
"""Commander pod politics and threat assessment."""
|
||||
threatLevel: str = "" # early/medium/late/low
|
||||
politicalTools: List[str] = Field(default_factory=list)
|
||||
adversarialRating: str = "" # low/medium/high
|
||||
recommendation: str = ""
|
||||
|
||||
|
||||
class TempoAssessment(BaseModel):
|
||||
"""When the deck 'comes online' and whether that's fast enough."""
|
||||
peakTurn: int = 0
|
||||
profile: str = "" # early/mid/late
|
||||
survivalWindow: str = "" # Assessment of whether it survives to peak
|
||||
assessment: str = ""
|
||||
|
||||
|
||||
class MetaMatchup(BaseModel):
|
||||
"""Strategic reasoning about deck vs a meta archetype."""
|
||||
archetype: str # fast-combo, stax, control, aggro, etc.
|
||||
assessment: str = ""
|
||||
keyThreats: List[str] = Field(default_factory=list)
|
||||
keyAnswers: List[str] = Field(default_factory=list)
|
||||
overallRating: str = "" # favored/even/unfavored
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Coach Session (persisted result)
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class CoachSession(BaseModel):
|
||||
"""
|
||||
Complete coaching session result.
|
||||
@@ -236,24 +131,6 @@ class CoachSession(BaseModel):
|
||||
promptTokens: int = 0
|
||||
completionTokens: int = 0
|
||||
goals: Optional[CoachGoals] = None
|
||||
isQuickDigest: bool = False # True for quick digest, False for full analysis
|
||||
|
||||
# Phase 2: Structured analysis fields
|
||||
upgradePriority: List[UpgradePriorityItem] = Field(default_factory=list)
|
||||
commanderDependency: Optional[CommanderDependency] = None
|
||||
mulliganAnalysis: Optional[MulliganAnalysis] = None
|
||||
|
||||
# Phase 3: Qualitative analysis fields
|
||||
removalCoverage: Optional[RemovalCoverage] = None
|
||||
rampQuality: Optional[RampQuality] = None
|
||||
drawEngineProfile: Optional[DrawEngineProfile] = None
|
||||
winConditions: List[WinCondition] = Field(default_factory=list)
|
||||
antiSynergyFlags: List[AntiSynergyFlag] = Field(default_factory=list)
|
||||
|
||||
# Phase 5: Pod politics & meta
|
||||
podPresence: Optional[PodPresence] = None
|
||||
tempoAssessment: Optional[TempoAssessment] = None
|
||||
metaMatchups: List[MetaMatchup] = Field(default_factory=list)
|
||||
|
||||
|
||||
class ApplyRequest(BaseModel):
|
||||
|
||||
+129
-335
@@ -6,6 +6,7 @@ Injects deck report data, underperformer analysis, and
|
||||
candidate replacement cards into a structured template.
|
||||
"""
|
||||
|
||||
import json
|
||||
from typing import List, Dict, Optional
|
||||
|
||||
from .models import DeckReport, CoachGoals, CardPerformance
|
||||
@@ -26,186 +27,40 @@ RULES:
|
||||
- Base suggestions on the simulation data provided, not general "goodstuff" advice.
|
||||
- Consider mana curve, role balance (ramp, draw, removal, threats), and synergy.
|
||||
- When suggesting replacements, prefer cards that fill the same functional role.
|
||||
- IMPORTANT: Suggest 5-8 DIFFERENT cards to cut and 5-8 DIFFERENT cards to add.
|
||||
- IMPORTANT: Suggest 3-5 DIFFERENT cards to cut and 3-5 DIFFERENT cards to add.
|
||||
- Each suggested add MUST be a different card — never suggest the same card twice.
|
||||
- Vary your suggestions across different functional roles (ramp, draw, removal, threats, utility).
|
||||
- If the deck is missing a functional role (e.g., no card draw, no removal), prioritize adding cards for that role.
|
||||
- If candidate replacements are provided from embeddings search, prefer those over generic suggestions.
|
||||
- For each suggested cut, provide a DETAILED reason citing specific stats (impact score, cast rate, dead card rate, clunkiness, synergy score).
|
||||
- For each suggested add, explain the SPECIFIC synergy with existing cards in the deck.
|
||||
- When reasoning about cuts, also consider keptInOpeningHandRate (low = bad in opening hands) and avgTurnCast (high = too slow for the curve).
|
||||
- When evaluating synergy, use the synergyScore: cards below 0.1 have weak co-occurrence with the rest of the deck.
|
||||
- Use perArchetypeWinRates to identify which matchup types this deck struggles with and tailor suggestions accordingly.
|
||||
- Provide at least 5 heuristic hints covering different strategic dimensions.
|
||||
- Assess how dependent the deck is on the commander being in play.
|
||||
- Evaluate opening hand quality and identify cards that cause bad mulligans.
|
||||
- Rank your suggested swaps by priority so the user knows what to change first.
|
||||
- Categorize the removal package by permanent type and flag coverage gaps.
|
||||
- Evaluate the ramp package for fragility (creature/artifact-heavy vs land-based).
|
||||
- Distinguish one-time draw from repeatable draw engines.
|
||||
- Identify the top 3 win conditions and rate each for independence.
|
||||
- Flag internal anti-synergies or card conflicts.
|
||||
- Assess pod threat perception: does this deck draw too much hate too early?
|
||||
- Evaluate when the deck comes online (tempo profile) and whether that's viable.
|
||||
- Reason about matchups vs fast combo, stax/prison, and control archetypes.
|
||||
{goals_section}
|
||||
|
||||
You MUST respond ONLY with valid JSON matching this exact structure:
|
||||
{{
|
||||
"summary": "4-6 sentence detailed overview of the deck's strengths, weaknesses, key synergies, and strategic identity. Reference specific win rates and simulation data.",
|
||||
"summary": "2-3 sentence overview of the deck's strengths and weaknesses",
|
||||
"suggestedCuts": [
|
||||
{{
|
||||
"cardName": "Card To Remove",
|
||||
"reason": "Detailed explanation citing specific simulation stats (impact score, cast rate, dead card rate, clunkiness score, synergy score, avg turn cast) and why this card underperforms in this specific deck context",
|
||||
"replacementOptions": ["Better Card 1", "Better Card 2"],
|
||||
"functionalRole": "ramp|draw|removal|threat|utility|combo|protection",
|
||||
"estimatedImpact": "How cutting this card is expected to improve the deck"
|
||||
"reason": "Why this card underperforms",
|
||||
"replacementOptions": ["Better Card 1", "Better Card 2"]
|
||||
}}
|
||||
],
|
||||
"suggestedAdds": [
|
||||
{{
|
||||
"cardName": "Card To Add",
|
||||
"role": "ramp|draw|removal|threat|utility|combo|protection",
|
||||
"reason": "Detailed explanation of why this card improves the deck, referencing specific weaknesses it addresses",
|
||||
"synergyWith": ["Card In Deck 1", "Card In Deck 2"],
|
||||
"estimatedManaCost": "The mana value of the suggested card",
|
||||
"strategicRationale": "How this card fits into the overall game plan and addresses a specific gap"
|
||||
"reason": "Why this card improves the deck",
|
||||
"synergyWith": ["Card In Deck 1", "Card In Deck 2"]
|
||||
}}
|
||||
],
|
||||
"upgradePriority": [
|
||||
{{
|
||||
"rank": 1,
|
||||
"cut": "Card to remove",
|
||||
"add": "Card to add instead",
|
||||
"reasoning": "Why this is the single highest-impact swap",
|
||||
"expectedImpact": "high|medium|low"
|
||||
}}
|
||||
],
|
||||
"commanderDependency": {{
|
||||
"score": 5,
|
||||
"dependentCards": ["Card that is nearly dead without commander"],
|
||||
"recoveryPlan": "Strategy if the commander gets removed or tucked repeatedly"
|
||||
}},
|
||||
"mulliganAnalysis": {{
|
||||
"estimatedKeepRate": "Percentage estimate of keepable 7-card hands, e.g. ~70%",
|
||||
"worstOffenders": ["Card most responsible for unkeepable hands"],
|
||||
"recommendation": "What to change to improve opening hand quality"
|
||||
}},
|
||||
"manaCurveAnalysis": {{
|
||||
"currentAssessment": "Detailed analysis of the current mana curve distribution and its implications",
|
||||
"recommendations": "Specific suggestions for curve adjustments with reasoning",
|
||||
"idealRange": "What the curve should look like for this deck's strategy"
|
||||
}},
|
||||
"roleBreakdown": {{
|
||||
"ramp": "Assessment of ramp package - count, quality, and suggestions",
|
||||
"draw": "Assessment of card draw package",
|
||||
"removal": "Assessment of removal package",
|
||||
"threats": "Assessment of win conditions and threats",
|
||||
"protection": "Assessment of protection and interaction"
|
||||
}},
|
||||
"synergyAnalysis": [
|
||||
"Description of a key synergy chain in the deck and how well it performed in simulation"
|
||||
],
|
||||
"heuristicHints": [
|
||||
"Detailed strategic tip explaining the reasoning and data behind the suggestion"
|
||||
"Concise strategic tip based on data"
|
||||
],
|
||||
"manaBaseAdvice": "Specific mana base improvement suggestion including land count, color fixing, and utility lands, or null if mana base is solid",
|
||||
"rawTextExplanation": "3-5 paragraph in-depth analysis covering: (1) overall deck strategy assessment and how well the deck executes its game plan based on simulation data, (2) mana curve and resource analysis with specific numbers including avgTurnCast for key cards, (3) card synergy evaluation highlighting the strongest and weakest interactions using synergyScore data, (4) meta considerations and matchup-specific insights referencing perArchetypeWinRates, and (5) prioritized list of improvements ranked by expected impact on win rate",
|
||||
"removalCoverage": {{
|
||||
"creatures": "Assessment of creature removal",
|
||||
"artifacts": "Assessment of artifact removal",
|
||||
"enchantments": "Assessment of enchantment removal",
|
||||
"planeswalkers": "Assessment of planeswalker removal",
|
||||
"lands": "Assessment of land destruction",
|
||||
"massRemoval": "Assessment of board wipes",
|
||||
"gaps": ["Permanent types with zero or weak coverage"]
|
||||
}},
|
||||
"rampQuality": {{
|
||||
"manaRocks": "2-mana rocks, signets, etc.",
|
||||
"landFetch": "Cultivate, Kodama's Reach, etc.",
|
||||
"manaDorks": "Llanowar Elves, Birds, etc.",
|
||||
"costReducers": "Medallions, Helm of Awakening, etc.",
|
||||
"fragility": "Overall fragility assessment",
|
||||
"canReachFourByTurnThree": "yes/no with reasoning"
|
||||
}},
|
||||
"drawEngineProfile": {{
|
||||
"burstDraw": ["One-time draw spells"],
|
||||
"repeatableEngines": ["Sustained draw engines"],
|
||||
"assessment": "Overall draw quality",
|
||||
"sustainability": "Whether draw is sustainable or burst-only"
|
||||
}},
|
||||
"winConditions": [
|
||||
{{
|
||||
"name": "Name of win condition",
|
||||
"cards": ["Key cards involved"],
|
||||
"independence": "high|medium|low",
|
||||
"description": "How this win con functions"
|
||||
}}
|
||||
],
|
||||
"antiSynergyFlags": [
|
||||
{{
|
||||
"cards": ["Card A", "Card B"],
|
||||
"conflict": "Description of conflict",
|
||||
"severity": "high|medium|low"
|
||||
}}
|
||||
],
|
||||
"podPresence": {{
|
||||
"threatLevel": "early|medium|late|low",
|
||||
"politicalTools": ["Pillowfort or group effect cards"],
|
||||
"adversarialRating": "low|medium|high",
|
||||
"recommendation": "How to manage threat perception in a pod"
|
||||
}},
|
||||
"tempoAssessment": {{
|
||||
"peakTurn": 5,
|
||||
"profile": "early|mid|late",
|
||||
"survivalWindow": "Assessment of whether the deck survives to its power window",
|
||||
"assessment": "Overall tempo evaluation"
|
||||
}},
|
||||
"metaMatchups": [
|
||||
{{
|
||||
"archetype": "fast-combo|stax|control|aggro|midrange",
|
||||
"assessment": "How the deck fares against this archetype",
|
||||
"keyThreats": ["Cards/strategies that threaten this deck"],
|
||||
"keyAnswers": ["Cards in the deck that answer this archetype"],
|
||||
"overallRating": "favored|even|unfavored"
|
||||
}}
|
||||
]
|
||||
"manaBaseAdvice": "Specific mana base improvement suggestion or null",
|
||||
"rawTextExplanation": "Detailed paragraph explaining the analysis and reasoning"
|
||||
}}
|
||||
|
||||
Do NOT include any text outside the JSON object. No markdown fences, no preamble."""
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Quick Digest Prompt
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
QUICK_DIGEST_SYSTEM_PROMPT = """You are an expert Magic: The Gathering Commander deck coach.
|
||||
Provide a FAST summary analysis of this deck. Be concise.
|
||||
|
||||
RULES:
|
||||
- NEVER suggest cutting the commander ({commander}).
|
||||
- Only suggest cards within the deck's color identity: {color_identity}.
|
||||
{goals_section}
|
||||
|
||||
You MUST respond ONLY with valid JSON matching this exact structure:
|
||||
{{
|
||||
"summary": "3-sentence deck overview: what it does, main strength, main weakness.",
|
||||
"upgradePriority": [
|
||||
{{
|
||||
"rank": 1,
|
||||
"cut": "Card to remove",
|
||||
"add": "Card to add instead",
|
||||
"reasoning": "Why this is a high-impact swap",
|
||||
"expectedImpact": "high|medium|low"
|
||||
}}
|
||||
],
|
||||
"commanderDependency": {{
|
||||
"score": 5,
|
||||
"dependentCards": ["Card that is nearly dead without commander"],
|
||||
"recoveryPlan": "Brief recovery strategy"
|
||||
}}
|
||||
}}
|
||||
Do NOT include any text outside the JSON object. No markdown fences, no preamble."""
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# User Prompt Builder
|
||||
@@ -227,173 +82,124 @@ Avg Game Length: {avg_game_length:.1f} turns
|
||||
### Matchup Data
|
||||
{matchup_section}
|
||||
|
||||
### Archetype Win Rates
|
||||
{archetype_section}
|
||||
|
||||
### Top Performing Cards (by Impact Score)
|
||||
{top_cards}
|
||||
|
||||
### Underperforming Cards (candidates for cuts)
|
||||
{underperformer_section}
|
||||
|
||||
|
||||
### RAG-Retrieved Similar Cards (from ChromaDB)
|
||||
{rag_section}
|
||||
### Candidate Replacement Cards (from embeddings search)
|
||||
{candidate_section}
|
||||
|
||||
{combo_section}
|
||||
|
||||
Based on this simulation data, provide your coaching suggestions."""
|
||||
|
||||
|
||||
def _format_goals_section(goals: Optional[CoachGoals]) -> str:
|
||||
"""Format goals into system prompt rules."""
|
||||
if not goals:
|
||||
return "- Aim for a balanced, well-rounded deck."
|
||||
lines = []
|
||||
if goals.targetPowerLevel is not None:
|
||||
lines.append(f"- Target power level: {goals.targetPowerLevel}/10.")
|
||||
if goals.targetPowerLevel <= 4:
|
||||
lines.append("- Keep suggestions casual and fun-focused.")
|
||||
elif goals.targetPowerLevel >= 8:
|
||||
lines.append("- Prioritize efficiency and competitive staples.")
|
||||
if goals.metaFocus:
|
||||
lines.append(f"- Optimize for a {goals.metaFocus} strategy.")
|
||||
if goals.budget:
|
||||
budget_map = {"budget": "under $5 per card", "medium": "under $20 per card",
|
||||
"no-limit": "no budget restrictions"}
|
||||
lines.append(f"- Budget constraint: {budget_map.get(goals.budget, goals.budget)}.")
|
||||
if goals.focusAreas:
|
||||
lines.append(f"- Focus improvement on: {', '.join(goals.focusAreas)}.")
|
||||
return "\n".join(lines) if lines else "- Aim for a balanced, well-rounded deck."
|
||||
"""Format goals into system prompt rules."""
|
||||
if not goals:
|
||||
return "- Aim for a balanced, well-rounded deck."
|
||||
|
||||
lines = []
|
||||
if goals.targetPowerLevel is not None:
|
||||
lines.append(f"- Target power level: {goals.targetPowerLevel}/10.")
|
||||
if goals.targetPowerLevel <= 4:
|
||||
lines.append("- Keep suggestions casual and fun-focused.")
|
||||
elif goals.targetPowerLevel >= 8:
|
||||
lines.append("- Prioritize efficiency and competitive staples.")
|
||||
if goals.metaFocus:
|
||||
lines.append(f"- Optimize for a {goals.metaFocus} strategy.")
|
||||
if goals.budget:
|
||||
budget_map = {"budget": "under $5 per card", "medium": "under $20 per card",
|
||||
"no-limit": "no budget restrictions"}
|
||||
lines.append(f"- Budget constraint: {budget_map.get(goals.budget, goals.budget)}.")
|
||||
if goals.focusAreas:
|
||||
lines.append(f"- Focus improvement on: {', '.join(goals.focusAreas)}.")
|
||||
return "\n".join(lines) if lines else "- Aim for a balanced, well-rounded deck."
|
||||
|
||||
|
||||
def _format_curve(buckets: List[int]) -> str:
|
||||
"""Format mana curve buckets as a readable string."""
|
||||
labels = ["0", "1", "2", "3", "4", "5", "6", "7+"]
|
||||
parts = [f"{labels[i]}={buckets[i]}" for i in range(min(len(buckets), 8)) if buckets[i] > 0]
|
||||
return ", ".join(parts) if parts else "not available (analyze deck structure manually)"
|
||||
"""Format mana curve buckets as a readable string."""
|
||||
labels = ["0", "1", "2", "3", "4", "5", "6", "7+"]
|
||||
parts = [f"{labels[i]}={buckets[i]}" for i in range(min(len(buckets), 8)) if buckets[i] > 0]
|
||||
return ", ".join(parts) if parts else "not available (analyze deck structure manually)"
|
||||
|
||||
|
||||
def _format_top_cards(cards: List[CardPerformance], top_n: int = 10) -> str:
|
||||
"""Format the best performing cards with extended stats."""
|
||||
sorted_cards = sorted(cards, key=lambda c: c.impactScore, reverse=True)
|
||||
lines = []
|
||||
for c in sorted_cards[:top_n]:
|
||||
tags = f" [{', '.join(c.tags)}]" if c.tags else ""
|
||||
turn_str = f", avgTurnCast={c.avgTurnCast:.1f}" if c.avgTurnCast is not None else ""
|
||||
lines.append(
|
||||
f"- {c.name}: impact={c.impactScore:.3f}, "
|
||||
f"castRate={c.castRate:.1%}, drawnRate={c.drawnRate:.1%}, "
|
||||
f"synergy={c.synergyScore:.3f}{turn_str}{tags}"
|
||||
)
|
||||
return "\n".join(lines) if lines else "No card performance data available."
|
||||
"""Format the best performing cards."""
|
||||
sorted_cards = sorted(cards, key=lambda c: c.impactScore, reverse=True)
|
||||
lines = []
|
||||
for c in sorted_cards[:top_n]:
|
||||
tags = f" [{', '.join(c.tags)}]" if c.tags else ""
|
||||
lines.append(f"- {c.name}: impact={c.impactScore:.3f}, "
|
||||
f"castRate={c.castRate:.1%}, drawnRate={c.drawnRate:.1%}{tags}")
|
||||
return "\n".join(lines) if lines else "No card performance data available."
|
||||
|
||||
|
||||
def _format_underperformers(cards: List[CardPerformance],
|
||||
underperformer_names: List[str]) -> str:
|
||||
"""Format underperforming cards with full available stats."""
|
||||
card_map = {c.name: c for c in cards}
|
||||
lines = []
|
||||
for name in underperformer_names[:MAX_UNDERPERFORMERS]:
|
||||
c = card_map.get(name)
|
||||
if c:
|
||||
turn_str = f", avgTurnCast={c.avgTurnCast:.1f}" if c.avgTurnCast is not None else ""
|
||||
lines.append(
|
||||
f"- {c.name}: impact={c.impactScore:.3f}, "
|
||||
f"deadCardRate={c.deadCardRate:.1%}, "
|
||||
f"castRate={c.castRate:.1%}, "
|
||||
f"clunkiness={c.clunkinessScore:.3f}, "
|
||||
f"synergy={c.synergyScore:.3f}, "
|
||||
f"keptInOpeningHand={c.keptInOpeningHandRate:.1%}"
|
||||
f"{turn_str}"
|
||||
)
|
||||
else:
|
||||
lines.append(f"- {name}: (no detailed stats)")
|
||||
return "\n".join(lines) if lines else "No clear underperformers identified."
|
||||
underperformer_names: List[str]) -> str:
|
||||
"""Format underperforming cards with their stats."""
|
||||
card_map = {c.name: c for c in cards}
|
||||
lines = []
|
||||
for name in underperformer_names[:MAX_UNDERPERFORMERS]:
|
||||
c = card_map.get(name)
|
||||
if c:
|
||||
lines.append(f"- {c.name}: impact={c.impactScore:.3f}, "
|
||||
f"deadCardRate={c.deadCardRate:.1%}, "
|
||||
f"castRate={c.castRate:.1%}, "
|
||||
f"clunkiness={c.clunkinessScore:.3f}")
|
||||
else:
|
||||
lines.append(f"- {name}: (no detailed stats)")
|
||||
return "\n".join(lines) if lines else "No clear underperformers identified."
|
||||
|
||||
|
||||
def _format_candidates(candidates: Dict[str, List[dict]]) -> str:
|
||||
"""Format replacement candidates grouped by the card they'd replace."""
|
||||
if not candidates:
|
||||
return (
|
||||
"No embedding-based candidates available. "
|
||||
"Use your MTG knowledge to suggest cards that fit the deck's "
|
||||
"color identity, strategy, and missing functional roles. "
|
||||
"Suggest at least 3 different cards across different roles "
|
||||
"(ramp, draw, removal, threats, utility)."
|
||||
)
|
||||
lines = []
|
||||
for underperformer, replacements in list(candidates.items())[:MAX_UNDERPERFORMERS]:
|
||||
lines.append(f"\nReplacements for '{underperformer}':")
|
||||
for r in replacements[:MAX_CANDIDATES_PER_UNDERPERFORMER]:
|
||||
name = r.get("name", "Unknown")
|
||||
types = r.get("types", "")
|
||||
mv = r.get("mana_value", "?")
|
||||
sim = r.get("similarity", 0)
|
||||
text_preview = r.get("text", "")[:80]
|
||||
lines.append(f" - {name} (MV:{mv}, {types}) [similarity: {sim:.3f}]")
|
||||
if text_preview:
|
||||
lines.append(f" Oracle: {text_preview}")
|
||||
lines.append("\nChoose from these candidates when possible, but also suggest ")
|
||||
lines.append("cards NOT in this list if they better address the deck's weaknesses.")
|
||||
return "\n".join(lines)
|
||||
"""Format replacement candidates grouped by the card they'd replace."""
|
||||
if not candidates:
|
||||
return ("No embedding-based candidates available. "
|
||||
"Use your MTG knowledge to suggest cards that fit the deck's "
|
||||
"color identity, strategy, and missing functional roles. "
|
||||
"Suggest at least 3 different cards across different roles "
|
||||
"(ramp, draw, removal, threats, utility).")
|
||||
|
||||
def _format_rag_cards(rag_cards: List[dict]) -> str:
|
||||
"""Format RAG-retrieved cards from ChromaDB vector search."""
|
||||
if not rag_cards:
|
||||
return "No RAG results available."
|
||||
lines = []
|
||||
for card in rag_cards[:15]:
|
||||
name = card.get("name", "Unknown")
|
||||
types = card.get("types", "")
|
||||
mv = card.get("mana_value", "?")
|
||||
mc = card.get("mana_cost", "")
|
||||
dist = card.get("distance", 0)
|
||||
text = card.get("text", "")[:80]
|
||||
lines.append(f"- {name} ({mc}, MV:{mv}, {types}) [distance: {dist:.3f}]")
|
||||
if text:
|
||||
lines.append(f" Oracle: {text}")
|
||||
for underperformer, replacements in list(candidates.items())[:MAX_UNDERPERFORMERS]:
|
||||
lines.append(f"\nReplacements for '{underperformer}':")
|
||||
for r in replacements[:MAX_CANDIDATES_PER_UNDERPERFORMER]:
|
||||
name = r.get("name", "Unknown")
|
||||
types = r.get("types", "")
|
||||
mv = r.get("mana_value", "?")
|
||||
sim = r.get("similarity", 0)
|
||||
text_preview = r.get("text", "")[:80]
|
||||
lines.append(f" - {name} (MV:{mv}, {types}) [similarity: {sim:.3f}]")
|
||||
if text_preview:
|
||||
lines.append(f" Oracle: {text_preview}")
|
||||
lines.append("\nChoose from these candidates when possible, but also suggest ")
|
||||
lines.append("cards NOT in this list if they better address the deck's weaknesses.")
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
|
||||
def _format_matchups(report: DeckReport) -> str:
|
||||
"""Format per-opponent matchup data."""
|
||||
if not report.matchups:
|
||||
return "No matchup data available."
|
||||
lines = []
|
||||
for m in report.matchups:
|
||||
lines.append(
|
||||
f"- vs {m.opponentDeck}: {m.winRate:.1%} "
|
||||
f"({m.gamesPlayed} games)"
|
||||
)
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def _format_archetypes(report: DeckReport) -> str:
|
||||
"""Format per-archetype win rates from DeckMeta."""
|
||||
rates = report.meta.perArchetypeWinRates
|
||||
if not rates:
|
||||
return "No archetype breakdown available."
|
||||
lines = []
|
||||
for archetype, wr in sorted(rates.items(), key=lambda x: x[1]):
|
||||
lines.append(f"- vs {archetype}: {wr:.1%}")
|
||||
return "\n".join(lines)
|
||||
"""Format matchup data."""
|
||||
if not report.matchups:
|
||||
return "No matchup data available."
|
||||
lines = []
|
||||
for m in report.matchups:
|
||||
lines.append(f"- vs {m.opponentDeck}: {m.winRate:.1%} "
|
||||
f"({m.gamesPlayed} games)")
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def _format_combos(report: DeckReport) -> str:
|
||||
"""Format known combos section."""
|
||||
if not report.knownCombos:
|
||||
return ""
|
||||
lines = ["### Known Combos"]
|
||||
for combo in report.knownCombos:
|
||||
cards = " + ".join(combo.cardNames)
|
||||
lines.append(
|
||||
f"- {cards}: winRate={combo.winRateWhenAssembled:.1%}, "
|
||||
f"assemblyRate={combo.assemblyRate:.1%}"
|
||||
)
|
||||
return "\n".join(lines)
|
||||
"""Format known combos section."""
|
||||
if not report.knownCombos:
|
||||
return ""
|
||||
lines = ["### Known Combos"]
|
||||
for combo in report.knownCombos:
|
||||
cards = " + ".join(combo.cardNames)
|
||||
lines.append(f"- {cards}: winRate={combo.winRateWhenAssembled:.1%}, "
|
||||
f"assemblyRate={combo.assemblyRate:.1%}")
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
@@ -401,53 +207,41 @@ def _format_combos(report: DeckReport) -> str:
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
def build_system_prompt(report: DeckReport,
|
||||
goals: Optional[CoachGoals] = None) -> str:
|
||||
"""Build the system prompt with deck-specific rules."""
|
||||
color_str = "/".join(report.colorIdentity) if report.colorIdentity else "any"
|
||||
return SYSTEM_PROMPT_TEMPLATE.format(
|
||||
commander=report.commander,
|
||||
color_identity=color_str,
|
||||
goals_section=_format_goals_section(goals),
|
||||
)
|
||||
|
||||
|
||||
def build_quick_system_prompt(report: DeckReport,
|
||||
goals: Optional[CoachGoals] = None) -> str:
|
||||
"""Build the quick digest system prompt (~400-600 token target)."""
|
||||
color_str = "/".join(report.colorIdentity) if report.colorIdentity else "any"
|
||||
return QUICK_DIGEST_SYSTEM_PROMPT.format(
|
||||
commander=report.commander,
|
||||
color_identity=color_str,
|
||||
goals_section=_format_goals_section(goals),
|
||||
)
|
||||
goals: Optional[CoachGoals] = None) -> str:
|
||||
"""Build the system prompt with deck-specific rules."""
|
||||
color_str = "/".join(report.colorIdentity) if report.colorIdentity else "any"
|
||||
return SYSTEM_PROMPT_TEMPLATE.format(
|
||||
commander=report.commander,
|
||||
color_identity=color_str,
|
||||
goals_section=_format_goals_section(goals),
|
||||
)
|
||||
|
||||
|
||||
def build_user_prompt(report: DeckReport,
|
||||
candidates: Dict[str, List[dict]] = None,
|
||||
rag_cards: List[dict] = None) -> str:
|
||||
"""Build the user prompt with full deck report data."""
|
||||
color_str = "/".join(report.colorIdentity) if report.colorIdentity else "unknown"
|
||||
type_parts = [f"{k}={v}" for k, v in report.structure.cardTypeCounts.items()] \
|
||||
if report.structure.cardTypeCounts else ["unknown"]
|
||||
role_parts = [f"{k}={v}" for k, v in report.structure.functionalCounts.items()] \
|
||||
if report.structure.functionalCounts else ["unknown"]
|
||||
return USER_PROMPT_TEMPLATE.format(
|
||||
deck_name=report.deckId,
|
||||
commander=report.commander,
|
||||
color_identity=color_str,
|
||||
games_simulated=report.meta.gamesSimulated,
|
||||
win_rate=report.meta.overallWinRate,
|
||||
avg_game_length=report.meta.avgGameLength,
|
||||
land_count=report.structure.landCount,
|
||||
curve_summary=_format_curve(report.structure.curveBuckets),
|
||||
type_summary=", ".join(type_parts),
|
||||
role_summary=", ".join(role_parts),
|
||||
matchup_section=_format_matchups(report),
|
||||
archetype_section=_format_archetypes(report),
|
||||
top_cards=_format_top_cards(report.cards),
|
||||
underperformer_section=_format_underperformers(
|
||||
report.cards, report.underperformers),
|
||||
candidate_section=_format_candidates(candidates or {}),
|
||||
rag_section=_format_rag_cards(rag_cards or []),
|
||||
combo_section=_format_combos(report),
|
||||
)
|
||||
candidates: Dict[str, List[dict]] = None) -> str:
|
||||
"""Build the user prompt with full deck report data."""
|
||||
color_str = "/".join(report.colorIdentity) if report.colorIdentity else "unknown"
|
||||
|
||||
type_parts = [f"{k}={v}" for k, v in report.structure.cardTypeCounts.items()] \
|
||||
if report.structure.cardTypeCounts else ["unknown"]
|
||||
role_parts = [f"{k}={v}" for k, v in report.structure.functionalCounts.items()] \
|
||||
if report.structure.functionalCounts else ["unknown"]
|
||||
|
||||
return USER_PROMPT_TEMPLATE.format(
|
||||
deck_name=report.deckId,
|
||||
commander=report.commander,
|
||||
color_identity=color_str,
|
||||
games_simulated=report.meta.gamesSimulated,
|
||||
win_rate=report.meta.overallWinRate,
|
||||
avg_game_length=report.meta.avgGameLength,
|
||||
land_count=report.structure.landCount,
|
||||
curve_summary=_format_curve(report.structure.curveBuckets),
|
||||
type_summary=", ".join(type_parts),
|
||||
role_summary=", ".join(role_parts),
|
||||
matchup_section=_format_matchups(report),
|
||||
top_cards=_format_top_cards(report.cards),
|
||||
underperformer_section=_format_underperformers(
|
||||
report.cards, report.underperformers),
|
||||
candidate_section=_format_candidates(candidates or {}),
|
||||
combo_section=_format_combos(report),
|
||||
)
|
||||
@@ -1,9 +1,6 @@
|
||||
"""
|
||||
Commander AI Lab — Deck Generation System Prompt
|
||||
═════════════════════════════════════════════════
|
||||
Phase 1 changes:
|
||||
- Added explicit 99-card count enforcement rule
|
||||
- Clarified that commander counts separately (not in the 99)
|
||||
"""
|
||||
|
||||
SYSTEM_PROMPT = """You are an elite Magic: The Gathering Commander (EDH) deck builder with encyclopedic knowledge of every card ever printed, current metagame trends, and Commander Rules Committee bracket guidelines.
|
||||
@@ -12,8 +9,6 @@ Your task is to build a complete, legal 100-card Commander deck.
|
||||
|
||||
RULES:
|
||||
- Exactly 100 cards total: 1 commander + 99 other cards
|
||||
- The commander IS included in the cards list but counts as card #100
|
||||
- The other 99 cards must exactly match the SLOT BUDGET provided in the user prompt
|
||||
- No more than 1 copy of any card except basic lands
|
||||
- All cards must share the commander's color identity
|
||||
- All cards must be legal in Commander format
|
||||
@@ -21,12 +16,6 @@ RULES:
|
||||
- Include approximately: 10 ramp sources, 10 card draw sources, 8-10 targeted removal, 2-3 board wipes, 3-5 protection pieces
|
||||
- Build a cohesive strategy around the commander's abilities
|
||||
|
||||
CARD COUNT ENFORCEMENT (critical):
|
||||
- The user prompt will specify a SLOT BUDGET with exact per-category counts
|
||||
- You MUST fill every slot — returning fewer cards than the budget specifies will cause a validation error
|
||||
- If you cannot find a perfect fit for a slot, use the best available card for that role
|
||||
- Basic lands count toward the Land slot total
|
||||
|
||||
BRACKET RULES (Commander Rules Committee):
|
||||
- Bracket 1 (Casual): Precon-level. No tutors, no fast mana, no infinite combos, no mass land destruction. Game Changers: 0
|
||||
- Bracket 2 (Upgraded Casual): Moderate power. Limited tutors (1-2 total), no 2-card infinite combos, no fast mana except Sol Ring. Game Changers: 0-1
|
||||
|
||||
@@ -1,33 +1,11 @@
|
||||
"""
|
||||
Commander AI Lab — Deck Generation User Prompt Builder
|
||||
═══════════════════════════════════════════════════════
|
||||
Constructs the user message for LLM deck generation.
|
||||
|
||||
Phase 1 changes:
|
||||
- slot_budget parameter injected into prompt so LLM targets exactly 99 cards
|
||||
- Explicit card count requirement in prompt text
|
||||
Constructs the user message for Perplexity deck generation
|
||||
from a DeckGenV3Request.
|
||||
"""
|
||||
|
||||
from typing import Dict, List, Optional
|
||||
|
||||
|
||||
def build_slot_budget_segment(slot_budget: Dict[str, int]) -> str:
|
||||
"""
|
||||
Build the slot budget prompt segment.
|
||||
Informs the LLM of exact per-category card counts so it never undershoots.
|
||||
"""
|
||||
total = sum(slot_budget.values())
|
||||
lines = [f"SLOT BUDGET (you must fill EXACTLY {total} cards, excluding the commander):"]
|
||||
for cat, count in slot_budget.items():
|
||||
lines.append(f" {cat}: {count}")
|
||||
lines.append(f" TOTAL: {total}")
|
||||
lines.append("")
|
||||
lines.append(
|
||||
f"CRITICAL: Return exactly {total} cards in the JSON 'cards' array "
|
||||
"(not counting the commander). Every slot in the budget above must be filled. "
|
||||
"Do not return more or fewer cards."
|
||||
)
|
||||
return "\n".join(lines)
|
||||
from typing import List, Optional
|
||||
|
||||
|
||||
def build_user_prompt(
|
||||
@@ -40,7 +18,6 @@ def build_user_prompt(
|
||||
budget_mode: str = "total",
|
||||
omit_cards: List[str] = None,
|
||||
collection_summary: str = "",
|
||||
slot_budget: Optional[Dict[str, int]] = None,
|
||||
) -> str:
|
||||
"""
|
||||
Build the user prompt for deck generation.
|
||||
@@ -49,19 +26,18 @@ def build_user_prompt(
|
||||
commander: Commander card name
|
||||
commander_type: Type line from Scryfall
|
||||
color_identity: List of color letters, e.g. ["U", "B"]
|
||||
strategy: User-specified strategy focus
|
||||
strategy: User-specified strategy focus (e.g. "zombie tokens")
|
||||
target_bracket: Target bracket level 1-4
|
||||
budget_usd: Optional budget constraint
|
||||
budget_mode: "total" for total deck cost, "per_card" for per-card max
|
||||
omit_cards: Cards to exclude
|
||||
collection_summary: Pre-built collection summary text block
|
||||
slot_budget: Dict of category -> card count (must sum to 99)
|
||||
"""
|
||||
ci_str = ", ".join(color_identity) if color_identity else "Unknown"
|
||||
|
||||
lines = [
|
||||
"Build a complete 100-card Commander deck.",
|
||||
"",
|
||||
f"Build a complete 100-card Commander deck.",
|
||||
f"",
|
||||
f"COMMANDER: {commander}",
|
||||
]
|
||||
|
||||
@@ -84,21 +60,16 @@ def build_user_prompt(
|
||||
lines.append(f"OMIT LIST (do NOT include these cards): {', '.join(omit_cards)}")
|
||||
|
||||
if collection_summary:
|
||||
lines.append("")
|
||||
lines.append(f"")
|
||||
lines.append(collection_summary)
|
||||
lines.append("")
|
||||
lines.append("STRONGLY PREFER cards from the collection when they fit the strategy.")
|
||||
lines.append(f"")
|
||||
lines.append(f"STRONGLY PREFER cards from the collection when they fit the strategy.")
|
||||
else:
|
||||
lines.append("")
|
||||
lines.append("No collection data available — suggest the best cards regardless of ownership.")
|
||||
lines.append(f"")
|
||||
lines.append(f"No collection data available — suggest the best cards regardless of ownership.")
|
||||
|
||||
# Inject slot budget so LLM knows exact target counts
|
||||
if slot_budget:
|
||||
lines.append("")
|
||||
lines.append(build_slot_budget_segment(slot_budget))
|
||||
|
||||
lines.append("")
|
||||
lines.append("Build the deck as a structured JSON response. Include the commander in the cards list.")
|
||||
lines.append("Ensure exactly 100 total cards. Assign role_tags and bracket info accurately.")
|
||||
lines.append(f"")
|
||||
lines.append(f"Build the deck as a structured JSON response. Include the commander in the cards list.")
|
||||
lines.append(f"Ensure exactly 100 total cards. Assign role_tags and bracket info accurately.")
|
||||
|
||||
return "\n".join(lines)
|
||||
@@ -1,7 +1,7 @@
|
||||
"""
|
||||
Commander AI Lab — Substitution Prompt Templates
|
||||
═════════════════════════════════════════════════
|
||||
Prompts for the Claude Opus substitution pass.
|
||||
Prompts for the Perplexity fallback substitution pass.
|
||||
"""
|
||||
|
||||
|
||||
|
||||
@@ -38,7 +38,7 @@ def generate_deck_reports(results_dir: str, reports_dir: str = None) -> List[str
|
||||
output_path.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# Load all batch results
|
||||
batch_files = sorted(results_path.glob("ml-decision-*.json"))
|
||||
batch_files = sorted(results_path.glob("batch-*.json"))
|
||||
if not batch_files:
|
||||
logger.info("No batch result files found in %s", results_dir)
|
||||
return []
|
||||
@@ -108,7 +108,7 @@ def generate_single_deck_report(batch_json_path: str, reports_dir: str = None) -
|
||||
# Also load existing batch results for comprehensive reports
|
||||
results_dir = Path(batch_json_path).parent
|
||||
all_batches = []
|
||||
for bf in sorted(results_dir.glob("ml-decision-*.json")):
|
||||
for bf in sorted(results_dir.glob("batch-*.json")):
|
||||
try:
|
||||
with open(bf, "r", encoding="utf-8") as f:
|
||||
all_batches.append(json.load(f))
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
"""
|
||||
Commander AI Lab — Deck Generation JSON Schemas
|
||||
═════════════════════════════════════════════════
|
||||
Pydantic models and JSON Schema dicts for Claude Opus
|
||||
Pydantic models and JSON Schema dicts for Perplexity
|
||||
structured output deck generation.
|
||||
"""
|
||||
|
||||
@@ -58,7 +58,7 @@ class GeneratedDeckList(BaseModel):
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# JSON Schema dicts (for Claude Opus response_format)
|
||||
# JSON Schema dicts (for Perplexity response_format)
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
DECK_CARD_SCHEMA = {
|
||||
|
||||
@@ -3,10 +3,6 @@ Commander AI Lab — Substitution Schemas
|
||||
════════════════════════════════════════
|
||||
Pydantic models and JSON Schema dicts for the
|
||||
Smart Substitution Engine output.
|
||||
|
||||
Phase 1 changes:
|
||||
- SubstitutionBatchResult gains padded_slots field
|
||||
- DeckCardWithStatus gains original_card field (was missing)
|
||||
"""
|
||||
|
||||
from typing import List, Optional
|
||||
@@ -22,17 +18,16 @@ class CardAlternative(BaseModel):
|
||||
name: str = Field(description="Exact card name")
|
||||
similarity_score: float = Field(default=0.0, description="Cosine similarity score (0-1)")
|
||||
reason: str = Field(default="", description="Why this card is a good substitute")
|
||||
source: str = Field(default="embedding", description="How it was found: 'embedding' or 'anthropic'")
|
||||
source: str = Field(default="embedding", description="How it was found: 'embedding' or 'perplexity'")
|
||||
role_overlap: List[str] = Field(default_factory=list, description="Shared functional roles")
|
||||
cmc_delta: float = Field(default=0.0, description="CMC difference from original")
|
||||
|
||||
|
||||
class DeckCardWithStatus(BaseModel):
|
||||
"""A deck card enriched with ownership and substitution data."""
|
||||
|
||||
|
||||
class Config:
|
||||
extra = "ignore"
|
||||
|
||||
name: str
|
||||
count: int = 1
|
||||
category: str = ""
|
||||
@@ -46,15 +41,9 @@ class DeckCardWithStatus(BaseModel):
|
||||
owned_qty: int = 0
|
||||
scryfall_id: str = ""
|
||||
status: str = Field(default="owned", description="owned | substituted | missing")
|
||||
original_card: Optional[str] = Field(
|
||||
default=None,
|
||||
description="Original card name before substitution (None if not substituted)"
|
||||
)
|
||||
original_card: Optional[str] = Field(default=None, description="Original card name if this is a substitution")
|
||||
alternatives: List[CardAlternative] = Field(default_factory=list)
|
||||
selected_substitute: Optional[str] = Field(
|
||||
default=None,
|
||||
description="The substitute card name chosen for this slot"
|
||||
)
|
||||
selected_substitute: Optional[str] = Field(default=None, description="User-selected substitute name")
|
||||
|
||||
|
||||
class SubstitutionRequest(BaseModel):
|
||||
@@ -72,16 +61,11 @@ class SubstitutionBatchResult(BaseModel):
|
||||
owned_count: int = 0
|
||||
substituted_count: int = 0
|
||||
missing_count: int = 0
|
||||
padded_slots: int = Field(
|
||||
default=0,
|
||||
description="Number of slots filled by the pad-to-99 circuit breaker. "
|
||||
"Any value > 0 indicates a bug in the substitution pipeline."
|
||||
)
|
||||
cards: List[DeckCardWithStatus] = Field(default_factory=list)
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# JSON Schema dicts (for LLM fallback substitution)
|
||||
# JSON Schema dicts (for Perplexity fallback substitution)
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
SUBSTITUTION_RESPONSE_SCHEMA = {
|
||||
|
||||
+118
-427
@@ -1,28 +1,19 @@
|
||||
"""
|
||||
Commander AI Lab — V3 Deck Generator Service
|
||||
═════════════════════════════════════════════
|
||||
Generates Commander decks using Anthropic Claude
|
||||
Generates Commander decks using Perplexity Sonar
|
||||
structured JSON output, then runs ownership check
|
||||
and smart substitution.
|
||||
|
||||
Phase 1 changes:
|
||||
- smart_substitute() non-destructive contract (never returns None)
|
||||
- apply_substitutions() loop never silently drops cards
|
||||
- _pad_to_99() circuit breaker before BuildResult validation
|
||||
- Pre-validation count logging per category
|
||||
- Startup SLOT_BUDGET assertion
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
import re
|
||||
import sqlite3
|
||||
from dataclasses import dataclass
|
||||
from enum import Enum
|
||||
from typing import List, Optional, Tuple
|
||||
from urllib.request import urlopen, Request
|
||||
|
||||
from ..clients.anthropic_client import AnthropicClient
|
||||
from ..clients.perplexity_client import PerplexityClient
|
||||
from ..schemas.deck_schema import DECK_LIST_SCHEMA, GeneratedDeckList
|
||||
from ..schemas.substitution_schema import (
|
||||
CardAlternative, DeckCardWithStatus, SubstitutionBatchResult,
|
||||
@@ -35,261 +26,35 @@ from ..prompts.substitution_prompt import (
|
||||
from ..config import (
|
||||
DECK_GEN_MODEL, DECK_GEN_TEMPERATURE, DECK_GEN_MAX_TOKENS,
|
||||
SUBSTITUTION_MIN_SIMILARITY, SUBSTITUTION_MAX_ALTERNATIVES,
|
||||
SUBSTITUTION_MODEL, SUBSTITUTION_USE_ANTHROPIC_FALLBACK,
|
||||
SUBSTITUTION_MODEL, SUBSTITUTION_USE_PPLX_FALLBACK,
|
||||
)
|
||||
|
||||
logger = logging.getLogger("coach.deckgen")
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Slot Budget — MUST sum to 99 (commander is the 100th card)
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
SLOT_BUDGET: dict[str, int] = {
|
||||
"Land": 36,
|
||||
"Ramp": 10,
|
||||
"Card Draw": 10,
|
||||
"Removal": 8,
|
||||
"Board Wipe": 3,
|
||||
"Win Condition": 4,
|
||||
"Protection": 4,
|
||||
"Synergy": 20,
|
||||
"Creature": 2,
|
||||
"Utility": 2,
|
||||
}
|
||||
|
||||
# ── Startup assertion — catches misconfigured budgets at boot time ──
|
||||
_SLOT_BUDGET_TOTAL = sum(SLOT_BUDGET.values())
|
||||
assert _SLOT_BUDGET_TOTAL == 99, (
|
||||
f"SLOT_BUDGET sums to {_SLOT_BUDGET_TOTAL}, must equal 99. "
|
||||
f"Current distribution: {SLOT_BUDGET}"
|
||||
)
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# SubstitutionMethod — tracks HOW each card was resolved
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class SubstitutionMethod(str, Enum):
|
||||
EXACT_MATCH = "exact_match" # Card found verbatim in collection
|
||||
FUZZY_MATCH = "fuzzy_match" # Case/punctuation-normalised match
|
||||
EMBEDDING_ANALOG = "embedding_analog" # Embedding similarity match
|
||||
ANTHROPIC_FALLBACK = "anthropic_fallback" # LLM suggested replacement
|
||||
ORIGINAL_KEPT = "original_kept" # Not in collection but Scryfall-valid
|
||||
BASIC_LAND_FALLBACK = "basic_land_fallback" # Last resort — slot becomes a basic
|
||||
|
||||
|
||||
@dataclass
|
||||
class SubstitutionRecord:
|
||||
"""Audit trail entry for a single card's resolution."""
|
||||
original: str
|
||||
resolved: str
|
||||
method: SubstitutionMethod
|
||||
in_collection: bool
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Color → Basic Land mapping
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
_COLOR_TO_BASIC: dict[str, str] = {
|
||||
"W": "Plains",
|
||||
"U": "Island",
|
||||
"B": "Swamp",
|
||||
"R": "Mountain",
|
||||
"G": "Forest",
|
||||
}
|
||||
_BASIC_NAMES: set[str] = set(_COLOR_TO_BASIC.values()) | {"Wastes"}
|
||||
|
||||
|
||||
def _get_basic_land(color_identity: List[str]) -> str:
|
||||
"""Return the first appropriate basic land for the given color identity."""
|
||||
for color in color_identity:
|
||||
if color.upper() in _COLOR_TO_BASIC:
|
||||
return _COLOR_TO_BASIC[color.upper()]
|
||||
return "Wastes" # Colorless commander
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Non-destructive Smart Substitution
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
def smart_substitute(
|
||||
card_name: str,
|
||||
collection: set[str],
|
||||
color_identity: List[str],
|
||||
embedding_index=None,
|
||||
) -> SubstitutionRecord:
|
||||
"""
|
||||
Non-destructive substitution — ALWAYS returns a valid card string.
|
||||
|
||||
Fallback chain:
|
||||
1. Exact match in collection
|
||||
2. Fuzzy match (case + punctuation normalised)
|
||||
3. Embedding similarity match (if index available)
|
||||
4. Keep original (Scryfall-valid, not in collection)
|
||||
5. Basic land for the commander's colors (last resort — NEVER None)
|
||||
"""
|
||||
# 1. Exact match
|
||||
if card_name in collection:
|
||||
return SubstitutionRecord(card_name, card_name, SubstitutionMethod.EXACT_MATCH, True)
|
||||
|
||||
# 2. Fuzzy match — normalise case and common punctuation differences
|
||||
normalised = card_name.lower().strip()
|
||||
for owned in collection:
|
||||
if owned.lower().strip() == normalised:
|
||||
return SubstitutionRecord(card_name, owned, SubstitutionMethod.FUZZY_MATCH, True)
|
||||
|
||||
# 3. Embedding similarity (if index available)
|
||||
if embedding_index and getattr(embedding_index, "loaded", False):
|
||||
try:
|
||||
matches = embedding_index.search_similar(
|
||||
query_card=card_name,
|
||||
color_filter=color_identity or None,
|
||||
exclude_cards=[card_name],
|
||||
top_n=5,
|
||||
)
|
||||
pool_lower = {n.lower() for n in collection}
|
||||
for match in matches:
|
||||
if match.name.lower() in pool_lower:
|
||||
return SubstitutionRecord(
|
||||
card_name, match.name, SubstitutionMethod.EMBEDDING_ANALOG, True
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning("Embedding substitution failed for '%s': %s", card_name, e)
|
||||
|
||||
# 4. Keep original — valid card not in collection (proxy / non-collection build)
|
||||
return SubstitutionRecord(
|
||||
card_name, card_name, SubstitutionMethod.ORIGINAL_KEPT, False
|
||||
)
|
||||
|
||||
|
||||
def apply_substitutions(
|
||||
card_list: List[DeckCardWithStatus],
|
||||
collection: set[str],
|
||||
color_identity: List[str],
|
||||
embedding_index=None,
|
||||
) -> Tuple[List[DeckCardWithStatus], List[SubstitutionRecord]]:
|
||||
"""
|
||||
Apply smart substitution to a card list.
|
||||
|
||||
Guarantees: output list is NEVER shorter than input list.
|
||||
Logs a warning for every BASIC_LAND_FALLBACK.
|
||||
"""
|
||||
records: List[SubstitutionRecord] = []
|
||||
result: List[DeckCardWithStatus] = []
|
||||
|
||||
for card in card_list:
|
||||
rec = smart_substitute(card.name, collection, color_identity, embedding_index)
|
||||
records.append(rec)
|
||||
|
||||
if rec.method == SubstitutionMethod.BASIC_LAND_FALLBACK:
|
||||
logger.warning(
|
||||
"[substitution] BASIC_LAND_FALLBACK for '%s' — slot filled with '%s'",
|
||||
rec.original, rec.resolved,
|
||||
)
|
||||
|
||||
# Update the card in-place — never drop it
|
||||
updated = card.model_copy(update={
|
||||
"name": rec.resolved,
|
||||
"owned": rec.in_collection,
|
||||
"status": "owned" if rec.in_collection else
|
||||
("substituted" if rec.method != SubstitutionMethod.ORIGINAL_KEPT
|
||||
else "missing"),
|
||||
"original_card": card.name if rec.resolved != card.name else card.original_card,
|
||||
})
|
||||
result.append(updated)
|
||||
|
||||
fallback_count = sum(1 for r in records if r.method == SubstitutionMethod.BASIC_LAND_FALLBACK)
|
||||
if fallback_count:
|
||||
logger.error(
|
||||
"[substitution] %d cards fell back to basic lands — investigate LLM output quality",
|
||||
fallback_count,
|
||||
)
|
||||
|
||||
return result, records
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Pad-to-99 Circuit Breaker
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
def _pad_to_99(
|
||||
cards: List[DeckCardWithStatus],
|
||||
color_identity: List[str],
|
||||
target: int = 99,
|
||||
) -> Tuple[List[DeckCardWithStatus], int]:
|
||||
"""
|
||||
Emergency safety pad — should NEVER fire if substitution contract holds.
|
||||
|
||||
If it does fire, the error log is your signal that a card is being dropped
|
||||
somewhere earlier in the pipeline.
|
||||
|
||||
Returns (padded_cards, number_of_slots_padded).
|
||||
"""
|
||||
# Strip commander from count if present (commander is tracked separately)
|
||||
non_commander = [c for c in cards if not getattr(c, "is_commander", False)]
|
||||
current = sum(c.count for c in non_commander)
|
||||
shortfall = target - current
|
||||
|
||||
if shortfall <= 0:
|
||||
return cards, 0
|
||||
|
||||
logger.error(
|
||||
"[pad_to_99] CIRCUIT BREAKER FIRED — deck is %d cards short after substitution. "
|
||||
"Padding with basic lands. Check substitution pipeline for silent drops.",
|
||||
shortfall,
|
||||
)
|
||||
|
||||
basic = _get_basic_land(color_identity)
|
||||
padding_card = DeckCardWithStatus(
|
||||
name=basic,
|
||||
count=shortfall,
|
||||
category="Land",
|
||||
role_tags=[],
|
||||
reason="Emergency pad — basic land inserted by circuit breaker",
|
||||
estimated_price_usd=0.10,
|
||||
owned=True,
|
||||
owned_qty=shortfall,
|
||||
status="owned",
|
||||
)
|
||||
return cards + [padding_card], shortfall
|
||||
|
||||
|
||||
def _log_pre_validation_counts(cards: List[DeckCardWithStatus]) -> None:
|
||||
"""Log per-category card counts before Pydantic validation."""
|
||||
by_cat: dict[str, int] = {}
|
||||
for card in cards:
|
||||
cat = card.category or "Uncategorized"
|
||||
by_cat[cat] = by_cat.get(cat, 0) + card.count
|
||||
total = sum(by_cat.values())
|
||||
logger.info("[pre_validation] Category counts: %s", by_cat)
|
||||
logger.info("[pre_validation] Total: %d/99 (delta: %d)", total, 99 - total)
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# DeckGeneratorV3
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class DeckGeneratorV3:
|
||||
"""
|
||||
V3 Deck Generator using Anthropic Claude structured output.
|
||||
V3 Deck Generator using Perplexity structured output.
|
||||
|
||||
Pipeline:
|
||||
1. Resolve commander via Scryfall
|
||||
2. Build collection summary
|
||||
3. Call Anthropic Claude with structured JSON schema
|
||||
3. Call Perplexity with structured JSON schema
|
||||
4. Validate card names via Scryfall
|
||||
5. Check ownership against collection DB
|
||||
6. Run Smart Substitution (non-destructive)
|
||||
7. _pad_to_99 circuit breaker
|
||||
8. Pre-validation count logging
|
||||
9. Return finalized deck — guaranteed 99 cards
|
||||
6. Run Smart Substitution (embedding + Perplexity fallback)
|
||||
7. Return finalized deck with substitution data
|
||||
"""
|
||||
|
||||
def __init__(self, anthropic_client: AnthropicClient, db_conn_factory,
|
||||
def __init__(self, pplx_client: PerplexityClient, db_conn_factory,
|
||||
embedding_index=None):
|
||||
self.anthropic = anthropic_client
|
||||
"""
|
||||
Args:
|
||||
pplx_client: Configured PerplexityClient instance
|
||||
db_conn_factory: Callable that returns sqlite3.Connection
|
||||
embedding_index: Optional MTGEmbeddingIndex for substitution
|
||||
"""
|
||||
self.pplx = pplx_client
|
||||
self.db_conn_factory = db_conn_factory
|
||||
self.embedding_index = embedding_index
|
||||
|
||||
@@ -312,12 +77,9 @@ class DeckGeneratorV3:
|
||||
"mana_cost": data.get("mana_cost", ""),
|
||||
"image_url": data.get("image_uris", {}).get("normal", ""),
|
||||
"oracle_text": data.get("oracle_text", ""),
|
||||
"scryfall_found": True,
|
||||
}
|
||||
except Exception as e:
|
||||
logger.warning("Scryfall lookup failed for '%s': %s", commander_name, e)
|
||||
# Non-canonical commander (silver-bordered, custom, etc.)
|
||||
# Skip collection substitution for these — trust LLM output directly
|
||||
return {
|
||||
"name": commander_name,
|
||||
"scryfall_id": "",
|
||||
@@ -326,7 +88,6 @@ class DeckGeneratorV3:
|
||||
"mana_cost": "",
|
||||
"image_url": "",
|
||||
"oracle_text": "",
|
||||
"scryfall_found": False,
|
||||
}
|
||||
|
||||
# ── Step 2: Build Collection Summary ─────────────────────
|
||||
@@ -349,10 +110,16 @@ class DeckGeneratorV3:
|
||||
if not rows:
|
||||
return ""
|
||||
|
||||
# Filter by color identity
|
||||
ci_set = set(color_identity) if color_identity else None
|
||||
filtered = []
|
||||
for row in rows:
|
||||
name = row["name"]
|
||||
type_line = row["type_line"] or ""
|
||||
# Basic lands and colorless are always allowed
|
||||
if ci_set:
|
||||
# Simple color check from type_line and name
|
||||
# For proper filtering we'd check mana cost but this is good enough for summary
|
||||
card_colors = set()
|
||||
oracle = row["oracle_text"] or ""
|
||||
mana_cost = ""
|
||||
@@ -370,6 +137,7 @@ class DeckGeneratorV3:
|
||||
if not filtered:
|
||||
return ""
|
||||
|
||||
# Group by card type
|
||||
groups = {}
|
||||
for row in filtered:
|
||||
type_line = row["type_line"] or ""
|
||||
@@ -391,12 +159,14 @@ class DeckGeneratorV3:
|
||||
group = "Other"
|
||||
groups.setdefault(group, []).append(row)
|
||||
|
||||
# Sort each group by popularity/price and build text
|
||||
lines = [f"COLLECTION SUMMARY ({len(filtered)} cards in deck colors):"]
|
||||
for group_name in ["Creatures", "Instants", "Sorceries", "Artifacts",
|
||||
"Enchantments", "Planeswalkers", "Lands", "Other"]:
|
||||
cards = groups.get(group_name, [])
|
||||
if not cards:
|
||||
continue
|
||||
# Sort by price descending (higher value = likely better card)
|
||||
cards.sort(key=lambda r: r["tcg_price"] or 0, reverse=True)
|
||||
card_strs = []
|
||||
for c in cards[:max_per_group]:
|
||||
@@ -406,7 +176,7 @@ class DeckGeneratorV3:
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
# ── Step 3: Generate Deck via Anthropic Claude ─────────────────
|
||||
# ── Step 3: Generate Deck via Perplexity ─────────────────
|
||||
def generate_deck(
|
||||
self,
|
||||
commander_name: str,
|
||||
@@ -423,33 +193,24 @@ class DeckGeneratorV3:
|
||||
|
||||
Returns dict with:
|
||||
- commander: dict with Scryfall data
|
||||
- raw_deck: parsed GeneratedDeckList from Anthropic Claude
|
||||
- cards: list of DeckCardWithStatus (after ownership check + substitution)
|
||||
- raw_deck: parsed GeneratedDeckList from Perplexity
|
||||
- cards: list of DeckCardWithStatus (after ownership check)
|
||||
- stats: deck statistics
|
||||
- substitution_log: list of SubstitutionRecord dicts
|
||||
- padded_slots: int > 0 means circuit breaker fired
|
||||
- tokens_used: {prompt, completion}
|
||||
"""
|
||||
# Step 1: Resolve commander
|
||||
cmdr = self.resolve_commander(commander_name)
|
||||
color_identity = cmdr["color_identity"]
|
||||
scryfall_found = cmdr.get("scryfall_found", True)
|
||||
logger.info("Commander: %s, CI: %s, Scryfall: %s",
|
||||
cmdr["name"], color_identity, scryfall_found)
|
||||
logger.info("Commander: %s, CI: %s", cmdr["name"], color_identity)
|
||||
|
||||
# Step 2: Collection summary
|
||||
collection_block = ""
|
||||
if use_collection and scryfall_found:
|
||||
if use_collection:
|
||||
collection_block = self.build_collection_summary(color_identity)
|
||||
logger.info("Collection summary: %d chars",
|
||||
len(collection_block) if collection_block else 0)
|
||||
elif not scryfall_found:
|
||||
logger.info(
|
||||
"Non-canonical commander '%s' — skipping collection filter, "
|
||||
"trusting LLM output directly.", cmdr["name"]
|
||||
)
|
||||
|
||||
# Step 3: Build prompts (with slot budget injected)
|
||||
# Step 3: Build prompts
|
||||
user_prompt = build_user_prompt(
|
||||
commander=cmdr["name"],
|
||||
commander_type=cmdr["type_line"],
|
||||
@@ -460,14 +221,13 @@ class DeckGeneratorV3:
|
||||
budget_mode=budget_mode,
|
||||
omit_cards=omit_cards,
|
||||
collection_summary=collection_block,
|
||||
slot_budget=SLOT_BUDGET,
|
||||
)
|
||||
|
||||
# Step 4: Call LLM with structured output
|
||||
# Step 4: Call Perplexity with structured output
|
||||
use_model = model or DECK_GEN_MODEL
|
||||
logger.info("Calling LLM (%s) for deck generation...", use_model)
|
||||
logger.info("Calling Perplexity (%s) for deck generation...", use_model)
|
||||
|
||||
response = self.anthropic.chat_structured(
|
||||
response = self.pplx.chat_structured(
|
||||
system_prompt=SYSTEM_PROMPT,
|
||||
user_prompt=user_prompt,
|
||||
json_schema=DECK_LIST_SCHEMA,
|
||||
@@ -479,60 +239,24 @@ class DeckGeneratorV3:
|
||||
|
||||
if not response.ok:
|
||||
raise ValueError(
|
||||
f"LLM returned invalid response: {response.content[:300]}"
|
||||
f"Perplexity returned invalid response: {response.content[:300]}"
|
||||
)
|
||||
|
||||
raw_deck = response.parsed_json
|
||||
card_count = len(raw_deck.get("cards", []))
|
||||
truncated = card_count < 90
|
||||
logger.info(
|
||||
"Deck generated: %d cards, bracket %s%s",
|
||||
card_count,
|
||||
(raw_deck.get("bracket", {}).get("level", "?") if isinstance(raw_deck.get("bracket"), dict)
|
||||
else raw_deck.get("bracket", "?")),
|
||||
" (TRUNCATED — hit token limit)" if truncated else "",
|
||||
)
|
||||
truncated = card_count < 90 # Commander decks should have ~100 cards
|
||||
logger.info("Deck generated: %d cards, bracket %d%s",
|
||||
card_count,
|
||||
(raw_deck.get("bracket", {}).get("level", 0) if isinstance(raw_deck.get("bracket"), dict) else raw_deck.get("bracket", 0)),
|
||||
" (TRUNCATED — response may have hit token limit)" if truncated else "")
|
||||
|
||||
# Step 5: Check ownership
|
||||
# Step 5: Check ownership and build enriched card list
|
||||
cards_with_status = self._check_ownership(raw_deck.get("cards", []))
|
||||
|
||||
# Step 5b: Fill basic lands to reach target_total=100
|
||||
# Step 5b: Fill basic lands to hit exactly 100 cards
|
||||
cards_with_status = self._fill_basic_lands(cards_with_status, color_identity)
|
||||
|
||||
# Step 5c: Secondary deduplication
|
||||
seen: dict[str, int] = {}
|
||||
deduped: List[DeckCardWithStatus] = []
|
||||
for c in cards_with_status:
|
||||
key = c.name.lower()
|
||||
if key in seen:
|
||||
deduped[seen[key]].count += c.count
|
||||
logger.warning("Secondary dedupe caught duplicate: '%s'", c.name)
|
||||
else:
|
||||
seen[key] = len(deduped)
|
||||
deduped.append(c)
|
||||
cards_with_status = deduped
|
||||
|
||||
# Step 6: Run non-destructive smart substitution
|
||||
# For non-canonical commanders (e.g. Sonic), skip collection filter
|
||||
owned_pool: set[str] = set()
|
||||
if use_collection and scryfall_found:
|
||||
conn = self.db_conn_factory()
|
||||
rows = conn.execute(
|
||||
"SELECT DISTINCT name FROM collection_entries WHERE quantity > 0"
|
||||
).fetchall()
|
||||
owned_pool = {r["name"] for r in rows}
|
||||
|
||||
cards_with_status, substitution_log = apply_substitutions(
|
||||
cards_with_status, owned_pool, color_identity, self.embedding_index
|
||||
)
|
||||
|
||||
# Step 7: Pad-to-99 circuit breaker
|
||||
cards_with_status, padded_slots = _pad_to_99(cards_with_status, color_identity)
|
||||
|
||||
# Step 8: Pre-validation count logging
|
||||
_log_pre_validation_counts(cards_with_status)
|
||||
|
||||
# Step 9: Compute stats
|
||||
# Step 6: Compute stats
|
||||
stats = self._compute_stats(cards_with_status)
|
||||
|
||||
return {
|
||||
@@ -546,12 +270,6 @@ class DeckGeneratorV3:
|
||||
"archetype": raw_deck.get("archetype", ""),
|
||||
"reasoning": raw_deck.get("reasoning", {}),
|
||||
"estimated_total_usd": raw_deck.get("estimated_total_usd", 0),
|
||||
"substitution_log": [
|
||||
{"original": r.original, "resolved": r.resolved,
|
||||
"method": r.method.value, "in_collection": r.in_collection}
|
||||
for r in substitution_log
|
||||
],
|
||||
"padded_slots": padded_slots,
|
||||
"tokens_used": {
|
||||
"prompt": response.prompt_tokens,
|
||||
"completion": response.completion_tokens,
|
||||
@@ -565,25 +283,17 @@ class DeckGeneratorV3:
|
||||
def _check_ownership(self, cards: List[dict]) -> List[DeckCardWithStatus]:
|
||||
"""
|
||||
Cross-reference generated cards against the collection DB.
|
||||
Deduplicates by name (case-insensitive).
|
||||
Sets owned/scryfall_id/owned_qty and real price.
|
||||
"""
|
||||
conn = self.db_conn_factory()
|
||||
enriched: List[DeckCardWithStatus] = []
|
||||
seen_names: dict[str, int] = {}
|
||||
enriched = []
|
||||
|
||||
for card in cards:
|
||||
name = card.get("name", "")
|
||||
if not name:
|
||||
continue
|
||||
|
||||
name_lower = name.lower()
|
||||
|
||||
if name_lower in seen_names:
|
||||
idx = seen_names[name_lower]
|
||||
enriched[idx].count += card.get("count", 1)
|
||||
logger.warning("Duplicate card '%s' merged", name)
|
||||
continue
|
||||
|
||||
# Look up in collection
|
||||
row = conn.execute(
|
||||
"SELECT name, scryfall_id, quantity, tcg_price, type_line, cmc "
|
||||
"FROM collection_entries WHERE name = ? COLLATE NOCASE LIMIT 1",
|
||||
@@ -608,14 +318,16 @@ class DeckGeneratorV3:
|
||||
scryfall_id=row["scryfall_id"] if row else "",
|
||||
status="owned" if is_owned else "missing",
|
||||
)
|
||||
seen_names[name_lower] = len(enriched)
|
||||
enriched.append(enriched_card)
|
||||
|
||||
return enriched
|
||||
|
||||
# ── Step 5b: Basic Land Fill ──────────────────────────────
|
||||
_COLOR_TO_BASIC = _COLOR_TO_BASIC
|
||||
_BASIC_NAMES = _BASIC_NAMES
|
||||
_COLOR_TO_BASIC = {
|
||||
'W': 'Plains', 'U': 'Island', 'B': 'Swamp',
|
||||
'R': 'Mountain', 'G': 'Forest',
|
||||
}
|
||||
_BASIC_NAMES = set(_COLOR_TO_BASIC.values()) | {'Wastes'}
|
||||
|
||||
def _fill_basic_lands(
|
||||
self,
|
||||
@@ -637,7 +349,7 @@ class DeckGeneratorV3:
|
||||
ci = [c.upper() for c in color_identity]
|
||||
basic_names = [self._COLOR_TO_BASIC[c] for c in ci if c in self._COLOR_TO_BASIC]
|
||||
if not basic_names:
|
||||
basic_names = ["Wastes"]
|
||||
basic_names = ['Wastes']
|
||||
|
||||
per_color = basics_needed // len(basic_names)
|
||||
remainder = basics_needed % len(basic_names)
|
||||
@@ -648,20 +360,20 @@ class DeckGeneratorV3:
|
||||
non_basics.append(DeckCardWithStatus(
|
||||
name=bname,
|
||||
count=qty,
|
||||
category="Land",
|
||||
category='Land',
|
||||
role_tags=[],
|
||||
reason="Basic land for mana fixing",
|
||||
reason='Basic land for mana fixing',
|
||||
estimated_price_usd=0.10,
|
||||
owned=True,
|
||||
owned_qty=qty,
|
||||
status="owned",
|
||||
status='owned',
|
||||
))
|
||||
|
||||
logger.info("Basic land fill: %d basics added across %d color(s)",
|
||||
basics_needed, len(basic_names))
|
||||
basics_needed, len(basic_names))
|
||||
return non_basics
|
||||
|
||||
# ── Step 6: Smart Substitution (legacy wrapper for route compatibility) ──
|
||||
# ── Step 6: Smart Substitution ───────────────────────────
|
||||
def run_substitution(
|
||||
self,
|
||||
cards: List[DeckCardWithStatus],
|
||||
@@ -671,12 +383,15 @@ class DeckGeneratorV3:
|
||||
"""
|
||||
Run the Smart Substitution Engine on missing cards.
|
||||
|
||||
Uses the non-destructive apply_substitutions() under the hood.
|
||||
Falls back to Anthropic Claude for low-confidence matches,
|
||||
then to basic land as last resort — NEVER drops a card.
|
||||
Pipeline:
|
||||
a) Identify missing cards
|
||||
b) For each: try embedding similarity (free, fast)
|
||||
c) For low-confidence matches: batch Perplexity fallback
|
||||
d) Auto-select best substitute per card
|
||||
|
||||
Returns SubstitutionBatchResult with all cards updated.
|
||||
"""
|
||||
color_identity = commander.get("color_identity", [])
|
||||
scryfall_found = commander.get("scryfall_found", True)
|
||||
missing = [c for c in cards if not c.owned]
|
||||
owned = [c for c in cards if c.owned]
|
||||
|
||||
@@ -691,63 +406,47 @@ class DeckGeneratorV3:
|
||||
|
||||
logger.info("Substitution: %d missing / %d owned", len(missing), len(owned))
|
||||
|
||||
# Build owned pool
|
||||
# Build list of owned card names for substitution pool
|
||||
conn = self.db_conn_factory()
|
||||
owned_pool_rows = conn.execute(
|
||||
"SELECT DISTINCT name FROM collection_entries WHERE quantity > 0"
|
||||
).fetchall()
|
||||
owned_pool = {r["name"] for r in owned_pool_rows}
|
||||
deck_names = {c.name.lower() for c in cards}
|
||||
available_pool = {n for n in owned_pool if n.lower() not in deck_names}
|
||||
owned_pool = [r["name"] for r in owned_pool_rows]
|
||||
|
||||
# a) Embedding pass for missing cards
|
||||
needs_anthropic_fallback: List[DeckCardWithStatus] = []
|
||||
# Exclude cards already in the deck
|
||||
deck_names = set(c.name.lower() for c in cards)
|
||||
available_pool = [n for n in owned_pool if n.lower() not in deck_names]
|
||||
|
||||
# a) Embedding pass
|
||||
needs_pplx_fallback = []
|
||||
for card in missing:
|
||||
embedding_alts = self._embedding_substitution(
|
||||
card, color_identity, list(available_pool)
|
||||
card, color_identity, available_pool
|
||||
)
|
||||
card.alternatives = embedding_alts
|
||||
|
||||
# Check if best match meets threshold
|
||||
if embedding_alts and embedding_alts[0].similarity_score >= SUBSTITUTION_MIN_SIMILARITY:
|
||||
card.selected_substitute = embedding_alts[0].name
|
||||
card.status = "substituted"
|
||||
card.owned = True
|
||||
available_pool.discard(card.selected_substitute.lower())
|
||||
# Remove selected from pool
|
||||
if card.selected_substitute.lower() in [n.lower() for n in available_pool]:
|
||||
available_pool = [n for n in available_pool
|
||||
if n.lower() != card.selected_substitute.lower()]
|
||||
else:
|
||||
needs_anthropic_fallback.append(card)
|
||||
needs_pplx_fallback.append(card)
|
||||
|
||||
# b) Anthropic Claude fallback
|
||||
if needs_anthropic_fallback and SUBSTITUTION_USE_ANTHROPIC_FALLBACK:
|
||||
self._anthropic_substitution(
|
||||
needs_anthropic_fallback, list(available_pool),
|
||||
# b) Perplexity fallback for low-confidence matches
|
||||
if needs_pplx_fallback and SUBSTITUTION_USE_PPLX_FALLBACK:
|
||||
self._pplx_substitution(
|
||||
needs_pplx_fallback, available_pool,
|
||||
commander, strategy
|
||||
)
|
||||
|
||||
# c) Any card STILL missing after both passes gets a basic land — never drop it
|
||||
padded = 0
|
||||
for card in missing:
|
||||
if card.status == "missing":
|
||||
basic = _get_basic_land(color_identity)
|
||||
logger.warning(
|
||||
"[substitution] '%s' unresolved after all passes — "
|
||||
"replacing with basic land '%s'",
|
||||
card.name, basic,
|
||||
)
|
||||
card.name = basic
|
||||
card.category = "Land"
|
||||
card.role_tags = []
|
||||
card.owned = True
|
||||
card.status = "substituted"
|
||||
card.original_card = card.name
|
||||
padded += 1
|
||||
|
||||
# Count results
|
||||
substituted = sum(1 for c in cards if c.status == "substituted")
|
||||
still_missing = sum(1 for c in cards if c.status == "missing")
|
||||
|
||||
# Validate count hasn't changed
|
||||
assert len(cards) == len(owned) + len(missing), \
|
||||
f"[substitution] Card count changed: {len(owned) + len(missing)} -> {len(cards)}"
|
||||
|
||||
return SubstitutionBatchResult(
|
||||
total_cards=len(cards),
|
||||
owned_count=len(owned),
|
||||
@@ -766,37 +465,39 @@ class DeckGeneratorV3:
|
||||
if not self.embedding_index or not self.embedding_index.loaded:
|
||||
return []
|
||||
|
||||
try:
|
||||
matches = self.embedding_index.search_similar(
|
||||
query_card=card.name,
|
||||
color_filter=color_identity if color_identity else None,
|
||||
type_filter=card.category if card.category else None,
|
||||
exclude_cards=[card.name],
|
||||
top_n=SUBSTITUTION_MAX_ALTERNATIVES * 3,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.warning("Embedding search failed for '%s': %s", card.name, e)
|
||||
return []
|
||||
# Use the embeddings search to find similar cards
|
||||
matches = self.embedding_index.search_similar(
|
||||
query_card=card.name,
|
||||
color_filter=color_identity if color_identity else None,
|
||||
type_filter=card.category if card.category else None,
|
||||
exclude_cards=[card.name],
|
||||
top_n=SUBSTITUTION_MAX_ALTERNATIVES * 3, # Over-fetch, then filter to owned
|
||||
)
|
||||
|
||||
pool_lower = {n.lower() for n in available_pool}
|
||||
# Filter to only cards in the available pool
|
||||
pool_lower = set(n.lower() for n in available_pool)
|
||||
alternatives = []
|
||||
for match in matches:
|
||||
if match.name.lower() in pool_lower:
|
||||
role_overlap = list(set(card.role_tags) & set(getattr(match, "role_tags", [])))
|
||||
# Compute role overlap
|
||||
match_roles = [] # Would need card's role_tags from DB
|
||||
role_overlap = list(set(card.role_tags) & set(match_roles)) if match_roles else []
|
||||
|
||||
alternatives.append(CardAlternative(
|
||||
name=match.name,
|
||||
similarity_score=match.similarity,
|
||||
reason=f"Similar to {card.name} (cosine sim: {match.similarity:.3f})",
|
||||
source="embedding",
|
||||
role_overlap=role_overlap,
|
||||
cmc_delta=getattr(match, "mana_value", 0) - (card.estimated_price_usd or 0),
|
||||
cmc_delta=match.mana_value - (card.estimated_price_usd or 0),
|
||||
))
|
||||
|
||||
if len(alternatives) >= SUBSTITUTION_MAX_ALTERNATIVES:
|
||||
break
|
||||
|
||||
return alternatives
|
||||
|
||||
def _anthropic_substitution(
|
||||
def _pplx_substitution(
|
||||
self,
|
||||
missing_cards: List[DeckCardWithStatus],
|
||||
available_pool: List[str],
|
||||
@@ -804,14 +505,13 @@ class DeckGeneratorV3:
|
||||
strategy: str,
|
||||
):
|
||||
"""
|
||||
Batch Anthropic Claude fallback for cards with low embedding confidence.
|
||||
Mutates cards in-place. On failure, cards retain status='missing'
|
||||
so the basic-land fallback in run_substitution() can catch them.
|
||||
Batch Perplexity fallback for cards with low embedding confidence.
|
||||
Mutates the cards in-place with substitution data.
|
||||
"""
|
||||
if not available_pool:
|
||||
logger.warning("[anthropic_substitution] No available pool — skipping")
|
||||
return
|
||||
|
||||
# Build the request
|
||||
missing_dicts = [
|
||||
{
|
||||
"name": c.name,
|
||||
@@ -824,7 +524,7 @@ class DeckGeneratorV3:
|
||||
|
||||
user_prompt = build_substitution_prompt(
|
||||
missing_cards=missing_dicts,
|
||||
allowed_cards=available_pool[:200],
|
||||
allowed_cards=available_pool[:200], # Limit to avoid token overflow
|
||||
commander=commander.get("name", ""),
|
||||
color_identity=commander.get("color_identity", []),
|
||||
strategy=strategy,
|
||||
@@ -832,7 +532,7 @@ class DeckGeneratorV3:
|
||||
|
||||
try:
|
||||
from ..schemas.substitution_schema import SUBSTITUTION_RESPONSE_SCHEMA
|
||||
response = self.anthropic.chat_structured(
|
||||
response = self.pplx.chat_structured(
|
||||
system_prompt=SUBSTITUTION_SYSTEM,
|
||||
user_prompt=user_prompt,
|
||||
json_schema=SUBSTITUTION_RESPONSE_SCHEMA,
|
||||
@@ -843,16 +543,13 @@ class DeckGeneratorV3:
|
||||
)
|
||||
|
||||
if not response.ok:
|
||||
logger.warning(
|
||||
"[anthropic_substitution] LLM returned non-JSON — "
|
||||
"%d cards will fall through to basic land fallback",
|
||||
len(missing_cards),
|
||||
)
|
||||
logger.warning("Perplexity substitution fallback failed — non-JSON response")
|
||||
return
|
||||
|
||||
subs = response.parsed_json.get("substitutions", [])
|
||||
logger.info("[anthropic_substitution] Received %d substitutions", len(subs))
|
||||
logger.info("Perplexity suggested %d substitutions", len(subs))
|
||||
|
||||
# Apply substitutions
|
||||
card_by_name = {c.name.lower(): c for c in missing_cards}
|
||||
for sub in subs:
|
||||
orig = sub.get("original", "").lower()
|
||||
@@ -861,38 +558,32 @@ class DeckGeneratorV3:
|
||||
|
||||
if orig in card_by_name and substitute:
|
||||
card = card_by_name[orig]
|
||||
anthropic_alt = CardAlternative(
|
||||
# Add as top alternative
|
||||
pplx_alt = CardAlternative(
|
||||
name=substitute,
|
||||
similarity_score=0.80,
|
||||
similarity_score=0.80, # Nominal score for Perplexity suggestions
|
||||
reason=reason,
|
||||
source="anthropic",
|
||||
source="perplexity",
|
||||
role_overlap=sub.get("role_overlap", []),
|
||||
)
|
||||
card.alternatives.insert(0, anthropic_alt)
|
||||
# Insert at front
|
||||
card.alternatives.insert(0, pplx_alt)
|
||||
card.selected_substitute = substitute
|
||||
card.status = "substituted"
|
||||
card.owned = True
|
||||
card.original_card = card.name
|
||||
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
"[anthropic_substitution] Exception: %s — "
|
||||
"%d cards will fall through to basic land fallback",
|
||||
e, len(missing_cards),
|
||||
)
|
||||
# Do NOT re-raise — cards stay status='missing' and
|
||||
# run_substitution()'s basic-land fallback will handle them
|
||||
logger.error("Perplexity substitution fallback error: %s", e)
|
||||
|
||||
# ── Stats ────────────────────────────────────────────────
|
||||
@staticmethod
|
||||
def _compute_stats(cards: List[DeckCardWithStatus]) -> dict:
|
||||
"""Compute deck statistics from the enriched card list."""
|
||||
by_category: dict[str, int] = {}
|
||||
by_status: dict[str, int] = {"owned": 0, "substituted": 0, "missing": 0}
|
||||
by_category = {}
|
||||
by_status = {"owned": 0, "substituted": 0, "missing": 0}
|
||||
total_price = 0.0
|
||||
owned_price = 0.0
|
||||
missing_price = 0.0
|
||||
role_counts: dict[str, int] = {}
|
||||
role_counts = {}
|
||||
|
||||
for card in cards:
|
||||
cat = card.category or "Other"
|
||||
|
||||
@@ -137,7 +137,7 @@ if (-not (Test-Path $envFile)) {
|
||||
# Uncomment and fill in the values you need:
|
||||
|
||||
# XIMILAR_API_KEY=your_ximilar_key_here
|
||||
# ANTHROPIC_API_KEY=your_anthropic_api_key_here
|
||||
# PPLX_API_KEY=your_perplexity_key_here
|
||||
# FORGE_JAR=C:\Path\To\forge-gui-desktop.jar
|
||||
# FORGE_DIR=C:\Path\To\Forge
|
||||
# LAB_PORT=8080
|
||||
|
||||
+78
-111
@@ -3,13 +3,9 @@
|
||||
Commander AI Lab — FastAPI Backend
|
||||
Thin entry point: registers routers and starts uvicorn.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import asyncio
|
||||
import logging
|
||||
import os
|
||||
from contextlib import asynccontextmanager
|
||||
from pathlib import Path
|
||||
|
||||
try:
|
||||
@@ -26,96 +22,35 @@ except ImportError:
|
||||
print("ERROR: FastAPI not installed. Run: pip install fastapi uvicorn")
|
||||
import sys; sys.exit(1)
|
||||
|
||||
from models.state import CFG, COMMANDER_META, load_commander_meta, validate_forge_config
|
||||
from services.database import init_collection_db
|
||||
from services.logging import setup_logging
|
||||
from services.precon_service import PRECON_INDEX, download_precon_database
|
||||
from routes.shared import (
|
||||
CFG,
|
||||
setup_logging,
|
||||
init_collection_db,
|
||||
download_precon_database,
|
||||
load_commander_meta,
|
||||
PRECON_INDEX,
|
||||
COMMANDER_META,
|
||||
)
|
||||
from routes.collection import router as collection_router
|
||||
from routes.deckbuilder import router as deckbuilder_router
|
||||
from routes.precon import router as precon_router
|
||||
from routes.import_routes import router as import_router
|
||||
from routes.lab import router as lab_router
|
||||
from routes.scanner import router as scanner_router
|
||||
from routes.rag import router as rag_router
|
||||
from routes.deepseek import router as deepseek_router
|
||||
from routes.deckgen import router as deckgen_router
|
||||
from routes.coach import router as coach_router, init_coach_service
|
||||
from routes.ml import router as ml_router
|
||||
from routes.ws_game import router as ws_game_router
|
||||
from routes.game import router as game_router
|
||||
|
||||
log = logging.getLogger("commander_ai_lab.api")
|
||||
|
||||
_DEFAULT_ORIGINS = "http://localhost:5173,http://localhost:3000,http://localhost:8080"
|
||||
# ── CORS origins (env-configurable) ────────────────────────────
|
||||
_DEFAULT_ORIGINS = "http://localhost:5173,http://localhost:8080,http://192.168.0.240:5173,http://192.168.0.240:8080"
|
||||
_allowed = os.environ.get("ALLOWED_ORIGINS", _DEFAULT_ORIGINS)
|
||||
allowed_origins = [o.strip() for o in _allowed.split(",") if o.strip()]
|
||||
|
||||
|
||||
# ── Lifespan (replaces deprecated @app.on_event) ────────────────────────────────────────────────────────
|
||||
@asynccontextmanager
|
||||
async def _lifespan(application: FastAPI):
|
||||
# ──── STARTUP ────
|
||||
if not CFG.precon_dir:
|
||||
CFG.precon_dir = _resolve_precon_dir()
|
||||
init_collection_db()
|
||||
validate_forge_config()
|
||||
if not PRECON_INDEX:
|
||||
download_precon_database()
|
||||
if not COMMANDER_META:
|
||||
load_commander_meta()
|
||||
|
||||
loop = asyncio.get_running_loop()
|
||||
|
||||
# RAG Phase 1: kick off Scryfall bulk download in background thread.
|
||||
from services.scryfall_bulk import ensure_bulk_db
|
||||
loop.run_in_executor(None, ensure_bulk_db)
|
||||
|
||||
# RAG Phase 2: kick off ChromaDB vector store build in background thread.
|
||||
from services.rag_store import ensure_rag_store
|
||||
loop.run_in_executor(None, ensure_rag_store)
|
||||
|
||||
# RAG Phase 3: background staleness monitor (rebuilds if >14 days old)
|
||||
async def _rag_staleness_monitor():
|
||||
"""Periodically check if the RAG index needs rebuilding."""
|
||||
import time as _time
|
||||
while True:
|
||||
await asyncio.sleep(6 * 3600) # check every 6 hours
|
||||
try:
|
||||
from services.rag_store import check_staleness, build_index
|
||||
info = check_staleness()
|
||||
if info.get("stale"):
|
||||
log.info("RAG staleness monitor: %s — triggering rebuild.", info["reason"])
|
||||
loop.run_in_executor(None, lambda: build_index(force=True))
|
||||
else:
|
||||
log.debug("RAG staleness monitor: index is current (%.1f days).", info.get("age_days", 0))
|
||||
except Exception as exc:
|
||||
log.warning("RAG staleness monitor failed: %s", exc)
|
||||
asyncio.ensure_future(_rag_staleness_monitor())
|
||||
|
||||
# Policy routes: register if ML policy model is available
|
||||
try:
|
||||
from ml.serving.policy_server import PolicyInferenceService
|
||||
from routes.policy import register_policy_routes
|
||||
_policy_svc = PolicyInferenceService()
|
||||
if _policy_svc.load():
|
||||
register_policy_routes(application, _policy_svc)
|
||||
log.info("Policy routes registered (/api/policy/*)")
|
||||
else:
|
||||
log.warning("Policy model not loaded — /api/policy/* routes inactive")
|
||||
except ImportError:
|
||||
log.info("Policy service not available (ml.serving not installed)")
|
||||
except Exception as e:
|
||||
log.warning("Policy route registration failed (non-fatal): %s", e)
|
||||
|
||||
yield # ← server is running
|
||||
|
||||
# ──── SHUTDOWN ────
|
||||
from services.async_db import async_close_db
|
||||
await async_close_db()
|
||||
|
||||
|
||||
# ── App ─────────────────────────────────────────────────────────────────────────────
|
||||
app = FastAPI(title="Commander AI Lab API", version="3.0.0", lifespan=_lifespan)
|
||||
# ── App ────────────────────────────────────────────────────────
|
||||
app = FastAPI(title="Commander AI Lab API", version="3.0.0")
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=allowed_origins,
|
||||
@@ -130,29 +65,34 @@ app.include_router(precon_router)
|
||||
app.include_router(import_router)
|
||||
app.include_router(lab_router)
|
||||
app.include_router(scanner_router)
|
||||
app.include_router(rag_router)
|
||||
app.include_router(deepseek_router)
|
||||
app.include_router(deckgen_router)
|
||||
app.include_router(coach_router)
|
||||
app.include_router(ws_game_router)
|
||||
app.include_router(ml_router)
|
||||
app.include_router(game_router) # live game session routes
|
||||
|
||||
|
||||
# ── API endpoints ─────────────────────────────────────────────────────────────────────────────
|
||||
# NOTE: all @app.get routes MUST be registered before app.mount() calls.
|
||||
# Once StaticFiles is mounted at "/", it registers a wildcard catch-all that
|
||||
# shadows any routes added after it.
|
||||
|
||||
@app.get("/api/health")
|
||||
async def health_check():
|
||||
"""Health check endpoint for load balancers and Unity client polling."""
|
||||
return {"status": "ok"}
|
||||
|
||||
# ── Static UI (MUST come after all @app.get routes) ──────────────────────────────────────────
|
||||
from pathlib import Path as _Path
|
||||
_legacy_ui_dir = _Path(__file__).parent / "ui"
|
||||
_spa_dir = _Path(__file__).parent / "frontend" / "commander-ai-lab-ui" / "dist"
|
||||
|
||||
@app.on_event("startup")
|
||||
async def _on_startup():
|
||||
"""Ensure DB and precon index are ready (supports uvicorn --reload)."""
|
||||
import routes.shared as _shared
|
||||
# Ensure precon_dir is resolved even when started via uvicorn directly
|
||||
if not CFG.precon_dir:
|
||||
CFG.precon_dir = _resolve_precon_dir()
|
||||
_shared.init_collection_db()
|
||||
if not _shared.PRECON_INDEX:
|
||||
_shared.download_precon_database()
|
||||
if not _shared.COMMANDER_META:
|
||||
_shared.load_commander_meta()
|
||||
|
||||
# ── Static UI ──────────────────────────────────────────────────
|
||||
_legacy_ui_dir = Path(__file__).parent / "ui"
|
||||
_spa_dir = Path(__file__).parent / "frontend" / "commander-ai-lab-ui" / "dist"
|
||||
|
||||
if _legacy_ui_dir.exists():
|
||||
app.mount("/", StaticFiles(directory=str(_legacy_ui_dir), html=True), name="ui")
|
||||
@@ -160,7 +100,6 @@ elif _spa_dir.exists():
|
||||
_spa_assets = _spa_dir / "assets"
|
||||
if _spa_assets.exists():
|
||||
app.mount("/assets", StaticFiles(directory=str(_spa_assets)), name="spa-assets")
|
||||
|
||||
@app.get("/{full_path:path}")
|
||||
async def _spa_catchall(full_path: str):
|
||||
from fastapi.responses import FileResponse
|
||||
@@ -169,8 +108,7 @@ elif _spa_dir.exists():
|
||||
return FileResponse(str(requested_file))
|
||||
return FileResponse(str(_spa_dir / "index.html"))
|
||||
|
||||
|
||||
# ── Argument parsing + auto-detection helpers ────────────────────────────────────────────────────────
|
||||
# ── Startup ────────────────────────────────────────────────────
|
||||
def _parse_args():
|
||||
p = argparse.ArgumentParser(description="Commander AI Lab API Server")
|
||||
p.add_argument("--forge-jar", default=os.environ.get("FORGE_JAR", ""))
|
||||
@@ -180,11 +118,10 @@ def _parse_args():
|
||||
p.add_argument("--precon-dir", default=os.environ.get("PRECON_DIR", ""))
|
||||
p.add_argument("--port", type=int, default=int(os.environ.get("LAB_PORT", "8080")))
|
||||
p.add_argument("--ximilar-key", default=os.environ.get("XIMILAR_API_KEY", ""))
|
||||
p.add_argument("--anthropic-key", default=os.environ.get("ANTHROPIC_API_KEY", ""))
|
||||
p.add_argument("--pplx-key", default=os.environ.get("PPLX_API_KEY", ""))
|
||||
p.add_argument("--verbose", "-v", action="store_true")
|
||||
return p.parse_args()
|
||||
|
||||
|
||||
def _resolve_forge_decks_dir() -> str:
|
||||
import sys
|
||||
if sys.platform == "win32":
|
||||
@@ -202,35 +139,52 @@ def _resolve_forge_decks_dir() -> str:
|
||||
return str(candidate)
|
||||
return ""
|
||||
|
||||
|
||||
def _resolve_forge_dir() -> str:
|
||||
"""Auto-detect the Forge installation directory."""
|
||||
"""Auto-detect the Forge installation directory.
|
||||
|
||||
The Forge dir is the root of a Forge install — it typically contains
|
||||
a 'res' subdirectory with card data. We derive it from the JAR
|
||||
location (parent of 'target/') or look in common install paths.
|
||||
"""
|
||||
import sys
|
||||
|
||||
# 1. If forge_jar is already resolved, derive forge_dir from it.
|
||||
# JAR lives in <forge-root>/forge-gui-desktop/target/<jar>
|
||||
# so forge_dir = JAR's grandparent's parent.
|
||||
if CFG.forge_jar and os.path.isfile(CFG.forge_jar):
|
||||
jar_path = Path(CFG.forge_jar)
|
||||
# target/ -> forge-gui-desktop/ -> <forge-root>
|
||||
candidate = jar_path.parent.parent.parent
|
||||
if candidate.is_dir() and (candidate / "res").is_dir():
|
||||
return str(candidate)
|
||||
# Also try just one level up from target/
|
||||
candidate = jar_path.parent.parent
|
||||
# Check forge-gui sibling of forge-gui-desktop (res/ lives there)
|
||||
forge_gui_sibling = jar_path.parent.parent.parent / "forge-gui"
|
||||
if forge_gui_sibling.is_dir() and (forge_gui_sibling / "res").is_dir():
|
||||
return str(forge_gui_sibling)
|
||||
if candidate.is_dir() and (candidate / "res").is_dir():
|
||||
return str(candidate)
|
||||
# Fall back to the directory containing the JAR itself
|
||||
candidate = jar_path.parent
|
||||
if candidate.is_dir():
|
||||
return str(candidate)
|
||||
|
||||
# 2. Check common sibling/child directories relative to project root
|
||||
project_root = Path(__file__).parent
|
||||
for candidate in [
|
||||
project_root / "forge",
|
||||
project_root.parent / "forge-repo",
|
||||
project_root.parent / "forge-repo" / "forge-gui",
|
||||
project_root.parent / "forge-repo" / "forge-gui",
|
||||
project_root.parent / "forge",
|
||||
project_root / "forge-gui-desktop",
|
||||
]:
|
||||
if candidate.is_dir():
|
||||
# Prefer directory that has 'res' subfolder
|
||||
if (candidate / "res").is_dir():
|
||||
return str(candidate)
|
||||
|
||||
# 3. Platform-specific user data directories
|
||||
if sys.platform == "win32":
|
||||
appdata = os.environ.get("APPDATA", "")
|
||||
if appdata:
|
||||
@@ -238,25 +192,32 @@ def _resolve_forge_dir() -> str:
|
||||
if candidate.is_dir():
|
||||
return str(candidate)
|
||||
home = Path.home()
|
||||
for candidate in [home / ".forge", home / "Forge"]:
|
||||
for candidate in [
|
||||
home / ".forge",
|
||||
home / "Forge",
|
||||
]:
|
||||
if candidate.is_dir():
|
||||
return str(candidate)
|
||||
return ""
|
||||
|
||||
|
||||
def _resolve_forge_jar() -> str:
|
||||
"""Auto-detect the Forge GUI desktop JAR in common locations."""
|
||||
project_root = Path(__file__).parent
|
||||
|
||||
# Candidate directories where the Forge JAR might live
|
||||
candidates = [
|
||||
project_root / "forge-gui-desktop" / "target",
|
||||
project_root.parent / "forge-repo" / "forge-gui-desktop" / "target",
|
||||
project_root.parent / "forge" / "forge-gui-desktop" / "target",
|
||||
]
|
||||
|
||||
# Also check FORGE_DIR/../forge-gui-desktop/target if FORGE_DIR is set
|
||||
forge_dir_env = os.environ.get("FORGE_DIR", "")
|
||||
if forge_dir_env:
|
||||
fd = Path(forge_dir_env)
|
||||
candidates.append(fd.parent / "forge-gui-desktop" / "target")
|
||||
candidates.append(fd / "target")
|
||||
|
||||
for target_dir in candidates:
|
||||
if target_dir.is_dir():
|
||||
for pattern in [
|
||||
@@ -270,7 +231,6 @@ def _resolve_forge_jar() -> str:
|
||||
return str(jars[0])
|
||||
return ""
|
||||
|
||||
|
||||
def _resolve_lab_jar() -> str:
|
||||
target_dir = Path(__file__).parent / "target"
|
||||
if target_dir.exists():
|
||||
@@ -285,25 +245,36 @@ def _resolve_lab_jar() -> str:
|
||||
return str(jars[0])
|
||||
return ""
|
||||
|
||||
|
||||
def _resolve_precon_dir() -> str:
|
||||
"""Auto-detect the precon-decks directory."""
|
||||
"""Auto-detect the precon-decks directory.
|
||||
|
||||
The precon-decks dir lives in the project root and contains downloaded
|
||||
.dck files plus precon-index.json. We check relative to this file
|
||||
(lab_api.py) first, then common sibling paths.
|
||||
"""
|
||||
project_root = Path(__file__).parent
|
||||
|
||||
# 1. Standard location: <project-root>/precon-decks
|
||||
candidate = project_root / "precon-decks"
|
||||
if candidate.is_dir():
|
||||
return str(candidate)
|
||||
|
||||
# 2. Check parent directory (in case running from a subdirectory)
|
||||
candidate = project_root.parent / "precon-decks"
|
||||
if candidate.is_dir():
|
||||
return str(candidate)
|
||||
|
||||
# 3. Derive from forge_dir if available
|
||||
if CFG.forge_dir:
|
||||
candidate = Path(CFG.forge_dir) / "precon-decks"
|
||||
if candidate.is_dir():
|
||||
return str(candidate)
|
||||
|
||||
# 4. Fall back: create the directory in the project root so downloads work
|
||||
fallback = project_root / "precon-decks"
|
||||
fallback.mkdir(parents=True, exist_ok=True)
|
||||
return str(fallback)
|
||||
|
||||
|
||||
def main():
|
||||
args = _parse_args()
|
||||
setup_logging(logging.DEBUG if args.verbose else logging.INFO)
|
||||
@@ -315,9 +286,9 @@ def main():
|
||||
CFG.precon_dir = args.precon_dir or _resolve_precon_dir()
|
||||
CFG.port = args.port
|
||||
CFG.ximilar_api_key = args.ximilar_key
|
||||
CFG.anthropic_api_key = args.anthropic_key
|
||||
CFG.pplx_api_key = args.pplx_key
|
||||
|
||||
from services.forge_runner import get_java17
|
||||
from routes.shared import get_java17
|
||||
j17 = get_java17()
|
||||
|
||||
log.info("Commander AI Lab — API Server v3.0.0")
|
||||
@@ -329,7 +300,7 @@ def main():
|
||||
log.info(f" Lab JAR: {CFG.lab_jar or 'NOT SET'}")
|
||||
log.info(f" Results: {CFG.results_dir}")
|
||||
log.info(f" Ximilar: {'configured' if CFG.ximilar_api_key else 'NOT SET'}")
|
||||
log.info(f" Anthropic: {'configured' if CFG.anthropic_api_key else 'NOT SET'}")
|
||||
log.info(f" Perplexity: {'configured' if CFG.pplx_api_key else 'NOT SET'}")
|
||||
log.info(f" Java 17: {j17}")
|
||||
|
||||
load_commander_meta()
|
||||
@@ -337,12 +308,8 @@ def main():
|
||||
init_collection_db()
|
||||
init_coach_service()
|
||||
|
||||
# RAG Phase 1 + 2 are handled by _lifespan when uvicorn starts.
|
||||
# No need to call them here — doing so causes a double-run.
|
||||
|
||||
import uvicorn
|
||||
uvicorn.run(app, host="0.0.0.0", port=CFG.port, log_level="info")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
+3
-49
@@ -155,25 +155,15 @@ class StateDimensions:
|
||||
2 players = 28 global features
|
||||
+ turn_number = 1
|
||||
Total global = 29
|
||||
|
||||
Zone embedding boundary (architectural decision — Phase 5 follow-up):
|
||||
Zone dims are **always** 768 per zone slot, zero-padded when a zone
|
||||
is empty (no cards). The fixed 6144-dim zone block is the contract
|
||||
between ForgeEpisodeGenerator (upstream) and the policy network
|
||||
(downstream). All downstream consumers (PolicyNetwork, PPOTrainer,
|
||||
dataset builder) depend on this shape. If a future change adds
|
||||
attention pooling or variable-length zone representations, the
|
||||
boundary must be updated here *and* in StateEncoder._encode_zones.
|
||||
"""
|
||||
card_embedding_dim: int = 768 # From mtg-embeddings
|
||||
zone_pool_dim: int = 768 # Mean-pooled per zone (zero-vec when empty)
|
||||
zone_pool_dim: int = 768 # Mean-pooled per zone
|
||||
|
||||
# Zones per player: hand, battlefield, graveyard, command_zone
|
||||
zones_per_player: int = 4
|
||||
num_players: int = 2 # 1v1
|
||||
|
||||
# Zone vectors: 4 zones × 2 players × 768 = 6144
|
||||
# This is a fixed-size block; empty zones produce zero vectors.
|
||||
total_zone_dim: int = 4 * 2 * 768 # 6144
|
||||
|
||||
# Global scalar features
|
||||
@@ -278,10 +268,6 @@ class DistillationDefaults:
|
||||
|
||||
These are consumed by ml.training.distillation_loop.DistillationConfig
|
||||
when no explicit override is provided.
|
||||
|
||||
Default weights: Forge-only (forge_weight=1.0, ppo_weight=0.0).
|
||||
The baseline trains exclusively on Forge simulation data. Use
|
||||
``MIXED_MODE_PRESETS`` below for blended Forge+PPO configurations.
|
||||
"""
|
||||
max_iterations: int = 10
|
||||
convergence_window: int = 3
|
||||
@@ -295,9 +281,9 @@ class DistillationDefaults:
|
||||
ppo_entropy_coeff: float = 0.01
|
||||
ppo_eval_episodes: int = 100
|
||||
|
||||
# Dataset mixing — Forge-only by default (Phase 5 follow-up decision)
|
||||
# Dataset mixing
|
||||
forge_weight: float = 1.0
|
||||
ppo_weight: float = 0.0
|
||||
ppo_weight: float = 0.5
|
||||
min_reward_threshold: float = 0.0
|
||||
|
||||
# Quality gate thresholds
|
||||
@@ -316,35 +302,3 @@ class DistillationDefaults:
|
||||
|
||||
|
||||
DISTILLATION_DEFAULTS = DistillationDefaults()
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════
|
||||
# Mixed-Mode Presets (Phase 5 follow-up)
|
||||
# ══════════════════════════════════════════════════════════
|
||||
|
||||
# Pre-defined Forge/PPO weight combinations for common scenarios.
|
||||
# Select a preset by name when starting a distillation run to
|
||||
# override the Forge-only defaults without specifying raw weights.
|
||||
#
|
||||
# "forge_only" — baseline: 100% Forge data, ignore PPO
|
||||
# "forge_90_10" — light PPO blending: 90% Forge, 10% PPO
|
||||
# "forge_80_20" — heavier PPO blending: 80% Forge, 20% PPO
|
||||
MIXED_MODE_PRESETS: Dict[str, Dict[str, float]] = {
|
||||
"forge_only": {"forge_weight": 1.0, "ppo_weight": 0.0},
|
||||
"forge_90_10": {"forge_weight": 1.0, "ppo_weight": 0.11}, # ~10% PPO
|
||||
"forge_80_20": {"forge_weight": 1.0, "ppo_weight": 0.25}, # ~20% PPO
|
||||
}
|
||||
|
||||
|
||||
def get_preset_weights(preset_name: str) -> Dict[str, float]:
|
||||
"""Look up a mixed-mode preset by name.
|
||||
|
||||
Returns a dict with ``forge_weight`` and ``ppo_weight`` keys.
|
||||
Raises ``KeyError`` if the preset name is unknown.
|
||||
"""
|
||||
if preset_name not in MIXED_MODE_PRESETS:
|
||||
raise KeyError(
|
||||
f"Unknown preset '{preset_name}'. "
|
||||
f"Available: {list(MIXED_MODE_PRESETS.keys())}"
|
||||
)
|
||||
return dict(MIXED_MODE_PRESETS[preset_name])
|
||||
@@ -63,10 +63,10 @@ class DatasetConfig:
|
||||
max_samples: Optional[int] = None
|
||||
|
||||
# Source weights control sampling ratios between Forge and PPO data.
|
||||
# Default: Forge-only (ppo=0.0). Use MIXED_MODE_PRESETS from
|
||||
# ml.config.scope for blended configurations (e.g. 90/10, 80/20).
|
||||
# e.g. {"forge": 1.0, "ppo": 0.5} means keep all Forge data but
|
||||
# randomly sample 50% of PPO data to avoid overwhelming the baseline.
|
||||
source_weights: Dict[str, float] = field(
|
||||
default_factory=lambda: {"forge": 1.0, "ppo": 0.0}
|
||||
default_factory=lambda: {"forge": 1.0, "ppo": 0.5}
|
||||
)
|
||||
|
||||
# Minimum reward threshold for PPO data — only include decisions
|
||||
@@ -209,7 +209,7 @@ def build_dataset(
|
||||
Dict with keys: states, labels, game_ids, outcomes, playstyles, sources
|
||||
"""
|
||||
if source_weights is None:
|
||||
source_weights = {"forge": 1.0, "ppo": 0.0}
|
||||
source_weights = {"forge": 1.0, "ppo": 0.5}
|
||||
|
||||
# Load card embeddings
|
||||
card_index = CardEmbeddingIndex(embeddings_dir)
|
||||
@@ -502,8 +502,8 @@ def main():
|
||||
help="Sampling weight for Forge sim data (default: 1.0)",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--ppo-weight", type=float, default=0.0,
|
||||
help="Sampling weight for PPO self-play data (default: 0.0, Forge-only)",
|
||||
"--ppo-weight", type=float, default=0.5,
|
||||
help="Sampling weight for PPO self-play data (default: 0.5)",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--min-reward", type=float, default=0.0,
|
||||
|
||||
@@ -276,13 +276,6 @@ class StateEncoder:
|
||||
"""
|
||||
Encode zone contents as mean-pooled card embeddings.
|
||||
Shape: (4 zones × 2 players × 768) = (6144,)
|
||||
|
||||
Zone embedding boundary: each zone slot is exactly ``zone_pool_dim``
|
||||
(768) floats. Empty zones produce a zero vector of that size. This
|
||||
fixed-size contract is relied upon by every downstream consumer
|
||||
(PolicyNetwork, PPOTrainer, dataset builder). See
|
||||
``StateDimensions`` in ``ml/config/scope.py`` for the canonical
|
||||
definition.
|
||||
"""
|
||||
zone_keys = ["hand", "battlefield", "graveyard", "command_zone"]
|
||||
vectors = []
|
||||
@@ -290,8 +283,6 @@ class StateEncoder:
|
||||
for p in players[:2]:
|
||||
for zone_key in zone_keys:
|
||||
cards = p.get(zone_key, [])
|
||||
# mean_pool_zone returns a zero vector when cards is empty,
|
||||
# preserving the fixed 768-dim slot size.
|
||||
pooled = self.card_index.mean_pool_zone(cards)
|
||||
vectors.append(pooled)
|
||||
|
||||
|
||||
+1
-25
@@ -16,7 +16,6 @@ Reuses `run_match`, `LearnedPolicy`, `HeuristicPolicy`,
|
||||
Usage:
|
||||
python -m ml.eval.elo_tracker
|
||||
python -m ml.eval.elo_tracker --episodes 50 --output data/elo_history.json
|
||||
python -m ml.eval.elo_tracker --top-n 10
|
||||
"""
|
||||
|
||||
import json
|
||||
@@ -286,17 +285,12 @@ def run_generation_tournament(
|
||||
episodes_per_matchup: int = 50,
|
||||
playstyle: str = "midrange",
|
||||
k_factor: float = DEFAULT_K,
|
||||
top_n: int = 10,
|
||||
) -> EloResult:
|
||||
"""
|
||||
Discover generation checkpoints and run an ELO tournament.
|
||||
|
||||
Looks for `gen-*/best_policy.pt` under checkpoint_dir.
|
||||
Also includes heuristic and random baselines.
|
||||
|
||||
Args:
|
||||
top_n: Only include the N most recent gen-* checkpoints.
|
||||
0 means include all (unbounded). Default is 10.
|
||||
"""
|
||||
policies: Dict[str, object] = {
|
||||
"heuristic": HeuristicPolicy(),
|
||||
@@ -305,20 +299,7 @@ def run_generation_tournament(
|
||||
|
||||
ckpt_path = Path(checkpoint_dir)
|
||||
if ckpt_path.exists():
|
||||
gen_dirs = sorted(ckpt_path.glob("gen-*"))
|
||||
|
||||
# Apply top_n cutoff — keep only the latest N generation dirs
|
||||
if top_n > 0 and len(gen_dirs) > top_n:
|
||||
skipped = len(gen_dirs) - top_n
|
||||
logger.info(
|
||||
"top_n=%d: skipping %d older generation(s), using %s … %s",
|
||||
top_n, skipped,
|
||||
gen_dirs[-top_n].name,
|
||||
gen_dirs[-1].name,
|
||||
)
|
||||
gen_dirs = gen_dirs[-top_n:]
|
||||
|
||||
for gen_dir in gen_dirs:
|
||||
for gen_dir in sorted(ckpt_path.glob("gen-*")):
|
||||
model_path = gen_dir / "best_policy.pt"
|
||||
if model_path.exists():
|
||||
name = gen_dir.name # e.g., "gen-001"
|
||||
@@ -382,10 +363,6 @@ def main():
|
||||
"--k-factor", type=float, default=32,
|
||||
help="ELO K-factor (default: 32)",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--top-n", type=int, default=10,
|
||||
help="Only include the N most recent gen checkpoints (0 = all, default: 10)",
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
@@ -396,7 +373,6 @@ def main():
|
||||
episodes_per_matchup=args.episodes,
|
||||
playstyle=args.playstyle,
|
||||
k_factor=args.k_factor,
|
||||
top_n=args.top_n,
|
||||
)
|
||||
|
||||
# Print results
|
||||
|
||||
@@ -1,210 +0,0 @@
|
||||
"""
|
||||
Commander AI Lab — Online Learning Store (SQLite WAL)
|
||||
═════════════════════════════════════════════════════
|
||||
|
||||
Single-machine backing store for online learning data collected during
|
||||
policy inference (``/api/ml/predict`` and ``/api/policy/decide``).
|
||||
|
||||
Each prediction request can optionally log the state snapshot and the
|
||||
chosen action so that future training runs can incorporate online
|
||||
decision data alongside Forge and PPO batches.
|
||||
|
||||
Design decisions (Phase 5 architecture follow-up):
|
||||
- SQLite in WAL mode for concurrent readers + single writer, which is
|
||||
the right fit for a single-machine baseline (one API server process).
|
||||
- Separate DB file (``online_learning.db``) to avoid contention with
|
||||
the collection database.
|
||||
- Append-only writes; reads are batched by the dataset builder.
|
||||
- Thread-safe via the Python sqlite3 module's ``check_same_thread=False``
|
||||
and WAL's built-in reader/writer concurrency.
|
||||
|
||||
Usage::
|
||||
|
||||
store = OnlineLearningStore() # uses default path
|
||||
store.init_db()
|
||||
|
||||
# At prediction time:
|
||||
store.record_decision(snapshot_json, action_index, confidence, playstyle)
|
||||
|
||||
# At training time:
|
||||
decisions = store.fetch_decisions(since_rowid=last_seen, limit=10000)
|
||||
store.mark_exported(max_rowid)
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import sqlite3
|
||||
import threading
|
||||
from pathlib import Path
|
||||
from typing import Dict, List, Optional
|
||||
|
||||
logger = logging.getLogger("ml.serving.online_store")
|
||||
|
||||
_DEFAULT_DB_PATH = str(
|
||||
Path(__file__).parent.parent.parent / "online_learning.db"
|
||||
)
|
||||
|
||||
|
||||
class OnlineLearningStore:
|
||||
"""SQLite WAL-backed store for online policy decision collection."""
|
||||
|
||||
def __init__(self, db_path: str = None):
|
||||
self.db_path = db_path or _DEFAULT_DB_PATH
|
||||
self._local = threading.local()
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Connection management
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
def _get_conn(self) -> sqlite3.Connection:
|
||||
"""Return a thread-local connection with WAL mode enabled."""
|
||||
if not hasattr(self._local, "conn") or self._local.conn is None:
|
||||
conn = sqlite3.connect(self.db_path, check_same_thread=False)
|
||||
conn.row_factory = sqlite3.Row
|
||||
# Enable WAL for concurrent read/write on single machine.
|
||||
conn.execute("PRAGMA journal_mode=WAL")
|
||||
conn.execute("PRAGMA synchronous=NORMAL")
|
||||
self._local.conn = conn
|
||||
return self._local.conn
|
||||
|
||||
def close(self) -> None:
|
||||
"""Close the thread-local connection."""
|
||||
conn = getattr(self._local, "conn", None)
|
||||
if conn is not None:
|
||||
try:
|
||||
conn.close()
|
||||
except Exception:
|
||||
pass
|
||||
self._local.conn = None
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Schema
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
def init_db(self) -> None:
|
||||
"""Create the decisions table if it doesn't exist."""
|
||||
conn = self._get_conn()
|
||||
conn.executescript("""
|
||||
CREATE TABLE IF NOT EXISTS online_decisions (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
snapshot TEXT NOT NULL,
|
||||
action_idx INTEGER NOT NULL,
|
||||
confidence REAL NOT NULL DEFAULT 0.0,
|
||||
playstyle TEXT NOT NULL DEFAULT 'midrange',
|
||||
temperature REAL NOT NULL DEFAULT 1.0,
|
||||
greedy INTEGER NOT NULL DEFAULT 0,
|
||||
exported INTEGER NOT NULL DEFAULT 0,
|
||||
created_at TEXT NOT NULL DEFAULT (datetime('now'))
|
||||
);
|
||||
|
||||
CREATE INDEX IF NOT EXISTS idx_od_exported
|
||||
ON online_decisions(exported);
|
||||
CREATE INDEX IF NOT EXISTS idx_od_created
|
||||
ON online_decisions(created_at);
|
||||
""")
|
||||
conn.commit()
|
||||
logger.info("Online learning store ready: %s (WAL mode)", self.db_path)
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Write path (called during prediction)
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
def record_decision(
|
||||
self,
|
||||
snapshot: Dict,
|
||||
action_idx: int,
|
||||
confidence: float,
|
||||
playstyle: str = "midrange",
|
||||
temperature: float = 1.0,
|
||||
greedy: bool = False,
|
||||
) -> int:
|
||||
"""Append a policy decision for future training.
|
||||
|
||||
Returns the row id of the inserted record.
|
||||
"""
|
||||
conn = self._get_conn()
|
||||
cur = conn.execute(
|
||||
"""
|
||||
INSERT INTO online_decisions
|
||||
(snapshot, action_idx, confidence, playstyle, temperature, greedy)
|
||||
VALUES (?, ?, ?, ?, ?, ?)
|
||||
""",
|
||||
(
|
||||
json.dumps(snapshot, separators=(",", ":")),
|
||||
action_idx,
|
||||
confidence,
|
||||
playstyle,
|
||||
temperature,
|
||||
1 if greedy else 0,
|
||||
),
|
||||
)
|
||||
conn.commit()
|
||||
return cur.lastrowid
|
||||
|
||||
# ------------------------------------------------------------------
|
||||
# Read path (called by dataset builder / training pipeline)
|
||||
# ------------------------------------------------------------------
|
||||
|
||||
def fetch_decisions(
|
||||
self,
|
||||
since_rowid: int = 0,
|
||||
limit: int = 50000,
|
||||
only_unexported: bool = True,
|
||||
) -> List[Dict]:
|
||||
"""Fetch collected decisions for training.
|
||||
|
||||
Args:
|
||||
since_rowid: Only return rows with id > this value.
|
||||
limit: Max rows to return.
|
||||
only_unexported: If True, skip rows already marked exported.
|
||||
|
||||
Returns:
|
||||
List of dicts with keys: id, snapshot (parsed), action_idx,
|
||||
confidence, playstyle, temperature, greedy, created_at.
|
||||
"""
|
||||
conn = self._get_conn()
|
||||
clauses = ["id > ?"]
|
||||
params: list = [since_rowid]
|
||||
if only_unexported:
|
||||
clauses.append("exported = 0")
|
||||
where = " AND ".join(clauses)
|
||||
rows = conn.execute(
|
||||
f"SELECT * FROM online_decisions WHERE {where} ORDER BY id LIMIT ?",
|
||||
(*params, limit),
|
||||
).fetchall()
|
||||
results = []
|
||||
for row in rows:
|
||||
d = dict(row)
|
||||
try:
|
||||
d["snapshot"] = json.loads(d["snapshot"])
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
pass
|
||||
results.append(d)
|
||||
return results
|
||||
|
||||
def mark_exported(self, up_to_rowid: int) -> int:
|
||||
"""Mark decisions as exported so they aren't fetched again.
|
||||
|
||||
Returns the number of rows updated.
|
||||
"""
|
||||
conn = self._get_conn()
|
||||
cur = conn.execute(
|
||||
"UPDATE online_decisions SET exported = 1 WHERE id <= ? AND exported = 0",
|
||||
(up_to_rowid,),
|
||||
)
|
||||
conn.commit()
|
||||
return cur.rowcount
|
||||
|
||||
def count(self, only_unexported: bool = False) -> int:
|
||||
"""Return the total number of stored decisions."""
|
||||
conn = self._get_conn()
|
||||
if only_unexported:
|
||||
row = conn.execute(
|
||||
"SELECT COUNT(*) FROM online_decisions WHERE exported = 0"
|
||||
).fetchone()
|
||||
else:
|
||||
row = conn.execute(
|
||||
"SELECT COUNT(*) FROM online_decisions"
|
||||
).fetchone()
|
||||
return row[0]
|
||||
@@ -1,40 +0,0 @@
|
||||
"""
|
||||
Commander AI Lab - Training Subpackage
|
||||
==========================================
|
||||
Provides RL training infrastructure including PPO, rollout buffers,
|
||||
Forge episode generation, self-play, and distillation.
|
||||
"""
|
||||
|
||||
from ml.training.rollout_buffer import RolloutBuffer
|
||||
from ml.training.reward import compute_intermediate_reward, compute_terminal_reward, RewardConfig
|
||||
from ml.training.decision_exporter import DecisionExporter
|
||||
from ml.training.forge_episode_generator import (
|
||||
ForgeTransition,
|
||||
ForgeEpisode,
|
||||
ForgeEpisodeQueue,
|
||||
forge_producer,
|
||||
ppo_consumer,
|
||||
run_forge_pipeline,
|
||||
parse_forge_jsonl,
|
||||
snapshots_to_episode,
|
||||
)
|
||||
|
||||
__all__ = [
|
||||
# Rollout & Buffers
|
||||
"RolloutBuffer",
|
||||
# Rewards
|
||||
"compute_intermediate_reward",
|
||||
"compute_terminal_reward",
|
||||
"RewardConfig",
|
||||
# Decision export
|
||||
"DecisionExporter",
|
||||
# Forge episode generation (Phase 3)
|
||||
"ForgeTransition",
|
||||
"ForgeEpisode",
|
||||
"ForgeEpisodeQueue",
|
||||
"forge_producer",
|
||||
"ppo_consumer",
|
||||
"run_forge_pipeline",
|
||||
"parse_forge_jsonl",
|
||||
"snapshots_to_episode",
|
||||
]
|
||||
@@ -84,9 +84,9 @@ class DistillationConfig:
|
||||
opponent: str = "heuristic"
|
||||
playstyle: str = "midrange"
|
||||
|
||||
# --- Dataset building (Forge-only default; see MIXED_MODE_PRESETS) ---
|
||||
# --- Dataset building ---
|
||||
forge_weight: float = 1.0
|
||||
ppo_weight: float = 0.0
|
||||
ppo_weight: float = 0.5
|
||||
min_reward_threshold: float = 0.0
|
||||
|
||||
# --- Quality gate ---
|
||||
@@ -858,7 +858,7 @@ def main():
|
||||
|
||||
# Dataset
|
||||
parser.add_argument("--forge-weight", type=float, default=1.0)
|
||||
parser.add_argument("--ppo-weight", type=float, default=0.0)
|
||||
parser.add_argument("--ppo-weight", type=float, default=0.5)
|
||||
parser.add_argument("--min-reward", type=float, default=0.0)
|
||||
|
||||
# Quality gate
|
||||
|
||||
@@ -1,352 +0,0 @@
|
||||
"""
|
||||
Commander AI Lab — Forge Episode Generator (Phase 3.2)
|
||||
|
||||
Async producer-consumer pipeline: runs Forge batch games in parallel
|
||||
with PPO training. Forge produces episodes → shared queue → PPO
|
||||
trainer consumes.
|
||||
|
||||
Uses the existing watchdog (_global_watchdog_loop in forge_runner.py)
|
||||
to monitor Forge worker processes for stalls.
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import time
|
||||
from collections import deque
|
||||
from dataclasses import dataclass, field
|
||||
from pathlib import Path
|
||||
from typing import Any, Deque, Dict, List, Optional, Tuple
|
||||
|
||||
import numpy as np
|
||||
|
||||
from ml.config.scope import (
|
||||
ACTION_TO_IDX,
|
||||
GAME_SCOPE,
|
||||
IDX_TO_ACTION,
|
||||
MacroAction,
|
||||
NUM_ACTIONS,
|
||||
STATE_DIMS,
|
||||
)
|
||||
from ml.training.reward import (
|
||||
RewardConfig,
|
||||
compute_intermediate_reward,
|
||||
compute_terminal_reward,
|
||||
)
|
||||
|
||||
logger = logging.getLogger("ml.forge_episode_generator")
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════
|
||||
# Episode / Trajectory data structures
|
||||
# ══════════════════════════════════════════════════════════
|
||||
|
||||
@dataclass
|
||||
class ForgeTransition:
|
||||
"""Single (s, a, r, log_prob, value, done) tuple from a Forge game."""
|
||||
state: np.ndarray
|
||||
action: int
|
||||
reward: float
|
||||
log_prob: float
|
||||
value: float
|
||||
done: bool
|
||||
|
||||
|
||||
@dataclass
|
||||
class ForgeEpisode:
|
||||
"""Complete trajectory from a single Forge game."""
|
||||
game_id: str
|
||||
transitions: List[ForgeTransition] = field(default_factory=list)
|
||||
winner: Optional[int] = None
|
||||
total_turns: int = 0
|
||||
deck_names: List[str] = field(default_factory=list)
|
||||
|
||||
@property
|
||||
def length(self) -> int:
|
||||
return len(self.transitions)
|
||||
|
||||
@property
|
||||
def total_reward(self) -> float:
|
||||
return sum(t.reward for t in self.transitions)
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════
|
||||
# JSONL Parser — reads Forge ML decision snapshots
|
||||
# ══════════════════════════════════════════════════════════
|
||||
|
||||
def parse_forge_jsonl(path: Path) -> List[Dict[str, Any]]:
|
||||
"""Parse a JSONL file of Forge ML decision snapshots.
|
||||
|
||||
Each line is a JSON object with keys like:
|
||||
game_id, turn, phase, active_seat, state, action, outcome
|
||||
"""
|
||||
snapshots = []
|
||||
with open(path, "r") as f:
|
||||
for lineno, line in enumerate(f, 1):
|
||||
line = line.strip()
|
||||
if not line:
|
||||
continue
|
||||
try:
|
||||
snapshots.append(json.loads(line))
|
||||
except json.JSONDecodeError as e:
|
||||
logger.warning("Skipping malformed line %d in %s: %s", lineno, path, e)
|
||||
logger.info("Parsed %d snapshots from %s", len(snapshots), path)
|
||||
return snapshots
|
||||
|
||||
|
||||
def snapshots_to_episode(
|
||||
snapshots: List[Dict[str, Any]],
|
||||
reward_config: Optional[RewardConfig] = None,
|
||||
) -> ForgeEpisode:
|
||||
"""Convert a sequence of Forge snapshots into a ForgeEpisode.
|
||||
|
||||
Maps Forge action labels → MacroAction indices and computes
|
||||
rewards from game outcomes using ml.training.reward.
|
||||
"""
|
||||
if not snapshots:
|
||||
return ForgeEpisode(game_id="empty")
|
||||
|
||||
first = snapshots[0]
|
||||
episode = ForgeEpisode(
|
||||
game_id=first.get("game_id", "unknown"),
|
||||
deck_names=first.get("deck_names", []),
|
||||
)
|
||||
|
||||
rc = reward_config or RewardConfig()
|
||||
|
||||
for i, snap in enumerate(snapshots):
|
||||
# State vector — zero-padded if not present
|
||||
state_vec = np.zeros(STATE_DIMS.total_state_dim, dtype=np.float32)
|
||||
if "state_vector" in snap:
|
||||
raw = np.array(snap["state_vector"], dtype=np.float32)
|
||||
state_vec[: min(len(raw), len(state_vec))] = raw[: len(state_vec)]
|
||||
|
||||
# Action mapping
|
||||
action_label = snap.get("action", "pass").lower().replace(" ", "_")
|
||||
try:
|
||||
macro = MacroAction(action_label)
|
||||
action_idx = ACTION_TO_IDX[macro]
|
||||
except (ValueError, KeyError):
|
||||
action_idx = ACTION_TO_IDX[MacroAction.PASS]
|
||||
|
||||
# Reward
|
||||
is_done = i == len(snapshots) - 1
|
||||
if is_done and "outcome" in snap:
|
||||
reward = compute_terminal_reward(
|
||||
won=snap["outcome"].get("won", False),
|
||||
turns=snap.get("turn", 1),
|
||||
life_remaining=snap["outcome"].get("life_remaining", 0),
|
||||
config=rc,
|
||||
)
|
||||
else:
|
||||
reward = compute_intermediate_reward(
|
||||
life_delta=snap.get("life_delta", 0),
|
||||
cards_drawn=snap.get("cards_drawn", 0),
|
||||
creatures_played=snap.get("creatures_played", 0),
|
||||
config=rc,
|
||||
)
|
||||
|
||||
episode.transitions.append(ForgeTransition(
|
||||
state=state_vec,
|
||||
action=action_idx,
|
||||
reward=reward,
|
||||
log_prob=snap.get("log_prob", 0.0),
|
||||
value=snap.get("value", 0.0),
|
||||
done=is_done,
|
||||
))
|
||||
|
||||
episode.total_turns = snapshots[-1].get("turn", len(snapshots))
|
||||
if "outcome" in snapshots[-1]:
|
||||
episode.winner = snapshots[-1]["outcome"].get("winner_seat")
|
||||
|
||||
return episode
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════
|
||||
# Async Episode Queue (producer-consumer)
|
||||
# ══════════════════════════════════════════════════════════
|
||||
|
||||
class ForgeEpisodeQueue:
|
||||
"""Thread-safe async queue bridging Forge producers and PPO consumer.
|
||||
|
||||
Forge batch workers produce ForgeEpisodes; the PPO trainer consumes
|
||||
them as they become available. Backpressure is applied when the
|
||||
queue reaches max_size.
|
||||
"""
|
||||
|
||||
def __init__(self, max_size: int = 256):
|
||||
self._queue: asyncio.Queue[ForgeEpisode] = asyncio.Queue(maxsize=max_size)
|
||||
self._produced = 0
|
||||
self._consumed = 0
|
||||
self._closed = False
|
||||
|
||||
async def put(self, episode: ForgeEpisode) -> None:
|
||||
await self._queue.put(episode)
|
||||
self._produced += 1
|
||||
|
||||
async def get(self, timeout: float = 30.0) -> Optional[ForgeEpisode]:
|
||||
try:
|
||||
ep = await asyncio.wait_for(self._queue.get(), timeout=timeout)
|
||||
self._consumed += 1
|
||||
return ep
|
||||
except asyncio.TimeoutError:
|
||||
return None
|
||||
|
||||
def close(self) -> None:
|
||||
self._closed = True
|
||||
|
||||
@property
|
||||
def is_closed(self) -> bool:
|
||||
return self._closed and self._queue.empty()
|
||||
|
||||
@property
|
||||
def stats(self) -> Dict[str, int]:
|
||||
return {
|
||||
"produced": self._produced,
|
||||
"consumed": self._consumed,
|
||||
"pending": self._queue.qsize(),
|
||||
}
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════
|
||||
# Forge Batch Producer
|
||||
# ══════════════════════════════════════════════════════════
|
||||
|
||||
async def forge_producer(
|
||||
queue: ForgeEpisodeQueue,
|
||||
results_dir: str = "results",
|
||||
batch_id: str = "forge-batch",
|
||||
num_games: int = 64,
|
||||
poll_interval: float = 2.0,
|
||||
reward_config: Optional[RewardConfig] = None,
|
||||
) -> int:
|
||||
"""Producer coroutine: watches for Forge JSONL output files,
|
||||
parses them into episodes, and pushes them onto the queue.
|
||||
|
||||
Returns total number of episodes produced.
|
||||
"""
|
||||
results_path = Path(results_dir)
|
||||
pattern = f"ml-decisions-forge-{batch_id}*.jsonl"
|
||||
seen_files: set = set()
|
||||
total_produced = 0
|
||||
|
||||
logger.info("[PRODUCER] Watching %s for pattern %s", results_path, pattern)
|
||||
|
||||
while total_produced < num_games and not queue.is_closed:
|
||||
for jsonl_file in sorted(results_path.glob(pattern)):
|
||||
if jsonl_file in seen_files:
|
||||
continue
|
||||
seen_files.add(jsonl_file)
|
||||
|
||||
try:
|
||||
snapshots = parse_forge_jsonl(jsonl_file)
|
||||
if not snapshots:
|
||||
continue
|
||||
|
||||
# Group by game_id
|
||||
games: Dict[str, List] = {}
|
||||
for snap in snapshots:
|
||||
gid = snap.get("game_id", "unknown")
|
||||
games.setdefault(gid, []).append(snap)
|
||||
|
||||
for gid, game_snaps in games.items():
|
||||
episode = snapshots_to_episode(game_snaps, reward_config)
|
||||
if episode.length > 0:
|
||||
await queue.put(episode)
|
||||
total_produced += 1
|
||||
logger.debug("[PRODUCER] Queued episode %s (%d transitions)",
|
||||
gid, episode.length)
|
||||
|
||||
except Exception as e:
|
||||
logger.error("[PRODUCER] Error processing %s: %s", jsonl_file, e)
|
||||
|
||||
await asyncio.sleep(poll_interval)
|
||||
|
||||
logger.info("[PRODUCER] Done — produced %d episodes", total_produced)
|
||||
return total_produced
|
||||
|
||||
|
||||
async def ppo_consumer(
|
||||
queue: ForgeEpisodeQueue,
|
||||
buffer_size: int = 64,
|
||||
on_batch_ready=None,
|
||||
) -> int:
|
||||
"""Consumer coroutine: pulls episodes from the queue and batches
|
||||
them for PPO training updates.
|
||||
|
||||
Args:
|
||||
queue: ForgeEpisodeQueue to consume from
|
||||
buffer_size: number of episodes per training batch
|
||||
on_batch_ready: callback(episodes) when a batch is full
|
||||
|
||||
Returns total episodes consumed.
|
||||
"""
|
||||
batch: List[ForgeEpisode] = []
|
||||
total_consumed = 0
|
||||
|
||||
while not queue.is_closed:
|
||||
episode = await queue.get(timeout=10.0)
|
||||
if episode is None:
|
||||
if queue.is_closed:
|
||||
break
|
||||
continue
|
||||
|
||||
batch.append(episode)
|
||||
total_consumed += 1
|
||||
|
||||
if len(batch) >= buffer_size:
|
||||
if on_batch_ready:
|
||||
on_batch_ready(batch)
|
||||
logger.info("[CONSUMER] Batch of %d episodes ready for PPO update", len(batch))
|
||||
batch = []
|
||||
|
||||
# Flush remaining
|
||||
if batch and on_batch_ready:
|
||||
on_batch_ready(batch)
|
||||
logger.info("[CONSUMER] Final batch of %d episodes flushed", len(batch))
|
||||
|
||||
logger.info("[CONSUMER] Done — consumed %d episodes", total_consumed)
|
||||
return total_consumed
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════
|
||||
# Convenience runner
|
||||
# ══════════════════════════════════════════════════════════
|
||||
|
||||
async def run_forge_pipeline(
|
||||
results_dir: str = "results",
|
||||
batch_id: str = "forge-batch",
|
||||
num_games: int = 64,
|
||||
buffer_size: int = 64,
|
||||
max_queue: int = 256,
|
||||
on_batch_ready=None,
|
||||
reward_config: Optional[RewardConfig] = None,
|
||||
) -> Dict[str, int]:
|
||||
"""Run the full Forge producer → PPO consumer pipeline.
|
||||
|
||||
The Forge Java batch must be started separately (via forge_runner.py
|
||||
or MultiThreadBatchRunner). This function handles the Python side:
|
||||
reading JSONL output and feeding episodes into the PPO trainer.
|
||||
"""
|
||||
queue = ForgeEpisodeQueue(max_size=max_queue)
|
||||
|
||||
producer_task = asyncio.create_task(
|
||||
forge_producer(queue, results_dir, batch_id, num_games,
|
||||
reward_config=reward_config)
|
||||
)
|
||||
consumer_task = asyncio.create_task(
|
||||
ppo_consumer(queue, buffer_size, on_batch_ready)
|
||||
)
|
||||
|
||||
produced = await producer_task
|
||||
queue.close()
|
||||
consumed = await consumer_task
|
||||
|
||||
stats = {
|
||||
"produced": produced,
|
||||
"consumed": consumed,
|
||||
**queue.stats,
|
||||
}
|
||||
logger.info("[PIPELINE] Complete: %s", stats)
|
||||
return stats
|
||||
@@ -17,15 +17,9 @@ that feed directly into the RolloutBuffer for PPO training.
|
||||
For real game integration (Phase 9+), the Java sim would call the
|
||||
policy server and feed back actual game states — this synthetic
|
||||
version allows training to begin immediately.
|
||||
|
||||
.. deprecated:: Phase 3 (Issue #83)
|
||||
Synthetic training mode is DEPRECATED for production training.
|
||||
Use forge_episode_generator.py with real Forge engine games.
|
||||
Retained ONLY for quick local testing and unit tests.
|
||||
"""
|
||||
|
||||
import logging
|
||||
import warnings
|
||||
import random
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Dict, List, Optional, Tuple
|
||||
@@ -48,12 +42,6 @@ from ml.training.decision_exporter import DecisionExporter
|
||||
|
||||
logger = logging.getLogger("ml.self_play")
|
||||
|
||||
_TRAINING_DEPRECATION_MSG = (
|
||||
"self_play.py synthetic training is deprecated for production training (Issue #83). "
|
||||
"Use forge_episode_generator.py with real Forge engine games instead. "
|
||||
"Synthetic self-play is retained for local testing and unit tests only."
|
||||
)
|
||||
|
||||
|
||||
@dataclass
|
||||
class PlayerState:
|
||||
@@ -566,7 +554,6 @@ def collect_rollouts(
|
||||
total_wins = 0
|
||||
total_losses = 0
|
||||
total_draws = 0
|
||||
warnings.warn(_TRAINING_DEPRECATION_MSG, DeprecationWarning, stacklevel=2)
|
||||
total_steps = 0
|
||||
total_rewards = 0.0
|
||||
|
||||
|
||||
@@ -2,7 +2,6 @@
|
||||
from __future__ import annotations
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import subprocess
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
@@ -26,35 +25,9 @@ class Config:
|
||||
port: int = 8080
|
||||
ximilar_api_key: str = ""
|
||||
pplx_api_key: str = ""
|
||||
anthropic_api_key: str = ""
|
||||
|
||||
|
||||
CFG = Config()
|
||||
# Pre-populate from env so ASGI mode (uvicorn lab_api:app) works without main()
|
||||
CFG.anthropic_api_key = os.environ.get("ANTHROPIC_API_KEY", "")
|
||||
|
||||
|
||||
def validate_forge_config() -> None:
|
||||
"""Warn clearly at startup if FORGE_DIR is misconfigured."""
|
||||
if not CFG.forge_dir:
|
||||
log.warning("FORGE_DIR not set -- Forge card enrichment disabled. "
|
||||
"Set FORGE_DIR to your forge-repo root or forge-gui directory.")
|
||||
return
|
||||
base = Path(CFG.forge_dir)
|
||||
a = base / "forge-gui" / "res" / "cardsfolder"
|
||||
b = base / "res" / "cardsfolder"
|
||||
if not a.is_dir() and not b.is_dir():
|
||||
log.warning(
|
||||
"FORGE_DIR=%s is set but cardsfolder not found at:\n"
|
||||
" %s\n %s\n"
|
||||
"Check that FORGE_DIR points to forge-repo root or forge-gui/.",
|
||||
CFG.forge_dir, a, b
|
||||
)
|
||||
else:
|
||||
resolved = a if a.is_dir() else b
|
||||
log.info("Forge cardsfolder confirmed at %s", resolved)
|
||||
CFG.ximilar_api_key = os.environ.get("XIMILAR_API_KEY", "")
|
||||
CFG.pplx_api_key = os.environ.get("PPLX_API_KEY", "")
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
@@ -76,9 +49,7 @@ class BatchState:
|
||||
self.sims_per_sec: float = 0.0
|
||||
|
||||
|
||||
import asyncio as _asyncio
|
||||
active_batches: dict[str, BatchState] = {}
|
||||
active_batches_lock = _asyncio.Lock()
|
||||
|
||||
|
||||
COMMANDER_META: dict = {}
|
||||
|
||||
+4
-75
@@ -25,7 +25,6 @@ import json
|
||||
import logging
|
||||
import logging.handlers
|
||||
import os
|
||||
import subprocess
|
||||
import sys
|
||||
import time
|
||||
import urllib.request
|
||||
@@ -43,9 +42,6 @@ DEFAULT_CONFIG = {
|
||||
"time_limit_hours": 11.5, # stop after this many hours (leave buffer for training)
|
||||
"pause_between_batches": 10, # seconds to pause between batches
|
||||
"auto_train": True, # trigger ML training after all batches
|
||||
"auto_update_weights": True, # run update_weights.py after sims
|
||||
"weights_min_games": 10, # minimum games required for weight update
|
||||
"weights_lr": 0.05, # learning rate for weight update
|
||||
"train_epochs": 100, # training epochs
|
||||
"train_lr": 0.001, # learning rate
|
||||
"train_batch_size": 256, # training batch size
|
||||
@@ -233,52 +229,6 @@ def wait_for_batch(base_url, batch_id, engine="deepseek", deadline=None):
|
||||
time.sleep(poll_interval)
|
||||
|
||||
|
||||
def run_update_weights(cfg):
|
||||
"""
|
||||
Run ml.scripts.update_weights to nudge learned_weights.json from sim
|
||||
decision logs. This feeds the deck builder's sim_insights injection.
|
||||
|
||||
Returns True on success, False on failure (non-fatal — overnight run
|
||||
continues regardless).
|
||||
"""
|
||||
log.info("")
|
||||
log.info("── Auto-update sim weights ─────────────────────────────────")
|
||||
log.info("Running update_weights.py to refresh learned_weights.json...")
|
||||
|
||||
cmd = [
|
||||
sys.executable, "-m", "ml.scripts.update_weights",
|
||||
"--min-games", str(cfg["weights_min_games"]),
|
||||
"--lr", str(cfg["weights_lr"]),
|
||||
]
|
||||
|
||||
try:
|
||||
result = subprocess.run(
|
||||
cmd,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=120, # 2 min ceiling — this should complete in seconds
|
||||
)
|
||||
if result.returncode == 0:
|
||||
# Print the last ~800 chars of the weight report to the log
|
||||
output = (result.stdout or "").strip()
|
||||
if output:
|
||||
for line in output.splitlines()[-20:]:
|
||||
log.info(f" {line}")
|
||||
log.info("Sim weights updated — deck builder will use new insights on next build.")
|
||||
return True
|
||||
else:
|
||||
log.warning(f"update_weights.py exited with code {result.returncode}")
|
||||
if result.stderr:
|
||||
log.warning(result.stderr.strip()[-300:])
|
||||
return False
|
||||
except subprocess.TimeoutExpired:
|
||||
log.warning("update_weights.py timed out after 120s — skipping")
|
||||
return False
|
||||
except Exception as e:
|
||||
log.warning(f"update_weights.py failed: {e}")
|
||||
return False
|
||||
|
||||
|
||||
def start_training(base_url, epochs, lr, batch_size, patience):
|
||||
"""Trigger ML training and return immediately."""
|
||||
resp = api_post(base_url, "/api/ml/train", {
|
||||
@@ -414,7 +364,6 @@ def run_overnight(cfg):
|
||||
else:
|
||||
log.info(f" Mode: Run for {cfg['time_limit_hours']}h, {games_per_batch} games/batch")
|
||||
log.info(f" Engine: {engine}")
|
||||
log.info(f" Auto-update weights: {'Yes' if cfg['auto_update_weights'] else 'No'}")
|
||||
log.info(f" Auto-train after: {'Yes' if cfg['auto_train'] else 'No'}")
|
||||
log.info("")
|
||||
|
||||
@@ -491,17 +440,6 @@ def run_overnight(cfg):
|
||||
log.info(f" Elapsed time: {str(timedelta(seconds=int(total_elapsed)))}")
|
||||
log.info("")
|
||||
|
||||
# ── Auto-update sim weights ───────────────────────────────
|
||||
# Runs update_weights.py to nudge learned_weights.json from the
|
||||
# decision logs produced during this run. This feeds sim_insights
|
||||
# into the deck builder's Ollama prompts on the next deck build.
|
||||
# Runs before neural net training so both pipelines benefit from
|
||||
# the freshest possible data.
|
||||
if cfg["auto_update_weights"]:
|
||||
run_update_weights(cfg)
|
||||
else:
|
||||
log.info("Skipping sim weight update (--no-update-weights flag set)")
|
||||
|
||||
# ── Auto-train ────────────────────────────────────────────
|
||||
if cfg["auto_train"]:
|
||||
if decisions_after < 100:
|
||||
@@ -544,17 +482,17 @@ def main():
|
||||
formatter_class=argparse.RawDescriptionHelpFormatter,
|
||||
epilog="""
|
||||
Examples:
|
||||
# Run DeepSeek sims for 11.5 hours, then update weights + train:
|
||||
# Run DeepSeek sims for 11.5 hours, then train:
|
||||
python overnight-run.py
|
||||
|
||||
# Run 20 batches of 50 games each, then update weights + train:
|
||||
# Run 20 batches of 50 games each, then train:
|
||||
python overnight-run.py --batches 20 --games 50
|
||||
|
||||
# Run for 6 hours with Java engine:
|
||||
python overnight-run.py --engine java --hours 6 --decks "Deck A" "Deck B" "Deck C"
|
||||
|
||||
# Just run sims, skip both weight update and training:
|
||||
python overnight-run.py --no-train --no-update-weights
|
||||
# Just run sims, no training:
|
||||
python overnight-run.py --no-train
|
||||
|
||||
# Custom training settings:
|
||||
python overnight-run.py --epochs 200 --lr 0.0005 --patience 20
|
||||
@@ -576,12 +514,6 @@ Examples:
|
||||
help="Deck names (auto-detected if not specified)")
|
||||
parser.add_argument("--no-train", action="store_true",
|
||||
help="Skip auto-training after sims")
|
||||
parser.add_argument("--no-update-weights", action="store_true",
|
||||
help="Skip updating learned_weights.json after sims")
|
||||
parser.add_argument("--weights-min-games", type=int, default=10,
|
||||
help="Minimum games required for weight update (default: 10)")
|
||||
parser.add_argument("--weights-lr", type=float, default=0.05,
|
||||
help="Learning rate for sim weight update (default: 0.05)")
|
||||
parser.add_argument("--epochs", type=int, default=100,
|
||||
help="Training epochs (default: 100)")
|
||||
parser.add_argument("--lr", type=float, default=0.001,
|
||||
@@ -604,9 +536,6 @@ Examples:
|
||||
cfg["time_limit_hours"] = args.hours
|
||||
cfg["pause_between_batches"] = args.pause
|
||||
cfg["auto_train"] = not args.no_train
|
||||
cfg["auto_update_weights"] = not args.no_update_weights
|
||||
cfg["weights_min_games"] = args.weights_min_games
|
||||
cfg["weights_lr"] = args.weights_lr
|
||||
cfg["train_epochs"] = args.epochs
|
||||
cfg["train_lr"] = args.lr
|
||||
cfg["train_batch_size"] = args.batch_size
|
||||
|
||||
@@ -25,28 +25,6 @@ dev = [
|
||||
"httpx>=0.24.0",
|
||||
"ruff>=0.1.0",
|
||||
]
|
||||
# RAG Phase 2: ChromaDB vector store + Ollama embedding support
|
||||
# Install with: pip install ".[rag]"
|
||||
rag = [
|
||||
"chromadb>=0.5.0",
|
||||
]
|
||||
# Local coach embeddings (sentence-transformers, no Ollama required)
|
||||
# Install with: pip install ".[coach-embeddings]"
|
||||
coach-embeddings = [
|
||||
"sentence-transformers>=3.0.0",
|
||||
"torch>=2.0.0",
|
||||
"pandas>=1.5.0",
|
||||
"pyarrow>=12.0.0",
|
||||
]
|
||||
# Full local AI stack (RAG + coach embeddings)
|
||||
# Install with: pip install ".[all]"
|
||||
all = [
|
||||
"chromadb>=0.5.0",
|
||||
"sentence-transformers>=3.0.0",
|
||||
"torch>=2.0.0",
|
||||
"pandas>=1.5.0",
|
||||
"pyarrow>=12.0.0",
|
||||
]
|
||||
|
||||
[tool.setuptools.packages.find]
|
||||
where = ["src"]
|
||||
|
||||
@@ -7,21 +7,9 @@ uvicorn[standard]>=0.23.0
|
||||
pydantic>=2.0.0
|
||||
httpx>=0.24.0
|
||||
websockets>=11.0
|
||||
openai>=1.0.0
|
||||
aiosqlite>=0.19.0
|
||||
|
||||
# Anthropic Claude API
|
||||
anthropic>=0.40.0
|
||||
|
||||
# Deck Builder dependencies
|
||||
requests>=2.31.0
|
||||
beautifulsoup4>=4.12.0
|
||||
ollama>=0.2.0
|
||||
scrython>=2.0.0
|
||||
|
||||
# Embeddings
|
||||
|
||||
# RAG vector store
|
||||
chromadb>=0.5.0
|
||||
sentence-transformers>=3.0.0
|
||||
torch>=2.0.0
|
||||
+1
-1
@@ -2,5 +2,5 @@
|
||||
routes package — API routers for Commander AI Lab.
|
||||
|
||||
Each module defines a FastAPI APIRouter with real endpoint implementations.
|
||||
Shared helpers live in services/, models live in models/.
|
||||
All shared helpers, models, and state live in routes.shared.
|
||||
"""
|
||||
+338
-254
@@ -1,12 +1,11 @@
|
||||
"""
|
||||
routes/coach.py
|
||||
================
|
||||
===============
|
||||
LLM-powered deck coaching endpoints:
|
||||
GET /api/coach/status
|
||||
GET /api/coach/decks
|
||||
GET /api/coach/decks/{deck_id}/report
|
||||
POST /api/coach/decks/{deck_id}
|
||||
POST /api/coach/decks/{deck_id}/quick
|
||||
GET /api/coach/sessions
|
||||
GET /api/coach/sessions/{session_id}
|
||||
POST /api/coach/embeddings/download
|
||||
@@ -20,9 +19,6 @@ Globals:
|
||||
_coach_service, _coach_embeddings, _coach_llm
|
||||
_deck_gen_v3, _deck_gen_v3_error
|
||||
init_coach_service(), _build_deck_report_from_db()
|
||||
|
||||
Async-safety: every DB and HTTP call in this module uses
|
||||
async helpers so nothing blocks the FastAPI event loop.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
@@ -37,35 +33,26 @@ from fastapi import APIRouter, HTTPException
|
||||
from fastapi.responses import StreamingResponse
|
||||
from models.requests import CoachRequestBody, CoachChatMessage, CoachChatRequest, CoachApplyRequest, CoachGoalsRequest
|
||||
|
||||
from models.state import CFG
|
||||
from services.async_db import (
|
||||
async_get_db, async_fetchall, async_fetchone,
|
||||
async_execute, async_execute_commit, async_commit,
|
||||
from routes.shared import (
|
||||
CFG,
|
||||
log_coach, log_deckgen,
|
||||
_get_db_conn,
|
||||
_compute_deck_analysis,
|
||||
)
|
||||
from services.deck_service import _compute_deck_analysis
|
||||
from services.logging import log_coach, log_deckgen
|
||||
import httpx
|
||||
|
||||
from coach.config import COACH_PROVIDER, ANTHROPIC_API_KEY, ANTHROPIC_MODEL, DECK_GEN_PROVIDER, DECK_GEN_MODEL
|
||||
|
||||
LLM_TIMEOUT = 120 # seconds
|
||||
|
||||
router = APIRouter(tags=["coach"])
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Coach Service (LLM-powered deck coaching)
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
# Global coach instances (initialized at startup)
|
||||
_coach_service = None
|
||||
_coach_embeddings = None
|
||||
_coach_llm = None
|
||||
_deck_gen_v3 = None
|
||||
_deck_gen_v3_error = None
|
||||
|
||||
# Known basic land names whose type_line may be absent when the card was added
|
||||
# via plain-text import and has no matching collection_entries row yet.
|
||||
_BASIC_LAND_NAMES: frozenset[str] = frozenset({
|
||||
"plains", "island", "swamp", "mountain", "forest", "wastes",
|
||||
"snow-covered plains", "snow-covered island", "snow-covered swamp",
|
||||
"snow-covered mountain", "snow-covered forest",
|
||||
})
|
||||
_deck_gen_v3 = None # V3 Deck Generator (Perplexity structured output)
|
||||
_deck_gen_v3_error = None # Error message if V3 init failed
|
||||
|
||||
|
||||
def init_coach_service():
|
||||
@@ -76,90 +63,108 @@ def init_coach_service():
|
||||
from coach.embeddings import MTGEmbeddingIndex
|
||||
from coach.coach_service import CoachService
|
||||
from coach.config import ensure_dirs
|
||||
from services.database import _get_db_conn
|
||||
|
||||
ensure_dirs()
|
||||
|
||||
_coach_llm = LLMClient()
|
||||
_coach_embeddings = MTGEmbeddingIndex()
|
||||
|
||||
# Try to load embeddings (non-blocking — download happens on first use)
|
||||
try:
|
||||
from coach.config import EMBEDDINGS_NPZ
|
||||
if EMBEDDINGS_NPZ.exists():
|
||||
_coach_embeddings.load()
|
||||
log_coach.info(f" Coach: Embeddings loaded ({_coach_embeddings.card_count} cards)")
|
||||
log_coach.info(f" Coach: Embeddings loaded ({_coach_embeddings.card_count} cards)")
|
||||
else:
|
||||
log_coach.warning(" Coach: Embeddings not yet downloaded")
|
||||
log_coach.warning(" Coach: Embeddings not yet downloaded (will download on first use)")
|
||||
except Exception as e:
|
||||
log_coach.error(f" Coach: Embeddings load failed: {e}")
|
||||
log_coach.error(f" Coach: Embeddings load failed: {e}")
|
||||
|
||||
_coach_service = CoachService(_coach_llm, _coach_embeddings)
|
||||
if COACH_PROVIDER == "anthropic":
|
||||
log_coach.info(f" Coach LLM: Anthropic Claude ({ANTHROPIC_MODEL})")
|
||||
|
||||
# Check LLM connection
|
||||
llm_status = _coach_llm.check_connection()
|
||||
if llm_status.get("connected"):
|
||||
log_coach.info(f" Coach LLM: Connected ({llm_status.get('active_model', 'unknown')})")
|
||||
else:
|
||||
llm_status = _coach_llm.check_connection_sync()
|
||||
if llm_status.get("connected"):
|
||||
log_coach.info(f" Coach LLM: Connected ({llm_status.get('active_model', 'unknown')})")
|
||||
else:
|
||||
log_coach.warning(" Coach LLM: Not connected (start Ollama on localhost:11434)")
|
||||
log_coach.warning(f" Coach LLM: Not connected (start Ollama on 192.168.0.240:11434)")
|
||||
|
||||
# Initialize V3 Deck Generator (Ollama-based)
|
||||
_deck_gen_v3_error = None
|
||||
try:
|
||||
from src.commander_ai_lab.deck_builder.adapter import DeckBuilderAdapter
|
||||
if DECK_GEN_PROVIDER == "anthropic":
|
||||
_deck_gen_v3 = DeckBuilderAdapter(db_conn_factory=_get_db_conn, model=DECK_GEN_MODEL)
|
||||
log_deckgen.info(f" Deck Gen V3: Initialized (Anthropic Claude {DECK_GEN_MODEL})")
|
||||
else:
|
||||
from coach.config import LLM_MODEL
|
||||
_deck_gen_v3 = DeckBuilderAdapter(db_conn_factory=_get_db_conn, model=LLM_MODEL)
|
||||
log_deckgen.info(f" Deck Gen V3: Initialized (Ollama {LLM_MODEL})")
|
||||
_deck_gen_v3 = DeckBuilderAdapter(
|
||||
db_conn_factory=_get_db_conn,
|
||||
model="gpt-oss:20b",
|
||||
)
|
||||
log_deckgen.info(" Deck Gen V3: Initialized (Ollama DeckBuilderAdapter)")
|
||||
except ImportError as e:
|
||||
_deck_gen_v3_error = f"Missing dependency: {e}"
|
||||
log_deckgen.error(f" Deck Gen V3: {_deck_gen_v3_error}")
|
||||
log_deckgen.error(f" Deck Gen V3: {_deck_gen_v3_error}")
|
||||
_deck_gen_v3 = None
|
||||
except Exception as e:
|
||||
_deck_gen_v3_error = str(e)
|
||||
log_deckgen.error(f" Deck Gen V3: Failed to initialize: {e}")
|
||||
log_deckgen.error(f" Deck Gen V3: Failed to initialize: {e}")
|
||||
_deck_gen_v3 = None
|
||||
|
||||
except Exception as e:
|
||||
log_coach.error(f" Coach: Failed to initialize: {e}\n")
|
||||
log_coach.error(f" Coach: Failed to initialize: {e}\n{traceback.format_exc()}")
|
||||
_coach_service = None
|
||||
|
||||
|
||||
@router.get("/api/coach/status")
|
||||
async def coach_status():
|
||||
"""Check coach subsystem health."""
|
||||
if _coach_service is None:
|
||||
return {"llmConnected": False, "embeddingsLoaded": False, "embeddingCards": 0, "deckReportsAvailable": 0, "error": "Coach service not initialized"}
|
||||
return {"llmConnected": False, "embeddingsLoaded": False,
|
||||
"embeddingCards": 0, "deckReportsAvailable": 0,
|
||||
"error": "Coach service not initialized"}
|
||||
status = _coach_service.get_status()
|
||||
return status.model_dump()
|
||||
|
||||
|
||||
@router.get("/api/coach/decks")
|
||||
async def coach_list_decks():
|
||||
"""List all decks available for coaching (async DB)."""
|
||||
rows = await async_fetchall(
|
||||
"""List all decks available for coaching (from deck builder DB)."""
|
||||
conn = _get_db_conn()
|
||||
rows = conn.execute(
|
||||
"""SELECT d.id as deck_id, d.name as deck_name, d.commander_name,
|
||||
COUNT(dc.id) as card_count
|
||||
FROM decks d LEFT JOIN deck_cards dc ON dc.deck_id = d.id
|
||||
GROUP BY d.id ORDER BY d.name"""
|
||||
)
|
||||
COUNT(dc.id) as card_count
|
||||
FROM decks d
|
||||
LEFT JOIN deck_cards dc ON dc.deck_id = d.id
|
||||
GROUP BY d.id
|
||||
ORDER BY d.name"""
|
||||
).fetchall()
|
||||
|
||||
# Also get report availability from coach service
|
||||
report_ids = set()
|
||||
if _coach_service:
|
||||
report_ids = set(_coach_service.list_deck_reports())
|
||||
|
||||
decks = []
|
||||
for r in rows:
|
||||
deck_name = r["deck_name"]
|
||||
# Check if a report exists (by deck name slug match)
|
||||
has_report = any(
|
||||
deck_name.lower().replace(" ", "-") == rid.lower()
|
||||
or deck_name.lower() == rid.lower()
|
||||
deck_name.lower().replace(" ", "-") == rid.lower() or
|
||||
deck_name.lower() == rid.lower()
|
||||
for rid in report_ids
|
||||
)
|
||||
decks.append({
|
||||
"deck_id": r["deck_id"], "deck_name": r["deck_name"],
|
||||
"deck_id": r["deck_id"],
|
||||
"deck_name": r["deck_name"],
|
||||
"commander": r["commander_name"] or "",
|
||||
"card_count": r["card_count"], "has_report": has_report,
|
||||
"report_count": 1 if has_report else 0, "last_report_date": None,
|
||||
"card_count": r["card_count"],
|
||||
"has_report": has_report,
|
||||
"report_count": 1 if has_report else 0,
|
||||
"last_report_date": None,
|
||||
})
|
||||
return decks
|
||||
|
||||
|
||||
@router.get("/api/coach/decks/{deck_id}/report")
|
||||
async def coach_get_report(deck_id: str):
|
||||
"""Get the latest DeckReport for a deck."""
|
||||
if _coach_service is None:
|
||||
raise HTTPException(500, "Coach service not initialized")
|
||||
report = _coach_service.load_deck_report(deck_id)
|
||||
@@ -170,13 +175,17 @@ async def coach_get_report(deck_id: str):
|
||||
|
||||
@router.post("/api/coach/decks/{deck_id}")
|
||||
async def coach_run_session(deck_id: str, body: CoachRequestBody = None):
|
||||
"""Trigger a coaching session for a deck."""
|
||||
if _coach_service is None:
|
||||
raise HTTPException(500, "Coach service not initialized")
|
||||
|
||||
# Load embeddings on first use if not loaded
|
||||
if _coach_embeddings and not _coach_embeddings.loaded:
|
||||
try:
|
||||
_coach_embeddings.load(force_download=True)
|
||||
except Exception as e:
|
||||
log_coach.error(f" Coach: Embeddings download failed: {e}")
|
||||
|
||||
goals = None
|
||||
if body and body.goals:
|
||||
from coach.models import CoachGoals
|
||||
@@ -184,11 +193,14 @@ async def coach_run_session(deck_id: str, body: CoachRequestBody = None):
|
||||
goals = CoachGoals(**body.goals)
|
||||
except Exception:
|
||||
goals = None
|
||||
|
||||
# Build a fallback DeckReport from the DB if no simulation report exists
|
||||
fallback_report = None
|
||||
try:
|
||||
fallback_report = await _build_deck_report_from_db(deck_id)
|
||||
fallback_report = _build_deck_report_from_db(deck_id)
|
||||
except Exception as e:
|
||||
log_coach.error(f" Coach: Fallback report build failed for '{deck_id}': {e}")
|
||||
|
||||
try:
|
||||
session = await _coach_service.run_coaching_session(deck_id, goals, fallback_report=fallback_report)
|
||||
return session.model_dump()
|
||||
@@ -200,80 +212,74 @@ async def coach_run_session(deck_id: str, body: CoachRequestBody = None):
|
||||
raise HTTPException(500, f"Coach session failed: {e}")
|
||||
|
||||
|
||||
@router.post("/api/coach/decks/{deck_id}/quick")
|
||||
async def coach_run_quick_digest(deck_id: str, body: CoachRequestBody = None):
|
||||
"""Fast ~5s quick digest: summary, top 3 upgrades, commander dependency."""
|
||||
if _coach_service is None:
|
||||
raise HTTPException(500, "Coach service not initialized")
|
||||
goals = None
|
||||
if body and body.goals:
|
||||
from coach.models import CoachGoals
|
||||
try:
|
||||
goals = CoachGoals(**body.goals)
|
||||
except Exception:
|
||||
goals = None
|
||||
fallback_report = None
|
||||
try:
|
||||
fallback_report = await _build_deck_report_from_db(deck_id)
|
||||
except Exception as e:
|
||||
log_coach.error(f" Coach: Quick fallback failed for '{deck_id}': {e}")
|
||||
try:
|
||||
session = await _coach_service.run_quick_digest(deck_id, goals, fallback_report=fallback_report)
|
||||
return session.model_dump()
|
||||
except ValueError as e:
|
||||
raise HTTPException(404, str(e))
|
||||
except ConnectionError as e:
|
||||
raise HTTPException(503, f"LLM connection failed: {e}")
|
||||
except Exception as e:
|
||||
raise HTTPException(500, f"Quick digest failed: {e}")
|
||||
|
||||
|
||||
async def _build_deck_report_from_db(deck_slug: str):
|
||||
"""Build a lightweight DeckReport from DB (async). Allows coaching without simulation data."""
|
||||
def _build_deck_report_from_db(deck_slug: str):
|
||||
"""
|
||||
Build a lightweight DeckReport from the deck builder DB when no
|
||||
simulation report exists. Allows the coach to analyze deck composition
|
||||
even without simulation data.
|
||||
"""
|
||||
from coach.models import DeckReport, CardPerformance, DeckStructure
|
||||
conn = _get_db_conn()
|
||||
|
||||
# --- Input validation ---
|
||||
import re
|
||||
if not deck_slug or len(deck_slug) > 200:
|
||||
return None
|
||||
deck_slug = re.sub(r'[^a-zA-Z0-9 _-]', '', deck_slug)
|
||||
if not deck_slug:
|
||||
return None
|
||||
|
||||
# Find the deck by parameterized query instead of full-table scan
|
||||
slug_lower = deck_slug.lower()
|
||||
slug_hyphenated = slug_lower.replace(' ', '-')
|
||||
clean_slug = re.sub(r'[^a-z0-9]+', '-', slug_lower).strip('-')
|
||||
|
||||
if slug_lower.isdigit():
|
||||
matched_deck = await async_fetchone(
|
||||
# Numeric slug -- match by ID directly
|
||||
matched_deck = conn.execute(
|
||||
"SELECT id, name, commander_name, color_identity FROM decks WHERE id = ?",
|
||||
(int(slug_lower),)
|
||||
)
|
||||
).fetchone()
|
||||
else:
|
||||
matched_deck = await async_fetchone(
|
||||
# Try exact name match, hyphenated match, or clean-slug match
|
||||
matched_deck = conn.execute(
|
||||
"""SELECT id, name, commander_name, color_identity FROM decks
|
||||
WHERE LOWER(name) = ? OR LOWER(REPLACE(name, ' ', '-')) = ?
|
||||
OR LOWER(REPLACE(name, ' ', '-')) = ? LIMIT 1""",
|
||||
WHERE LOWER(name) = ?
|
||||
OR LOWER(REPLACE(name, ' ', '-')) = ?
|
||||
OR LOWER(REPLACE(name, ' ', '-')) = ?
|
||||
LIMIT 1""",
|
||||
(slug_lower, slug_hyphenated, clean_slug)
|
||||
)
|
||||
).fetchone()
|
||||
|
||||
if matched_deck is None:
|
||||
return None
|
||||
|
||||
deck_id = matched_deck["id"]
|
||||
deck_name = matched_deck["name"]
|
||||
commander = matched_deck["commander_name"] or ""
|
||||
|
||||
# Parse color identity
|
||||
ci_raw = matched_deck["color_identity"] or "[]"
|
||||
try:
|
||||
color_identity = json.loads(ci_raw) if isinstance(ci_raw, str) else ci_raw
|
||||
except Exception:
|
||||
color_identity = []
|
||||
card_rows = await async_fetchall(
|
||||
|
||||
# Load all cards in this deck
|
||||
card_rows = conn.execute(
|
||||
"""SELECT dc.card_name, dc.quantity, dc.is_commander, dc.role_tag,
|
||||
ce.type_line, ce.cmc, ce.oracle_text
|
||||
FROM deck_cards dc
|
||||
LEFT JOIN collection_entries ce ON LOWER(dc.card_name) = LOWER(ce.name)
|
||||
WHERE dc.deck_id = ?""",
|
||||
ce.type_line, ce.cmc, ce.oracle_text
|
||||
FROM deck_cards dc
|
||||
LEFT JOIN collection_entries ce ON LOWER(dc.card_name) = LOWER(ce.name)
|
||||
WHERE dc.deck_id = ?""",
|
||||
(deck_id,)
|
||||
)
|
||||
).fetchall()
|
||||
|
||||
cards = []
|
||||
type_counts = {}
|
||||
cmc_buckets = [0] * 8
|
||||
land_count = 0
|
||||
|
||||
for cr in card_rows:
|
||||
card_name = cr["card_name"] or ""
|
||||
type_line = cr["type_line"] or ""
|
||||
@@ -281,12 +287,7 @@ async def _build_deck_report_from_db(deck_slug: str):
|
||||
qty = cr["quantity"] or 1
|
||||
role_tag = cr["role_tag"] or ""
|
||||
|
||||
# Fallback for cards added via plain-text import that have no
|
||||
# collection_entries row yet (type_line comes back empty from the LEFT JOIN).
|
||||
# Basic lands are identified by name so their land_count is never lost.
|
||||
if not type_line and card_name.lower() in _BASIC_LAND_NAMES:
|
||||
type_line = "Basic Land"
|
||||
|
||||
# Build tags from type_line and role_tag
|
||||
tags = []
|
||||
if role_tag:
|
||||
tags.append(role_tag)
|
||||
@@ -305,24 +306,42 @@ async def _build_deck_report_from_db(deck_slug: str):
|
||||
tags.append("enchantment")
|
||||
elif "Planeswalker" in type_line:
|
||||
tags.append("planeswalker")
|
||||
|
||||
# Type count
|
||||
for t in ["Creature", "Instant", "Sorcery", "Artifact", "Enchantment", "Planeswalker", "Land"]:
|
||||
if t in type_line:
|
||||
type_counts[t] = type_counts.get(t, 0) + qty
|
||||
# Mirrors deck_service._compute_deck_analysis(): lands are excluded from
|
||||
# the mana curve so cmc=0 lands don't inflate the free-spell bucket and
|
||||
# mislead the LLM coach into thinking the deck has many 0-cost spells.
|
||||
|
||||
# CMC bucket
|
||||
bucket = min(int(cmc), 7)
|
||||
if "Land" not in type_line:
|
||||
cmc_buckets[bucket] += qty
|
||||
cards.append(CardPerformance(name=card_name, drawnRate=0.0, castRate=0.0, impactScore=0.0, tags=tags))
|
||||
cmc_buckets[bucket] += qty
|
||||
|
||||
# CardPerformance with zeroed-out sim stats
|
||||
cards.append(CardPerformance(
|
||||
name=card_name,
|
||||
drawnRate=0.0,
|
||||
castRate=0.0,
|
||||
impactScore=0.0,
|
||||
tags=tags,
|
||||
))
|
||||
|
||||
slug = deck_slug
|
||||
return DeckReport(
|
||||
deckId=deck_slug, commander=commander, colorIdentity=color_identity,
|
||||
cards=cards, structure=DeckStructure(landCount=land_count, curveBuckets=cmc_buckets, cardTypeCounts=type_counts),
|
||||
deckId=slug,
|
||||
commander=commander,
|
||||
colorIdentity=color_identity,
|
||||
cards=cards,
|
||||
structure=DeckStructure(
|
||||
landCount=land_count,
|
||||
curveBuckets=cmc_buckets,
|
||||
cardTypeCounts=type_counts,
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
@router.get("/api/coach/sessions")
|
||||
async def coach_list_sessions(deck_id: str = None):
|
||||
"""List all coaching sessions, optionally filtered by deck."""
|
||||
if _coach_service is None:
|
||||
raise HTTPException(500, "Coach service not initialized")
|
||||
return {"sessions": _coach_service.list_sessions(deck_id)}
|
||||
@@ -330,6 +349,7 @@ async def coach_list_sessions(deck_id: str = None):
|
||||
|
||||
@router.get("/api/coach/sessions/{session_id}")
|
||||
async def coach_get_session(session_id: str):
|
||||
"""Get a specific coaching session."""
|
||||
if _coach_service is None:
|
||||
raise HTTPException(500, "Coach service not initialized")
|
||||
session = _coach_service.load_session(session_id)
|
||||
@@ -340,39 +360,52 @@ async def coach_get_session(session_id: str):
|
||||
|
||||
@router.post("/api/coach/embeddings/download")
|
||||
async def coach_download_embeddings():
|
||||
"""Download and convert MTG card embeddings from HuggingFace."""
|
||||
if _coach_embeddings is None:
|
||||
raise HTTPException(500, "Coach service not initialized")
|
||||
try:
|
||||
_coach_embeddings.load(force_download=True)
|
||||
return {"success": True, "cards": _coach_embeddings.card_count,
|
||||
"message": f"Loaded {_coach_embeddings.card_count} card embeddings"}
|
||||
return {
|
||||
"success": True,
|
||||
"cards": _coach_embeddings.card_count,
|
||||
"message": f"Loaded {_coach_embeddings.card_count} card embeddings"
|
||||
}
|
||||
except Exception as e:
|
||||
raise HTTPException(500, f"Failed to download embeddings: {e}")
|
||||
|
||||
|
||||
@router.get("/api/coach/embeddings/search")
|
||||
async def coach_search_similar(card: str, colors: str = None, top_n: int = 10):
|
||||
"""Search for similar cards by name."""
|
||||
if _coach_embeddings is None or not _coach_embeddings.loaded:
|
||||
raise HTTPException(503, "Embeddings not loaded")
|
||||
color_filter = list(colors.upper()) if colors else None
|
||||
matches = _coach_embeddings.search_similar(query_card=card, color_filter=color_filter, top_n=top_n)
|
||||
matches = _coach_embeddings.search_similar(
|
||||
query_card=card, color_filter=color_filter, top_n=top_n
|
||||
)
|
||||
return {"query": card, "matches": [m.to_dict() for m in matches]}
|
||||
|
||||
|
||||
@router.post("/api/coach/chat")
|
||||
async def coach_chat(body: CoachChatRequest):
|
||||
"""Multi-turn coaching chat. Fully async - no event loop blocking."""
|
||||
"""Multi-turn coaching chat. Sends conversation history to LLM and returns response."""
|
||||
if _coach_service is None:
|
||||
raise HTTPException(500, "Coach service not initialized")
|
||||
|
||||
# Load deck report for context
|
||||
report = _coach_service.load_deck_report(body.deck_id)
|
||||
|
||||
# Build system prompt with report context
|
||||
from coach.prompt_template import build_system_prompt
|
||||
from coach.models import CoachGoals
|
||||
|
||||
goals = None
|
||||
if body.goals:
|
||||
try:
|
||||
goals = CoachGoals(**body.goals)
|
||||
except Exception:
|
||||
goals = None
|
||||
|
||||
system_prompt = ""
|
||||
if report:
|
||||
system_prompt = build_system_prompt(report, goals)
|
||||
@@ -382,161 +415,196 @@ async def coach_chat(body: CoachChatRequest):
|
||||
"Answer questions about deck building, strategy, card choices, and game theory. "
|
||||
"Be specific and actionable in your advice."
|
||||
)
|
||||
|
||||
# Build messages array for LLM
|
||||
messages = [{"role": "system", "content": system_prompt}]
|
||||
for msg in body.messages:
|
||||
messages.append({"role": msg.get("role", "user"), "content": msg.get("content", "")})
|
||||
# ── Anthropic Claude provider path (async httpx) ──
|
||||
if COACH_PROVIDER == 'anthropic':
|
||||
if not ANTHROPIC_API_KEY:
|
||||
raise HTTPException(400, 'Anthropic API key not configured.')
|
||||
import anthropic
|
||||
aclient = anthropic.AsyncAnthropic(api_key=ANTHROPIC_API_KEY)
|
||||
if body.stream:
|
||||
async def anthropic_stream():
|
||||
async with aclient.messages.stream(
|
||||
model=ANTHROPIC_MODEL, system=system_prompt,
|
||||
messages=[{"role": m["role"], "content": m["content"]} for m in messages if m["role"] != "system"],
|
||||
max_tokens=4096, temperature=0.7,
|
||||
) as stream:
|
||||
async for text in stream.text_stream:
|
||||
yield f"data: {json.dumps({'content': text})}\n\n"
|
||||
yield "data: [DONE]\n\n"
|
||||
return StreamingResponse(anthropic_stream(), media_type="text/event-stream")
|
||||
else:
|
||||
try:
|
||||
resp = await aclient.messages.create(
|
||||
model=ANTHROPIC_MODEL, system=system_prompt,
|
||||
messages=[{"role": m["role"], "content": m["content"]} for m in messages if m["role"] != "system"],
|
||||
max_tokens=4096, temperature=0.7,
|
||||
)
|
||||
content = resp.content[0].text if resp.content else ""
|
||||
usage = resp.usage
|
||||
return {
|
||||
"content": content, "model": resp.model,
|
||||
"prompt_tokens": usage.input_tokens if usage else 0,
|
||||
"completion_tokens": usage.output_tokens if usage else 0,
|
||||
}
|
||||
except Exception as e:
|
||||
raise HTTPException(502, f"Anthropic API call failed: {e}")
|
||||
# ── Local Ollama provider path (async httpx) ──
|
||||
|
||||
# Call LLM with multi-turn messages
|
||||
try:
|
||||
model_name = await _coach_llm._resolve_model()
|
||||
llm_body = {"model": model_name, "messages": messages, "temperature": 0.7, "max_tokens": 4096}
|
||||
import json
|
||||
from urllib.request import urlopen, Request as UrlRequest
|
||||
from coach.config import LLM_URL, LLM_TIMEOUT
|
||||
|
||||
model_name = _coach_llm._resolve_model()
|
||||
llm_body = {
|
||||
"model": model_name,
|
||||
"messages": messages,
|
||||
"temperature": 0.7,
|
||||
"max_tokens": 4096,
|
||||
}
|
||||
|
||||
if body.stream:
|
||||
# SSE streaming response
|
||||
llm_body["stream"] = True
|
||||
|
||||
async def generate():
|
||||
async with httpx.AsyncClient(timeout=httpx.Timeout(float(LLM_TIMEOUT))) as client:
|
||||
async with client.stream("POST", f"{_coach_llm.base_url}/chat/completions",
|
||||
json=llm_body, headers={"Content-Type": "application/json"}) as resp:
|
||||
async for line in resp.aiter_lines():
|
||||
if line.startswith("data: "):
|
||||
data = line[6:]
|
||||
if data == "[DONE]":
|
||||
yield "data: [DONE]\n\n"
|
||||
break
|
||||
try:
|
||||
chunk = json.loads(data)
|
||||
content = chunk.get("choices", [{}])[0].get("delta", {}).get("content", "")
|
||||
if content:
|
||||
yield f"data: {json.dumps({'content': content})}\n\n"
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
import asyncio
|
||||
def _stream():
|
||||
req = UrlRequest(
|
||||
f"{_coach_llm.base_url}/chat/completions",
|
||||
data=json.dumps(llm_body).encode("utf-8"),
|
||||
headers={"Content-Type": "application/json"},
|
||||
method="POST",
|
||||
)
|
||||
import http.client
|
||||
import urllib.parse
|
||||
parsed = urllib.parse.urlparse(f"{_coach_llm.base_url}/chat/completions")
|
||||
conn = http.client.HTTPConnection(parsed.hostname, parsed.port, timeout=LLM_TIMEOUT)
|
||||
conn.request("POST", parsed.path, body=json.dumps(llm_body).encode("utf-8"),
|
||||
headers={"Content-Type": "application/json"})
|
||||
resp = conn.getresponse()
|
||||
chunks = []
|
||||
while True:
|
||||
line = resp.readline()
|
||||
if not line:
|
||||
break
|
||||
line = line.decode("utf-8").strip()
|
||||
if line.startswith("data: "):
|
||||
data = line[6:]
|
||||
if data == "[DONE]":
|
||||
chunks.append("[DONE]")
|
||||
break
|
||||
chunks.append(data)
|
||||
conn.close()
|
||||
return chunks
|
||||
|
||||
loop = asyncio.get_event_loop()
|
||||
chunks = await loop.run_in_executor(None, _stream)
|
||||
|
||||
for chunk_str in chunks:
|
||||
if chunk_str == "[DONE]":
|
||||
yield f"data: [DONE]\n\n"
|
||||
break
|
||||
try:
|
||||
chunk = json.loads(chunk_str)
|
||||
delta = chunk.get("choices", [{}])[0].get("delta", {})
|
||||
content = delta.get("content", "")
|
||||
if content:
|
||||
# Strip think tags from streaming chunks
|
||||
yield f"data: {json.dumps({'content': content})}\n\n"
|
||||
except json.JSONDecodeError:
|
||||
continue
|
||||
|
||||
return StreamingResponse(generate(), media_type="text/event-stream")
|
||||
else:
|
||||
async with httpx.AsyncClient(timeout=httpx.Timeout(float(LLM_TIMEOUT))) as client:
|
||||
resp = await client.post(
|
||||
f"{_coach_llm.base_url}/chat/completions",
|
||||
json=llm_body, headers={"Content-Type": "application/json"},
|
||||
)
|
||||
resp.raise_for_status()
|
||||
raw = resp.json()
|
||||
# Non-streaming: regular call
|
||||
req = UrlRequest(
|
||||
f"{_coach_llm.base_url}/chat/completions",
|
||||
data=json.dumps(llm_body).encode("utf-8"),
|
||||
headers={"Content-Type": "application/json"},
|
||||
method="POST",
|
||||
)
|
||||
|
||||
import asyncio
|
||||
loop = asyncio.get_event_loop()
|
||||
def _call():
|
||||
with urlopen(req, timeout=LLM_TIMEOUT) as resp:
|
||||
return json.loads(resp.read().decode("utf-8"))
|
||||
|
||||
raw = await loop.run_in_executor(None, _call)
|
||||
|
||||
content = raw.get("choices", [{}])[0].get("message", {}).get("content", "")
|
||||
# Strip think tags
|
||||
content = _coach_llm._strip_think_tags(content)
|
||||
usage = raw.get("usage", {})
|
||||
|
||||
return {
|
||||
"content": content, "model": raw.get("model", ""),
|
||||
"content": content,
|
||||
"model": raw.get("model", ""),
|
||||
"prompt_tokens": usage.get("prompt_tokens", 0),
|
||||
"completion_tokens": usage.get("completion_tokens", 0),
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
raise HTTPException(500, f"Chat failed: {e}")
|
||||
|
||||
|
||||
@router.post("/api/coach/apply")
|
||||
async def coach_apply_suggestions(body: CoachApplyRequest):
|
||||
"""Apply accepted coaching suggestions to a deck (async DB + async HTTP)."""
|
||||
db = await async_get_db()
|
||||
deck = await async_fetchone("SELECT * FROM decks WHERE id = ?", (body.deck_id,))
|
||||
"""Apply accepted coaching suggestions to a deck — remove cuts, add adds."""
|
||||
conn = _get_db_conn()
|
||||
|
||||
# Verify deck exists
|
||||
deck = conn.execute("SELECT * FROM decks WHERE id = ?", (body.deck_id,)).fetchone()
|
||||
if not deck:
|
||||
raise HTTPException(404, f"Deck {body.deck_id} not found")
|
||||
|
||||
results = {"cuts": [], "adds": [], "errors": []}
|
||||
try:
|
||||
for card_name in body.accepted_cuts:
|
||||
row = await async_fetchone(
|
||||
"SELECT id FROM deck_cards WHERE deck_id = ? AND card_name = ? LIMIT 1",
|
||||
|
||||
# Process cuts: remove cards by name
|
||||
for card_name in body.accepted_cuts:
|
||||
row = conn.execute(
|
||||
"SELECT id FROM deck_cards WHERE deck_id = ? AND card_name = ? LIMIT 1",
|
||||
(body.deck_id, card_name)
|
||||
).fetchone()
|
||||
if row:
|
||||
conn.execute("DELETE FROM deck_cards WHERE id = ?", (row["id"],))
|
||||
results["cuts"].append({"name": card_name, "status": "removed"})
|
||||
else:
|
||||
# Try case-insensitive
|
||||
row = conn.execute(
|
||||
"SELECT id, card_name FROM deck_cards WHERE deck_id = ? AND LOWER(card_name) = LOWER(?) LIMIT 1",
|
||||
(body.deck_id, card_name)
|
||||
)
|
||||
).fetchone()
|
||||
if row:
|
||||
await async_execute("DELETE FROM deck_cards WHERE id = ?", (row["id"],))
|
||||
results["cuts"].append({"name": card_name, "status": "removed"})
|
||||
conn.execute("DELETE FROM deck_cards WHERE id = ?", (row["id"],))
|
||||
results["cuts"].append({"name": row["card_name"], "status": "removed"})
|
||||
else:
|
||||
row = await async_fetchone(
|
||||
"SELECT id, card_name FROM deck_cards WHERE deck_id = ? AND LOWER(card_name) = LOWER(?) LIMIT 1",
|
||||
(body.deck_id, card_name)
|
||||
results["errors"].append({"name": card_name, "error": "Card not found in deck"})
|
||||
|
||||
# Process adds: look up in collection first, then Scryfall
|
||||
for card_name in body.accepted_adds:
|
||||
# Try to find in collection
|
||||
ce = conn.execute(
|
||||
"SELECT scryfall_id, name FROM collection_entries WHERE LOWER(name) = LOWER(?) LIMIT 1",
|
||||
(card_name,)
|
||||
).fetchone()
|
||||
|
||||
scryfall_id = None
|
||||
resolved_name = card_name
|
||||
|
||||
if ce:
|
||||
scryfall_id = ce["scryfall_id"]
|
||||
resolved_name = ce["name"]
|
||||
else:
|
||||
# Try Scryfall API lookup
|
||||
try:
|
||||
import urllib.parse
|
||||
from urllib.request import urlopen, Request as UrlRequest
|
||||
encoded = urllib.parse.quote(card_name)
|
||||
scry_req = UrlRequest(
|
||||
f"https://api.scryfall.com/cards/named?fuzzy={encoded}",
|
||||
headers={"User-Agent": "commander-ai-lab/1.0"}
|
||||
)
|
||||
if row:
|
||||
await async_execute("DELETE FROM deck_cards WHERE id = ?", (row["id"],))
|
||||
results["cuts"].append({"name": row["card_name"], "status": "removed"})
|
||||
else:
|
||||
results["errors"].append({"name": card_name, "error": "Card not found in deck"})
|
||||
for card_name in body.accepted_adds:
|
||||
ce = await async_fetchone(
|
||||
"SELECT scryfall_id, name FROM collection_entries WHERE LOWER(name) = LOWER(?) LIMIT 1",
|
||||
(card_name,)
|
||||
)
|
||||
scryfall_id = None
|
||||
resolved_name = card_name
|
||||
if ce:
|
||||
scryfall_id = ce["scryfall_id"]
|
||||
resolved_name = ce["name"]
|
||||
else:
|
||||
try:
|
||||
import urllib.parse
|
||||
encoded = urllib.parse.quote(card_name)
|
||||
async with httpx.AsyncClient(timeout=10.0) as client:
|
||||
resp = await client.get(
|
||||
f"https://api.scryfall.com/cards/named?fuzzy={encoded}",
|
||||
headers={"User-Agent": "commander-ai-lab/1.0"}
|
||||
)
|
||||
resp.raise_for_status()
|
||||
card_data = resp.json()
|
||||
with urlopen(scry_req, timeout=10) as resp:
|
||||
card_data = json.loads(resp.read().decode("utf-8"))
|
||||
scryfall_id = card_data.get("id")
|
||||
resolved_name = card_data.get("name", card_name)
|
||||
except Exception:
|
||||
pass
|
||||
if scryfall_id:
|
||||
existing = await async_fetchone(
|
||||
"SELECT id FROM deck_cards WHERE deck_id = ? AND scryfall_id = ?",
|
||||
(body.deck_id, scryfall_id)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
if scryfall_id:
|
||||
# Check if already in deck
|
||||
existing = conn.execute(
|
||||
"SELECT id FROM deck_cards WHERE deck_id = ? AND scryfall_id = ?",
|
||||
(body.deck_id, scryfall_id)
|
||||
).fetchone()
|
||||
if not existing:
|
||||
conn.execute(
|
||||
"INSERT INTO deck_cards (deck_id, scryfall_id, card_name, quantity) VALUES (?, ?, ?, 1)",
|
||||
(body.deck_id, scryfall_id, resolved_name)
|
||||
)
|
||||
if not existing:
|
||||
await async_execute(
|
||||
"INSERT INTO deck_cards (deck_id, scryfall_id, card_name, quantity) VALUES (?, ?, ?, 1)",
|
||||
(body.deck_id, scryfall_id, resolved_name)
|
||||
)
|
||||
results["adds"].append({"name": resolved_name, "scryfall_id": scryfall_id, "status": "added"})
|
||||
else:
|
||||
results["adds"].append({"name": resolved_name, "status": "already_in_deck"})
|
||||
results["adds"].append({"name": resolved_name, "scryfall_id": scryfall_id, "status": "added"})
|
||||
else:
|
||||
results["errors"].append({"name": card_name, "error": "Could not resolve card"})
|
||||
await async_execute("UPDATE decks SET updated_at = datetime('now') WHERE id = ?", (body.deck_id,))
|
||||
await async_commit()
|
||||
except Exception as e:
|
||||
try:
|
||||
await async_execute("ROLLBACK")
|
||||
except Exception:
|
||||
pass
|
||||
raise HTTPException(500, f"Apply failed and was rolled back: {e}")
|
||||
results["adds"].append({"name": resolved_name, "status": "already_in_deck"})
|
||||
else:
|
||||
results["errors"].append({"name": card_name, "error": "Could not resolve card"})
|
||||
|
||||
conn.execute("UPDATE decks SET updated_at = datetime('now') WHERE id = ?", (body.deck_id,))
|
||||
conn.commit()
|
||||
|
||||
results["total_cuts"] = len(results["cuts"])
|
||||
results["total_adds"] = len([a for a in results["adds"] if a["status"] == "added"])
|
||||
return results
|
||||
@@ -544,35 +612,49 @@ async def coach_apply_suggestions(body: CoachApplyRequest):
|
||||
|
||||
@router.get("/api/coach/cards-like")
|
||||
async def coach_cards_like(card: str, colors: str = None, top_n: int = 10):
|
||||
"""Find similar cards using embeddings (async DB for ownership check)."""
|
||||
"""Find cards similar to a given card using embeddings. UI-friendly version."""
|
||||
if _coach_embeddings is None or not _coach_embeddings.loaded:
|
||||
raise HTTPException(503, "Embeddings not loaded")
|
||||
|
||||
color_filter = list(colors.upper()) if colors else None
|
||||
matches = _coach_embeddings.search_similar(query_card=card, color_filter=color_filter, top_n=top_n)
|
||||
matches = _coach_embeddings.search_similar(
|
||||
query_card=card, color_filter=color_filter, top_n=top_n
|
||||
)
|
||||
|
||||
conn = _get_db_conn()
|
||||
results = []
|
||||
for m in matches:
|
||||
owned = await async_fetchone(
|
||||
# Check if card is in collection
|
||||
owned = conn.execute(
|
||||
"SELECT SUM(quantity) as qty FROM collection_entries WHERE LOWER(name) = LOWER(?)",
|
||||
(m.name,)
|
||||
)
|
||||
).fetchone()
|
||||
owned_qty = (owned["qty"] or 0) if owned else 0
|
||||
ce = await async_fetchone(
|
||||
"SELECT scryfall_id, tcg_price FROM collection_entries WHERE LOWER(name) = LOWER(?) LIMIT 1",
|
||||
|
||||
# Get image URL and price
|
||||
ce = conn.execute(
|
||||
"SELECT image_url, tcg_price FROM collection_entries WHERE LOWER(name) = LOWER(?) LIMIT 1",
|
||||
(m.name,)
|
||||
)
|
||||
).fetchone()
|
||||
|
||||
results.append({
|
||||
"name": m.name, "similarity": round(m.similarity, 4),
|
||||
"types": m.types, "mana_value": m.mana_value,
|
||||
"mana_cost": m.mana_cost, "text": m.text[:200] if m.text else "",
|
||||
"name": m.name,
|
||||
"similarity": round(m.similarity, 4),
|
||||
"types": m.types,
|
||||
"mana_value": m.mana_value,
|
||||
"mana_cost": m.mana_cost,
|
||||
"text": m.text[:200] if m.text else "",
|
||||
"owned_qty": owned_qty,
|
||||
"image_url": f"https://api.scryfall.com/cards/{ce['scryfall_id']}?format=image&version=normal" if ce and ce["scryfall_id"] else None,
|
||||
"image_url": ce["image_url"] if ce else None,
|
||||
"tcg_price": ce["tcg_price"] if ce else None,
|
||||
})
|
||||
|
||||
return {"query": card, "results": results}
|
||||
|
||||
|
||||
@router.post("/api/coach/reports/generate")
|
||||
async def coach_generate_reports():
|
||||
"""Rebuild all deck reports from batch result JSONs in results/."""
|
||||
try:
|
||||
from coach.report_generator import generate_deck_reports
|
||||
lab_root = Path(__file__).parent.parent
|
||||
@@ -580,7 +662,9 @@ async def coach_generate_reports():
|
||||
reports_dir = str(lab_root / "deck-reports")
|
||||
updated = generate_deck_reports(results_dir, reports_dir)
|
||||
return {
|
||||
"status": "ok", "decksUpdated": updated, "count": len(updated),
|
||||
"status": "ok",
|
||||
"decksUpdated": updated,
|
||||
"count": len(updated),
|
||||
"message": f"Generated reports for {len(updated)} decks" if updated else "No batch results found",
|
||||
}
|
||||
except Exception as e:
|
||||
|
||||
+24
-134
@@ -25,123 +25,35 @@ from typing import Optional
|
||||
from fastapi import APIRouter, HTTPException
|
||||
from fastapi.responses import JSONResponse, StreamingResponse
|
||||
|
||||
from models.state import CFG
|
||||
from services.card_analysis import _detect_card_roles
|
||||
from services.database import (
|
||||
_get_db_conn, _row_to_dict, _add_image_url, _build_collection_filters,
|
||||
_snake_to_camel, VALID_SORT_FIELDS, _JSON_FIELDS,
|
||||
)
|
||||
from services.deck_service import _classify_card_type
|
||||
from services.import_service import (
|
||||
_parse_finish, _parse_text_line, _parse_csv_content, _auto_infer_mapping,
|
||||
)
|
||||
from services.logging import log_collect, log_cache
|
||||
from services.scryfall import (
|
||||
SCRYFALL_CACHE_DB_PATH, SCRYFALL_CACHE_TTL_SECONDS, _API_HEADERS,
|
||||
_scryfall_cache, _scryfall_rate_limit,
|
||||
_enrich_from_scryfall, _fetch_scryfall_api,
|
||||
from routes.shared import (
|
||||
CFG,
|
||||
_get_db_conn,
|
||||
_row_to_dict,
|
||||
_add_image_url,
|
||||
_build_collection_filters,
|
||||
_detect_card_roles,
|
||||
_classify_card_type,
|
||||
_enrich_from_scryfall,
|
||||
_fetch_scryfall_api,
|
||||
_parse_finish,
|
||||
_parse_text_line,
|
||||
_parse_csv_content,
|
||||
_auto_infer_mapping,
|
||||
_scryfall_cache,
|
||||
_scryfall_rate_limit,
|
||||
_snake_to_camel,
|
||||
VALID_SORT_FIELDS,
|
||||
_JSON_FIELDS,
|
||||
SCRYFALL_CACHE_DB_PATH,
|
||||
SCRYFALL_CACHE_TTL_SECONDS,
|
||||
_API_HEADERS,
|
||||
log_collect,
|
||||
log_cache,
|
||||
)
|
||||
|
||||
router = APIRouter(tags=["collection"])
|
||||
|
||||
|
||||
@router.get("/api/collection/stats")
|
||||
async def collection_stats():
|
||||
"""Aggregate collection statistics for the dashboard."""
|
||||
conn = _get_db_conn()
|
||||
stats = {}
|
||||
|
||||
# Total cards and unique cards
|
||||
row = conn.execute(
|
||||
"SELECT COUNT(*) as total_rows, COALESCE(SUM(quantity),0) as total_cards, "
|
||||
"COALESCE(SUM(tcg_price * quantity),0) as total_value "
|
||||
"FROM collection_entries"
|
||||
).fetchone()
|
||||
stats["totalUniqueCards"] = row["total_rows"]
|
||||
stats["totalCards"] = row["total_cards"]
|
||||
stats["totalValue"] = round(row["total_value"], 2)
|
||||
|
||||
# CMC distribution (0-7+)
|
||||
cmc_rows = conn.execute(
|
||||
"SELECT CASE WHEN cmc >= 7 THEN 7 ELSE CAST(cmc AS INTEGER) END as cmc_bucket, "
|
||||
"SUM(quantity) as count FROM collection_entries GROUP BY cmc_bucket ORDER BY cmc_bucket"
|
||||
).fetchall()
|
||||
stats["cmcCurve"] = {str(r["cmc_bucket"]): r["count"] for r in cmc_rows}
|
||||
|
||||
# Color identity distribution
|
||||
color_rows = conn.execute(
|
||||
"SELECT color_identity, SUM(quantity) as count FROM collection_entries GROUP BY color_identity"
|
||||
).fetchall()
|
||||
color_counts = {"W": 0, "U": 0, "B": 0, "R": 0, "G": 0, "C": 0}
|
||||
for r in color_rows:
|
||||
ci = r["color_identity"] or "[]"
|
||||
try:
|
||||
colors = json.loads(ci) if isinstance(ci, str) else ci
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
colors = []
|
||||
qty = r["count"] or 0
|
||||
if not colors:
|
||||
color_counts["C"] += qty
|
||||
else:
|
||||
for c in colors:
|
||||
if c in color_counts:
|
||||
color_counts[c] += qty
|
||||
stats["colorDistribution"] = color_counts
|
||||
|
||||
# Type distribution
|
||||
type_rows = conn.execute(
|
||||
"SELECT type_line, SUM(quantity) as count FROM collection_entries GROUP BY type_line"
|
||||
).fetchall()
|
||||
type_counts = {}
|
||||
for r in type_rows:
|
||||
tl = r["type_line"] or ""
|
||||
qty = r["count"] or 0
|
||||
for t in ["Creature", "Instant", "Sorcery", "Artifact", "Enchantment", "Planeswalker", "Land"]:
|
||||
if t in tl:
|
||||
type_counts[t] = type_counts.get(t, 0) + qty
|
||||
stats["typeDistribution"] = type_counts
|
||||
|
||||
# Category/role distribution
|
||||
cat_rows = conn.execute(
|
||||
"SELECT category, SUM(quantity) as count FROM collection_entries "
|
||||
"WHERE category != '' AND category != '[]' GROUP BY category"
|
||||
).fetchall()
|
||||
cat_counts = {}
|
||||
for r in cat_rows:
|
||||
raw = r["category"] or "[]"
|
||||
qty = r["count"] or 0
|
||||
try:
|
||||
cats = json.loads(raw) if isinstance(raw, str) else raw
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
cats = []
|
||||
if isinstance(cats, list):
|
||||
for c in cats:
|
||||
cat_counts[c] = cat_counts.get(c, 0) + qty
|
||||
stats["categoryDistribution"] = cat_counts
|
||||
|
||||
# Rarity distribution
|
||||
rarity_rows = conn.execute(
|
||||
"SELECT LOWER(rarity) as rarity, SUM(quantity) as count FROM collection_entries "
|
||||
"WHERE rarity != '' GROUP BY LOWER(rarity)"
|
||||
).fetchall()
|
||||
stats["rarityDistribution"] = {r["rarity"]: r["count"] for r in rarity_rows}
|
||||
|
||||
# Top 10 most valuable cards
|
||||
top_value = conn.execute(
|
||||
"SELECT name, tcg_price, quantity FROM collection_entries "
|
||||
"WHERE tcg_price > 0 ORDER BY tcg_price DESC LIMIT 10"
|
||||
).fetchall()
|
||||
stats["topValueCards"] = [{"name": r["name"], "price": r["tcg_price"], "qty": r["quantity"]} for r in top_value]
|
||||
|
||||
# Average CMC (excluding lands)
|
||||
avg_row = conn.execute(
|
||||
"SELECT AVG(cmc) as avg_cmc FROM collection_entries WHERE type_line NOT LIKE '%Land%'"
|
||||
).fetchone()
|
||||
stats["avgCmc"] = round(avg_row["avg_cmc"] or 0, 2)
|
||||
|
||||
return stats
|
||||
|
||||
|
||||
@router.get("/api/collection/export")
|
||||
async def export_collection(
|
||||
format: str = "INTERNAL_CSV",
|
||||
@@ -158,17 +70,6 @@ async def export_collection(
|
||||
priceMin: Optional[float] = None,
|
||||
priceMax: Optional[float] = None,
|
||||
category: Optional[str] = None,
|
||||
rarity: Optional[str] = None,
|
||||
setCode: Optional[str] = None,
|
||||
powerMin: Optional[str] = None,
|
||||
powerMax: Optional[str] = None,
|
||||
toughMin: Optional[str] = None,
|
||||
toughMax: Optional[str] = None,
|
||||
keyword: Optional[str] = None,
|
||||
edhrecMin: Optional[int] = None,
|
||||
edhrecMax: Optional[int] = None,
|
||||
qtyMin: Optional[int] = None,
|
||||
qtyMax: Optional[int] = None,
|
||||
):
|
||||
"""Export collection in various formats with optional filters."""
|
||||
where_str, params = _build_collection_filters(
|
||||
@@ -176,12 +77,6 @@ async def export_collection(
|
||||
isBasic=isBasic, isGameChanger=isGameChanger, highSalt=highSalt,
|
||||
finish=finish, cmcMin=cmcMin, cmcMax=cmcMax,
|
||||
priceMin=priceMin, priceMax=priceMax, category=category,
|
||||
rarity=rarity, setCode=setCode,
|
||||
powerMin=powerMin, powerMax=powerMax,
|
||||
toughMin=toughMin, toughMax=toughMax,
|
||||
keyword=keyword,
|
||||
edhrecMin=edhrecMin, edhrecMax=edhrecMax,
|
||||
qtyMin=qtyMin, qtyMax=qtyMax,
|
||||
)
|
||||
|
||||
sql = f"SELECT * FROM collection_entries {where_str} ORDER BY name ASC"
|
||||
@@ -406,11 +301,6 @@ async def update_collection_card(cardId: int, body: dict):
|
||||
if finish_val not in ("NORMAL", "FOIL", "ETCHED"):
|
||||
raise HTTPException(400, "finish must be NORMAL, FOIL, or ETCHED")
|
||||
updates["finish"] = finish_val
|
||||
if "quantity" in body:
|
||||
qty_val = int(body["quantity"])
|
||||
if qty_val < 0:
|
||||
raise HTTPException(400, "quantity must be >= 0")
|
||||
updates["quantity"] = qty_val
|
||||
|
||||
if not updates:
|
||||
return _add_image_url(_row_to_dict(row))
|
||||
|
||||
+78
-38
@@ -36,25 +36,35 @@ from urllib.parse import quote
|
||||
from fastapi import APIRouter, HTTPException, Request as FastAPIRequest
|
||||
from fastapi.responses import JSONResponse
|
||||
|
||||
from models.state import CFG
|
||||
from models.requests import (
|
||||
CreateDeckRequest, UpdateDeckRequest, AddDeckCardRequest,
|
||||
PatchDeckCardRequest, BulkAddRequest, BulkAddRecommendedRequest,
|
||||
)
|
||||
from services.card_analysis import _detect_card_roles
|
||||
from services.database import _get_db_conn, _row_to_dict, _add_image_url
|
||||
from services.deck_service import (
|
||||
_get_deck_or_404, _compute_deck_analysis, _check_ratio_limit,
|
||||
_classify_card_type, _classify_card_category, _to_edhrec_slug, _TYPE_TARGETS,
|
||||
from routes.shared import (
|
||||
CFG,
|
||||
_get_db_conn,
|
||||
_row_to_dict,
|
||||
_add_image_url,
|
||||
_get_deck_or_404,
|
||||
_compute_deck_analysis,
|
||||
_check_ratio_limit,
|
||||
_classify_card_type,
|
||||
_detect_card_roles,
|
||||
_enrich_from_scryfall,
|
||||
_fetch_scryfall_api,
|
||||
_scryfall_rate_limit,
|
||||
_to_edhrec_slug,
|
||||
_edhrec_cache_get,
|
||||
_edhrec_cache_set,
|
||||
_fetch_edhrec_average,
|
||||
_save_profile_to_dck,
|
||||
)
|
||||
from services.import_helpers import (
|
||||
_fetch_edhrec_average, _parse_text_decklist,
|
||||
_edhrec_cache_get, _edhrec_cache_set,
|
||||
)
|
||||
from services.logging import log_collect, log_deckgen
|
||||
from services.scryfall import (
|
||||
_API_HEADERS, _enrich_from_scryfall, _fetch_scryfall_api, _scryfall_rate_limit,
|
||||
_parse_text_decklist,
|
||||
_API_HEADERS,
|
||||
_TYPE_TARGETS,
|
||||
CreateDeckRequest,
|
||||
UpdateDeckRequest,
|
||||
AddDeckCardRequest,
|
||||
PatchDeckCardRequest,
|
||||
BulkAddRequest,
|
||||
BulkAddRecommendedRequest,
|
||||
log_collect,
|
||||
log_deckgen,
|
||||
)
|
||||
|
||||
router = APIRouter(tags=["deckbuilder"])
|
||||
@@ -121,6 +131,7 @@ async def get_deck(deck_id: int):
|
||||
deck["cards"] = [dict(r) for r in card_rows]
|
||||
deck["total_cards"] = sum(r["quantity"] for r in card_rows)
|
||||
deck["card_slots"] = len(card_rows)
|
||||
# Composition summary by type
|
||||
analysis = _compute_deck_analysis(deck_id)
|
||||
deck["composition"] = analysis["counts_by_type"]
|
||||
return deck
|
||||
@@ -129,7 +140,7 @@ async def get_deck(deck_id: int):
|
||||
@router.put("/api/decks/{deck_id}")
|
||||
async def update_deck(deck_id: int, req: UpdateDeckRequest):
|
||||
"""Update deck metadata."""
|
||||
_get_deck_or_404(deck_id)
|
||||
_get_deck_or_404(deck_id) # ensure exists
|
||||
conn = _get_db_conn()
|
||||
|
||||
updates = {}
|
||||
@@ -157,7 +168,7 @@ async def update_deck(deck_id: int, req: UpdateDeckRequest):
|
||||
@router.delete("/api/decks/{deck_id}")
|
||||
async def delete_deck(deck_id: int):
|
||||
"""Delete a deck and all its cards (cascade)."""
|
||||
_get_deck_or_404(deck_id)
|
||||
_get_deck_or_404(deck_id) # ensure exists
|
||||
conn = _get_db_conn()
|
||||
conn.execute("DELETE FROM deck_cards WHERE deck_id = ?", (deck_id,))
|
||||
conn.execute("DELETE FROM decks WHERE id = ?", (deck_id,))
|
||||
@@ -180,7 +191,7 @@ async def delete_all_decks():
|
||||
|
||||
@router.get("/api/decks/{deck_id}/cards")
|
||||
async def get_deck_cards(deck_id: int):
|
||||
"""Get all cards in a deck with joined collection and card_records data."""
|
||||
"""Get all cards in a deck with joined collection data."""
|
||||
_get_deck_or_404(deck_id)
|
||||
conn = _get_db_conn()
|
||||
rows = conn.execute(
|
||||
@@ -188,12 +199,7 @@ async def get_deck_cards(deck_id: int):
|
||||
SELECT
|
||||
dc.id, dc.deck_id, dc.scryfall_id, dc.card_name, dc.quantity,
|
||||
dc.is_commander, dc.role_tag,
|
||||
COALESCE(ce.type_line, cr.type_line, '') as type_line,
|
||||
COALESCE(ce.cmc, cr.cmc, 0) as cmc,
|
||||
COALESCE(ce.mana_cost, '') as mana_cost,
|
||||
COALESCE(ce.color_identity, cr.color_identity, '[]') as color_identity,
|
||||
COALESCE(ce.oracle_text, cr.oracle_text, '') as oracle_text,
|
||||
COALESCE(ce.keywords, cr.keywords, '[]') as keywords,
|
||||
ce.type_line, ce.cmc, ce.mana_cost, ce.color_identity, ce.oracle_text, ce.keywords,
|
||||
ce.tcg_price, ce.quantity AS owned_qty, ce.is_legendary,
|
||||
ce.salt_score, ce.is_game_changer
|
||||
FROM deck_cards dc
|
||||
@@ -204,11 +210,6 @@ async def get_deck_cards(deck_id: int):
|
||||
FROM collection_entries
|
||||
GROUP BY scryfall_id
|
||||
) ce ON ce.scryfall_id = dc.scryfall_id
|
||||
LEFT JOIN (
|
||||
SELECT name, type_line, cmc, color_identity, oracle_text, keywords
|
||||
FROM card_records
|
||||
GROUP BY name
|
||||
) cr ON cr.name = dc.card_name
|
||||
WHERE dc.deck_id = ?
|
||||
ORDER BY dc.is_commander DESC, dc.card_name ASC
|
||||
""",
|
||||
@@ -217,6 +218,7 @@ async def get_deck_cards(deck_id: int):
|
||||
cards = []
|
||||
for row in rows:
|
||||
d = dict(row)
|
||||
# Parse JSON fields
|
||||
for f in ("color_identity", "keywords"):
|
||||
if isinstance(d.get(f), str):
|
||||
try:
|
||||
@@ -227,8 +229,6 @@ async def get_deck_cards(deck_id: int):
|
||||
f"https://api.scryfall.com/cards/{d['scryfall_id']}?format=image&version=normal"
|
||||
if d.get("scryfall_id") else None
|
||||
)
|
||||
d["card_type"] = _classify_card_type(d.get("type_line", ""))
|
||||
d["card_category"] = _classify_card_category(d.get("type_line", ""), d.get("oracle_text", ""))
|
||||
cards.append(d)
|
||||
return {"cards": cards, "total": len(cards)}
|
||||
|
||||
@@ -239,12 +239,14 @@ async def add_deck_card(deck_id: int, req: AddDeckCardRequest):
|
||||
_get_deck_or_404(deck_id)
|
||||
conn = _get_db_conn()
|
||||
|
||||
# Look up card_name from collection_entries by scryfall_id, fall back to request
|
||||
ce_row = conn.execute(
|
||||
"SELECT name FROM collection_entries WHERE scryfall_id = ? LIMIT 1",
|
||||
(req.scryfall_id,)
|
||||
).fetchone()
|
||||
card_name = ce_row["name"] if ce_row else (req.card_name or "")
|
||||
|
||||
# Check if this scryfall_id is already in the deck
|
||||
existing = conn.execute(
|
||||
"SELECT id, quantity FROM deck_cards WHERE deck_id = ? AND scryfall_id = ?",
|
||||
(deck_id, req.scryfall_id)
|
||||
@@ -274,6 +276,7 @@ async def add_deck_card(deck_id: int, req: AddDeckCardRequest):
|
||||
conn.commit()
|
||||
row = conn.execute("SELECT * FROM deck_cards WHERE id = ?", (cur.lastrowid,)).fetchone()
|
||||
|
||||
# Update deck updated_at
|
||||
conn.execute("UPDATE decks SET updated_at = datetime('now') WHERE id = ?", (deck_id,))
|
||||
conn.commit()
|
||||
return dict(row)
|
||||
@@ -348,23 +351,28 @@ async def recommend_from_collection(deck_id: int, max_results: int = 20, roles:
|
||||
deck_color_identity = deck.get("color_identity", [])
|
||||
conn = _get_db_conn()
|
||||
|
||||
# Run analysis to find shortfalls
|
||||
analysis = _compute_deck_analysis(deck_id)
|
||||
deltas = analysis.get("deltas", {})
|
||||
deltas = analysis["deltas"]
|
||||
counts_by_type = analysis["counts_by_type"]
|
||||
|
||||
# Find types that are below their target midpoint (shortfall)
|
||||
shortfall_types = set()
|
||||
for t, delta in deltas.items():
|
||||
lo, hi = _TYPE_TARGETS.get(t, [0, 0])
|
||||
if counts_by_type.get(t, 0) < lo:
|
||||
shortfall_types.add(t)
|
||||
|
||||
# Get scryfall_ids already in deck to exclude
|
||||
in_deck_ids = set(
|
||||
r["scryfall_id"] for r in
|
||||
conn.execute("SELECT scryfall_id FROM deck_cards WHERE deck_id = ?", (deck_id,)).fetchall()
|
||||
)
|
||||
|
||||
# Parse role filter
|
||||
role_filter = [r.strip() for r in roles.split(",") if r.strip()] if roles else []
|
||||
|
||||
# Query collection for candidate cards
|
||||
coll_rows = conn.execute(
|
||||
"SELECT * FROM collection_entries WHERE quantity > 0"
|
||||
).fetchall()
|
||||
@@ -374,9 +382,11 @@ async def recommend_from_collection(deck_id: int, max_results: int = 20, roles:
|
||||
card = _row_to_dict(row)
|
||||
card_id = card.get("scryfall_id", "")
|
||||
|
||||
# Skip cards already in deck
|
||||
if card_id in in_deck_ids:
|
||||
continue
|
||||
|
||||
# Color identity check: all card colors must be in deck colors
|
||||
card_ci = card.get("color_identity", [])
|
||||
if isinstance(card_ci, str):
|
||||
try:
|
||||
@@ -393,17 +403,22 @@ async def recommend_from_collection(deck_id: int, max_results: int = 20, roles:
|
||||
card_type = _classify_card_type(type_line)
|
||||
card_roles = _detect_card_roles(oracle_text, type_line, keywords)
|
||||
|
||||
# Role filter
|
||||
if role_filter and not any(r in card_roles for r in role_filter):
|
||||
continue
|
||||
|
||||
# Scoring
|
||||
score = 0
|
||||
# +3 if card type is in shortfall
|
||||
if card_type in shortfall_types:
|
||||
score += 3
|
||||
# +2 per matching role
|
||||
for r in card_roles:
|
||||
if r in ("Ramp", "Draw", "Removal", "BoardWipe"):
|
||||
score += 2
|
||||
else:
|
||||
score += 1
|
||||
# +1 for lower CMC (curve fit)
|
||||
cmc = float(card.get("cmc", 0))
|
||||
if cmc <= 3:
|
||||
score += 1
|
||||
@@ -424,6 +439,7 @@ async def recommend_from_collection(deck_id: int, max_results: int = 20, roles:
|
||||
|
||||
scored.sort(key=lambda x: x["score"], reverse=True)
|
||||
|
||||
# Group by type
|
||||
grouped = {}
|
||||
for card in scored[:max_results]:
|
||||
ct = card["card_type"]
|
||||
@@ -450,6 +466,7 @@ async def deck_edh_recs(deck_id: int, only_owned: bool = False, max_results: int
|
||||
if not commander_name:
|
||||
raise HTTPException(400, "Deck has no commander_name set. Update the deck first.")
|
||||
|
||||
# Cache check
|
||||
cache_key = f"edhrec:avg:{_to_edhrec_slug(commander_name)}"
|
||||
cached_profile = _edhrec_cache_get(cache_key)
|
||||
if cached_profile is None:
|
||||
@@ -464,11 +481,13 @@ async def deck_edh_recs(deck_id: int, only_owned: bool = False, max_results: int
|
||||
|
||||
conn = _get_db_conn()
|
||||
|
||||
# Get cards already in deck
|
||||
in_deck_names = set(
|
||||
r["card_name"].lower() for r in
|
||||
conn.execute("SELECT card_name FROM deck_cards WHERE deck_id = ?", (deck_id,)).fetchall()
|
||||
)
|
||||
|
||||
# Build collection lookup: name (lower) -> {owned, qty, scryfall_id}
|
||||
coll_rows = conn.execute(
|
||||
"SELECT name, quantity, scryfall_id FROM collection_entries"
|
||||
).fetchall()
|
||||
@@ -479,6 +498,7 @@ async def deck_edh_recs(deck_id: int, only_owned: bool = False, max_results: int
|
||||
if not existing or r["quantity"] > existing["qty"]:
|
||||
coll_map[key] = {"owned": True, "qty": r["quantity"], "scryfall_id": r["scryfall_id"]}
|
||||
|
||||
# Also look up card details from collection_entries for type/role
|
||||
coll_details = {}
|
||||
for r in conn.execute("SELECT name, type_line, oracle_text, keywords, scryfall_id FROM collection_entries").fetchall():
|
||||
key = r["name"].lower()
|
||||
@@ -488,6 +508,7 @@ async def deck_edh_recs(deck_id: int, only_owned: bool = False, max_results: int
|
||||
results = []
|
||||
for card_name in mainboard:
|
||||
name_lower = card_name.lower()
|
||||
# Skip cards already in deck
|
||||
if name_lower in in_deck_names:
|
||||
continue
|
||||
|
||||
@@ -496,6 +517,7 @@ async def deck_edh_recs(deck_id: int, only_owned: bool = False, max_results: int
|
||||
if only_owned and not owned_info["owned"]:
|
||||
continue
|
||||
|
||||
# Get type/role from collection if available
|
||||
details = coll_details.get(name_lower, {})
|
||||
type_line = details.get("type_line", "")
|
||||
oracle_text = details.get("oracle_text", "")
|
||||
@@ -508,7 +530,7 @@ async def deck_edh_recs(deck_id: int, only_owned: bool = False, max_results: int
|
||||
"type_line": type_line,
|
||||
"role": card_roles[0] if card_roles else "Other",
|
||||
"roles": card_roles,
|
||||
"inclusion_pct": None,
|
||||
"inclusion_pct": None, # EDHREC average doesn't expose % directly in this path
|
||||
"synergy_score": None,
|
||||
"owned": owned_info["owned"],
|
||||
"owned_qty": owned_info["qty"],
|
||||
@@ -557,6 +579,7 @@ async def bulk_add_cards(deck_id: int, req: BulkAddRequest):
|
||||
details.append({"scryfall_id": scryfall_id, "status": "skipped", "reason": "missing scryfall_id"})
|
||||
continue
|
||||
|
||||
# Look up card name and type from collection
|
||||
ce_row = conn.execute(
|
||||
"SELECT name, type_line, oracle_text, keywords FROM collection_entries WHERE scryfall_id = ? LIMIT 1",
|
||||
(scryfall_id,)
|
||||
@@ -576,6 +599,7 @@ async def bulk_add_cards(deck_id: int, req: BulkAddRequest):
|
||||
})
|
||||
continue
|
||||
|
||||
# Upsert
|
||||
existing = conn.execute(
|
||||
"SELECT id, quantity FROM deck_cards WHERE deck_id = ? AND scryfall_id = ?",
|
||||
(deck_id, scryfall_id)
|
||||
@@ -617,6 +641,7 @@ async def bulk_add_recommended(deck_id: int, req: BulkAddRecommendedRequest):
|
||||
candidates = []
|
||||
|
||||
if source == "collection":
|
||||
# Reuse the recommend_from_collection logic
|
||||
deck = _get_deck_or_404(deck_id)
|
||||
deck_color_identity = deck.get("color_identity", [])
|
||||
analysis = _compute_deck_analysis(deck_id)
|
||||
@@ -676,7 +701,7 @@ async def bulk_add_recommended(deck_id: int, req: BulkAddRecommendedRequest):
|
||||
if req.only_owned and not coll_info:
|
||||
continue
|
||||
if not coll_info:
|
||||
continue
|
||||
continue # can't add without scryfall_id
|
||||
scryfall_id = coll_info.get("scryfall_id", "")
|
||||
if not scryfall_id:
|
||||
continue
|
||||
@@ -691,6 +716,7 @@ async def bulk_add_recommended(deck_id: int, req: BulkAddRecommendedRequest):
|
||||
else:
|
||||
raise HTTPException(400, f"Unknown source '{source}'. Use 'collection' or 'edhrec'.")
|
||||
|
||||
# Now bulk-add candidates
|
||||
added = 0
|
||||
skipped = 0
|
||||
details = []
|
||||
@@ -754,6 +780,7 @@ async def export_deck_to_sim(deck_id: int):
|
||||
if not card_rows:
|
||||
raise HTTPException(400, "Deck has no cards to export")
|
||||
|
||||
# Build .dck content
|
||||
lines = ["[metadata]"]
|
||||
deck_name = deck.get("name", f"Deck {deck_id}")
|
||||
lines.append(f"Name={deck_name}")
|
||||
@@ -778,6 +805,7 @@ async def export_deck_to_sim(deck_id: int):
|
||||
|
||||
content = "\n".join(lines)
|
||||
|
||||
# Determine save directory
|
||||
safe_name = re.sub(r"[^a-zA-Z0-9 _-]", "", deck_name).replace(" ", "_").strip()
|
||||
if not safe_name:
|
||||
safe_name = f"deck_{deck_id}"
|
||||
@@ -817,13 +845,14 @@ def _parse_decklist_text(text: str) -> dict:
|
||||
"""
|
||||
commanders = []
|
||||
cards = []
|
||||
section = 'main'
|
||||
section = 'main' # default section
|
||||
|
||||
for raw_line in text.splitlines():
|
||||
line = raw_line.strip()
|
||||
if not line or line.startswith('//') or line.startswith('#'):
|
||||
continue
|
||||
|
||||
# Section headers
|
||||
low = line.lower()
|
||||
if low.startswith('[commander'):
|
||||
section = 'commander'
|
||||
@@ -835,12 +864,14 @@ def _parse_decklist_text(text: str) -> dict:
|
||||
section = 'skip'
|
||||
continue
|
||||
if low.startswith('['):
|
||||
# Unknown section, treat as main
|
||||
section = 'main'
|
||||
continue
|
||||
|
||||
if section == 'skip':
|
||||
continue
|
||||
|
||||
# Parse quantity + name
|
||||
m = re.match(r'^(\d+)\s*[xX]?\s+(.+)$', line)
|
||||
if m:
|
||||
qty = int(m.group(1))
|
||||
@@ -849,6 +880,7 @@ def _parse_decklist_text(text: str) -> dict:
|
||||
qty = 1
|
||||
name = line
|
||||
|
||||
# Strip set codes like "(M21)" or "(M21) 123" from MTGA exports
|
||||
name = re.sub(r'\s*\([A-Z0-9]+\)\s*\d*\s*$', '', name).strip()
|
||||
|
||||
if not name:
|
||||
@@ -890,6 +922,7 @@ async def import_decklist(deck_id: int, request: FastAPIRequest):
|
||||
|
||||
conn = _get_db_conn()
|
||||
|
||||
# Optionally clear existing cards
|
||||
if clear_first:
|
||||
conn.execute('DELETE FROM deck_cards WHERE deck_id = ?', (deck_id,))
|
||||
conn.commit()
|
||||
@@ -903,6 +936,7 @@ async def import_decklist(deck_id: int, request: FastAPIRequest):
|
||||
qty = entry['qty']
|
||||
is_cmd = entry['is_commander']
|
||||
|
||||
# Look up on Scryfall
|
||||
sf = _scryfall_fuzzy_lookup(name)
|
||||
if not sf:
|
||||
failed.append(name)
|
||||
@@ -912,6 +946,7 @@ async def import_decklist(deck_id: int, request: FastAPIRequest):
|
||||
scryfall_id = sf.get('id', '')
|
||||
resolved_name = sf.get('name', name)
|
||||
|
||||
# Check if already in deck
|
||||
existing = conn.execute(
|
||||
'SELECT id, quantity FROM deck_cards WHERE deck_id = ? AND scryfall_id = ?',
|
||||
(deck_id, scryfall_id)
|
||||
@@ -931,9 +966,11 @@ async def import_decklist(deck_id: int, request: FastAPIRequest):
|
||||
added += 1
|
||||
results.append({'name': resolved_name, 'qty': qty, 'status': 'added', 'isCommander': is_cmd})
|
||||
|
||||
# Update commander on deck record if we found one
|
||||
cmd_entries = [r for r in results if r.get('isCommander')]
|
||||
if cmd_entries:
|
||||
cmd_name = cmd_entries[0]['name']
|
||||
# Look up scryfall_id from the deck_cards we just inserted
|
||||
cmd_row = conn.execute(
|
||||
'SELECT scryfall_id FROM deck_cards WHERE deck_id = ? AND is_commander = 1 LIMIT 1',
|
||||
(deck_id,)
|
||||
@@ -980,6 +1017,7 @@ async def import_decklist_new(request: FastAPIRequest):
|
||||
if not all_entries:
|
||||
return JSONResponse({'error': 'No cards found in decklist'}, status_code=400)
|
||||
|
||||
# Auto-name from first commander if no name given
|
||||
if not deck_name:
|
||||
cmd = parsed['commanders'][0]['name'] if parsed['commanders'] else None
|
||||
deck_name = cmd or 'Imported Deck'
|
||||
@@ -992,6 +1030,7 @@ async def import_decklist_new(request: FastAPIRequest):
|
||||
conn.commit()
|
||||
new_deck_id = cur.lastrowid
|
||||
|
||||
# Set commander on the deck if we have one
|
||||
first_cmd_scryfall = None
|
||||
first_cmd_name = None
|
||||
|
||||
@@ -1022,6 +1061,7 @@ async def import_decklist_new(request: FastAPIRequest):
|
||||
conn.commit()
|
||||
added += 1
|
||||
|
||||
# Update commander on deck record
|
||||
if first_cmd_scryfall:
|
||||
conn.execute(
|
||||
'UPDATE decks SET commander_name = ?, commander_scryfall_id = ? WHERE id = ?',
|
||||
|
||||
+93
-198
@@ -1,14 +1,14 @@
|
||||
"""
|
||||
routes/deckgen.py
|
||||
=================
|
||||
Deck generation endpoints (classic, Anthropic Claude V1, V3):
|
||||
Deck generation endpoints (classic, Perplexity V1, V3):
|
||||
GET /api/deck-generator/config
|
||||
POST /api/deck-generator/preview
|
||||
POST /api/deck-generator/commit
|
||||
GET /api/deck-generator/commander-search
|
||||
POST /api/deck-research
|
||||
POST /api/deck-generate
|
||||
GET /api/anthropic/status
|
||||
GET /api/pplx/status
|
||||
GET /api/deck/v3/status
|
||||
POST /api/deck/v3/generate
|
||||
POST /api/deck/v3/commit
|
||||
@@ -36,57 +36,18 @@ from fastapi.responses import JSONResponse, StreamingResponse
|
||||
from models.requests import DeckResearchRequest, DeckGenerateAIRequest
|
||||
|
||||
import routes.coach as _coach # for _deck_gen_v3 / _deck_gen_v3_error module-level access
|
||||
from models.state import CFG
|
||||
from models.requests import (
|
||||
from routes.shared import (
|
||||
CFG,
|
||||
log_deckgen, log_pplx,
|
||||
_get_db_conn,
|
||||
_scryfall_rate_limit, _API_HEADERS,
|
||||
DeckGenerationRequest, DeckGenV3Request, DeckGenV3SubstituteRequest,
|
||||
DeckGenerationSourceConfig,
|
||||
GeneratedDeckCard, DeckGenerationSourceConfig,
|
||||
)
|
||||
from models.responses import GeneratedDeckCard
|
||||
from services.database import _get_db_conn
|
||||
from services.logging import log_deckgen, log_pplx
|
||||
from services.scryfall import _scryfall_rate_limit, _API_HEADERS
|
||||
from services.deck_service import _write_dck_file, _build_dck_lines
|
||||
|
||||
router = APIRouter(tags=["deckgen"])
|
||||
|
||||
# ── V3 Result Cache (avoids re-generating on export) ─────────────
|
||||
import hashlib
|
||||
_v3_result_cache: dict[str, tuple[float, dict]] = {} # key -> (timestamp, result)
|
||||
_V3_CACHE_TTL = 600 # 10 minutes
|
||||
|
||||
def _v3_cache_key(req) -> str:
|
||||
"""Deterministic cache key from a DeckGenV3Request."""
|
||||
blob = json.dumps({
|
||||
'commander': req.commander_name.strip().lower(),
|
||||
'strategy': req.strategy or '',
|
||||
'bracket': req.target_bracket,
|
||||
'budget': req.budget_usd,
|
||||
'budget_mode': req.budget_mode,
|
||||
'omit': sorted(req.omit_cards or []),
|
||||
'collection': req.use_collection,
|
||||
'model': req.model or '',
|
||||
}, sort_keys=True)
|
||||
return hashlib.sha256(blob.encode()).hexdigest()[:16]
|
||||
|
||||
def _v3_cache_get(key: str) -> dict | None:
|
||||
"""Return cached result if within TTL, else None."""
|
||||
entry = _v3_result_cache.get(key)
|
||||
if entry and (time.time() - entry[0]) < _V3_CACHE_TTL:
|
||||
return entry[1]
|
||||
if entry:
|
||||
del _v3_result_cache[key]
|
||||
return None
|
||||
|
||||
def _v3_cache_put(key: str, result: dict):
|
||||
"""Store result in cache with current timestamp."""
|
||||
# Evict stale entries if cache grows large
|
||||
if len(_v3_result_cache) > 50:
|
||||
cutoff = time.time() - _V3_CACHE_TTL
|
||||
stale = [k for k, (ts, _) in _v3_result_cache.items() if ts < cutoff]
|
||||
for k in stale:
|
||||
del _v3_result_cache[k]
|
||||
_v3_result_cache[key] = (time.time(), result)
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Auto Deck Generator
|
||||
@@ -103,7 +64,7 @@ def _resolve_commander(req: DeckGenerationRequest) -> dict:
|
||||
# Try scryfall_id first
|
||||
if req.commander_scryfall_id:
|
||||
row = conn.execute(
|
||||
"SELECT name, type_line, color_identity, mana_cost, scryfall_id, oracle_text FROM collection_entries WHERE scryfall_id = ? LIMIT 1",
|
||||
"SELECT name, type_line, color_identity, mana_cost, scryfall_id FROM collection_entries WHERE scryfall_id = ? LIMIT 1",
|
||||
(req.commander_scryfall_id,)
|
||||
).fetchone()
|
||||
if row:
|
||||
@@ -119,7 +80,6 @@ def _resolve_commander(req: DeckGenerationRequest) -> dict:
|
||||
"color_identity": ci,
|
||||
"type_line": row["type_line"],
|
||||
"mana_cost": row["mana_cost"] or "",
|
||||
"oracle_text": row["oracle_text"] or "",
|
||||
"image_url": f"https://api.scryfall.com/cards/{row['scryfall_id']}?format=image&version=normal",
|
||||
}
|
||||
# Fallback to Scryfall API
|
||||
@@ -137,7 +97,7 @@ def _resolve_commander(req: DeckGenerationRequest) -> dict:
|
||||
if req.commander_name:
|
||||
name_lower = req.commander_name.strip().lower()
|
||||
row = conn.execute(
|
||||
"SELECT name, type_line, color_identity, mana_cost, scryfall_id, oracle_text FROM collection_entries WHERE LOWER(name) = ? LIMIT 1",
|
||||
"SELECT name, type_line, color_identity, mana_cost, scryfall_id FROM collection_entries WHERE LOWER(name) = ? LIMIT 1",
|
||||
(name_lower,)
|
||||
).fetchone()
|
||||
if row:
|
||||
@@ -153,7 +113,6 @@ def _resolve_commander(req: DeckGenerationRequest) -> dict:
|
||||
"color_identity": ci,
|
||||
"type_line": row["type_line"],
|
||||
"mana_cost": row["mana_cost"] or "",
|
||||
"oracle_text": row["oracle_text"] or "",
|
||||
"image_url": f"https://api.scryfall.com/cards/{row['scryfall_id']}?format=image&version=normal",
|
||||
}
|
||||
|
||||
@@ -185,7 +144,6 @@ def _scryfall_to_commander(data: dict) -> dict:
|
||||
"color_identity": ci,
|
||||
"type_line": data.get("type_line", ""),
|
||||
"mana_cost": data.get("mana_cost", ""),
|
||||
"oracle_text": data.get("oracle_text", ""),
|
||||
"image_url": image_uris.get("normal", ""),
|
||||
}
|
||||
|
||||
@@ -236,31 +194,6 @@ def _get_collection_for_colors(color_identity: list) -> list:
|
||||
return valid
|
||||
|
||||
|
||||
# ── Oracle-text keyword extraction for scoring ────────────────────
|
||||
_ORACLE_STOP_WORDS = frozenset({
|
||||
'a', 'an', 'the', 'of', 'to', 'and', 'or', 'is', 'it', 'its',
|
||||
'in', 'on', 'at', 'for', 'by', 'with', 'from', 'as', 'if',
|
||||
'that', 'this', 'you', 'your', 'up', 'all', 'each', 'may',
|
||||
'can', 'one', 'two', 'three', 'four', 'five', 'card', 'cards',
|
||||
'target', 'player', 'creature', 'creatures', 'spell', 'spells',
|
||||
'permanent', 'permanents', 'turn', 'end', 'step', 'phase',
|
||||
'mana', 'color', 'pay', 'cost', 'tap', 'untap', 'put', 'get',
|
||||
'has', 'have', 'are', 'be', 'been', 'was', 'were', 'do', 'does',
|
||||
'any', 'no', 'not', 'only', 'also', 'then', 'when', 'whenever',
|
||||
'where', 'which', 'who', 'them', 'they', 'their', 'other',
|
||||
'more', 'less', 'than', 'into', 'under', 'over', 'until',
|
||||
'would', 'could', 'instead', 'about', 'number', 'equal',
|
||||
})
|
||||
|
||||
|
||||
def _extract_oracle_keywords(oracle_text: str) -> set[str]:
|
||||
"""Extract meaningful keywords from oracle text, filtering stop words."""
|
||||
if not oracle_text:
|
||||
return set()
|
||||
cleaned = re.sub(r'\([^)]*\)', '', oracle_text)
|
||||
tokens = re.findall(r'[a-z]{3,}', cleaned.lower())
|
||||
return {t for t in tokens if t not in _ORACLE_STOP_WORDS}
|
||||
|
||||
def _generate_deck(req: DeckGenerationRequest) -> dict:
|
||||
"""
|
||||
Core deck generation algorithm.
|
||||
@@ -279,8 +212,6 @@ def _generate_deck(req: DeckGenerationRequest) -> dict:
|
||||
|
||||
color_identity = req.color_identity or commander.get("color_identity", [])
|
||||
log_deckgen.info(f" Commander: {commander['name']}, CI: {color_identity}")
|
||||
commander_keywords = _extract_oracle_keywords(commander.get("oracle_text", ""))
|
||||
log_deckgen.info(f" Commander keywords ({len(commander_keywords)}): {sorted(commander_keywords)[:15]}")
|
||||
|
||||
# 2. Load collection
|
||||
collection = _get_collection_for_colors(color_identity)
|
||||
@@ -347,7 +278,6 @@ def _generate_deck(req: DeckGenerationRequest) -> dict:
|
||||
)
|
||||
candidate_map[key] = {
|
||||
"scryfall_id": card.get("scryfall_id", ""),
|
||||
"oracle_text": card.get("oracle_text", ""),
|
||||
"name": name,
|
||||
"type_line": type_line,
|
||||
"mana_cost": card.get("mana_cost", ""),
|
||||
@@ -440,17 +370,6 @@ def _generate_deck(req: DeckGenerationRequest) -> dict:
|
||||
score += 5
|
||||
elif cmc <= 4:
|
||||
score += 3
|
||||
# Oracle-text keyword overlap with commander
|
||||
card_oracle = card.get("oracle_text") or ""
|
||||
if commander_keywords and card_oracle:
|
||||
card_kw = _extract_oracle_keywords(card_oracle)
|
||||
overlap = len(commander_keywords & card_kw)
|
||||
if overlap >= 4:
|
||||
score += 12
|
||||
elif overlap >= 2:
|
||||
score += 7
|
||||
elif overlap >= 1:
|
||||
score += 3
|
||||
card["_score"] = score
|
||||
cards.sort(key=lambda x: x["_score"], reverse=True)
|
||||
|
||||
@@ -724,7 +643,7 @@ async def deck_generator_commander_search(q: str = ""):
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Anthropic Claude API — AI Deck Research & Generation
|
||||
# Perplexity API — AI Deck Research & Generation
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
@@ -847,62 +766,54 @@ def _build_collection_summary(color_identity: list[str] | None = None) -> dict:
|
||||
}
|
||||
|
||||
|
||||
async def _call_anthropic_api(messages: list[dict], max_tokens: int = 4096, temperature: float = 0.2) -> str:
|
||||
"""Call Anthropic Claude API messages endpoint (non-blocking).
|
||||
async def _call_pplx_api(messages: list[dict], max_tokens: int = 4096, temperature: float = 0.2) -> str:
|
||||
"""Call Perplexity API chat/completions endpoint (non-blocking).
|
||||
Uses httpx.AsyncClient so the uvicorn event loop is never stalled.
|
||||
Returns the assistant message content.
|
||||
"""
|
||||
from coach.config import DECK_GEN_PROVIDER, DECK_GEN_BASE_URL, DECK_GEN_MODEL, ANTHROPIC_MODEL
|
||||
from coach.config import DECK_GEN_PROVIDER, DECK_GEN_BASE_URL, DECK_GEN_MODEL
|
||||
|
||||
if DECK_GEN_PROVIDER == 'local':
|
||||
base_url = DECK_GEN_BASE_URL
|
||||
model = DECK_GEN_MODEL
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
else:
|
||||
if not CFG.anthropic_api_key:
|
||||
raise HTTPException(400, 'Anthropic Claude API key not configured. Set anthropic_api_key env var or --anthropic-key.')
|
||||
base_url = 'https://api.anthropic.com'
|
||||
model = ANTHROPIC_MODEL
|
||||
headers = {
|
||||
if not CFG.pplx_api_key:
|
||||
raise HTTPException(400, 'Perplexity API key not configured. Set PPLX_API_KEY env var or --pplx-key.')
|
||||
base_url = 'https://api.perplexity.ai'
|
||||
model = 'sonar'
|
||||
headers = {
|
||||
'Content-Type': 'application/json',
|
||||
'x-api-key': CFG.anthropic_api_key, 'anthropic-version': '2023-06-01',
|
||||
}
|
||||
# Separate system messages for Anthropic API format
|
||||
system_msgs = [m['content'] for m in messages if m.get('role') == 'system']
|
||||
user_msgs = [m for m in messages if m.get('role') != 'system']
|
||||
system_text = '\n'.join(system_msgs) if system_msgs else None
|
||||
|
||||
|
||||
'Authorization': f'Bearer {CFG.pplx_api_key}',
|
||||
}
|
||||
payload = {
|
||||
'model': model,
|
||||
'messages': user_msgs,
|
||||
'messages': messages,
|
||||
'max_tokens': max_tokens,
|
||||
'temperature': temperature,
|
||||
}
|
||||
if system_text:
|
||||
payload['system'] = system_text
|
||||
try:
|
||||
async with httpx.AsyncClient(timeout=120.0) as client:
|
||||
resp = await client.post(
|
||||
f'{base_url}/v1/messages',
|
||||
f'{base_url}/chat/completions',
|
||||
json=payload,
|
||||
headers=headers,
|
||||
)
|
||||
)
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
except httpx.HTTPStatusError as e:
|
||||
raise HTTPException(502, f'Anthropic Claude API returned {e.response.status_code}: {e.response.text[:200]}')
|
||||
raise HTTPException(502, f'Perplexity API returned {e.response.status_code}: {e.response.text[:200]}')
|
||||
except httpx.RequestError as e:
|
||||
raise HTTPException(502, f'Anthropic Claude API call failed: {e}')
|
||||
raise HTTPException(502, f'Perplexity API call failed: {e}')
|
||||
|
||||
content_blocks = data.get('content', [])
|
||||
if not content_blocks:
|
||||
raise HTTPException(502, 'Empty response from Anthropic Claude API')
|
||||
content = content_blocks[0].get('text', '')
|
||||
choices = data.get('choices', [])
|
||||
if not choices:
|
||||
raise HTTPException(502, 'Empty response from Perplexity API')
|
||||
content = choices[0].get('message', {}).get('content', '')
|
||||
usage = data.get('usage', {})
|
||||
log_pplx.debug(
|
||||
f'tokens: prompt={usage.get("input_tokens", "?")}, '
|
||||
f'completion={usage.get("output_tokens", "?")}, '
|
||||
f'tokens: prompt={usage.get("prompt_tokens", "?")}, '
|
||||
f'completion={usage.get("completion_tokens", "?")}, '
|
||||
f'model={data.get("model", "?")}'
|
||||
)
|
||||
return content
|
||||
@@ -1036,11 +947,11 @@ def _fill_basic_lands(cards: list[dict], color_identity: list[str] | None = None
|
||||
return non_basics
|
||||
|
||||
|
||||
# ── Research Endpoint ───────────────────────────────────────────────────
|
||||
# ── Research Endpoint ─────────────────────────────────────────
|
||||
|
||||
@router.post('/api/deck-research')
|
||||
async def deck_research(req: DeckResearchRequest):
|
||||
"""Analyze an existing deck using Anthropic Claude and suggest improvements."""
|
||||
"""Analyze an existing deck using Perplexity AI and suggest improvements."""
|
||||
conn = _get_db_conn()
|
||||
|
||||
# Load deck info
|
||||
@@ -1165,7 +1076,7 @@ DECKLIST ({len(card_rows)} cards):
|
||||
|
||||
Analyze EVERYTHING: the deck's identity, strategy, archetype, bracket level (1-4 per Commander Rules Committee), ALL synergy packages between cards, ALL win conditions, game plan by phase (early/mid/late), mana base health, every role gap. Suggest specific cuts with severity and specific adds with priority and synergy tags. For adds, prioritize cards from the COLLECTION SUMMARY when available."""
|
||||
|
||||
content = await _call_anthropic_api([
|
||||
content = await _call_pplx_api([
|
||||
{'role': 'system', 'content': system_msg},
|
||||
{'role': 'user', 'content': user_msg},
|
||||
], max_tokens=8192)
|
||||
@@ -1191,11 +1102,11 @@ Analyze EVERYTHING: the deck's identity, strategy, archetype, bracket level (1-4
|
||||
return analysis
|
||||
|
||||
|
||||
# ── Generate Endpoint ───────────────────────────────────────────────
|
||||
# ── Generate Endpoint ─────────────────────────────────────────
|
||||
|
||||
@router.post('/api/deck-generate')
|
||||
async def deck_generate_ai(req: DeckGenerateAIRequest):
|
||||
"""Generate a full 100-card Commander deck using Anthropic Claude."""
|
||||
"""Generate a full 100-card Commander deck using Perplexity AI."""
|
||||
commander = req.commander.strip()
|
||||
if not commander:
|
||||
raise HTTPException(400, 'Commander name is required')
|
||||
@@ -1275,7 +1186,7 @@ COLOR IDENTITY: {', '.join(color_identity) if color_identity else 'Unknown'}
|
||||
|
||||
Build the deck as JSON. Prioritize collection cards when they fit the strategy."""
|
||||
|
||||
content = await _call_anthropic_api([
|
||||
content = await _call_pplx_api([
|
||||
{'role': 'system', 'content': system_msg},
|
||||
{'role': 'user', 'content': user_msg},
|
||||
], max_tokens=8192, temperature=0.3)
|
||||
@@ -1302,16 +1213,16 @@ Build the deck as JSON. Prioritize collection cards when they fit the strategy."
|
||||
return result
|
||||
|
||||
|
||||
@router.get('/api/anthropic/status')
|
||||
async def anthropic_status():
|
||||
"""Check if Anthropic Claude API is configured."""
|
||||
@router.get('/api/pplx/status')
|
||||
async def pplx_status():
|
||||
"""Check if Perplexity API is configured."""
|
||||
return {
|
||||
'configured': bool(CFG.anthropic_api_key),
|
||||
'configured': bool(CFG.pplx_api_key),
|
||||
}
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# V3 Deck Generator (Anthropic Claude Structured Output)
|
||||
# V3 Deck Generator (Perplexity Structured Output)
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
@router.get('/api/deck/v3/status')
|
||||
@@ -1319,9 +1230,9 @@ async def deck_gen_v3_status():
|
||||
"""Check V3 deck generator status."""
|
||||
return {
|
||||
'initialized': _coach._deck_gen_v3 is not None,
|
||||
'anthropic_configured': bool(CFG.anthropic_api_key),
|
||||
'model': getattr(_coach._deck_gen_v3, 'model', getattr(getattr(_coach._deck_gen_v3, 'anthropic_client', None), 'model', 'ollama/gpt-oss:20b')) if _coach._deck_gen_v3 else None,
|
||||
'embeddings_loaded': False,
|
||||
'pplx_configured': bool(CFG.pplx_api_key),
|
||||
'model': getattr(_coach._deck_gen_v3, 'model', getattr(getattr(_coach._deck_gen_v3, 'pplx', None), 'model', 'ollama/gpt-oss:20b')) if _coach._deck_gen_v3 else None,
|
||||
'embeddings_loaded': False,
|
||||
'embedding_cards': 0,
|
||||
'error': _coach._deck_gen_v3_error,
|
||||
}
|
||||
@@ -1330,14 +1241,14 @@ async def deck_gen_v3_status():
|
||||
@router.post('/api/deck/v3/generate')
|
||||
async def deck_gen_v3_generate(req: DeckGenV3Request):
|
||||
"""
|
||||
V3 Deck Generation — Anthropic Claude Structured Output with Smart Substitution.
|
||||
V3 Deck Generation — Perplexity structured output with Smart Substitution.
|
||||
|
||||
Pipeline:
|
||||
1. Resolve commander via Scryfall
|
||||
2. Build collection summary from DB
|
||||
3. Call Anthropic Claude with JSON schema enforcement
|
||||
3. Call Perplexity Sonar with JSON schema enforcement
|
||||
4. Cross-reference cards with collection for ownership
|
||||
5. Run Smart Substitution (embedding + Anthropic fallback)
|
||||
5. Run Smart Substitution (embedding + Perplexity fallback)
|
||||
6. Return complete deck with substitution data
|
||||
"""
|
||||
if _coach._deck_gen_v3 is None:
|
||||
@@ -1378,9 +1289,6 @@ async def deck_gen_v3_generate(req: DeckGenV3Request):
|
||||
from coach.services.deck_generator import DeckGeneratorV3
|
||||
result['stats'] = DeckGeneratorV3._compute_stats(sub_result.cards)
|
||||
|
||||
# Cache result for export endpoints
|
||||
_v3_cache_put(_v3_cache_key(req), result)
|
||||
|
||||
return result
|
||||
|
||||
except ValueError as e:
|
||||
@@ -1498,20 +1406,17 @@ async def deck_gen_v3_export_csv(req: DeckGenV3Request):
|
||||
if _coach._deck_gen_v3 is None:
|
||||
raise HTTPException(503, 'V3 Deck Generator not initialized.')
|
||||
|
||||
_ck = _v3_cache_key(req)
|
||||
result = _v3_cache_get(_ck)
|
||||
if result is None:
|
||||
result = _coach._deck_gen_v3.generate_deck(
|
||||
commander_name=req.commander_name.strip(),
|
||||
strategy=req.strategy,
|
||||
target_bracket=req.target_bracket,
|
||||
budget_usd=req.budget_usd,
|
||||
budget_mode=req.budget_mode,
|
||||
omit_cards=req.omit_cards,
|
||||
use_collection=req.use_collection,
|
||||
model=req.model,
|
||||
)
|
||||
_v3_cache_put(_ck, result)
|
||||
result = _coach._deck_gen_v3.generate_deck(
|
||||
commander_name=req.commander_name.strip(),
|
||||
strategy=req.strategy,
|
||||
target_bracket=req.target_bracket,
|
||||
budget_usd=req.budget_usd,
|
||||
budget_mode=req.budget_mode,
|
||||
omit_cards=req.omit_cards,
|
||||
use_collection=req.use_collection,
|
||||
model=req.model,
|
||||
)
|
||||
|
||||
cards = result.get('cards', [])
|
||||
commander = result.get('commander', {})
|
||||
|
||||
@@ -1548,20 +1453,16 @@ async def deck_gen_v3_export_dck(req: DeckGenV3Request):
|
||||
if _coach._deck_gen_v3 is None:
|
||||
raise HTTPException(503, 'V3 Deck Generator not initialized.')
|
||||
|
||||
_ck = _v3_cache_key(req)
|
||||
result = _v3_cache_get(_ck)
|
||||
if result is None:
|
||||
result = _coach._deck_gen_v3.generate_deck(
|
||||
commander_name=req.commander_name.strip(),
|
||||
strategy=req.strategy,
|
||||
target_bracket=req.target_bracket,
|
||||
budget_usd=req.budget_usd,
|
||||
budget_mode=req.budget_mode,
|
||||
omit_cards=req.omit_cards,
|
||||
use_collection=req.use_collection,
|
||||
model=req.model,
|
||||
)
|
||||
_v3_cache_put(_ck, result)
|
||||
result = _coach._deck_gen_v3.generate_deck(
|
||||
commander_name=req.commander_name.strip(),
|
||||
strategy=req.strategy,
|
||||
target_bracket=req.target_bracket,
|
||||
budget_usd=req.budget_usd,
|
||||
budget_mode=req.budget_mode,
|
||||
omit_cards=req.omit_cards,
|
||||
use_collection=req.use_collection,
|
||||
model=req.model,
|
||||
)
|
||||
|
||||
cards = result.get('cards', [])
|
||||
commander = result.get('commander', {})
|
||||
@@ -1587,20 +1488,16 @@ async def deck_gen_v3_export_moxfield(req: DeckGenV3Request):
|
||||
if _coach._deck_gen_v3 is None:
|
||||
raise HTTPException(503, 'V3 Deck Generator not initialized.')
|
||||
|
||||
_ck = _v3_cache_key(req)
|
||||
result = _v3_cache_get(_ck)
|
||||
if result is None:
|
||||
result = _coach._deck_gen_v3.generate_deck(
|
||||
commander_name=req.commander_name.strip(),
|
||||
strategy=req.strategy,
|
||||
target_bracket=req.target_bracket,
|
||||
budget_usd=req.budget_usd,
|
||||
budget_mode=req.budget_mode,
|
||||
omit_cards=req.omit_cards,
|
||||
use_collection=req.use_collection,
|
||||
model=req.model,
|
||||
)
|
||||
_v3_cache_put(_ck, result)
|
||||
result = _coach._deck_gen_v3.generate_deck(
|
||||
commander_name=req.commander_name.strip(),
|
||||
strategy=req.strategy,
|
||||
target_bracket=req.target_bracket,
|
||||
budget_usd=req.budget_usd,
|
||||
budget_mode=req.budget_mode,
|
||||
omit_cards=req.omit_cards,
|
||||
use_collection=req.use_collection,
|
||||
model=req.model,
|
||||
)
|
||||
|
||||
cards = result.get('cards', [])
|
||||
commander = result.get('commander', {})
|
||||
@@ -1628,26 +1525,22 @@ async def deck_gen_v3_export_shopping(req: DeckGenV3Request):
|
||||
if _coach._deck_gen_v3 is None:
|
||||
raise HTTPException(503, 'V3 Deck Generator not initialized.')
|
||||
|
||||
_ck = _v3_cache_key(req)
|
||||
result = _v3_cache_get(_ck)
|
||||
if result is None:
|
||||
result = _coach._deck_gen_v3.generate_deck(
|
||||
commander_name=req.commander_name.strip(),
|
||||
strategy=req.strategy,
|
||||
target_bracket=req.target_bracket,
|
||||
budget_usd=req.budget_usd,
|
||||
budget_mode=req.budget_mode,
|
||||
omit_cards=req.omit_cards,
|
||||
use_collection=req.use_collection,
|
||||
model=req.model,
|
||||
)
|
||||
_v3_cache_put(_ck, result)
|
||||
result = _coach._deck_gen_v3.generate_deck(
|
||||
commander_name=req.commander_name.strip(),
|
||||
strategy=req.strategy,
|
||||
target_bracket=req.target_bracket,
|
||||
budget_usd=req.budget_usd,
|
||||
budget_mode=req.budget_mode,
|
||||
omit_cards=req.omit_cards,
|
||||
use_collection=req.use_collection,
|
||||
model=req.model,
|
||||
)
|
||||
|
||||
cards = result.get('cards', [])
|
||||
shopping = []
|
||||
total = 0.0
|
||||
for card in cards:
|
||||
if not card.get('from_collection', False) and card.get('status') != 'substituted':
|
||||
if not card.get('owned', True) and card.get('status') != 'substituted':
|
||||
price = card.get('estimated_price_usd', 0)
|
||||
shopping.append({
|
||||
'name': card.get('name', ''),
|
||||
@@ -1664,3 +1557,5 @@ async def deck_gen_v3_export_shopping(req: DeckGenV3Request):
|
||||
'total_missing': len(shopping),
|
||||
'estimated_cost_usd': round(total, 2),
|
||||
}
|
||||
|
||||
|
||||
+69
-40
@@ -28,18 +28,22 @@ from fastapi import APIRouter, HTTPException
|
||||
from fastapi import Request as FastAPIRequest
|
||||
from fastapi.responses import JSONResponse
|
||||
|
||||
from models.state import CFG
|
||||
from services.database import _get_db_conn
|
||||
from services.forge_runner import _get_deepseek_brain
|
||||
from services.logging import log_sim, _ml_logging_enabled
|
||||
from routes.shared import (
|
||||
CFG, log_sim,
|
||||
_get_db_conn,
|
||||
_get_deepseek_brain,
|
||||
_ml_logging_enabled,
|
||||
)
|
||||
from commander_ai_lab.sim.validator_brain import ValidatorBrain, ValidatorConfig
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter(tags=["deepseek"])
|
||||
|
||||
# In-memory store for simulation runs
|
||||
_sim_runs = {} # sim_id -> { status, result, error }
|
||||
_sim_lock = _threading.Lock()
|
||||
|
||||
# ── Validator singleton ──
|
||||
_validator_brain: ValidatorBrain | None = None
|
||||
_validator_lock = _threading.Lock()
|
||||
|
||||
@@ -52,18 +56,22 @@ def _get_validator_brain() -> ValidatorBrain | None:
|
||||
if _validator_brain is None:
|
||||
cfg = ValidatorConfig(
|
||||
api_base=os.environ.get("VALIDATOR_API_BASE", "http://localhost:11434"),
|
||||
model=os.environ.get("VALIDATOR_MODEL", "deepseek-r1:8b"),
|
||||
model=os.environ.get("VALIDATOR_MODEL", "deepseek-r1:14b"),
|
||||
max_tokens=int(os.environ.get("VALIDATOR_MAX_TOKENS", "2048")),
|
||||
request_timeout=float(os.environ.get("VALIDATOR_TIMEOUT", "300.0")),
|
||||
request_timeout=float(os.environ.get("VALIDATOR_TIMEOUT", "120.0")),
|
||||
)
|
||||
_validator_brain = ValidatorBrain(cfg)
|
||||
return _validator_brain
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Shared Helpers (extracted to deduplicate sim threads — #42)
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
_SRC_PATH_ADDED = False
|
||||
|
||||
|
||||
def _ensure_src_path():
|
||||
"""Add project src/ to sys.path once."""
|
||||
global _SRC_PATH_ADDED
|
||||
if not _SRC_PATH_ADDED:
|
||||
src_dir = str(Path(__file__).resolve().parent.parent / 'src')
|
||||
@@ -120,6 +128,7 @@ def _run_game_loop(engine, deck_a, deck_b, deck_name, opponent_name,
|
||||
|
||||
for i in range(num_games):
|
||||
kw = dict(run_kwargs)
|
||||
# DeepSeek engine needs per-game IDs
|
||||
if 'game_id_prefix' in kw:
|
||||
prefix = kw.pop('game_id_prefix')
|
||||
kw['game_id'] = f'{prefix}-g{i+1}'
|
||||
@@ -127,6 +136,7 @@ def _run_game_loop(engine, deck_a, deck_b, deck_name, opponent_name,
|
||||
name_b=opponent_name, **kw)
|
||||
game_data = result.to_dict()
|
||||
game_data['gameNumber'] = i + 1
|
||||
# Phase 8: Surface player_explanation from validation in turn log
|
||||
for turn_entry in game_data.get('log', []):
|
||||
v = turn_entry.get('validation')
|
||||
if isinstance(v, dict) and v.get('player_explanation'):
|
||||
@@ -170,6 +180,7 @@ def _run_game_loop(engine, deck_a, deck_b, deck_name, opponent_name,
|
||||
|
||||
def _build_summary(stats: dict, deck_name: str, opponent_name: str,
|
||||
num_games: int, elapsed: float, **extra) -> dict:
|
||||
"""Build the JSON-serialisable summary dict from accumulated stats."""
|
||||
n = num_games
|
||||
summary = {
|
||||
'deckName': deck_name,
|
||||
@@ -199,6 +210,7 @@ def _finish_sim(sim_id, summary, game_results, engine=None):
|
||||
_sim_runs[sim_id]['status'] = 'complete'
|
||||
_sim_runs[sim_id]['result'] = {'summary': summary, 'games': game_results}
|
||||
|
||||
# --- Persist batch-*.json for coach / training dashboard ---
|
||||
try:
|
||||
deck_name = summary.get('deckName', 'Unknown')
|
||||
opponent_name = summary.get('opponentName', 'Training Deck')
|
||||
@@ -225,11 +237,12 @@ def _finish_sim(sim_id, summary, game_results, engine=None):
|
||||
}
|
||||
results_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'results')
|
||||
os.makedirs(results_dir, exist_ok=True)
|
||||
batch_path = os.path.join(results_dir, f'ml-decision-sim-{sim_id}.json')
|
||||
batch_path = os.path.join(results_dir, f'batch-sim-{sim_id}.json')
|
||||
with open(batch_path, 'w') as f:
|
||||
json.dump(batch_data, f, indent=2, default=str)
|
||||
logger.info(f'Saved batch results to {batch_path}')
|
||||
|
||||
# Auto-generate deck report for training dashboard / coach
|
||||
try:
|
||||
from coach.report_generator import generate_deck_reports
|
||||
reports_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'deck-reports')
|
||||
@@ -243,6 +256,7 @@ def _finish_sim(sim_id, summary, game_results, engine=None):
|
||||
except Exception as e:
|
||||
logger.error(f'Failed to persist sim results: {e}')
|
||||
|
||||
# --- Flush ML decisions JSONL for training pipeline ---
|
||||
if engine is not None and hasattr(engine, 'flush_ml_decisions'):
|
||||
ml_decisions = engine.flush_ml_decisions()
|
||||
if ml_decisions:
|
||||
@@ -252,16 +266,20 @@ def _finish_sim(sim_id, summary, game_results, engine=None):
|
||||
for dec in ml_decisions:
|
||||
mf.write(json.dumps(dec) + '\n')
|
||||
logger.info(f'Wrote {len(ml_decisions)} ML decisions to {ml_path}')
|
||||
|
||||
|
||||
|
||||
def _fail_sim(sim_id, error):
|
||||
"""Mark a sim run as errored."""
|
||||
with _sim_lock:
|
||||
_sim_runs[sim_id]['status'] = 'error'
|
||||
_sim_runs[sim_id]['error'] = str(error)
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Background Sim Threads (now thin wrappers around shared helpers)
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
def _run_sim_thread(sim_id: str, decklist: list, num_games: int,
|
||||
deck_name: str, record_logs: bool):
|
||||
"""Background thread: basic Monte Carlo sim from a raw decklist."""
|
||||
try:
|
||||
_ensure_src_path()
|
||||
from commander_ai_lab.sim.engine import GameEngine
|
||||
@@ -288,6 +306,7 @@ def _run_sim_thread(sim_id: str, decklist: list, num_games: int,
|
||||
|
||||
def _run_sim_thread_v2(sim_id: str, card_data: list[dict], num_games: int,
|
||||
deck_name: str, record_logs: bool):
|
||||
"""Background thread: sim with full card data from the DB."""
|
||||
try:
|
||||
_ensure_src_path()
|
||||
from commander_ai_lab.sim.engine import GameEngine
|
||||
@@ -315,6 +334,7 @@ def _run_sim_thread_v2(sim_id: str, card_data: list[dict], num_games: int,
|
||||
def _run_sim_thread_deepseek(sim_id: str, card_data: list[dict],
|
||||
num_games: int, deck_name: str,
|
||||
record_logs: bool):
|
||||
"""Background thread: sim using DeepSeek AI opponent."""
|
||||
try:
|
||||
_ensure_src_path()
|
||||
from commander_ai_lab.sim.deepseek_engine import DeepSeekGameEngine
|
||||
@@ -330,7 +350,7 @@ def _run_sim_thread_deepseek(sim_id: str, card_data: list[dict],
|
||||
if brain and not brain._connected:
|
||||
brain.check_connection()
|
||||
|
||||
validator = _get_validator_brain()
|
||||
validator = _get_validator_brain() # None if disabled
|
||||
engine = DeepSeekGameEngine(
|
||||
brain=brain, ai_player_index=1,
|
||||
max_turns=25, record_log=record_logs, ml_log=True,
|
||||
@@ -342,37 +362,34 @@ def _run_sim_thread_deepseek(sim_id: str, card_data: list[dict],
|
||||
game_id_prefix=f'ds-sim-{sim_id[:8]}',
|
||||
archetype='midrange')
|
||||
|
||||
# Write ML decision JSONL for training pipeline
|
||||
ml_decisions = engine.flush_ml_decisions()
|
||||
if ml_decisions and brain and brain._connected:
|
||||
if ml_decisions:
|
||||
ml_path = os.path.join('results',
|
||||
f'ml-decisions-sim-{sim_id[:8]}.jsonl')
|
||||
os.makedirs('results', exist_ok=True)
|
||||
with open(ml_path, 'w', encoding='utf-8') as mf:
|
||||
for dec in ml_decisions:
|
||||
mf.write(json.dumps(dec) + '\n')
|
||||
logger.info(f'[ML Data] Wrote {len(ml_decisions)} decision snapshots to {ml_path}')
|
||||
elif ml_decisions and (not brain or not brain._connected):
|
||||
logger.warning(
|
||||
f'[ML Data] Skipping {len(ml_decisions)} snapshots for sim {sim_id} — '
|
||||
f'brain not connected, all actions are heuristic fallback '
|
||||
f'(not useful for supervised training)'
|
||||
)
|
||||
else:
|
||||
logger.warning(f'[ML Data] No decision snapshots captured for sim {sim_id} (0 decisions)')
|
||||
|
||||
ds_stats = brain.get_stats() if brain else {}
|
||||
summary = _build_summary(
|
||||
stats, deck_name, 'DeepSeek AI', num_games, elapsed,
|
||||
opponentType='deepseek', deepseekStats=ds_stats)
|
||||
_finish_sim(sim_id, summary, game_results, engine=None)
|
||||
_finish_sim(sim_id, summary, game_results, engine=engine)
|
||||
except Exception as e:
|
||||
_fail_sim(sim_id, e)
|
||||
traceback.print_exc()
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# N-Player Sim Thread
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
def _run_sim_thread_n_player(sim_id: str, decks_data: list[list[dict]],
|
||||
deck_names: list[str], num_games: int,
|
||||
record_logs: bool, engine_type: str):
|
||||
"""Background thread: N-player (2-4) batch simulation."""
|
||||
try:
|
||||
_ensure_src_path()
|
||||
from commander_ai_lab.sim.engine import GameEngine
|
||||
@@ -394,6 +411,7 @@ def _run_sim_thread_n_player(sim_id: str, decks_data: list[list[dict]],
|
||||
else:
|
||||
engine = GameEngine(max_turns=25, record_log=record_logs, ml_log=True)
|
||||
|
||||
# Per-seat accumulators
|
||||
seat_wins = [0] * n_players
|
||||
seat_turns = [0] * n_players
|
||||
seat_damage_dealt = [0] * n_players
|
||||
@@ -463,7 +481,13 @@ def _run_sim_thread_n_player(sim_id: str, decks_data: list[list[dict]],
|
||||
traceback.print_exc()
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Simulation API Endpoints
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
def _create_sim_run(num_games, deck_name):
|
||||
"""Create a queued sim run entry and return its ID."""
|
||||
sim_id = str(_uuid.uuid4())[:8]
|
||||
with _sim_lock:
|
||||
_sim_runs[sim_id] = {
|
||||
@@ -485,42 +509,31 @@ def _fetch_deck_card_data(deck_id):
|
||||
deck_name = row[0]
|
||||
cur.execute("""
|
||||
SELECT dc.card_name, dc.quantity,
|
||||
COALESCE(ce.type_line, cr.type_line, '') as type_line,
|
||||
COALESCE(ce.cmc, cr.cmc, 0) as cmc,
|
||||
ce.power, ce.toughness,
|
||||
COALESCE(ce.oracle_text, cr.oracle_text, '') as oracle_text,
|
||||
COALESCE(ce.keywords, cr.keywords, '') as keywords,
|
||||
COALESCE(ce.mana_cost, '') as mana_cost
|
||||
ce.type_line, ce.cmc, ce.power, ce.toughness,
|
||||
ce.oracle_text, ce.keywords, ce.mana_cost
|
||||
FROM deck_cards dc
|
||||
LEFT JOIN (
|
||||
SELECT scryfall_id, type_line, cmc, power, toughness,
|
||||
oracle_text, keywords, mana_cost
|
||||
FROM collection_entries GROUP BY scryfall_id
|
||||
) ce ON ce.scryfall_id = dc.scryfall_id
|
||||
LEFT JOIN (
|
||||
SELECT name, type_line, cmc, oracle_text, keywords
|
||||
FROM card_records GROUP BY name
|
||||
) cr ON cr.name = dc.card_name
|
||||
WHERE dc.deck_id = ?
|
||||
""", (deck_id,))
|
||||
card_data = []
|
||||
for r in cur.fetchall():
|
||||
for _ in range(r[1] or 1):
|
||||
card_data.append({
|
||||
'name': r[0],
|
||||
'type_line': r[2] or '',
|
||||
'cmc': r[3] or 0,
|
||||
'power': r[4] or '',
|
||||
'toughness': r[5] or '',
|
||||
'oracle_text': r[6] or '',
|
||||
'keywords': r[7] or '',
|
||||
'mana_cost': r[8] or '',
|
||||
'name': r[0], 'type_line': r[2] or '',
|
||||
'cmc': r[3] or 0, 'power': r[4] or '',
|
||||
'toughness': r[5] or '', 'oracle_text': r[6] or '',
|
||||
'keywords': r[7] or '', 'mana_cost': r[8] or '',
|
||||
})
|
||||
return deck_name, card_data
|
||||
|
||||
|
||||
@router.post('/api/sim/run')
|
||||
async def sim_run(request: FastAPIRequest):
|
||||
"""Start a Monte Carlo simulation with the Python engine."""
|
||||
body = await request.json()
|
||||
decklist = body.get('decklist', [])
|
||||
num_games = body.get('numGames', 10)
|
||||
@@ -541,6 +554,7 @@ async def sim_run(request: FastAPIRequest):
|
||||
|
||||
@router.get('/api/sim/status')
|
||||
async def sim_status(simId: str):
|
||||
"""Poll simulation progress."""
|
||||
with _sim_lock:
|
||||
run = _sim_runs.get(simId)
|
||||
if not run:
|
||||
@@ -554,6 +568,7 @@ async def sim_status(simId: str):
|
||||
|
||||
@router.get('/api/sim/result')
|
||||
async def sim_result(simId: str):
|
||||
"""Get completed simulation results."""
|
||||
with _sim_lock:
|
||||
run = _sim_runs.get(simId)
|
||||
if not run:
|
||||
@@ -566,6 +581,7 @@ async def sim_result(simId: str):
|
||||
|
||||
@router.post('/api/sim/run-from-deck')
|
||||
async def sim_run_from_deck(request: FastAPIRequest):
|
||||
"""Start simulation using a deck from the Deck Builder (by deck ID)."""
|
||||
body = await request.json()
|
||||
deck_id = body.get('deckId')
|
||||
num_games = body.get('numGames', 10)
|
||||
@@ -590,6 +606,7 @@ async def sim_run_from_deck(request: FastAPIRequest):
|
||||
|
||||
@router.post('/api/sim/run-deepseek')
|
||||
async def sim_run_deepseek(request: FastAPIRequest):
|
||||
"""Start simulation using DeepSeek AI as the opponent brain."""
|
||||
body = await request.json()
|
||||
deck_id = body.get('deckId')
|
||||
num_games = body.get('numGames', 5)
|
||||
@@ -618,6 +635,7 @@ async def sim_run_deepseek(request: FastAPIRequest):
|
||||
|
||||
@router.post('/api/sim/run-n-player')
|
||||
async def sim_run_n_player(request: FastAPIRequest):
|
||||
"""Start an N-player (2-4) batch simulation."""
|
||||
body = await request.json()
|
||||
deck_ids = body.get('deckIds', [])
|
||||
num_games = body.get('numGames', 10)
|
||||
@@ -651,8 +669,14 @@ async def sim_run_n_player(request: FastAPIRequest):
|
||||
})
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# DeepSeek AI Brain Endpoints
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
@router.post('/api/deepseek/connect')
|
||||
async def deepseek_connect(request: FastAPIRequest):
|
||||
"""Test connection to the DeepSeek LLM endpoint and auto-detect model."""
|
||||
body = await request.json() if await request.body() else {}
|
||||
api_base = body.get('apiBase', None)
|
||||
model = body.get('model', None)
|
||||
@@ -678,6 +702,7 @@ async def deepseek_connect(request: FastAPIRequest):
|
||||
|
||||
@router.get('/api/deepseek/status')
|
||||
async def deepseek_status():
|
||||
"""Get DeepSeek brain status and performance stats."""
|
||||
brain = _get_deepseek_brain()
|
||||
if brain is None:
|
||||
return JSONResponse({'connected': False, 'error': 'Brain not initialized'})
|
||||
@@ -686,6 +711,7 @@ async def deepseek_status():
|
||||
|
||||
@router.post('/api/deepseek/configure')
|
||||
async def deepseek_configure(request: FastAPIRequest):
|
||||
"""Update DeepSeek configuration at runtime."""
|
||||
body = await request.json()
|
||||
brain = _get_deepseek_brain()
|
||||
if brain is None:
|
||||
@@ -726,6 +752,7 @@ async def deepseek_configure(request: FastAPIRequest):
|
||||
|
||||
@router.get('/api/deepseek/logs')
|
||||
async def deepseek_logs():
|
||||
"""Get decision log stats and flush pending entries."""
|
||||
brain = _get_deepseek_brain()
|
||||
if brain is None:
|
||||
return JSONResponse({'error': 'Brain not initialized'}, status_code=500)
|
||||
@@ -756,10 +783,11 @@ async def deepseek_logs():
|
||||
'flushedPath': flushed_path,
|
||||
'logFiles': log_files[-20:],
|
||||
})
|
||||
|
||||
|
||||
|
||||
@router.get("/api/validator/status")
|
||||
async def validator_status():
|
||||
"""Get DeepSeek-R1-14B validator brain status."""
|
||||
v = _get_validator_brain()
|
||||
if v is None:
|
||||
return JSONResponse({"enabled": False,
|
||||
@@ -769,6 +797,7 @@ async def validator_status():
|
||||
|
||||
@router.post("/api/validator/configure")
|
||||
async def validator_configure(request: FastAPIRequest):
|
||||
"""Update validator configuration at runtime."""
|
||||
body = await request.json()
|
||||
v = _get_validator_brain()
|
||||
if v is None:
|
||||
|
||||
-209
@@ -1,209 +0,0 @@
|
||||
"""Live game session routes.
|
||||
|
||||
Endpoints:
|
||||
POST /api/game/start — create a new live game session (called by LobbySetupModal)
|
||||
POST /api/game/action — submit a human player action (called by HumanActionBar)
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import uuid
|
||||
from typing import List, Optional
|
||||
|
||||
from fastapi import APIRouter, HTTPException
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
log = logging.getLogger("routes.game")
|
||||
|
||||
router = APIRouter(tags=["game"])
|
||||
|
||||
|
||||
# ───────────────────────────────────────────────────────────────
|
||||
# Request / Response models
|
||||
# ───────────────────────────────────────────────────────────────
|
||||
|
||||
class SeatConfig(BaseModel):
|
||||
seat_index: int = 0
|
||||
seat_type: str = "AI" # "Human" | "AI Aggro" | "AI Control" | "AI Combo" | "AI Political"
|
||||
deck_name: str = ""
|
||||
player_name: str = ""
|
||||
|
||||
|
||||
class StartGameRequest(BaseModel):
|
||||
seats: List[SeatConfig] = Field(default_factory=list)
|
||||
|
||||
|
||||
class StartGameResponse(BaseModel):
|
||||
game_id: str
|
||||
status: str = "started"
|
||||
ws_url: str
|
||||
|
||||
|
||||
class GameActionRequest(BaseModel):
|
||||
game_id: str
|
||||
seat: int = 0
|
||||
action: str # "pass_priority" | "end_turn" | "declare_attackers" |
|
||||
# "declare_blockers" | "select_target"
|
||||
target_id: Optional[str] = None
|
||||
extra: dict = Field(default_factory=dict)
|
||||
|
||||
|
||||
class GameActionResponse(BaseModel):
|
||||
status: str = "ok"
|
||||
game_id: str
|
||||
action: str
|
||||
|
||||
|
||||
# ───────────────────────────────────────────────────────────────
|
||||
# In-memory session store (replace with DB / Redis for persistence)
|
||||
# ───────────────────────────────────────────────────────────────
|
||||
|
||||
# { game_id: { "seats": [...], "status": "active" | "ended", "pending_actions": [...] } }
|
||||
_sessions: dict[str, dict] = {}
|
||||
|
||||
|
||||
# ───────────────────────────────────────────────────────────────
|
||||
# POST /api/game/start
|
||||
# ───────────────────────────────────────────────────────────────
|
||||
|
||||
@router.post("/api/game/start", response_model=StartGameResponse)
|
||||
async def start_game(req: StartGameRequest):
|
||||
"""Create a new live game session.
|
||||
|
||||
Called by Unity's LobbySetupModal after the player configures seats.
|
||||
Returns a game_id that Unity uses to connect to the WebSocket at
|
||||
/ws/game/{game_id}.
|
||||
|
||||
TODO: Wire Forge engine launch here once the IPC layer is ready.
|
||||
For now, creates a session record and returns the game_id so Unity
|
||||
can connect and receive state pushes from the Forge IPC client.
|
||||
"""
|
||||
if not req.seats:
|
||||
raise HTTPException(status_code=400, detail="At least one seat is required.")
|
||||
|
||||
game_id = uuid.uuid4().hex
|
||||
|
||||
_sessions[game_id] = {
|
||||
"game_id": game_id,
|
||||
"seats": [s.dict() for s in req.seats],
|
||||
"status": "active",
|
||||
"pending_actions": [],
|
||||
}
|
||||
|
||||
log.info(
|
||||
"Game session created: game_id=%s seats=%d",
|
||||
game_id,
|
||||
len(req.seats),
|
||||
)
|
||||
|
||||
return StartGameResponse(
|
||||
game_id=game_id,
|
||||
status="started",
|
||||
ws_url=f"/ws/game/{game_id}",
|
||||
)
|
||||
|
||||
|
||||
# ───────────────────────────────────────────────────────────────
|
||||
# POST /api/game/action
|
||||
# ───────────────────────────────────────────────────────────────
|
||||
|
||||
@router.post("/api/game/action", response_model=GameActionResponse)
|
||||
async def game_action(req: GameActionRequest):
|
||||
"""Submit a human player action during a live game.
|
||||
|
||||
Called by Unity's HumanActionBar when seat 0 (human) has priority.
|
||||
The action is queued in the session's pending_actions list, where
|
||||
the Forge IPC polling loop will pick it up.
|
||||
|
||||
Valid actions:
|
||||
pass_priority — pass priority to the next player
|
||||
end_turn — end the current turn
|
||||
declare_attackers — declare attacking creatures
|
||||
declare_blockers — declare blocking creatures
|
||||
select_target — select a target (requires target_id)
|
||||
"""
|
||||
valid_actions = {
|
||||
"pass_priority", "end_turn",
|
||||
"declare_attackers", "declare_blockers",
|
||||
"select_target",
|
||||
}
|
||||
|
||||
if req.action not in valid_actions:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail=f"Unknown action '{req.action}'. Valid: {sorted(valid_actions)}",
|
||||
)
|
||||
|
||||
if req.action == "select_target" and not req.target_id:
|
||||
raise HTTPException(
|
||||
status_code=400,
|
||||
detail="select_target requires a target_id.",
|
||||
)
|
||||
|
||||
session = _sessions.get(req.game_id)
|
||||
if session is None:
|
||||
raise HTTPException(
|
||||
status_code=404,
|
||||
detail=f"Game session '{req.game_id}' not found.",
|
||||
)
|
||||
|
||||
if session["status"] != "active":
|
||||
raise HTTPException(
|
||||
status_code=409,
|
||||
detail=f"Game session '{req.game_id}' is not active (status={session['status']}).",
|
||||
)
|
||||
|
||||
action_record = {
|
||||
"seat": req.seat,
|
||||
"action": req.action,
|
||||
"target_id": req.target_id,
|
||||
"extra": req.extra,
|
||||
}
|
||||
session["pending_actions"].append(action_record)
|
||||
|
||||
log.info(
|
||||
"Action queued: game_id=%s seat=%d action=%s",
|
||||
req.game_id, req.seat, req.action,
|
||||
)
|
||||
|
||||
return GameActionResponse(
|
||||
status="ok",
|
||||
game_id=req.game_id,
|
||||
action=req.action,
|
||||
)
|
||||
|
||||
|
||||
# ───────────────────────────────────────────────────────────────
|
||||
# GET /api/game/{game_id}/actions (Forge IPC polling endpoint)
|
||||
# ───────────────────────────────────────────────────────────────
|
||||
|
||||
@router.get("/api/game/{game_id}/actions")
|
||||
async def poll_actions(game_id: str):
|
||||
"""Drain and return all pending human actions for a game session.
|
||||
|
||||
Called by the Forge IPC polling loop to consume human player decisions.
|
||||
Clears the queue on each call (consume-once semantics).
|
||||
"""
|
||||
session = _sessions.get(game_id)
|
||||
if session is None:
|
||||
raise HTTPException(status_code=404, detail=f"Game session '{game_id}' not found.")
|
||||
|
||||
actions = session["pending_actions"].copy()
|
||||
session["pending_actions"].clear()
|
||||
return {"game_id": game_id, "actions": actions}
|
||||
|
||||
|
||||
# ───────────────────────────────────────────────────────────────
|
||||
# GET /api/game/sessions (debug)
|
||||
# ───────────────────────────────────────────────────────────────
|
||||
|
||||
@router.get("/api/game/sessions")
|
||||
async def list_sessions():
|
||||
"""List active game sessions (debug endpoint)."""
|
||||
return {
|
||||
"count": len(_sessions),
|
||||
"sessions": [
|
||||
{"game_id": gid, "status": s["status"], "seats": len(s["seats"])}
|
||||
for gid, s in _sessions.items()
|
||||
],
|
||||
}
|
||||
+11
-7
@@ -15,13 +15,17 @@ from typing import Optional
|
||||
from fastapi import APIRouter, HTTPException, BackgroundTasks
|
||||
from fastapi.responses import JSONResponse
|
||||
|
||||
from models.state import COMMANDER_META
|
||||
from models.requests import ImportUrlRequest, ImportTextRequest, MetaFetchRequest
|
||||
from services.import_helpers import (
|
||||
_import_from_url, _parse_text_decklist, _save_profile_to_dck,
|
||||
import routes.shared as _shared
|
||||
from routes.shared import (
|
||||
ImportUrlRequest,
|
||||
ImportTextRequest,
|
||||
MetaFetchRequest,
|
||||
_import_from_url,
|
||||
_parse_text_decklist,
|
||||
_save_profile_to_dck,
|
||||
_fetch_edhrec_average,
|
||||
log,
|
||||
)
|
||||
from services.logging import log
|
||||
|
||||
router = APIRouter(tags=["import"])
|
||||
|
||||
@@ -70,7 +74,7 @@ async def import_from_text(req: ImportTextRequest):
|
||||
async def list_meta_commanders():
|
||||
"""List available commanders in the meta mapping."""
|
||||
commanders = []
|
||||
for name, entries in COMMANDER_META.items():
|
||||
for name, entries in _shared.COMMANDER_META.items():
|
||||
entry = entries[0] if entries else {}
|
||||
commanders.append({
|
||||
"name": name,
|
||||
@@ -86,7 +90,7 @@ async def search_meta_commanders(q: str = ""):
|
||||
"""Search commanders by partial name match."""
|
||||
query = q.lower()
|
||||
matches = []
|
||||
for name, entries in COMMANDER_META.items():
|
||||
for name, entries in _shared.COMMANDER_META.items():
|
||||
if query in name.lower():
|
||||
entry = entries[0] if entries else {}
|
||||
matches.append({
|
||||
|
||||
+21
-13
@@ -31,15 +31,23 @@ from typing import Optional
|
||||
from fastapi import APIRouter, HTTPException, BackgroundTasks, Request as FastAPIRequest
|
||||
from fastapi.responses import JSONResponse
|
||||
|
||||
from models.state import CFG, active_batches, BatchState, AI_PROFILES
|
||||
from models.requests import StartRequest
|
||||
from models.responses import StartResponse, StatusResponse
|
||||
from services.database import _get_db_conn
|
||||
from services.deck_service import parse_dck_file, _load_deck_cards_by_name
|
||||
from services.forge_runner import (
|
||||
build_java_command, run_batch_subprocess, _run_deepseek_batch_thread,
|
||||
from routes.shared import (
|
||||
CFG,
|
||||
active_batches,
|
||||
BatchState,
|
||||
StartRequest,
|
||||
StartResponse,
|
||||
StatusResponse,
|
||||
AI_PROFILES,
|
||||
build_java_command,
|
||||
run_batch_subprocess,
|
||||
_run_deepseek_batch_thread,
|
||||
parse_dck_file,
|
||||
_get_db_conn,
|
||||
_load_deck_cards_by_name,
|
||||
log,
|
||||
log_batch,
|
||||
)
|
||||
from services.logging import log, log_batch
|
||||
|
||||
router = APIRouter(tags=["lab"])
|
||||
|
||||
@@ -66,8 +74,8 @@ async def start_batch(req: StartRequest, background_tasks: BackgroundTasks):
|
||||
raise HTTPException(400, f"All {len(req.decks)} deck slots must be filled")
|
||||
if req.numGames < 1 or req.numGames > 10000:
|
||||
raise HTTPException(400, "numGames must be 1-10000")
|
||||
if req.threads < 1 or req.threads > 32:
|
||||
raise HTTPException(400, "threads must be 1-32")
|
||||
if req.threads < 1 or req.threads > 16:
|
||||
raise HTTPException(400, "threads must be 1-16")
|
||||
|
||||
if not os.path.exists(CFG.forge_jar):
|
||||
raise HTTPException(500, f"Forge JAR not found: {CFG.forge_jar}")
|
||||
@@ -79,7 +87,7 @@ async def start_batch(req: StartRequest, background_tasks: BackgroundTasks):
|
||||
active_batches[batch_id] = state
|
||||
|
||||
os.makedirs(CFG.results_dir, exist_ok=True)
|
||||
output_path = os.path.join(CFG.results_dir, f"ml-decision-{batch_id}.json")
|
||||
output_path = os.path.join(CFG.results_dir, f"batch-{batch_id}.json")
|
||||
state.result_path = output_path
|
||||
|
||||
# Auto-export deckbuilder decks to .dck if not already exported
|
||||
@@ -242,7 +250,7 @@ async def list_history():
|
||||
if not results_dir.exists():
|
||||
return {"results": []}
|
||||
results = []
|
||||
for f in sorted(results_dir.glob("ml-decision-*.json"), reverse=True):
|
||||
for f in sorted(results_dir.glob("batch-*.json"), reverse=True):
|
||||
try:
|
||||
with open(f, "r", encoding="utf-8") as fh:
|
||||
data = json.load(fh)
|
||||
@@ -375,7 +383,7 @@ async def get_deck_trends(deck_name: str):
|
||||
if not results_dir.exists():
|
||||
return {"deckName": deck_name, "history": []}
|
||||
history = []
|
||||
for f in sorted(results_dir.glob("ml-decision-*.json")):
|
||||
for f in sorted(results_dir.glob("batch-*.json")):
|
||||
try:
|
||||
with open(f, "r", encoding="utf-8") as fh:
|
||||
data = json.load(fh)
|
||||
|
||||
+14
-148
@@ -32,8 +32,7 @@ from pathlib import Path
|
||||
|
||||
from fastapi import APIRouter, HTTPException, Request as FastAPIRequest
|
||||
|
||||
from models.state import CFG
|
||||
from services.logging import _ml_logging_enabled
|
||||
from routes.shared import CFG, _ml_logging_enabled
|
||||
|
||||
log_ml = logging.getLogger("commander_ai_lab.ml")
|
||||
|
||||
@@ -122,7 +121,7 @@ def _get_policy_service():
|
||||
@router.get("/api/ml/status")
|
||||
async def ml_status():
|
||||
"""Get ML decision logging status and available training data."""
|
||||
import services.logging as _logging_mod
|
||||
import routes.shared as _shared
|
||||
lab_root = Path(__file__).resolve().parent.parent
|
||||
results_dir = lab_root / CFG.results_dir
|
||||
ml_files = []
|
||||
@@ -141,7 +140,7 @@ async def ml_status():
|
||||
})
|
||||
total_decisions = sum(f["decisions"] for f in ml_files)
|
||||
return {
|
||||
"ml_logging_enabled": _logging_mod._ml_logging_enabled,
|
||||
"ml_logging_enabled": _shared._ml_logging_enabled,
|
||||
"training_files": ml_files,
|
||||
"total_decisions": total_decisions,
|
||||
"total_files": len(ml_files),
|
||||
@@ -151,10 +150,10 @@ async def ml_status():
|
||||
@router.post("/api/ml/toggle")
|
||||
async def ml_toggle(enable: bool = True):
|
||||
"""Enable or disable ML decision logging for future batch runs."""
|
||||
import services.logging as _logging_mod
|
||||
_logging_mod._ml_logging_enabled = enable
|
||||
import routes.shared as _shared
|
||||
_shared._ml_logging_enabled = enable
|
||||
return {
|
||||
"ml_logging_enabled": _logging_mod._ml_logging_enabled,
|
||||
"ml_logging_enabled": _shared._ml_logging_enabled,
|
||||
"message": f"ML decision logging {'enabled' if enable else 'disabled'} for future batches",
|
||||
}
|
||||
|
||||
@@ -189,95 +188,10 @@ async def ml_get_decisions(filename: str, limit: int = 100, offset: int = 0):
|
||||
}
|
||||
|
||||
|
||||
# ==============================================================
|
||||
# Online Learning Store (SQLite WAL — Phase 5 follow-up)
|
||||
# ==============================================================
|
||||
|
||||
_online_store = None
|
||||
_online_store_init_attempted = False
|
||||
|
||||
def _get_online_store():
|
||||
"""Lazy-init the online learning store singleton."""
|
||||
global _online_store, _online_store_init_attempted
|
||||
if _online_store is None and not _online_store_init_attempted:
|
||||
_online_store_init_attempted = True
|
||||
try:
|
||||
from ml.serving.online_learning_store import OnlineLearningStore
|
||||
_online_store = OnlineLearningStore()
|
||||
_online_store.init_db()
|
||||
log_ml.info("Online learning store initialized")
|
||||
except Exception as e:
|
||||
log_ml.error("Online learning store init failed: %s", e)
|
||||
return _online_store
|
||||
|
||||
|
||||
# ==============================================================
|
||||
# ML Policy Inference Endpoints
|
||||
# ==============================================================
|
||||
|
||||
@router.post("/api/policy/decide")
|
||||
async def policy_decide(request: FastAPIRequest):
|
||||
"""Predict a macro-action and log the decision for online learning.
|
||||
|
||||
Combines prediction with automatic data collection: every decision
|
||||
is appended to the SQLite WAL-backed online learning store so
|
||||
future training runs can incorporate live gameplay data.
|
||||
"""
|
||||
svc = _get_policy_service()
|
||||
if svc is None or not svc._loaded:
|
||||
detail = "Policy model not loaded. "
|
||||
if svc:
|
||||
detail += svc._load_error or "Train a model first."
|
||||
else:
|
||||
detail += "PyTorch may not be installed."
|
||||
raise HTTPException(status_code=503, detail=detail)
|
||||
|
||||
body = await request.json()
|
||||
playstyle = body.pop("archetype", "midrange")
|
||||
temperature = body.pop("temperature", 1.0)
|
||||
greedy = body.pop("greedy", False)
|
||||
collect = body.pop("collect", True) # opt-out flag
|
||||
|
||||
result = svc.predict(
|
||||
decision_snapshot=body,
|
||||
playstyle=playstyle,
|
||||
temperature=temperature,
|
||||
greedy=greedy,
|
||||
)
|
||||
if "error" in result:
|
||||
raise HTTPException(status_code=500, detail=result["error"])
|
||||
|
||||
# Record to online learning store (fire-and-forget — don't block response)
|
||||
if collect:
|
||||
store = _get_online_store()
|
||||
if store is not None:
|
||||
try:
|
||||
store.record_decision(
|
||||
snapshot=body,
|
||||
action_idx=result["action_index"],
|
||||
confidence=result["confidence"],
|
||||
playstyle=playstyle,
|
||||
temperature=temperature,
|
||||
greedy=greedy,
|
||||
)
|
||||
except Exception as e:
|
||||
log_ml.warning("Online learning record failed: %s", e)
|
||||
|
||||
return result
|
||||
|
||||
|
||||
@router.get("/api/policy/decide/stats")
|
||||
async def policy_decide_stats():
|
||||
"""Return counts of collected online learning decisions."""
|
||||
store = _get_online_store()
|
||||
if store is None:
|
||||
return {"total": 0, "unexported": 0, "error": "Store not initialized"}
|
||||
return {
|
||||
"total": store.count(),
|
||||
"unexported": store.count(only_unexported=True),
|
||||
}
|
||||
|
||||
|
||||
@router.post("/api/ml/predict")
|
||||
async def ml_predict(request: FastAPIRequest):
|
||||
"""Predict a macro-action from a game state snapshot."""
|
||||
@@ -863,8 +777,6 @@ def _run_distillation_pipeline(
|
||||
opponent: str,
|
||||
playstyle: str,
|
||||
min_win_rate: float,
|
||||
forge_weight: float = 1.0,
|
||||
ppo_weight: float = 0.0,
|
||||
):
|
||||
"""Run the distillation loop in a background thread."""
|
||||
global _distillation_loop
|
||||
@@ -888,8 +800,6 @@ def _run_distillation_pipeline(
|
||||
opponent=opponent,
|
||||
playstyle=playstyle,
|
||||
min_ppo_win_rate=min_win_rate,
|
||||
forge_weight=forge_weight,
|
||||
ppo_weight=ppo_weight,
|
||||
results_dir=os.path.join(project_root, "results"),
|
||||
models_dir=os.path.join(project_root, "ml", "models"),
|
||||
checkpoint_dir=os.path.join(project_root, "ml", "models", "checkpoints"),
|
||||
@@ -937,21 +847,9 @@ def _run_distillation_pipeline(
|
||||
_distillation_loop = None
|
||||
|
||||
|
||||
@router.get("/api/ml/distill/presets")
|
||||
async def ml_distill_presets():
|
||||
"""List available mixed-mode weight presets for distillation."""
|
||||
from ml.config.scope import MIXED_MODE_PRESETS
|
||||
return {"presets": MIXED_MODE_PRESETS}
|
||||
|
||||
|
||||
@router.post("/api/ml/distill/start")
|
||||
async def ml_start_distillation(request: FastAPIRequest):
|
||||
"""Start the closed-loop distillation pipeline.
|
||||
|
||||
Accepts an optional ``preset`` field (e.g. ``"forge_90_10"``)
|
||||
which overrides ``forgeWeight`` / ``ppoWeight`` with a named
|
||||
configuration from ``MIXED_MODE_PRESETS``.
|
||||
"""
|
||||
"""Start the closed-loop distillation pipeline."""
|
||||
if _distillation_state.running:
|
||||
raise HTTPException(409, "Distillation loop already in progress")
|
||||
if _training_state.running:
|
||||
@@ -973,22 +871,6 @@ async def ml_start_distillation(request: FastAPIRequest):
|
||||
playstyle = body.get("playstyle", "midrange")
|
||||
min_win_rate = body.get("minWinRate", 0.30)
|
||||
|
||||
# Resolve weights: preset > explicit params > defaults (Forge-only)
|
||||
forge_weight = 1.0
|
||||
ppo_weight = 0.0
|
||||
preset_name = body.get("preset")
|
||||
if preset_name:
|
||||
from ml.config.scope import get_preset_weights
|
||||
try:
|
||||
pw = get_preset_weights(preset_name)
|
||||
forge_weight = pw["forge_weight"]
|
||||
ppo_weight = pw["ppo_weight"]
|
||||
except KeyError as e:
|
||||
raise HTTPException(400, str(e))
|
||||
else:
|
||||
forge_weight = body.get("forgeWeight", 1.0)
|
||||
ppo_weight = body.get("ppoWeight", 0.0)
|
||||
|
||||
with _distillation_lock:
|
||||
_distillation_state.running = True
|
||||
_distillation_state.generation = 0
|
||||
@@ -1008,19 +890,12 @@ async def ml_start_distillation(request: FastAPIRequest):
|
||||
supervised_epochs, supervised_lr,
|
||||
ppo_iterations, ppo_episodes_per_iter, ppo_lr,
|
||||
opponent, playstyle, min_win_rate,
|
||||
forge_weight, ppo_weight,
|
||||
),
|
||||
daemon=True,
|
||||
)
|
||||
thread.start()
|
||||
|
||||
return {
|
||||
"status": "started",
|
||||
"max_iterations": max_iterations,
|
||||
"forge_weight": forge_weight,
|
||||
"ppo_weight": ppo_weight,
|
||||
"preset": preset_name,
|
||||
}
|
||||
return {"status": "started", "max_iterations": max_iterations}
|
||||
|
||||
|
||||
@router.get("/api/ml/distill/status")
|
||||
@@ -1097,7 +972,7 @@ _elo_tournament_state = _EloTournamentState()
|
||||
_elo_tournament_lock = threading.Lock()
|
||||
|
||||
|
||||
def _run_elo_tournament_pipeline(episodes: int, playstyle: str, top_n: int):
|
||||
def _run_elo_tournament_pipeline(episodes: int, playstyle: str):
|
||||
"""Run ELO tournament in a background thread."""
|
||||
try:
|
||||
import sys
|
||||
@@ -1108,7 +983,7 @@ def _run_elo_tournament_pipeline(episodes: int, playstyle: str, top_n: int):
|
||||
with _elo_tournament_lock:
|
||||
_elo_tournament_state.running = True
|
||||
_elo_tournament_state.phase = "running"
|
||||
_elo_tournament_state.message = f"Running ELO tournament (top {top_n} generations)..."
|
||||
_elo_tournament_state.message = "Running ELO tournament..."
|
||||
_elo_tournament_state.error = None
|
||||
_elo_tournament_state.result = None
|
||||
|
||||
@@ -1121,7 +996,6 @@ def _run_elo_tournament_pipeline(episodes: int, playstyle: str, top_n: int):
|
||||
checkpoint_dir=ckpt_dir,
|
||||
episodes_per_matchup=episodes,
|
||||
playstyle=playstyle,
|
||||
top_n=top_n,
|
||||
)
|
||||
|
||||
# Save to ELO history
|
||||
@@ -1156,37 +1030,29 @@ def _run_elo_tournament_pipeline(episodes: int, playstyle: str, top_n: int):
|
||||
|
||||
@router.post("/api/ml/elo/tournament")
|
||||
async def ml_start_elo_tournament(request: FastAPIRequest):
|
||||
"""Start an ELO-rated tournament across generation checkpoints.
|
||||
|
||||
Body params:
|
||||
episodes (int): Games per matchup pair (default 50)
|
||||
playstyle (str): Game playstyle (default midrange)
|
||||
topN (int): Max number of most-recent gen checkpoints to include
|
||||
(default 10, 0 = unlimited)
|
||||
"""
|
||||
"""Start an ELO-rated tournament across all generation checkpoints."""
|
||||
if _elo_tournament_state.running:
|
||||
raise HTTPException(409, "ELO tournament already in progress")
|
||||
|
||||
body = await request.json() if await request.body() else {}
|
||||
episodes = body.get("episodes", 50)
|
||||
playstyle = body.get("playstyle", "midrange")
|
||||
top_n = body.get("topN", 10)
|
||||
|
||||
with _elo_tournament_lock:
|
||||
_elo_tournament_state.running = True
|
||||
_elo_tournament_state.phase = "starting"
|
||||
_elo_tournament_state.message = f"Initializing ELO tournament (top {top_n} generations)..."
|
||||
_elo_tournament_state.message = "Initializing ELO tournament..."
|
||||
_elo_tournament_state.result = None
|
||||
_elo_tournament_state.error = None
|
||||
|
||||
thread = threading.Thread(
|
||||
target=_run_elo_tournament_pipeline,
|
||||
args=(episodes, playstyle, top_n),
|
||||
args=(episodes, playstyle),
|
||||
daemon=True,
|
||||
)
|
||||
thread.start()
|
||||
|
||||
return {"status": "started", "episodes": episodes, "top_n": top_n}
|
||||
return {"status": "started", "episodes": episodes}
|
||||
|
||||
|
||||
@router.get("/api/ml/elo/tournament/status")
|
||||
|
||||
@@ -1,321 +0,0 @@
|
||||
"""Commander AI Lab — Policy Decision Routes (Phase 2)
|
||||
════════════════════════════════════════════════════
|
||||
|
||||
Live Forge ↔ policy server IPC endpoints for online training.
|
||||
These endpoints are purpose-built for the real-time decision loop
|
||||
where Forge's Java side calls the Python policy server at each
|
||||
game decision point.
|
||||
|
||||
Endpoints:
|
||||
POST /api/policy/decide — Accept full Forge game state, return action + log_prob + value
|
||||
POST /api/policy/collect — Accept batch of (state, action, reward) tuples
|
||||
POST /api/policy/reward — Submit end-of-game reward
|
||||
GET /api/policy/health — Readiness check for the live IPC loop
|
||||
GET /api/policy/stats — Online learning session statistics
|
||||
|
||||
Refs: Issue #83 Phase 2.2
|
||||
"""
|
||||
import logging
|
||||
import time
|
||||
from typing import Dict, List, Optional
|
||||
|
||||
from fastapi import APIRouter, HTTPException
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
logger = logging.getLogger("routes.policy")
|
||||
|
||||
router = APIRouter(prefix="/api/policy", tags=["policy"])
|
||||
|
||||
|
||||
# ================================================================
|
||||
# Request / Response Models
|
||||
# ================================================================
|
||||
|
||||
class PlayerZoneState(BaseModel):
|
||||
"""Per-player zone state from Forge."""
|
||||
seat: int = 0
|
||||
name: str = ""
|
||||
life: int = 40
|
||||
poison: int = 0
|
||||
cmdr_dmg: Dict[str, int] = Field(default_factory=dict)
|
||||
cmdr_tax: int = 0
|
||||
mana_available: int = 0
|
||||
mana_pool: Dict[str, int] = Field(default_factory=dict)
|
||||
# Full zone contents
|
||||
hand: List[str] = Field(default_factory=list)
|
||||
hand_count: int = 0
|
||||
battlefield: List[Dict] = Field(default_factory=list)
|
||||
graveyard: List[str] = Field(default_factory=list)
|
||||
exile: List[str] = Field(default_factory=list)
|
||||
command_zone: List[str] = Field(default_factory=list)
|
||||
library_count: int = 0
|
||||
|
||||
|
||||
class DecideRequest(BaseModel):
|
||||
"""Full Forge game state for live decision-making."""
|
||||
# Game metadata
|
||||
game_id: str = ""
|
||||
turn: int = 1
|
||||
phase: str = "main_1"
|
||||
active_player: int = 0
|
||||
priority_player: int = 0
|
||||
# Per-player state with full zones
|
||||
players: List[PlayerZoneState] = Field(default_factory=list)
|
||||
# Stack (spells/abilities currently resolving)
|
||||
stack: List[Dict] = Field(default_factory=list)
|
||||
# Legal actions from Forge
|
||||
legal_actions: List[Dict] = Field(default_factory=list)
|
||||
# Inference params
|
||||
playstyle: str = "midrange"
|
||||
greedy: bool = False
|
||||
temperature: float = 1.0
|
||||
# Optional commander info
|
||||
commander: str = ""
|
||||
deck_name: str = ""
|
||||
|
||||
|
||||
class DecideResponse(BaseModel):
|
||||
"""Action decision with metadata for online learning."""
|
||||
action: str
|
||||
action_index: int
|
||||
confidence: float
|
||||
log_prob: float = 0.0
|
||||
value: float = 0.0
|
||||
probabilities: Dict[str, float] = Field(default_factory=dict)
|
||||
inference_ms: float = 0.0
|
||||
error: Optional[str] = None
|
||||
|
||||
|
||||
class CollectRequest(BaseModel):
|
||||
"""Batch of online learning tuples from live Forge games."""
|
||||
tuples: List[Dict] = Field(default_factory=list)
|
||||
count: int = 0
|
||||
|
||||
|
||||
class RewardRequest(BaseModel):
|
||||
"""End-of-game reward submission."""
|
||||
game_id: str
|
||||
reward: float
|
||||
winner_seat: int = -1
|
||||
turns_played: int = 0
|
||||
reason: str = "" # e.g., "life", "commander_damage", "concede"
|
||||
|
||||
|
||||
# ================================================================
|
||||
# Module-level state (initialized by register_policy_routes)
|
||||
# ================================================================
|
||||
|
||||
_policy_service = None
|
||||
_online_store = None
|
||||
_session_stats = {
|
||||
"total_decisions": 0,
|
||||
"total_tuples_collected": 0,
|
||||
"total_rewards_submitted": 0,
|
||||
"games_completed": 0,
|
||||
"session_start": 0.0,
|
||||
"last_decision_ms": 0.0,
|
||||
}
|
||||
|
||||
|
||||
def register_policy_routes(app, policy_service, online_store=None):
|
||||
"""Register the policy routes on the FastAPI app.
|
||||
|
||||
Args:
|
||||
app: FastAPI application instance
|
||||
policy_service: PolicyInferenceService from ml.serving.policy_server
|
||||
online_store: Optional OnlineLearningStore for tuple collection
|
||||
"""
|
||||
global _policy_service, _online_store
|
||||
_policy_service = policy_service
|
||||
_online_store = online_store
|
||||
_session_stats["session_start"] = time.time()
|
||||
app.include_router(router)
|
||||
logger.info("Policy routes registered (online_store=%s)",
|
||||
"enabled" if online_store else "disabled")
|
||||
|
||||
|
||||
# ================================================================
|
||||
# POST /api/policy/decide
|
||||
# ================================================================
|
||||
|
||||
@router.post("/decide", response_model=DecideResponse)
|
||||
async def decide(req: DecideRequest):
|
||||
"""Accept full Forge game state, run policy inference, return action.
|
||||
|
||||
This is the primary endpoint for live Forge IPC. The Java
|
||||
PolicyClient calls this at each decision point during a real
|
||||
Forge game.
|
||||
|
||||
Returns the macro-action plus log_prob and value estimate
|
||||
needed for online PPO updates.
|
||||
"""
|
||||
if _policy_service is None or not _policy_service._loaded:
|
||||
raise HTTPException(
|
||||
503,
|
||||
detail="Policy model not loaded"
|
||||
)
|
||||
|
||||
t_start = time.time()
|
||||
_session_stats["total_decisions"] += 1
|
||||
|
||||
# Convert request to snapshot dict for the encoder
|
||||
snapshot = req.dict(exclude={"temperature", "greedy", "playstyle"})
|
||||
|
||||
# Map phase names from Forge conventions
|
||||
snapshot["phase"] = _map_forge_phase(req.phase)
|
||||
snapshot["active_seat"] = req.active_player
|
||||
|
||||
result = _policy_service.predict(
|
||||
snapshot,
|
||||
playstyle=req.playstyle,
|
||||
temperature=req.temperature,
|
||||
greedy=req.greedy,
|
||||
)
|
||||
|
||||
elapsed_ms = (time.time() - t_start) * 1000
|
||||
_session_stats["last_decision_ms"] = elapsed_ms
|
||||
|
||||
if "error" in result:
|
||||
raise HTTPException(500, detail=result["error"])
|
||||
|
||||
# Add log_prob and value estimate for online learning
|
||||
log_prob = 0.0
|
||||
value = 0.0
|
||||
try:
|
||||
import math
|
||||
conf = result.get("confidence", 0.5)
|
||||
log_prob = math.log(max(conf, 1e-8))
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return DecideResponse(
|
||||
action=result["action"],
|
||||
action_index=result["action_index"],
|
||||
confidence=result["confidence"],
|
||||
log_prob=round(log_prob, 6),
|
||||
value=round(value, 6),
|
||||
probabilities=result.get("probabilities", {}),
|
||||
inference_ms=round(elapsed_ms, 2),
|
||||
)
|
||||
|
||||
|
||||
# ================================================================
|
||||
# POST /api/policy/collect
|
||||
# ================================================================
|
||||
|
||||
@router.post("/collect")
|
||||
async def collect_tuples(req: CollectRequest):
|
||||
"""Accept a batch of (state, action, reward) tuples from live games
|
||||
for online PPO updates.
|
||||
"""
|
||||
count = len(req.tuples)
|
||||
_session_stats["total_tuples_collected"] += count
|
||||
|
||||
if _online_store is not None:
|
||||
try:
|
||||
_online_store.add_tuples(req.tuples)
|
||||
except Exception as e:
|
||||
logger.error("Failed to store tuples: %s", e)
|
||||
raise HTTPException(500, detail=str(e))
|
||||
|
||||
return {
|
||||
"accepted": count,
|
||||
"total_buffered": (
|
||||
_online_store.size() if _online_store else count
|
||||
),
|
||||
}
|
||||
|
||||
|
||||
# ================================================================
|
||||
# POST /api/policy/reward
|
||||
# ================================================================
|
||||
|
||||
@router.post("/reward")
|
||||
async def submit_reward(req: RewardRequest):
|
||||
"""Submit end-of-game reward for all tuples in a game.
|
||||
Propagates the terminal reward back through the game's trajectory.
|
||||
"""
|
||||
_session_stats["total_rewards_submitted"] += 1
|
||||
_session_stats["games_completed"] += 1
|
||||
|
||||
if _online_store is not None:
|
||||
try:
|
||||
_online_store.assign_reward(
|
||||
game_id=req.game_id,
|
||||
reward=req.reward,
|
||||
winner_seat=req.winner_seat,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error("Failed to assign reward: %s", e)
|
||||
raise HTTPException(500, detail=str(e))
|
||||
|
||||
return {
|
||||
"game_id": req.game_id,
|
||||
"reward": req.reward,
|
||||
"status": "accepted",
|
||||
}
|
||||
|
||||
|
||||
# ================================================================
|
||||
# GET /api/policy/health
|
||||
# ================================================================
|
||||
|
||||
@router.get("/health")
|
||||
async def policy_health():
|
||||
"""Readiness check for the live Forge IPC loop."""
|
||||
model_loaded = (
|
||||
_policy_service is not None and _policy_service._loaded
|
||||
)
|
||||
return {
|
||||
"ready": model_loaded,
|
||||
"status": "ok" if model_loaded else "degraded",
|
||||
"model_loaded": model_loaded,
|
||||
"online_store": _online_store is not None,
|
||||
}
|
||||
|
||||
|
||||
# ================================================================
|
||||
# GET /api/policy/stats
|
||||
# ================================================================
|
||||
|
||||
@router.get("/stats")
|
||||
async def policy_stats():
|
||||
"""Online learning session statistics."""
|
||||
uptime = time.time() - _session_stats["session_start"]
|
||||
return {
|
||||
**_session_stats,
|
||||
"uptime_seconds": round(uptime, 1),
|
||||
"decisions_per_second": (
|
||||
round(_session_stats["total_decisions"] / max(uptime, 1), 2)
|
||||
),
|
||||
"online_store_size": (
|
||||
_online_store.size() if _online_store else 0
|
||||
),
|
||||
}
|
||||
|
||||
|
||||
# ================================================================
|
||||
# Helpers
|
||||
# ================================================================
|
||||
|
||||
_FORGE_PHASE_MAP = {
|
||||
"UNTAP": "main_1",
|
||||
"UPKEEP": "main_1",
|
||||
"DRAW": "main_1",
|
||||
"MAIN1": "main_1",
|
||||
"BEGIN_COMBAT": "combat",
|
||||
"DECLARE_ATTACKERS": "combat",
|
||||
"DECLARE_BLOCKERS": "combat",
|
||||
"DAMAGE": "combat",
|
||||
"COMBAT_DAMAGE": "combat",
|
||||
"END_COMBAT": "combat",
|
||||
"MAIN2": "main_2",
|
||||
"END": "end",
|
||||
"END_STEP": "end",
|
||||
"CLEANUP": "end",
|
||||
}
|
||||
|
||||
|
||||
def _map_forge_phase(phase: str) -> str:
|
||||
"""Map Forge phase string to ML GamePhase enum value."""
|
||||
return _FORGE_PHASE_MAP.get(phase.upper(), "main_1")
|
||||
+3
-4
@@ -15,9 +15,8 @@ from pathlib import Path
|
||||
|
||||
from fastapi import APIRouter, HTTPException
|
||||
|
||||
from models.state import CFG
|
||||
from services.precon_service import download_precon_database, PRECON_INDEX
|
||||
from services.logging import log
|
||||
import routes.shared as _shared # module reference, not value import
|
||||
from routes.shared import CFG, download_precon_database, log
|
||||
from services.precon_service import _get_precon_dir
|
||||
|
||||
router = APIRouter(tags=["precon"])
|
||||
@@ -26,7 +25,7 @@ router = APIRouter(tags=["precon"])
|
||||
@router.get("/api/lab/precons")
|
||||
async def list_precons():
|
||||
"""List all available precon decks."""
|
||||
return {"precons": PRECON_INDEX} # reads current value every call
|
||||
return {"precons": _shared.PRECON_INDEX} # reads current value every call
|
||||
|
||||
|
||||
@router.post("/api/lab/precons/install")
|
||||
|
||||
-121
@@ -1,121 +0,0 @@
|
||||
"""
|
||||
routes/rag.py
|
||||
=============
|
||||
RAG (Retrieval-Augmented Generation) endpoints for semantic card search.
|
||||
|
||||
Endpoints:
|
||||
POST /api/rag/build — build / rebuild the ChromaDB vector index
|
||||
POST /api/rag/search — semantic search over indexed cards
|
||||
GET /api/rag/status — index health & stats
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from typing import List, Optional
|
||||
|
||||
from fastapi import APIRouter, HTTPException
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
log = logging.getLogger("commander_ai_lab.routes.rag")
|
||||
|
||||
router = APIRouter(tags=["rag"])
|
||||
|
||||
|
||||
# ── Request / Response models ────────────────────────────────────────────────
|
||||
|
||||
class RAGSearchRequest(BaseModel):
|
||||
query: str = Field(..., description="Natural-language card search query")
|
||||
color_identity: Optional[List[str]] = Field(
|
||||
None,
|
||||
description="Optional color identity filter, e.g. ['W','U','B']",
|
||||
)
|
||||
top_k: int = Field(10, ge=1, le=50, description="Number of results to return")
|
||||
|
||||
|
||||
class RAGCardResult(BaseModel):
|
||||
name: str
|
||||
type_line: str = ""
|
||||
oracle_text: str = ""
|
||||
color_identity: str = ""
|
||||
score: float = 0.0
|
||||
|
||||
|
||||
class RAGSearchResponse(BaseModel):
|
||||
query: str
|
||||
results: List[RAGCardResult]
|
||||
total: int
|
||||
|
||||
|
||||
class RAGBuildRequest(BaseModel):
|
||||
force: bool = Field(False, description="Force full rebuild even if index exists")
|
||||
batch_size: int = Field(500, ge=50, le=5000)
|
||||
|
||||
|
||||
# ── Endpoints ────────────────────────────────────────────────────────────────
|
||||
|
||||
@router.post("/api/rag/build")
|
||||
async def rag_build(body: RAGBuildRequest = RAGBuildRequest()):
|
||||
"""
|
||||
Build or rebuild the ChromaDB vector index from the Scryfall bulk DB.
|
||||
Runs synchronously (may take 1-5 min on first build).
|
||||
"""
|
||||
try:
|
||||
from services.rag_store import build_index
|
||||
result = build_index(force=body.force, batch_size=body.batch_size)
|
||||
return {"status": "ok", **result}
|
||||
except FileNotFoundError as exc:
|
||||
raise HTTPException(status_code=404, detail=str(exc))
|
||||
except Exception as exc:
|
||||
log.exception("RAG build failed")
|
||||
raise HTTPException(status_code=500, detail=str(exc))
|
||||
|
||||
|
||||
@router.post("/api/rag/search")
|
||||
async def rag_search(body: RAGSearchRequest):
|
||||
"""
|
||||
Semantic search over the ChromaDB card index.
|
||||
Returns ranked card results with relevance scores.
|
||||
"""
|
||||
try:
|
||||
from services.rag_store import query_cards
|
||||
raw_results = query_cards(
|
||||
query=body.query,
|
||||
n_results=body.top_k,
|
||||
color_identity=body.color_identity,
|
||||
)
|
||||
results = [
|
||||
RAGCardResult(
|
||||
name=r.get("name", ""),
|
||||
type_line=r.get("type_line", ""),
|
||||
oracle_text=r.get("oracle_text", ""),
|
||||
color_identity=r.get("color_identity", ""),
|
||||
score=round(1.0 - r.get("distance", 0.0), 4),
|
||||
)
|
||||
for r in raw_results
|
||||
]
|
||||
return RAGSearchResponse(
|
||||
query=body.query,
|
||||
results=results,
|
||||
total=len(results),
|
||||
)
|
||||
except FileNotFoundError as exc:
|
||||
raise HTTPException(
|
||||
status_code=404,
|
||||
detail=f"Index not built yet. Call POST /api/rag/build first. {exc}",
|
||||
)
|
||||
except Exception as exc:
|
||||
log.exception("RAG search failed")
|
||||
raise HTTPException(status_code=500, detail=str(exc))
|
||||
|
||||
|
||||
@router.get("/api/rag/status")
|
||||
async def rag_status_detail():
|
||||
"""
|
||||
Detailed RAG index status including card count and age.
|
||||
"""
|
||||
try:
|
||||
from services.rag_store import get_rag_stats
|
||||
return {"status": "ok", **get_rag_stats()}
|
||||
except Exception as exc:
|
||||
log.exception("RAG status check failed")
|
||||
return {"status": "error", "error": str(exc)}
|
||||
+7
-7
@@ -22,13 +22,13 @@ from urllib.error import URLError
|
||||
from fastapi import APIRouter, HTTPException
|
||||
from fastapi import Request as FastAPIRequest
|
||||
|
||||
from models.state import CFG
|
||||
from services.card_analysis import _detect_card_roles
|
||||
from services.database import _get_db_conn, _row_to_dict
|
||||
from services.deck_service import _to_edhrec_slug
|
||||
from services.import_helpers import _edhrec_cache_get, _edhrec_cache_set
|
||||
from services.logging import log_scan, log_deckgen
|
||||
from services.scryfall import _API_HEADERS, _enrich_from_scryfall, _scryfall_fuzzy_lookup
|
||||
from routes.shared import (
|
||||
CFG, log_scan, log_deckgen,
|
||||
_get_db_conn, _row_to_dict, _enrich_from_scryfall,
|
||||
_scryfall_fuzzy_lookup, _detect_card_roles,
|
||||
_to_edhrec_slug, _API_HEADERS,
|
||||
_edhrec_cache_get, _edhrec_cache_set,
|
||||
)
|
||||
|
||||
router = APIRouter(tags=["scanner"])
|
||||
|
||||
|
||||
@@ -0,0 +1,204 @@
|
||||
"""
|
||||
routes/shared.py
|
||||
================
|
||||
Single source of truth for everything every router needs.
|
||||
|
||||
Contains:
|
||||
- Config class + CFG singleton
|
||||
- Logging setup + all named loggers
|
||||
- FastAPI app instance
|
||||
- In-memory state (active_batches, COMMANDER_META, PRECON_INDEX, AI_PROFILES)
|
||||
- All Pydantic request/response models
|
||||
- SQLite DB helpers (_get_db_conn, init_collection_db)
|
||||
- Scryfall cache + enrichment helpers
|
||||
- Collection helpers (_detect_card_roles, _classify_card_type,
|
||||
_build_collection_filters, _parse_finish, _parse_csv_content,
|
||||
_parse_text_line, _auto_infer_mapping, _row_to_dict, _add_image_url,
|
||||
_snake_to_camel, VALID_SORT_FIELDS, _JSON_FIELDS)
|
||||
- Deck helpers (_get_deck_or_404, _compute_deck_analysis, _check_ratio_limit,
|
||||
_TYPE_TARGETS, _TYPE_PRIORITY, _classify_card_type)
|
||||
- Import helpers (_import_from_url, _fetch_archidekt_deck,
|
||||
_fetch_edhrec_average, _parse_text_decklist, _save_profile_to_dck,
|
||||
_to_edhrec_slug, _http_get, _API_HEADERS, _edhrec_cache_get,
|
||||
_edhrec_cache_set)
|
||||
- Precon helpers (PRECON_DIR, PRECON_INDEX, download_precon_database,
|
||||
load_precon_index, GITHUB_PRECON_URL, PRECON_CACHE_HOURS)
|
||||
- Sim helpers (build_java_command, get_java17, BatchState, parse_dck_file,
|
||||
AI_PROFILES, run_batch_subprocess, _run_process_blocking,
|
||||
_run_deepseek_batch_thread, _load_deck_cards_by_name, _get_deepseek_brain)
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import asyncio
|
||||
import csv
|
||||
import io
|
||||
import json
|
||||
import logging
|
||||
import logging.handlers
|
||||
import os
|
||||
import re
|
||||
import sqlite3
|
||||
import subprocess
|
||||
import sys
|
||||
import threading
|
||||
import time
|
||||
import uuid
|
||||
from collections import Counter
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
from urllib.request import urlopen, Request
|
||||
from urllib.error import URLError
|
||||
|
||||
try:
|
||||
from fastapi import FastAPI, HTTPException, BackgroundTasks, Request as FastAPIRequest
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from fastapi.responses import FileResponse, JSONResponse, StreamingResponse
|
||||
from fastapi.staticfiles import StaticFiles
|
||||
from pydantic import BaseModel
|
||||
except ImportError:
|
||||
print("ERROR: FastAPI not installed. Run: pip install fastapi uvicorn")
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Configuration
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
# Configuration (imported from models/state)
|
||||
from models.state import Config, CFG
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Logging Setup
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
_LOG_FORMAT = "%(asctime)s %(levelname)-5s [%(name)s] %(message)s"
|
||||
_LOG_DATE_FMT = "%Y-%m-%d %H:%M:%S"
|
||||
_LOG_DIR = Path(os.environ.get("CAL_LOG_DIR", "logs"))
|
||||
_LOG_MAX_BYTES = int(os.environ.get("CAL_LOG_MAX_MB", "25")) * 1024 * 1024
|
||||
_LOG_BACKUP_COUNT = int(os.environ.get("CAL_LOG_BACKUP_COUNT", "5"))
|
||||
|
||||
|
||||
def setup_logging(level: int = logging.INFO) -> None:
|
||||
_LOG_DIR.mkdir(parents=True, exist_ok=True)
|
||||
root_logger = logging.getLogger("commander_ai_lab")
|
||||
root_logger.setLevel(level)
|
||||
if root_logger.handlers:
|
||||
return
|
||||
formatter = logging.Formatter(_LOG_FORMAT, datefmt=_LOG_DATE_FMT)
|
||||
console = logging.StreamHandler(sys.stdout)
|
||||
console.setLevel(level)
|
||||
console.setFormatter(formatter)
|
||||
root_logger.addHandler(console)
|
||||
file_handler = logging.handlers.RotatingFileHandler(
|
||||
_LOG_DIR / "commander-ai-lab.log",
|
||||
maxBytes=_LOG_MAX_BYTES,
|
||||
backupCount=_LOG_BACKUP_COUNT,
|
||||
encoding="utf-8",
|
||||
)
|
||||
file_handler.setLevel(level)
|
||||
file_handler.setFormatter(formatter)
|
||||
root_logger.addHandler(file_handler)
|
||||
|
||||
|
||||
log = logging.getLogger("commander_ai_lab.api")
|
||||
log_batch = logging.getLogger("commander_ai_lab.batch")
|
||||
log_sim = logging.getLogger("commander_ai_lab.sim")
|
||||
log_coach = logging.getLogger("commander_ai_lab.coach")
|
||||
log_deckgen = logging.getLogger("commander_ai_lab.deckgen")
|
||||
log_collect = logging.getLogger("commander_ai_lab.collection")
|
||||
log_scan = logging.getLogger("commander_ai_lab.scanner")
|
||||
log_ml = logging.getLogger("commander_ai_lab.ml")
|
||||
log_cache = logging.getLogger("commander_ai_lab.cache")
|
||||
log_pplx = logging.getLogger("commander_ai_lab.pplx")
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# In-Memory State
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
# In-Memory State (imported from models/state)
|
||||
from models.state import (
|
||||
BatchState, active_batches, COMMANDER_META,
|
||||
BUILTIN_COMMANDERS, load_commander_meta,
|
||||
)
|
||||
|
||||
|
||||
# Pydantic Models (imported from models/)
|
||||
from models.requests import (
|
||||
StartRequest, ImportUrlRequest, ImportTextRequest, MetaFetchRequest,
|
||||
CreateDeckRequest, UpdateDeckRequest, AddDeckCardRequest,
|
||||
PatchDeckCardRequest, BulkAddRequest, BulkAddRecommendedRequest,
|
||||
DeckGenerationSourceConfig, DeckGenerationRequest,
|
||||
DeckGenV3Request, DeckGenV3SubstituteRequest,
|
||||
)
|
||||
from models.responses import (
|
||||
StartResponse, StatusResponse, DeckInfo, GeneratedDeckCard,
|
||||
)
|
||||
|
||||
|
||||
# Collection Database (imported from services/database.py)
|
||||
from services.database import (
|
||||
COLLECTION_DB_PATH, _get_db_conn, init_collection_db,
|
||||
_JSON_FIELDS, VALID_SORT_FIELDS,
|
||||
_row_to_dict, _snake_to_camel, _add_image_url, _build_collection_filters,
|
||||
)
|
||||
# Card Role Detection (imported from services/card_analysis.py)
|
||||
from services.card_analysis import _detect_card_roles
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Deck Helpers (imported from services/deck_service.py)
|
||||
from services.deck_service import (
|
||||
_TYPE_PRIORITY, _TYPE_TARGETS, _classify_card_type, _get_deck_or_404,
|
||||
_compute_deck_analysis, _check_ratio_limit, _to_edhrec_slug,
|
||||
parse_dck_file, _save_profile_to_dck, _load_deck_cards_by_name,
|
||||
)
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Scryfall Cache (imported from services/scryfall.py)
|
||||
from services.scryfall import (
|
||||
SCRYFALL_CACHE_DB_PATH, SCRYFALL_CACHE_TTL_SECONDS, _API_HEADERS,
|
||||
_ScryfallCache, _scryfall_cache, _scryfall_lock, _scryfall_last_call,
|
||||
_scryfall_rate_limit, _fetch_scryfall_api, _enrich_from_scryfall, _scryfall_fuzzy_lookup,
|
||||
)
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Import Helpers (extracted to services/import_helpers.py)
|
||||
from services.import_helpers import (
|
||||
_http_get, _fetch_archidekt_deck, _fetch_edhrec_average,
|
||||
_import_from_url, _parse_text_decklist, _save_profile_to_dck,
|
||||
_edhrec_cache, _EDHREC_CACHE_TTL, _edhrec_cache_get, _edhrec_cache_set,
|
||||
)
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Collection Import Helpers (extracted to services/import_service.py)
|
||||
from services.import_service import (
|
||||
_parse_finish, _parse_text_line, _auto_infer_mapping, _parse_csv_content,
|
||||
)
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Precon Helpers (extracted to services/precon_service.py)
|
||||
from services.precon_service import (
|
||||
PRECON_DIR, PRECON_INDEX, GITHUB_PRECON_URL, PRECON_CACHE_HOURS,
|
||||
load_precon_index, _sanitize_filename, _deck_to_dck, download_precon_database,
|
||||
_get_precon_dir,
|
||||
)
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# AI Profiles (imported from models/state)
|
||||
from models.state import AI_PROFILES
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Java / Sim Helpers (extracted to services/forge_runner.py)
|
||||
from services.forge_runner import (
|
||||
_find_java17, get_java17, build_java_command,
|
||||
run_batch_subprocess, _run_process_blocking,
|
||||
_run_deepseek_batch_thread, _get_deepseek_brain,
|
||||
)
|
||||
|
||||
_ml_logging_enabled = True
|
||||
@@ -1,176 +0,0 @@
|
||||
"""WebSocket route for real-time game state streaming.
|
||||
|
||||
Endpoints:
|
||||
WS /ws/game/{game_id} — Stream state deltas to Unity
|
||||
POST /api/ws/game/{game_id}/push — Push a state update (called by Forge IPC)
|
||||
POST /api/ws/game/{game_id}/decision — Push AI decision event
|
||||
POST /api/ws/game/{game_id}/end — Signal game over
|
||||
GET /api/ws/stats — Connection statistics
|
||||
|
||||
Unity connects to the WebSocket endpoint and receives:
|
||||
1. An initial full snapshot on first state push
|
||||
2. Subsequent delta-only messages as state changes
|
||||
3. Decision events when the AI acts
|
||||
4. A game_over event when the game ends
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import copy
|
||||
import logging
|
||||
import time
|
||||
import uuid
|
||||
from typing import Optional
|
||||
|
||||
from fastapi import APIRouter, WebSocket, WebSocketDisconnect
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from ws.connection_manager import game_manager
|
||||
from ws.game_state import get_tracker, remove_tracker
|
||||
|
||||
log = logging.getLogger("routes.ws_game")
|
||||
|
||||
router = APIRouter(tags=["websocket"])
|
||||
|
||||
|
||||
# ────────────────────────────────────────────────────────────
|
||||
# WebSocket endpoint — Unity connects here
|
||||
# ────────────────────────────────────────────────────────────
|
||||
|
||||
@router.websocket("/ws/game/{game_id}")
|
||||
async def game_ws(websocket: WebSocket, game_id: str):
|
||||
"""WebSocket endpoint for Unity game-state streaming.
|
||||
|
||||
Query params:
|
||||
client_id — optional unique identifier for this client
|
||||
|
||||
The connection stays open for the duration of the game.
|
||||
The server pushes messages; the client can send:
|
||||
{"type": "ping"} — keep-alive
|
||||
{"type": "request_snapshot"} — request a full re-sync
|
||||
"""
|
||||
client_id = (
|
||||
websocket.query_params.get("client_id")
|
||||
or f"unity-{uuid.uuid4().hex[:8]}"
|
||||
)
|
||||
|
||||
client = await game_manager.connect(websocket, game_id, client_id)
|
||||
|
||||
# If the tracker already has a baseline, send the current state
|
||||
tracker = get_tracker(game_id)
|
||||
if tracker.has_baseline:
|
||||
snapshot_msg = tracker.update(tracker._last_snapshot)
|
||||
await websocket.send_json(snapshot_msg)
|
||||
|
||||
try:
|
||||
while True:
|
||||
data = await websocket.receive_json()
|
||||
msg_type = data.get("type", "")
|
||||
|
||||
if msg_type == "ping":
|
||||
await websocket.send_json({"type": "pong"})
|
||||
|
||||
elif msg_type == "request_snapshot":
|
||||
if tracker.has_baseline:
|
||||
snap = copy.deepcopy(tracker._last_snapshot)
|
||||
tracker._seq += 1
|
||||
await websocket.send_json({
|
||||
"type": "snapshot",
|
||||
"seq": tracker._seq,
|
||||
"game_id": game_id,
|
||||
"timestamp": time.time(),
|
||||
"state": snap,
|
||||
})
|
||||
else:
|
||||
await websocket.send_json({
|
||||
"type": "error",
|
||||
"message": "No game state available yet",
|
||||
})
|
||||
|
||||
except WebSocketDisconnect:
|
||||
pass
|
||||
except Exception as e:
|
||||
log.warning("WS error game=%s client=%s: %s", game_id, client_id, e)
|
||||
finally:
|
||||
await game_manager.disconnect(game_id, client_id)
|
||||
|
||||
|
||||
# ────────────────────────────────────────────────────────────
|
||||
# REST endpoints — called by Forge IPC / policy server
|
||||
# ────────────────────────────────────────────────────────────
|
||||
|
||||
class PushStateRequest(BaseModel):
|
||||
"""Game state snapshot pushed from Forge."""
|
||||
game_id: str = ""
|
||||
turn: int = 0
|
||||
phase: str = ""
|
||||
active_player: int = 0
|
||||
players: list = Field(default_factory=list)
|
||||
stack: list = Field(default_factory=list)
|
||||
legal_actions: list = Field(default_factory=list)
|
||||
|
||||
|
||||
class DecisionEvent(BaseModel):
|
||||
"""AI decision event pushed after policy inference."""
|
||||
action: str
|
||||
action_index: int = 0
|
||||
confidence: float = 0.0
|
||||
probabilities: dict = Field(default_factory=dict)
|
||||
inference_ms: float = 0.0
|
||||
|
||||
|
||||
class GameOverEvent(BaseModel):
|
||||
"""Game-over event."""
|
||||
winner_seat: int = -1
|
||||
reason: str = ""
|
||||
turns_played: int = 0
|
||||
|
||||
|
||||
@router.post("/api/ws/game/{game_id}/push")
|
||||
async def push_game_state(game_id: str, req: PushStateRequest):
|
||||
"""Push a game state update to all connected Unity clients."""
|
||||
tracker = get_tracker(game_id)
|
||||
snapshot = req.dict()
|
||||
delta_msg = tracker.update(snapshot)
|
||||
sent = await game_manager.broadcast_to_game(game_id, delta_msg)
|
||||
return {
|
||||
"status": "ok",
|
||||
"type": delta_msg["type"],
|
||||
"seq": delta_msg["seq"],
|
||||
"clients_notified": sent,
|
||||
"changes": len(delta_msg.get("changes", [])),
|
||||
}
|
||||
|
||||
|
||||
@router.post("/api/ws/game/{game_id}/decision")
|
||||
async def push_decision(game_id: str, event: DecisionEvent):
|
||||
"""Push an AI decision event to connected Unity clients."""
|
||||
tracker = get_tracker(game_id)
|
||||
msg = tracker.make_decision_event(
|
||||
action=event.action,
|
||||
action_index=event.action_index,
|
||||
confidence=event.confidence,
|
||||
probabilities=event.probabilities,
|
||||
inference_ms=event.inference_ms,
|
||||
)
|
||||
sent = await game_manager.broadcast_to_game(game_id, msg)
|
||||
return {"status": "ok", "clients_notified": sent}
|
||||
|
||||
|
||||
@router.post("/api/ws/game/{game_id}/end")
|
||||
async def push_game_over(game_id: str, event: GameOverEvent):
|
||||
"""Signal game over to all connected clients and clean up."""
|
||||
tracker = get_tracker(game_id)
|
||||
msg = tracker.make_game_over_event(
|
||||
winner_seat=event.winner_seat,
|
||||
reason=event.reason,
|
||||
turns_played=event.turns_played,
|
||||
)
|
||||
sent = await game_manager.broadcast_to_game(game_id, msg)
|
||||
remove_tracker(game_id)
|
||||
return {"status": "ok", "clients_notified": sent}
|
||||
|
||||
|
||||
@router.get("/api/ws/stats")
|
||||
async def ws_stats():
|
||||
"""Return WebSocket connection statistics."""
|
||||
return game_manager.stats()
|
||||
@@ -85,7 +85,7 @@ def start_batch(base_url, decks, num_games, playstyle, threads):
|
||||
def poll_batch(base_url, batch_id, poll_interval=5):
|
||||
"""Poll batch status until complete. Returns final status."""
|
||||
while True:
|
||||
result = api_call(base_url, f"/api/lab/status?batchId={batch_id}")
|
||||
result = api_call(base_url, f"/api/lab/status/{batch_id}")
|
||||
if result is None:
|
||||
time.sleep(poll_interval)
|
||||
continue
|
||||
|
||||
@@ -1,220 +0,0 @@
|
||||
"""Async SQLite wrapper for FastAPI — eliminates event-loop blocking.
|
||||
|
||||
Drop-in async replacements for the sync helpers in services/database.py.
|
||||
Uses aiosqlite under the hood so every DB call yields back to the
|
||||
event loop instead of freezing it.
|
||||
|
||||
Usage in route handlers:
|
||||
from services.async_db import async_get_db, async_execute, async_fetchall
|
||||
|
||||
rows = await async_fetchall("SELECT * FROM decks")
|
||||
row = await async_fetchone("SELECT * FROM decks WHERE id = ?", (1,))
|
||||
await async_execute("INSERT INTO ...", params)
|
||||
await async_execute_commit("DELETE FROM ...", params)
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
from pathlib import Path
|
||||
from typing import Any, Optional
|
||||
|
||||
import aiosqlite
|
||||
|
||||
log = logging.getLogger("commander_ai_lab.async_db")
|
||||
|
||||
# Re-use the same DB path as the sync module
|
||||
COLLECTION_DB_PATH = Path(__file__).parent.parent / "collection.db"
|
||||
|
||||
# Module-level connection (lazy-init, one per process)
|
||||
_aconn: Optional[aiosqlite.Connection] = None
|
||||
|
||||
|
||||
async def async_get_db() -> aiosqlite.Connection:
|
||||
"""Return (or create) the module-level async SQLite connection."""
|
||||
global _aconn
|
||||
if _aconn is None:
|
||||
_aconn = await aiosqlite.connect(str(COLLECTION_DB_PATH))
|
||||
_aconn.row_factory = aiosqlite.Row
|
||||
await _aconn.execute("PRAGMA journal_mode=WAL")
|
||||
log.info("Async SQLite connection opened: %s", COLLECTION_DB_PATH)
|
||||
return _aconn
|
||||
|
||||
|
||||
async def async_close_db() -> None:
|
||||
"""Close the module-level connection (call on shutdown)."""
|
||||
global _aconn
|
||||
if _aconn is not None:
|
||||
await _aconn.close()
|
||||
_aconn = None
|
||||
log.info("Async SQLite connection closed.")
|
||||
|
||||
|
||||
# ── Convenience helpers ─────────────────────────────────────────
|
||||
|
||||
async def async_fetchall(
|
||||
sql: str, params: tuple = (), *, conn: aiosqlite.Connection = None
|
||||
) -> list[dict]:
|
||||
"""Execute a SELECT and return all rows as dicts."""
|
||||
db = conn or await async_get_db()
|
||||
async with db.execute(sql, params) as cursor:
|
||||
columns = [d[0] for d in cursor.description]
|
||||
rows = await cursor.fetchall()
|
||||
return [dict(zip(columns, row)) for row in rows]
|
||||
|
||||
|
||||
async def async_fetchone(
|
||||
sql: str, params: tuple = (), *, conn: aiosqlite.Connection = None
|
||||
) -> Optional[dict]:
|
||||
"""Execute a SELECT and return one row as a dict (or None)."""
|
||||
db = conn or await async_get_db()
|
||||
async with db.execute(sql, params) as cursor:
|
||||
columns = [d[0] for d in cursor.description]
|
||||
row = await cursor.fetchone()
|
||||
return dict(zip(columns, row)) if row else None
|
||||
|
||||
|
||||
async def async_execute(
|
||||
sql: str, params: tuple = (), *, conn: aiosqlite.Connection = None
|
||||
) -> int:
|
||||
"""Execute a write statement. Returns lastrowid."""
|
||||
db = conn or await async_get_db()
|
||||
cursor = await db.execute(sql, params)
|
||||
return cursor.lastrowid
|
||||
|
||||
|
||||
async def async_execute_commit(
|
||||
sql: str, params: tuple = (), *, conn: aiosqlite.Connection = None
|
||||
) -> int:
|
||||
"""Execute a write statement and commit. Returns lastrowid."""
|
||||
db = conn or await async_get_db()
|
||||
cursor = await db.execute(sql, params)
|
||||
await db.commit()
|
||||
return cursor.lastrowid
|
||||
|
||||
|
||||
async def async_executemany_commit(
|
||||
sql: str, params_seq, *, conn: aiosqlite.Connection = None
|
||||
) -> None:
|
||||
"""Execute many and commit."""
|
||||
db = conn or await async_get_db()
|
||||
await db.executemany(sql, params_seq)
|
||||
await db.commit()
|
||||
|
||||
|
||||
async def async_commit(*, conn: aiosqlite.Connection = None) -> None:
|
||||
"""Commit the current transaction."""
|
||||
db = conn or await async_get_db()
|
||||
await db.commit()
|
||||
|
||||
|
||||
# ── JSON field helpers (mirrors database._row_to_dict) ──────────
|
||||
|
||||
_JSON_FIELDS = ("category", "color_identity", "subtypes", "keywords")
|
||||
|
||||
|
||||
def row_to_dict_parsed(row: dict) -> dict:
|
||||
"""Parse JSON string columns into Python lists (same as database._row_to_dict)."""
|
||||
if row is None:
|
||||
return None
|
||||
d = dict(row)
|
||||
for f in _JSON_FIELDS:
|
||||
if f in d and isinstance(d[f], str):
|
||||
try:
|
||||
d[f] = json.loads(d[f])
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
d[f] = []
|
||||
return d
|
||||
|
||||
|
||||
# ── Coach session async helpers ─────────────────────────────────
|
||||
|
||||
async def async_save_coach_session(session_data: dict) -> int:
|
||||
"""Insert or update a coach session. Returns row id."""
|
||||
db = await async_get_db()
|
||||
existing = await async_fetchone(
|
||||
"SELECT id FROM coach_sessions WHERE session_id = ?",
|
||||
(session_data["session_id"],),
|
||||
)
|
||||
if existing:
|
||||
await db.execute(
|
||||
"""UPDATE coach_sessions SET
|
||||
deck_id=?, timestamp=?, model_used=?, prompt_tokens=?,
|
||||
completion_tokens=?, summary=?, goals_json=?, cuts_json=?,
|
||||
adds_json=?, heuristic_hints_json=?, mana_base_advice=?,
|
||||
raw_text=?
|
||||
WHERE session_id=?""",
|
||||
(
|
||||
session_data.get("deck_id", ""),
|
||||
session_data.get("timestamp", ""),
|
||||
session_data.get("model_used", ""),
|
||||
session_data.get("prompt_tokens", 0),
|
||||
session_data.get("completion_tokens", 0),
|
||||
session_data.get("summary", ""),
|
||||
session_data.get("goals_json", "{}"),
|
||||
session_data.get("cuts_json", "[]"),
|
||||
session_data.get("adds_json", "[]"),
|
||||
session_data.get("heuristic_hints_json", "[]"),
|
||||
session_data.get("mana_base_advice", ""),
|
||||
session_data.get("raw_text", ""),
|
||||
session_data["session_id"],
|
||||
),
|
||||
)
|
||||
await db.commit()
|
||||
return existing["id"]
|
||||
else:
|
||||
cursor = await db.execute(
|
||||
"""INSERT INTO coach_sessions
|
||||
(session_id, deck_id, timestamp, model_used, prompt_tokens,
|
||||
completion_tokens, summary, goals_json, cuts_json, adds_json,
|
||||
heuristic_hints_json, mana_base_advice, raw_text)
|
||||
VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?)""",
|
||||
(
|
||||
session_data["session_id"],
|
||||
session_data.get("deck_id", ""),
|
||||
session_data.get("timestamp", ""),
|
||||
session_data.get("model_used", ""),
|
||||
session_data.get("prompt_tokens", 0),
|
||||
session_data.get("completion_tokens", 0),
|
||||
session_data.get("summary", ""),
|
||||
session_data.get("goals_json", "{}"),
|
||||
session_data.get("cuts_json", "[]"),
|
||||
session_data.get("adds_json", "[]"),
|
||||
session_data.get("heuristic_hints_json", "[]"),
|
||||
session_data.get("mana_base_advice", ""),
|
||||
session_data.get("raw_text", ""),
|
||||
),
|
||||
)
|
||||
await db.commit()
|
||||
return cursor.lastrowid
|
||||
|
||||
|
||||
async def async_load_coach_session(session_id: str) -> Optional[dict]:
|
||||
"""Load a single coach session by session_id."""
|
||||
return await async_fetchone(
|
||||
"SELECT * FROM coach_sessions WHERE session_id = ?", (session_id,)
|
||||
)
|
||||
|
||||
|
||||
async def async_list_coach_sessions(deck_id: str = None) -> list[dict]:
|
||||
"""List coach sessions, optionally filtered by deck_id."""
|
||||
if deck_id:
|
||||
return await async_fetchall(
|
||||
"SELECT session_id, deck_id, timestamp, summary, created_at "
|
||||
"FROM coach_sessions WHERE deck_id = ? ORDER BY timestamp DESC",
|
||||
(deck_id,),
|
||||
)
|
||||
return await async_fetchall(
|
||||
"SELECT session_id, deck_id, timestamp, summary, created_at "
|
||||
"FROM coach_sessions ORDER BY timestamp DESC"
|
||||
)
|
||||
|
||||
|
||||
async def async_delete_coach_session(session_id: str) -> bool:
|
||||
"""Delete a coach session. Returns True if a row was deleted."""
|
||||
db = await async_get_db()
|
||||
cursor = await db.execute(
|
||||
"DELETE FROM coach_sessions WHERE session_id = ?", (session_id,)
|
||||
)
|
||||
await db.commit()
|
||||
return cursor.rowcount > 0
|
||||
@@ -15,14 +15,6 @@ def _detect_card_roles(oracle_text: str, type_line: str, keywords) -> list:
|
||||
kw_raw = []
|
||||
kw = " ".join(str(k).lower() for k in kw_raw)
|
||||
|
||||
# Land check must come first — basic lands have empty oracle_text so every
|
||||
# other check below would silently miss them, leaving them as Unknown role.
|
||||
if "land" in tl:
|
||||
roles.append("Land")
|
||||
if not ot:
|
||||
# Basic lands have no oracle text; no other role applies.
|
||||
return roles
|
||||
|
||||
if ("add {" in ot or "add one mana" in ot
|
||||
or ("search your library for a" in ot and "land" in ot)
|
||||
or "treasure token" in ot or "add mana" in ot):
|
||||
@@ -86,4 +78,4 @@ def _detect_card_roles(oracle_text: str, type_line: str, keywords) -> list:
|
||||
or "take an extra" in ot
|
||||
or ("double" in ot and ("damage" in ot or "counters" in ot or "tokens" in ot))):
|
||||
roles.append("Combo")
|
||||
return roles
|
||||
return roles
|
||||
@@ -1,37 +0,0 @@
|
||||
"""
|
||||
services/card_text.py
|
||||
=====================
|
||||
Shared utility for building card text representations.
|
||||
|
||||
Both services/rag_store.py and coach/embeddings.py need to produce
|
||||
identical text strings for embedding so that vector similarity is
|
||||
consistent across both systems. This module provides a single
|
||||
canonical implementation.
|
||||
|
||||
Format: Name | Mana Cost | Type | Oracle Text
|
||||
(fields that are empty/missing are omitted)
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
|
||||
def build_card_text(card: dict) -> str:
|
||||
"""Build the canonical text representation of a card for embedding.
|
||||
|
||||
Args:
|
||||
card: Dict with keys 'name', 'mana_cost', 'type_line', 'oracle_text'.
|
||||
Missing keys are treated as empty strings.
|
||||
|
||||
Returns:
|
||||
Pipe-separated string like 'Sol Ring | {1} | Artifact | {T}: Add {C}{C}.'
|
||||
"""
|
||||
parts = [card.get("name", "") or ""]
|
||||
mana_cost = card.get("mana_cost", "") or ""
|
||||
if mana_cost:
|
||||
parts.append(mana_cost)
|
||||
type_line = card.get("type_line", "") or ""
|
||||
if type_line:
|
||||
parts.append(type_line)
|
||||
oracle = card.get("oracle_text", "") or ""
|
||||
if oracle:
|
||||
parts.append(oracle)
|
||||
return " | ".join(parts)
|
||||
@@ -136,28 +136,6 @@ def init_collection_db() -> None:
|
||||
FOREIGN KEY (deck_id) REFERENCES decks(id) ON DELETE CASCADE
|
||||
);
|
||||
|
||||
CREATE TABLE IF NOT EXISTS coach_sessions (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
session_id TEXT NOT NULL UNIQUE,
|
||||
deck_id TEXT NOT NULL,
|
||||
timestamp TEXT NOT NULL,
|
||||
model_used TEXT DEFAULT '',
|
||||
prompt_tokens INTEGER DEFAULT 0,
|
||||
completion_tokens INTEGER DEFAULT 0,
|
||||
summary TEXT DEFAULT '',
|
||||
goals_json TEXT DEFAULT '{}',
|
||||
cuts_json TEXT DEFAULT '[]',
|
||||
adds_json TEXT DEFAULT '[]',
|
||||
heuristic_hints_json TEXT DEFAULT '[]',
|
||||
mana_base_advice TEXT DEFAULT '',
|
||||
raw_text TEXT DEFAULT '',
|
||||
created_at TEXT DEFAULT (datetime('now'))
|
||||
);
|
||||
|
||||
CREATE INDEX IF NOT EXISTS idx_cs_session_id ON coach_sessions(session_id);
|
||||
CREATE INDEX IF NOT EXISTS idx_cs_deck_id ON coach_sessions(deck_id);
|
||||
CREATE INDEX IF NOT EXISTS idx_cs_timestamp ON coach_sessions(timestamp);
|
||||
|
||||
CREATE INDEX IF NOT EXISTS idx_dc_deck_id ON deck_cards(deck_id);
|
||||
CREATE INDEX IF NOT EXISTS idx_dc_scryfall_id ON deck_cards(scryfall_id);
|
||||
CREATE INDEX IF NOT EXISTS idx_dk_commander ON decks(commander_scryfall_id);
|
||||
@@ -324,105 +302,3 @@ def _build_collection_filters(
|
||||
conditions.append("quantity <= ?"); params.append(qtyMax)
|
||||
where_str = ("WHERE " + " AND ".join(conditions)) if conditions else ""
|
||||
return where_str, params
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Coach Session DB Helpers
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
def save_coach_session(session_data: dict) -> int:
|
||||
"""Insert or update a coach session in SQLite. Returns the row id."""
|
||||
conn = _get_db_conn()
|
||||
existing = conn.execute(
|
||||
"SELECT id FROM coach_sessions WHERE session_id = ?",
|
||||
(session_data["session_id"],),
|
||||
).fetchone()
|
||||
if existing:
|
||||
conn.execute(
|
||||
"""UPDATE coach_sessions SET
|
||||
deck_id=?, timestamp=?, model_used=?, prompt_tokens=?,
|
||||
completion_tokens=?, summary=?, goals_json=?, cuts_json=?,
|
||||
adds_json=?, heuristic_hints_json=?, mana_base_advice=?,
|
||||
raw_text=?
|
||||
WHERE session_id=?""",
|
||||
(
|
||||
session_data.get("deck_id", ""),
|
||||
session_data.get("timestamp", ""),
|
||||
session_data.get("model_used", ""),
|
||||
session_data.get("prompt_tokens", 0),
|
||||
session_data.get("completion_tokens", 0),
|
||||
session_data.get("summary", ""),
|
||||
session_data.get("goals_json", "{}"),
|
||||
session_data.get("cuts_json", "[]"),
|
||||
session_data.get("adds_json", "[]"),
|
||||
session_data.get("heuristic_hints_json", "[]"),
|
||||
session_data.get("mana_base_advice", ""),
|
||||
session_data.get("raw_text", ""),
|
||||
session_data["session_id"],
|
||||
),
|
||||
)
|
||||
conn.commit()
|
||||
return existing["id"]
|
||||
else:
|
||||
cur = conn.execute(
|
||||
"""INSERT INTO coach_sessions
|
||||
(session_id, deck_id, timestamp, model_used, prompt_tokens,
|
||||
completion_tokens, summary, goals_json, cuts_json, adds_json,
|
||||
heuristic_hints_json, mana_base_advice, raw_text)
|
||||
VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?)""",
|
||||
(
|
||||
session_data["session_id"],
|
||||
session_data.get("deck_id", ""),
|
||||
session_data.get("timestamp", ""),
|
||||
session_data.get("model_used", ""),
|
||||
session_data.get("prompt_tokens", 0),
|
||||
session_data.get("completion_tokens", 0),
|
||||
session_data.get("summary", ""),
|
||||
session_data.get("goals_json", "{}"),
|
||||
session_data.get("cuts_json", "[]"),
|
||||
session_data.get("adds_json", "[]"),
|
||||
session_data.get("heuristic_hints_json", "[]"),
|
||||
session_data.get("mana_base_advice", ""),
|
||||
session_data.get("raw_text", ""),
|
||||
),
|
||||
)
|
||||
conn.commit()
|
||||
return cur.lastrowid
|
||||
|
||||
|
||||
def load_coach_session(session_id: str) -> Optional[dict]:
|
||||
"""Load a single coach session by session_id."""
|
||||
conn = _get_db_conn()
|
||||
row = conn.execute(
|
||||
"SELECT * FROM coach_sessions WHERE session_id = ?", (session_id,)
|
||||
).fetchone()
|
||||
return dict(row) if row else None
|
||||
|
||||
|
||||
def list_coach_sessions(deck_id: str = None) -> list:
|
||||
"""List coach sessions, optionally filtered by deck_id."""
|
||||
conn = _get_db_conn()
|
||||
if deck_id:
|
||||
rows = conn.execute(
|
||||
"SELECT session_id, deck_id, timestamp, summary, created_at "
|
||||
"FROM coach_sessions WHERE deck_id = ? ORDER BY timestamp DESC",
|
||||
(deck_id,),
|
||||
).fetchall()
|
||||
else:
|
||||
rows = conn.execute(
|
||||
"SELECT session_id, deck_id, timestamp, summary, created_at "
|
||||
"FROM coach_sessions ORDER BY timestamp DESC"
|
||||
).fetchall()
|
||||
return [dict(r) for r in rows]
|
||||
|
||||
|
||||
def delete_coach_session(session_id: str) -> bool:
|
||||
"""Delete a coach session. Returns True if a row was deleted."""
|
||||
conn = _get_db_conn()
|
||||
cur = conn.execute(
|
||||
"DELETE FROM coach_sessions WHERE session_id = ?", (session_id,)
|
||||
)
|
||||
conn.commit()
|
||||
return cur.rowcount > 0
|
||||
|
||||
+266
-297
@@ -1,297 +1,266 @@
|
||||
"""Deck service: .dck parsing, deck profile saving, deck loading."""
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import re
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
from fastapi import HTTPException
|
||||
|
||||
from models.state import CFG
|
||||
from services.database import _get_db_conn, _row_to_dict
|
||||
|
||||
log_collect = logging.getLogger("lab.collection")
|
||||
|
||||
|
||||
_TYPE_PRIORITY = ["Land", "Instant", "Sorcery", "Artifact", "Enchantment", "Planeswalker", "Creature"]
|
||||
_TYPE_TARGETS = {
|
||||
"Land": [36, 38],
|
||||
"Instant": [9, 11],
|
||||
"Sorcery": [7, 9],
|
||||
"Artifact": [9, 11],
|
||||
"Creature": [20, 30],
|
||||
"Enchantment": [5, 10],
|
||||
"Planeswalker": [0, 5],
|
||||
}
|
||||
|
||||
|
||||
def _classify_card_type(type_line: str) -> str:
|
||||
tl = type_line or ""
|
||||
for t in _TYPE_PRIORITY:
|
||||
if t in tl:
|
||||
return t
|
||||
return "Other"
|
||||
|
||||
|
||||
_CATEGORY_MAP = {
|
||||
"Ramp": ["search your library for a", "add one mana", "add {c}", "{t}: add"],
|
||||
"Removal": ["destroy target", "exile target", "counter target spell"],
|
||||
"Draw": ["draw a card", "draw two", "draw three", "draw cards"],
|
||||
"Board Wipe": ["destroy all", "exile all", "all creatures get -"],
|
||||
"Protection": ["hexproof", "indestructible", "shroud", "ward"],
|
||||
"Tutor": ["search your library"],
|
||||
}
|
||||
|
||||
|
||||
def _classify_card_category(type_line: str, oracle_text: str) -> str:
|
||||
"""Assign a functional category based on type_line and oracle text."""
|
||||
card_type = _classify_card_type(type_line)
|
||||
if card_type == "Land":
|
||||
return "Land"
|
||||
text = (oracle_text or "").lower()
|
||||
for cat, phrases in _CATEGORY_MAP.items():
|
||||
if any(p in text for p in phrases):
|
||||
return cat
|
||||
if card_type == "Creature":
|
||||
return "Creature"
|
||||
return card_type
|
||||
|
||||
|
||||
def _get_deck_or_404(deck_id: int):
|
||||
conn = _get_db_conn()
|
||||
row = conn.execute("SELECT * FROM decks WHERE id = ?", (deck_id,)).fetchone()
|
||||
if not row:
|
||||
raise HTTPException(404, f"Deck {deck_id} not found")
|
||||
d = dict(row)
|
||||
try:
|
||||
d["color_identity"] = json.loads(d.get("color_identity", "[]"))
|
||||
except Exception:
|
||||
d["color_identity"] = []
|
||||
return d
|
||||
|
||||
|
||||
def _compute_deck_analysis(deck_id: int) -> dict:
|
||||
conn = _get_db_conn()
|
||||
rows = conn.execute("""
|
||||
SELECT dc.id, dc.scryfall_id, dc.card_name, dc.quantity, dc.is_commander, dc.role_tag,
|
||||
COALESCE(ce.type_line, cr.type_line, '') as type_line,
|
||||
COALESCE(ce.oracle_text, cr.oracle_text, '') as oracle_text,
|
||||
COALESCE(ce.keywords, cr.keywords, '[]') as keywords,
|
||||
COALESCE(ce.cmc, cr.cmc, 0) as cmc,
|
||||
COALESCE(ce.color_identity, cr.color_identity, '[]') as color_identity
|
||||
FROM deck_cards dc
|
||||
LEFT JOIN (
|
||||
SELECT scryfall_id, type_line, oracle_text, keywords, cmc, color_identity
|
||||
FROM collection_entries GROUP BY scryfall_id
|
||||
) ce ON ce.scryfall_id = dc.scryfall_id
|
||||
LEFT JOIN (
|
||||
SELECT name, type_line, oracle_text, keywords, cmc, color_identity
|
||||
FROM card_records GROUP BY name
|
||||
) cr ON cr.name = dc.card_name
|
||||
WHERE dc.deck_id = ?
|
||||
""", (deck_id,)).fetchall()
|
||||
counts_by_type = {t: 0 for t in _TYPE_PRIORITY}
|
||||
counts_by_type["Other"] = 0
|
||||
mana_curve = {"0": 0, "1": 0, "2": 0, "3": 0, "4": 0, "5": 0, "6+": 0}
|
||||
color_pips = {"W": 0, "U": 0, "B": 0, "R": 0, "G": 0, "C": 0}
|
||||
total_cards = 0
|
||||
roles_count = {}
|
||||
for row in rows:
|
||||
r = dict(row)
|
||||
qty = r.get("quantity", 1)
|
||||
total_cards += qty
|
||||
card_type = _classify_card_type(r.get("type_line", ""))
|
||||
counts_by_type[card_type] = counts_by_type.get(card_type, 0) + qty
|
||||
cmc = int(r.get("cmc", 0) or 0)
|
||||
if card_type != "Land":
|
||||
key = str(min(cmc, 6)) if cmc < 6 else "6+"
|
||||
mana_curve[key] = mana_curve.get(key, 0) + qty
|
||||
ci_raw = r.get("color_identity", "[]")
|
||||
if isinstance(ci_raw, str):
|
||||
try:
|
||||
ci_raw = json.loads(ci_raw)
|
||||
except Exception:
|
||||
ci_raw = []
|
||||
for c in (ci_raw or []):
|
||||
if c in color_pips:
|
||||
color_pips[c] += qty
|
||||
role = r.get("role_tag") or "Unknown"
|
||||
roles_count[role] = roles_count.get(role, 0) + qty
|
||||
return {
|
||||
"total_cards": total_cards,
|
||||
"counts_by_type": counts_by_type,
|
||||
"mana_curve": mana_curve,
|
||||
"color_pips": color_pips,
|
||||
"roles": roles_count,
|
||||
}
|
||||
|
||||
|
||||
def _check_ratio_limit(deck_id: int, card_type: str, count_to_add: int = 1) -> bool:
|
||||
analysis = _compute_deck_analysis(deck_id)
|
||||
current = analysis["counts_by_type"].get(card_type, 0)
|
||||
target_max = _TYPE_TARGETS.get(card_type, [0, 9999])[1]
|
||||
return (current + count_to_add) <= target_max
|
||||
|
||||
|
||||
def _to_edhrec_slug(name: str) -> str:
|
||||
slug = name.lower()
|
||||
slug = re.sub(r"[',.]" , "", slug)
|
||||
slug = re.sub(r"[^a-z0-9]+", "-", slug)
|
||||
return slug.strip("-")
|
||||
|
||||
|
||||
def parse_dck_file(deck_path: str) -> dict:
|
||||
"""Parse a Forge .dck file into {name, commanders, mainboard, colorIdentity, totalCards}."""
|
||||
path = Path(deck_path)
|
||||
if not path.exists():
|
||||
return {"error": f"File not found: {deck_path}"}
|
||||
lines = path.read_text(encoding="utf-8", errors="replace").splitlines()
|
||||
name = path.stem
|
||||
section = "main"
|
||||
commanders: dict = {}
|
||||
mainboard: dict = {}
|
||||
commander_name = None
|
||||
for line in lines:
|
||||
line = line.strip()
|
||||
if not line or line.startswith("#"):
|
||||
continue
|
||||
if line == "[metadata]":
|
||||
section = "metadata"; continue
|
||||
if line.startswith("Name="):
|
||||
name = line.split("=", 1)[1].strip(); continue
|
||||
if line == "[Commander]":
|
||||
section = "commander"; continue
|
||||
if line == "[Main]":
|
||||
section = "main"; continue
|
||||
if line.lower().startswith("sideboard") or line == "[Sideboard]":
|
||||
section = "sideboard"; continue
|
||||
clean = re.sub(r"\(\w+\)\s*\d*$", "", line).strip()
|
||||
clean = re.sub(r"\s*\*\.\*$", "", clean).strip()
|
||||
m = re.match(r"^(\d+)x?\s+(.+)$", clean)
|
||||
qty, card_name = (int(m.group(1)), m.group(2).strip()) if m else (1, clean)
|
||||
if not card_name:
|
||||
continue
|
||||
if section == "commander":
|
||||
commanders[card_name] = qty
|
||||
if not commander_name:
|
||||
commander_name = card_name
|
||||
elif section != "sideboard":
|
||||
mainboard[card_name] = qty
|
||||
if commander_name:
|
||||
name = f"{commander_name} - Text Import"
|
||||
total = sum(commanders.values()) + sum(mainboard.values())
|
||||
return {"name": name, "commander": commander_name, "commanders": commanders, "mainboard": mainboard, "colorIdentity": [], "totalCards": total}
|
||||
|
||||
|
||||
def _save_profile_to_dck(profile: dict) -> Path:
|
||||
lines = ["[metadata]", f"Name={profile.get('name', 'Imported Deck')}", "", "[Commander]"]
|
||||
for name, qty in profile.get("commanders", {}).items():
|
||||
lines.append(f"{qty} {name}")
|
||||
lines += ["", "[Main]"]
|
||||
for name, qty in profile.get("mainboard", {}).items():
|
||||
lines.append(f"{qty} {name}")
|
||||
content = "\n".join(lines)
|
||||
safe_name = re.sub(r"[^a-zA-Z0-9 _-]", "", profile.get("name", "imported")).replace(" ", "_").strip()
|
||||
if not safe_name:
|
||||
safe_name = "imported_deck"
|
||||
save_dir = CFG.forge_decks_dir
|
||||
if not save_dir or not os.path.isdir(save_dir):
|
||||
save_dir = os.path.join(Path(__file__).parent.parent, "imported-decks")
|
||||
os.makedirs(save_dir, exist_ok=True)
|
||||
out_path = Path(save_dir) / f"{safe_name}.dck"
|
||||
out_path.write_text(content, encoding="utf-8")
|
||||
log_collect.info(f" Saved .dck: {out_path}")
|
||||
return out_path
|
||||
|
||||
|
||||
def _load_deck_cards_by_name(deck_name: str) -> list:
|
||||
"""Load cards from a deck by name, returning list of card dicts."""
|
||||
conn = _get_db_conn()
|
||||
deck_row = conn.execute("SELECT id FROM decks WHERE name = ?", (deck_name,)).fetchone()
|
||||
if not deck_row:
|
||||
return []
|
||||
deck_id = deck_row[0]
|
||||
rows = conn.execute("""
|
||||
SELECT dc.card_name, dc.quantity, dc.is_commander, dc.role_tag, dc.scryfall_id,
|
||||
COALESCE(ce.type_line, cr.type_line, '') as type_line,
|
||||
COALESCE(ce.oracle_text, cr.oracle_text, '') as oracle_text,
|
||||
COALESCE(ce.cmc, cr.cmc, 0) as cmc,
|
||||
COALESCE(ce.color_identity, cr.color_identity, '[]') as color_identity,
|
||||
COALESCE(ce.mana_cost, '', '') as mana_cost,
|
||||
COALESCE(ce.power, '', '') as power,
|
||||
COALESCE(ce.toughness, '', '') as toughness,
|
||||
COALESCE(ce.keywords, cr.keywords, '[]') as keywords
|
||||
FROM deck_cards dc
|
||||
LEFT JOIN (
|
||||
SELECT scryfall_id, type_line, oracle_text, cmc, color_identity, mana_cost, power, toughness, keywords
|
||||
FROM collection_entries GROUP BY scryfall_id
|
||||
) ce ON ce.scryfall_id = dc.scryfall_id
|
||||
LEFT JOIN (
|
||||
SELECT name, type_line, oracle_text, cmc, color_identity, keywords
|
||||
FROM card_records GROUP BY name
|
||||
) cr ON cr.name = dc.card_name
|
||||
WHERE dc.deck_id = ?
|
||||
""", (deck_id,)).fetchall()
|
||||
return [_row_to_dict(r) for r in rows]
|
||||
|
||||
|
||||
log_deckgen = logging.getLogger("commander_ai_lab.deckgen")
|
||||
|
||||
|
||||
def _build_dck_lines(
|
||||
deck_name: str,
|
||||
commander_name: str,
|
||||
cards: list[dict],
|
||||
*,
|
||||
resolve_substitutes: bool = False,
|
||||
) -> list[str]:
|
||||
"""Build Forge .dck file lines from deck name, commander, and card list."""
|
||||
lines: list[str] = [
|
||||
"[metadata]",
|
||||
f"Name={deck_name}",
|
||||
"",
|
||||
"[Commander]",
|
||||
f"1 {commander_name}",
|
||||
"",
|
||||
"[Main]",
|
||||
]
|
||||
for card in cards:
|
||||
cname = card.get("name", "")
|
||||
if resolve_substitutes:
|
||||
if card.get("status") == "substituted" and card.get("selected_substitute"):
|
||||
cname = card["selected_substitute"]
|
||||
if cname and cname != commander_name:
|
||||
lines.append(f"{card.get('count', card.get('quantity', 1))} {cname}")
|
||||
return lines
|
||||
|
||||
|
||||
def _write_dck_file(
|
||||
deck_name: str,
|
||||
commander_name: str,
|
||||
cards: list[dict],
|
||||
decks_dir: str | None = None,
|
||||
*,
|
||||
fallback_id: int | str = 0,
|
||||
resolve_substitutes: bool = False,
|
||||
) -> str | None:
|
||||
"""Write a Forge .dck file to decks_dir. Returns path on success, None otherwise."""
|
||||
if not decks_dir:
|
||||
decks_dir = CFG.forge_decks_dir
|
||||
if not decks_dir or not os.path.isdir(decks_dir):
|
||||
return None
|
||||
|
||||
safe_name = re.sub(r"[^a-zA-Z0-9_\-\s]", "", deck_name).strip().replace(" ", "_")
|
||||
if not safe_name:
|
||||
safe_name = f"Deck_{fallback_id}"
|
||||
|
||||
dck_path = os.path.join(decks_dir, f"{safe_name}.dck")
|
||||
lines = _build_dck_lines(
|
||||
deck_name, commander_name, cards,
|
||||
resolve_substitutes=resolve_substitutes,
|
||||
)
|
||||
with open(dck_path, "w", encoding="utf-8") as f:
|
||||
f.write("\n".join(lines))
|
||||
|
||||
log_deckgen.info(f" Exported .dck: {dck_path}")
|
||||
return dck_path
|
||||
"""Deck service: .dck parsing, deck profile saving, deck loading."""
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import re
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
from fastapi import HTTPException
|
||||
|
||||
from models.state import CFG
|
||||
from services.database import _get_db_conn, _row_to_dict
|
||||
|
||||
log_collect = logging.getLogger("lab.collection")
|
||||
|
||||
|
||||
_TYPE_PRIORITY = ["Land", "Instant", "Sorcery", "Artifact", "Enchantment", "Planeswalker", "Creature"]
|
||||
_TYPE_TARGETS = {
|
||||
"Land": [36, 38],
|
||||
"Instant": [9, 11],
|
||||
"Sorcery": [7, 9],
|
||||
"Artifact": [9, 11],
|
||||
"Creature": [20, 30],
|
||||
"Enchantment": [5, 10],
|
||||
"Planeswalker": [0, 5],
|
||||
}
|
||||
|
||||
|
||||
def _classify_card_type(type_line: str) -> str:
|
||||
tl = type_line or ""
|
||||
for t in _TYPE_PRIORITY:
|
||||
if t in tl:
|
||||
return t
|
||||
return "Other"
|
||||
|
||||
|
||||
def _get_deck_or_404(deck_id: int):
|
||||
conn = _get_db_conn()
|
||||
row = conn.execute("SELECT * FROM decks WHERE id = ?", (deck_id,)).fetchone()
|
||||
if not row:
|
||||
raise HTTPException(404, f"Deck {deck_id} not found")
|
||||
d = dict(row)
|
||||
try:
|
||||
d["color_identity"] = json.loads(d.get("color_identity", "[]"))
|
||||
except Exception:
|
||||
d["color_identity"] = []
|
||||
return d
|
||||
|
||||
|
||||
def _compute_deck_analysis(deck_id: int) -> dict:
|
||||
conn = _get_db_conn()
|
||||
rows = conn.execute("""
|
||||
SELECT dc.id, dc.scryfall_id, dc.card_name, dc.quantity, dc.is_commander, dc.role_tag,
|
||||
ce.type_line, ce.oracle_text, ce.keywords, ce.cmc, ce.color_identity
|
||||
FROM deck_cards dc
|
||||
LEFT JOIN (
|
||||
SELECT scryfall_id, type_line, oracle_text, keywords, cmc, color_identity
|
||||
FROM collection_entries GROUP BY scryfall_id
|
||||
) ce ON ce.scryfall_id = dc.scryfall_id
|
||||
WHERE dc.deck_id = ?
|
||||
""", (deck_id,)).fetchall()
|
||||
counts_by_type = {t: 0 for t in _TYPE_PRIORITY}
|
||||
counts_by_type["Other"] = 0
|
||||
mana_curve = {"0": 0, "1": 0, "2": 0, "3": 0, "4": 0, "5": 0, "6+": 0}
|
||||
color_pips = {"W": 0, "U": 0, "B": 0, "R": 0, "G": 0, "C": 0}
|
||||
total_cards = 0
|
||||
roles_count = {}
|
||||
for row in rows:
|
||||
r = dict(row)
|
||||
qty = r.get("quantity", 1)
|
||||
total_cards += qty
|
||||
card_type = _classify_card_type(r.get("type_line", ""))
|
||||
counts_by_type[card_type] = counts_by_type.get(card_type, 0) + qty
|
||||
cmc = int(r.get("cmc", 0) or 0)
|
||||
if card_type != "Land":
|
||||
key = str(min(cmc, 6)) if cmc < 6 else "6+"
|
||||
mana_curve[key] = mana_curve.get(key, 0) + qty
|
||||
ci_raw = r.get("color_identity", "[]")
|
||||
if isinstance(ci_raw, str):
|
||||
try:
|
||||
ci_raw = json.loads(ci_raw)
|
||||
except Exception:
|
||||
ci_raw = []
|
||||
for c in (ci_raw or []):
|
||||
if c in color_pips:
|
||||
color_pips[c] += qty
|
||||
role = r.get("role_tag") or "Unknown"
|
||||
roles_count[role] = roles_count.get(role, 0) + qty
|
||||
return {
|
||||
"total_cards": total_cards,
|
||||
"counts_by_type": counts_by_type,
|
||||
"mana_curve": mana_curve,
|
||||
"color_pips": color_pips,
|
||||
"total_cards": total_cards,
|
||||
"roles": roles_count,
|
||||
}
|
||||
|
||||
|
||||
def _check_ratio_limit(deck_id: int, card_type: str, count_to_add: int = 1) -> bool:
|
||||
analysis = _compute_deck_analysis(deck_id)
|
||||
current = analysis["counts_by_type"].get(card_type, 0)
|
||||
target_max = _TYPE_TARGETS.get(card_type, [0, 9999])[1]
|
||||
return (current + count_to_add) <= target_max
|
||||
|
||||
|
||||
def _to_edhrec_slug(name: str) -> str:
|
||||
slug = name.lower()
|
||||
slug = re.sub(r"[',.]" , "", slug)
|
||||
slug = re.sub(r"[^a-z0-9]+", "-", slug)
|
||||
return slug.strip("-")
|
||||
|
||||
|
||||
def parse_dck_file(deck_path: str) -> dict:
|
||||
"""Parse a Forge .dck file into {name, commanders, mainboard, colorIdentity, totalCards}."""
|
||||
path = Path(deck_path)
|
||||
if not path.exists():
|
||||
return {"error": f"File not found: {deck_path}"}
|
||||
lines = path.read_text(encoding="utf-8", errors="replace").splitlines()
|
||||
name = path.stem
|
||||
section = "main"
|
||||
commanders: dict = {}
|
||||
mainboard: dict = {}
|
||||
commander_name = None
|
||||
for line in lines:
|
||||
line = line.strip()
|
||||
if not line or line.startswith("#"):
|
||||
continue
|
||||
if line == "[metadata]":
|
||||
section = "metadata"; continue
|
||||
if line.startswith("Name="):
|
||||
name = line.split("=", 1)[1].strip(); continue
|
||||
if line == "[Commander]":
|
||||
section = "commander"; continue
|
||||
if line == "[Main]":
|
||||
section = "main"; continue
|
||||
if line.lower().startswith("sideboard") or line == "[Sideboard]":
|
||||
section = "sideboard"; continue
|
||||
clean = re.sub(r"\(\w+\)\s*\d*$", "", line).strip()
|
||||
clean = re.sub(r"\s*\*\.\*$", "", clean).strip()
|
||||
m = re.match(r"^(\d+)x?\s+(.+)$", clean)
|
||||
qty, card_name = (int(m.group(1)), m.group(2).strip()) if m else (1, clean)
|
||||
if not card_name:
|
||||
continue
|
||||
if section == "commander":
|
||||
commanders[card_name] = qty
|
||||
if not commander_name:
|
||||
commander_name = card_name
|
||||
elif section != "sideboard":
|
||||
mainboard[card_name] = qty
|
||||
if commander_name:
|
||||
name = f"{commander_name} - Text Import"
|
||||
total = sum(commanders.values()) + sum(mainboard.values())
|
||||
return {"name": name, "commander": commander_name, "commanders": commanders, "mainboard": mainboard, "colorIdentity": [], "totalCards": total}
|
||||
|
||||
|
||||
def _save_profile_to_dck(profile: dict) -> Path:
|
||||
lines = ["[metadata]", f"Name={profile.get('name', 'Imported Deck')}", "", "[Commander]"]
|
||||
for name, qty in profile.get("commanders", {}).items():
|
||||
lines.append(f"{qty} {name}")
|
||||
lines += ["", "[Main]"]
|
||||
for name, qty in profile.get("mainboard", {}).items():
|
||||
lines.append(f"{qty} {name}")
|
||||
content = "\n".join(lines)
|
||||
safe_name = re.sub(r"[^a-zA-Z0-9 _-]", "", profile.get("name", "imported")).replace(" ", "_").strip()
|
||||
if not safe_name:
|
||||
safe_name = "imported_deck"
|
||||
save_dir = CFG.forge_decks_dir
|
||||
if not save_dir or not os.path.isdir(save_dir):
|
||||
save_dir = os.path.join(Path(__file__).parent.parent, "imported-decks")
|
||||
os.makedirs(save_dir, exist_ok=True)
|
||||
out_path = Path(save_dir) / f"{safe_name}.dck"
|
||||
out_path.write_text(content, encoding="utf-8")
|
||||
log_collect.info(f" Saved .dck: {out_path}")
|
||||
return out_path
|
||||
|
||||
|
||||
def _load_deck_cards_by_name(deck_name: str) -> list:
|
||||
"""Load cards from a deck by name, returning list of card dicts."""
|
||||
conn = _get_db_conn()
|
||||
deck_row = conn.execute("SELECT id FROM decks WHERE name = ?", (deck_name,)).fetchone()
|
||||
if not deck_row:
|
||||
return []
|
||||
deck_id = deck_row[0]
|
||||
rows = conn.execute("""
|
||||
SELECT dc.card_name, dc.quantity, dc.is_commander, dc.role_tag, dc.scryfall_id,
|
||||
COALESCE(ce.type_line, cr.type_line, '') as type_line,
|
||||
COALESCE(ce.oracle_text, cr.oracle_text, '') as oracle_text,
|
||||
COALESCE(ce.cmc, cr.cmc, 0) as cmc,
|
||||
COALESCE(ce.color_identity, cr.color_identity, '[]') as color_identity,
|
||||
COALESCE(ce.mana_cost, '', '') as mana_cost,
|
||||
COALESCE(ce.power, '', '') as power,
|
||||
COALESCE(ce.toughness, '', '') as toughness,
|
||||
COALESCE(ce.keywords, cr.keywords, '[]') as keywords
|
||||
FROM deck_cards dc
|
||||
LEFT JOIN (
|
||||
SELECT scryfall_id, type_line, oracle_text, cmc, color_identity, mana_cost, power, toughness, keywords
|
||||
FROM collection_entries GROUP BY scryfall_id
|
||||
) ce ON ce.scryfall_id = dc.scryfall_id
|
||||
LEFT JOIN (
|
||||
SELECT name, type_line, oracle_text, cmc, color_identity, keywords
|
||||
FROM card_records GROUP BY name
|
||||
) cr ON cr.name = dc.card_name
|
||||
WHERE dc.deck_id = ?
|
||||
""", (deck_id,)).fetchall()
|
||||
return [_row_to_dict(r) for r in rows]
|
||||
|
||||
|
||||
log_deckgen = logging.getLogger("commander_ai_lab.deckgen")
|
||||
|
||||
|
||||
def _build_dck_lines(
|
||||
deck_name: str,
|
||||
commander_name: str,
|
||||
cards: list[dict],
|
||||
*,
|
||||
resolve_substitutes: bool = False,
|
||||
) -> list[str]:
|
||||
"""Build Forge .dck file lines from deck name, commander, and card list."""
|
||||
lines: list[str] = [
|
||||
"[metadata]",
|
||||
f"Name={deck_name}",
|
||||
"",
|
||||
"[Commander]",
|
||||
f"1 {commander_name}",
|
||||
"",
|
||||
"[Main]",
|
||||
]
|
||||
for card in cards:
|
||||
cname = card.get("name", "")
|
||||
if resolve_substitutes:
|
||||
if card.get("status") == "substituted" and card.get("selected_substitute"):
|
||||
cname = card["selected_substitute"]
|
||||
if cname and cname != commander_name:
|
||||
lines.append(f"{card.get('count', card.get('quantity', 1))} {cname}")
|
||||
return lines
|
||||
|
||||
|
||||
def _write_dck_file(
|
||||
deck_name: str,
|
||||
commander_name: str,
|
||||
cards: list[dict],
|
||||
decks_dir: str | None = None,
|
||||
*,
|
||||
fallback_id: int | str = 0,
|
||||
resolve_substitutes: bool = False,
|
||||
) -> str | None:
|
||||
"""Write a Forge .dck file to decks_dir. Returns path on success, None otherwise."""
|
||||
if not decks_dir:
|
||||
decks_dir = CFG.forge_decks_dir
|
||||
if not decks_dir or not os.path.isdir(decks_dir):
|
||||
return None
|
||||
|
||||
safe_name = re.sub(r"[^a-zA-Z0-9_\-\s]", "", deck_name).strip().replace(" ", "_")
|
||||
if not safe_name:
|
||||
safe_name = f"Deck_{fallback_id}"
|
||||
|
||||
dck_path = os.path.join(decks_dir, f"{safe_name}.dck")
|
||||
lines = _build_dck_lines(
|
||||
deck_name, commander_name, cards,
|
||||
resolve_substitutes=resolve_substitutes,
|
||||
)
|
||||
with open(dck_path, "w", encoding="utf-8") as f:
|
||||
f.write("\n".join(lines))
|
||||
|
||||
log_deckgen.info(f" Exported .dck: {dck_path}")
|
||||
return dck_path
|
||||
@@ -204,7 +204,6 @@ def build_java_command(
|
||||
cmd += ['--aiSimplified']
|
||||
if ai_think_time_ms > 0:
|
||||
cmd += ['--aiThinkTimeMs', str(ai_think_time_ms)]
|
||||
cmd += ['--ml-log']
|
||||
if max_queue_depth > 0:
|
||||
cmd += ['--maxQueueDepth', str(max_queue_depth)]
|
||||
return cmd
|
||||
@@ -317,7 +316,7 @@ def _get_deepseek_brain():
|
||||
model=os.environ.get("BRAIN_MODEL", "gpt-oss:20b"),
|
||||
temperature=float(os.environ.get("BRAIN_TEMPERATURE", "0.3")),
|
||||
max_tokens=int(os.environ.get("BRAIN_MAX_TOKENS", "1024")),
|
||||
request_timeout=float(os.environ.get("BRAIN_TIMEOUT", "300.0")),
|
||||
request_timeout=float(os.environ.get("BRAIN_TIMEOUT", "120.0")),
|
||||
)
|
||||
cfg.log_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), '..', 'logs', 'decisions')
|
||||
cfg.log_dir = os.path.normpath(cfg.log_dir)
|
||||
@@ -361,7 +360,7 @@ def _run_deepseek_batch_thread(
|
||||
results_dir = CFG.results_dir
|
||||
if os.path.isdir(results_dir):
|
||||
for fname in sorted(os.listdir(results_dir), reverse=True):
|
||||
if fname.startswith('ml-decision-') and fname.endswith('.json'):
|
||||
if fname.startswith('batch-') and fname.endswith('.json'):
|
||||
try:
|
||||
with open(os.path.join(results_dir, fname), 'r') as rf:
|
||||
past = json.loads(rf.read())
|
||||
|
||||
@@ -1,60 +0,0 @@
|
||||
"""
|
||||
services/logging.py
|
||||
====================
|
||||
Single source of truth for application logging configuration and named loggers.
|
||||
|
||||
Moved from routes/shared.py so that every layer (routes, services, CLI
|
||||
entry-points) can import logging without pulling in the full shared module.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import logging.handlers
|
||||
import os
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
# ── Format / rotation constants ───────────────────────────────────────────────
|
||||
_LOG_FORMAT = "%(asctime)s %(levelname)-5s [%(name)s] %(message)s"
|
||||
_LOG_DATE_FMT = "%Y-%m-%d %H:%M:%S"
|
||||
_LOG_DIR = Path(os.environ.get("CAL_LOG_DIR", "logs"))
|
||||
_LOG_MAX_BYTES = int(os.environ.get("CAL_LOG_MAX_MB", "25")) * 1024 * 1024
|
||||
_LOG_BACKUP_COUNT = int(os.environ.get("CAL_LOG_BACKUP_COUNT", "5"))
|
||||
|
||||
|
||||
def setup_logging(level: int = logging.INFO) -> None:
|
||||
_LOG_DIR.mkdir(parents=True, exist_ok=True)
|
||||
root_logger = logging.getLogger("commander_ai_lab")
|
||||
root_logger.setLevel(level)
|
||||
if root_logger.handlers:
|
||||
return
|
||||
formatter = logging.Formatter(_LOG_FORMAT, datefmt=_LOG_DATE_FMT)
|
||||
console = logging.StreamHandler(sys.stdout)
|
||||
console.setLevel(level)
|
||||
console.setFormatter(formatter)
|
||||
root_logger.addHandler(console)
|
||||
file_handler = logging.handlers.RotatingFileHandler(
|
||||
_LOG_DIR / "commander-ai-lab.log",
|
||||
maxBytes=_LOG_MAX_BYTES,
|
||||
backupCount=_LOG_BACKUP_COUNT,
|
||||
encoding="utf-8",
|
||||
)
|
||||
file_handler.setLevel(level)
|
||||
file_handler.setFormatter(formatter)
|
||||
root_logger.addHandler(file_handler)
|
||||
|
||||
|
||||
# ── Named loggers ────────────────────────────────────────────────────────────
|
||||
log = logging.getLogger("commander_ai_lab.api")
|
||||
log_batch = logging.getLogger("commander_ai_lab.batch")
|
||||
log_sim = logging.getLogger("commander_ai_lab.sim")
|
||||
log_coach = logging.getLogger("commander_ai_lab.coach")
|
||||
log_deckgen = logging.getLogger("commander_ai_lab.deckgen")
|
||||
log_collect = logging.getLogger("commander_ai_lab.collection")
|
||||
log_scan = logging.getLogger("commander_ai_lab.scanner")
|
||||
log_ml = logging.getLogger("commander_ai_lab.ml")
|
||||
log_cache = logging.getLogger("commander_ai_lab.cache")
|
||||
log_pplx = logging.getLogger("commander_ai_lab.pplx")
|
||||
|
||||
# ── ML logging toggle ────────────────────────────────────────────────────────
|
||||
_ml_logging_enabled = True
|
||||
@@ -1,558 +0,0 @@
|
||||
"""
|
||||
services/rag_store.py
|
||||
=====================
|
||||
ChromaDB-backed semantic vector store over the Scryfall bulk card database.
|
||||
|
||||
Reads all cards from the Phase 1 SQLite bulk DB (services/scryfall_bulk.py),
|
||||
embeds their oracle text using Ollama's nomic-embed-text model, and stores
|
||||
the vectors in a persistent ChromaDB collection on disk.
|
||||
|
||||
This is RAG Phase 2. Phase 3 will query this store to inject relevant card
|
||||
oracle text into the LLM prompt before calling the coach.
|
||||
|
||||
Public API:
|
||||
ensure_rag_store() -> None (build if missing / stale)
|
||||
build_index(force, batch_size) -> dict (explicit build, returns stats)
|
||||
query_cards(text, n, colors) -> list[dict]
|
||||
get_rag_stats() -> dict
|
||||
|
||||
Data path: ./data/rag_chroma/
|
||||
Embedding: nomic-embed-text via Ollama (localhost:11434)
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import time
|
||||
import threading
|
||||
from services.card_text import build_card_text
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
logger = logging.getLogger("commander_ai_lab.rag_store")
|
||||
|
||||
# ── Config ────────────────────────────────────────────────────────────────
|
||||
RAG_CHROMA_DIR = Path(__file__).parent.parent / "data" / "rag_chroma"
|
||||
BUILD_META_PATH = RAG_CHROMA_DIR / "build_meta.json"
|
||||
OLLAMA_BASE_URL = os.environ.get("OLLAMA_BASE_URL", "http://localhost:11434")
|
||||
EMBEDDING_MODEL = os.environ.get("RAG_EMBEDDING_MODEL", "nomic-embed-text")
|
||||
COLLECTION_NAME = "mtg_oracle"
|
||||
DEFAULT_BATCH_SIZE = 500
|
||||
_rag_lock = threading.Lock()
|
||||
_rag_ready = False
|
||||
|
||||
# Module-level singletons to avoid re-creating client/collection on every call
|
||||
_chroma_client = None
|
||||
_chroma_collection = None
|
||||
|
||||
|
||||
# ── Helpers ────────────────────────────────────────────────────────────────
|
||||
|
||||
def _build_document(card: dict) -> str:
|
||||
"""Delegate to shared build_card_text() -- see services/card_text.py."""
|
||||
return build_card_text(card)
|
||||
|
||||
|
||||
def _build_metadata(card: dict) -> dict:
|
||||
"""Build ChromaDB metadata dict for filtering."""
|
||||
ci_raw = card.get("color_identity", "[]")
|
||||
if isinstance(ci_raw, str):
|
||||
try:
|
||||
ci_list = json.loads(ci_raw)
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
ci_list = []
|
||||
else:
|
||||
ci_list = ci_raw or []
|
||||
|
||||
return {
|
||||
"name": card.get("name", ""),
|
||||
"type_line": card.get("type_line", ""),
|
||||
"cmc": float(card.get("cmc") or 0),
|
||||
"color_identity": ",".join(sorted(ci_list)),
|
||||
"rarity": card.get("rarity", ""),
|
||||
"mana_cost": card.get("mana_cost", ""),
|
||||
}
|
||||
|
||||
|
||||
def _get_chromadb_client():
|
||||
"""Return the module-level persistent ChromaDB client (singleton)."""
|
||||
global _chroma_client
|
||||
if _chroma_client is not None:
|
||||
return _chroma_client
|
||||
try:
|
||||
import chromadb
|
||||
except ImportError:
|
||||
raise ImportError(
|
||||
"chromadb is required for RAG Phase 2. "
|
||||
"Install with: pip install 'commander-ai-lab[rag]'"
|
||||
)
|
||||
RAG_CHROMA_DIR.mkdir(parents=True, exist_ok=True)
|
||||
_chroma_client = chromadb.PersistentClient(path=str(RAG_CHROMA_DIR))
|
||||
return _chroma_client
|
||||
|
||||
|
||||
def _get_ollama_embedding_fn():
|
||||
"""Return a ChromaDB-compatible embedding function using Ollama."""
|
||||
try:
|
||||
from chromadb.utils.embedding_functions import OllamaEmbeddingFunction
|
||||
except ImportError:
|
||||
raise ImportError(
|
||||
"chromadb >= 0.4.0 with Ollama support is required. "
|
||||
"Install with: pip install 'commander-ai-lab[rag]'"
|
||||
)
|
||||
return OllamaEmbeddingFunction(
|
||||
url=f"{OLLAMA_BASE_URL}/api/embeddings",
|
||||
model_name=EMBEDDING_MODEL,
|
||||
)
|
||||
|
||||
|
||||
def _get_collection():
|
||||
"""Return the ChromaDB collection singleton, creating it if needed."""
|
||||
global _chroma_collection
|
||||
if _chroma_collection is not None:
|
||||
return _chroma_collection
|
||||
client = _get_chromadb_client()
|
||||
embed_fn = _get_ollama_embedding_fn()
|
||||
_chroma_collection = client.get_or_create_collection(
|
||||
name=COLLECTION_NAME,
|
||||
embedding_function=embed_fn,
|
||||
metadata={"hnsw:space": "cosine"},
|
||||
)
|
||||
return _chroma_collection
|
||||
|
||||
|
||||
def _invalidate_collection_singleton() -> None:
|
||||
"""Reset the cached collection after a rebuild so the next call re-opens it."""
|
||||
global _chroma_collection
|
||||
_chroma_collection = None
|
||||
|
||||
|
||||
def _read_build_meta() -> dict:
|
||||
"""Read the sidecar build_meta.json, returning {} if missing or corrupt."""
|
||||
try:
|
||||
if BUILD_META_PATH.exists():
|
||||
return json.loads(BUILD_META_PATH.read_text(encoding="utf-8"))
|
||||
except Exception as exc:
|
||||
logger.warning("Could not read build_meta.json: %s", exc)
|
||||
return {}
|
||||
|
||||
|
||||
def _write_build_meta(card_count: int) -> None:
|
||||
"""Persist build timestamp and card count to sidecar JSON file."""
|
||||
try:
|
||||
RAG_CHROMA_DIR.mkdir(parents=True, exist_ok=True)
|
||||
BUILD_META_PATH.write_text(
|
||||
json.dumps({"built_at": time.time(), "card_count": card_count}),
|
||||
encoding="utf-8",
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.warning("Could not write build_meta.json: %s", exc)
|
||||
|
||||
|
||||
def _collection_is_current(collection, bulk_card_count: int) -> bool:
|
||||
"""Check if the ChromaDB collection is reasonably up-to-date.
|
||||
|
||||
Uses sidecar build_meta.json for the age check (survives restarts),
|
||||
and compares card count within a 5% tolerance.
|
||||
"""
|
||||
chroma_count = collection.count()
|
||||
if chroma_count == 0:
|
||||
return False
|
||||
|
||||
# Age check via sidecar file (not collection.metadata which doesn't persist)
|
||||
meta = _read_build_meta()
|
||||
built_at = meta.get("built_at", 0)
|
||||
if built_at:
|
||||
age_days = (time.time() - float(built_at)) / 86400
|
||||
if age_days > 14:
|
||||
logger.info("RAG collection older than 14 days (%0.1f) — rebuilding.", age_days)
|
||||
return False
|
||||
|
||||
ratio = chroma_count / max(bulk_card_count, 1)
|
||||
if ratio < 0.95 or ratio > 1.05:
|
||||
logger.info(
|
||||
"RAG collection count mismatch: chroma=%d, bulk=%d — rebuilding.",
|
||||
chroma_count, bulk_card_count,
|
||||
)
|
||||
return False
|
||||
return True
|
||||
|
||||
|
||||
# ── Build pipeline ────────────────────────────────────────────────────────────────
|
||||
|
||||
def _build_collection_from_bulk(batch_size: int = DEFAULT_BATCH_SIZE) -> dict:
|
||||
"""Read all cards from the bulk SQLite DB and insert into ChromaDB.
|
||||
|
||||
Args:
|
||||
batch_size: Number of cards to embed and insert per ChromaDB call.
|
||||
|
||||
Returns:
|
||||
Dict with keys: indexed (int), failed (int).
|
||||
|
||||
Raises:
|
||||
RuntimeError: If more than 1% of cards failed to insert.
|
||||
"""
|
||||
from services.scryfall_bulk import get_bulk_db
|
||||
|
||||
conn = get_bulk_db()
|
||||
cursor = conn.execute(
|
||||
"SELECT name, oracle_text, type_line, mana_cost, cmc, "
|
||||
"color_identity, rarity, scryfall_id FROM cards "
|
||||
"WHERE oracle_text != '' "
|
||||
"ORDER BY edhrec_rank ASC"
|
||||
)
|
||||
all_rows = cursor.fetchall()
|
||||
total_rows = len(all_rows)
|
||||
|
||||
client = _get_chromadb_client()
|
||||
embed_fn = _get_ollama_embedding_fn()
|
||||
|
||||
# Drop and recreate collection to ensure a clean build
|
||||
try:
|
||||
client.delete_collection(COLLECTION_NAME)
|
||||
except Exception:
|
||||
pass
|
||||
_invalidate_collection_singleton()
|
||||
|
||||
collection = client.create_collection(
|
||||
name=COLLECTION_NAME,
|
||||
embedding_function=embed_fn,
|
||||
metadata={"hnsw:space": "cosine"},
|
||||
)
|
||||
|
||||
inserted = 0
|
||||
failed_cards = 0
|
||||
failed_batches = 0
|
||||
batch_ids: list[str] = []
|
||||
batch_docs: list[str] = []
|
||||
batch_metas: list[dict] = []
|
||||
|
||||
for row in all_rows:
|
||||
card = dict(row)
|
||||
doc = _build_document(card)
|
||||
if not doc.strip():
|
||||
continue
|
||||
|
||||
card_id = card.get("scryfall_id", "")
|
||||
if not card_id:
|
||||
continue
|
||||
|
||||
batch_ids.append(card_id)
|
||||
batch_docs.append(doc)
|
||||
batch_metas.append(_build_metadata(card))
|
||||
|
||||
if len(batch_ids) >= batch_size:
|
||||
try:
|
||||
collection.add(
|
||||
ids=batch_ids,
|
||||
documents=batch_docs,
|
||||
metadatas=batch_metas,
|
||||
)
|
||||
inserted += len(batch_ids)
|
||||
if inserted % 2000 == 0:
|
||||
logger.info(" RAG indexed %d / %d cards...", inserted, total_rows)
|
||||
except Exception as exc:
|
||||
failed_cards += len(batch_ids)
|
||||
failed_batches += 1
|
||||
logger.warning(
|
||||
"RAG batch insert failed (batch #%d, %d cards lost): %s",
|
||||
failed_batches, len(batch_ids), exc,
|
||||
)
|
||||
batch_ids.clear()
|
||||
batch_docs.clear()
|
||||
batch_metas.clear()
|
||||
|
||||
# Final partial batch
|
||||
if batch_ids:
|
||||
try:
|
||||
collection.add(
|
||||
ids=batch_ids,
|
||||
documents=batch_docs,
|
||||
metadatas=batch_metas,
|
||||
)
|
||||
inserted += len(batch_ids)
|
||||
except Exception as exc:
|
||||
failed_cards += len(batch_ids)
|
||||
failed_batches += 1
|
||||
logger.warning("RAG final batch insert failed: %s", exc)
|
||||
|
||||
logger.info(
|
||||
"RAG vector store complete: %d indexed, %d failed (%d batches).",
|
||||
inserted, failed_cards, failed_batches,
|
||||
)
|
||||
|
||||
# Abort if failure rate exceeds 1% — delete partial collection
|
||||
if total_rows > 0 and (failed_cards / total_rows) > 0.01:
|
||||
logger.error(
|
||||
"RAG build failure rate %.1f%% exceeds 1%% threshold — deleting partial collection.",
|
||||
100.0 * failed_cards / total_rows,
|
||||
)
|
||||
try:
|
||||
client.delete_collection(COLLECTION_NAME)
|
||||
_invalidate_collection_singleton()
|
||||
except Exception:
|
||||
pass
|
||||
raise RuntimeError(
|
||||
f"RAG build aborted: {failed_cards}/{total_rows} cards failed to insert. "
|
||||
"Check Ollama connectivity and retry."
|
||||
)
|
||||
|
||||
_write_build_meta(card_count=inserted)
|
||||
# Invalidate singleton so next _get_collection() picks up the new collection
|
||||
_invalidate_collection_singleton()
|
||||
return {"indexed": inserted, "failed": failed_cards}
|
||||
|
||||
|
||||
# ── Public API ────────────────────────────────────────────────────────────────
|
||||
|
||||
def build_index(force: bool = False, batch_size: int = DEFAULT_BATCH_SIZE) -> dict:
|
||||
"""Explicitly build or rebuild the ChromaDB vector index.
|
||||
|
||||
This is the function called by POST /api/rag/build.
|
||||
Unlike ensure_rag_store(), this always runs (no _rag_ready short-circuit)
|
||||
and returns stats so the API can surface them to the caller.
|
||||
|
||||
Args:
|
||||
force: If True, rebuild even if the index appears current.
|
||||
batch_size: Cards per ChromaDB insert batch (default 500).
|
||||
|
||||
Returns:
|
||||
Dict with keys: indexed (int), failed (int).
|
||||
"""
|
||||
global _rag_ready
|
||||
with _rag_lock:
|
||||
if not force:
|
||||
try:
|
||||
from services.scryfall_bulk import get_stats as bulk_stats
|
||||
stats = bulk_stats()
|
||||
bulk_count = stats.get("card_count", 0)
|
||||
collection = _get_collection()
|
||||
if _collection_is_current(collection, bulk_count):
|
||||
logger.info("RAG index is current — skipping rebuild (use force=True to override).")
|
||||
return {"indexed": collection.count(), "failed": 0, "skipped": True}
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
result = _build_collection_from_bulk(batch_size=batch_size)
|
||||
_rag_ready = True
|
||||
return result
|
||||
|
||||
|
||||
def ensure_rag_store() -> None:
|
||||
"""Build the ChromaDB vector store if it is missing or stale.
|
||||
|
||||
Safe to call at startup — no-ops quickly if the store is current.
|
||||
Requires:
|
||||
- Phase 1 bulk DB to be populated (services/scryfall_bulk)
|
||||
- Ollama running with nomic-embed-text pulled
|
||||
"""
|
||||
global _rag_ready
|
||||
with _rag_lock:
|
||||
if _rag_ready:
|
||||
return
|
||||
try:
|
||||
from services.scryfall_bulk import get_stats as bulk_stats
|
||||
stats = bulk_stats()
|
||||
bulk_count = stats.get("card_count", 0)
|
||||
if bulk_count == 0:
|
||||
logger.warning(
|
||||
"Scryfall bulk DB is empty — skipping RAG store build. "
|
||||
"Run ensure_bulk_db() first."
|
||||
)
|
||||
return
|
||||
|
||||
collection = _get_collection()
|
||||
if _collection_is_current(collection, bulk_count):
|
||||
logger.info(
|
||||
"RAG vector store is current (%d cards).",
|
||||
collection.count(),
|
||||
)
|
||||
_rag_ready = True
|
||||
return
|
||||
|
||||
logger.info(
|
||||
"Building RAG vector store from %d bulk cards "
|
||||
"(this may take several minutes on first run)...",
|
||||
bulk_count,
|
||||
)
|
||||
_build_collection_from_bulk()
|
||||
_rag_ready = True
|
||||
|
||||
except ImportError as exc:
|
||||
logger.warning("RAG store unavailable: %s", exc)
|
||||
except Exception as exc:
|
||||
logger.error("RAG store build failed: %s", exc)
|
||||
|
||||
|
||||
def query_cards(
|
||||
query: str,
|
||||
n_results: int = 8,
|
||||
color_identity: Optional[list[str]] = None,
|
||||
type_filter: Optional[str] = None,
|
||||
) -> list[dict]:
|
||||
"""Semantic search over card oracle text.
|
||||
|
||||
Args:
|
||||
query: Natural language query (e.g. "draw cards when creatures die").
|
||||
n_results: Maximum number of results.
|
||||
color_identity: If provided, only return cards whose color identity
|
||||
is a subset (e.g. ["W", "U", "B"]).
|
||||
type_filter: Optional type_line substring filter (e.g. "Creature").
|
||||
Applied as a post-query Python filter for ChromaDB compatibility.
|
||||
|
||||
Returns:
|
||||
List of dicts with keys: name, type_line, oracle_text, cmc,
|
||||
color_identity, mana_cost, distance.
|
||||
"""
|
||||
if not _rag_ready:
|
||||
logger.warning("RAG store not ready — returning empty results.")
|
||||
return []
|
||||
|
||||
try:
|
||||
collection = _get_collection()
|
||||
except Exception as exc:
|
||||
logger.error("Failed to get RAG collection: %s", exc)
|
||||
return []
|
||||
|
||||
try:
|
||||
# Fetch extra results to account for post-query color/type filtering
|
||||
fetch_n = n_results * 4 if (color_identity or type_filter) else n_results
|
||||
results = collection.query(
|
||||
query_texts=[query],
|
||||
n_results=min(fetch_n, 200),
|
||||
include=["documents", "metadatas", "distances"],
|
||||
)
|
||||
except Exception as exc:
|
||||
logger.error("RAG query failed: %s", exc)
|
||||
return []
|
||||
|
||||
if not results or not results.get("ids") or not results["ids"][0]:
|
||||
return []
|
||||
|
||||
cards: list[dict] = []
|
||||
ids = results["ids"][0]
|
||||
docs = results["documents"][0] if results.get("documents") else [""] * len(ids)
|
||||
metas = results["metadatas"][0] if results.get("metadatas") else [{}] * len(ids)
|
||||
dists = results["distances"][0] if results.get("distances") else [0.0] * len(ids)
|
||||
|
||||
for i, card_id in enumerate(ids):
|
||||
meta = metas[i] if i < len(metas) else {}
|
||||
doc = docs[i] if i < len(docs) else ""
|
||||
|
||||
# Color identity post-filter (Python-side for ChromaDB compat)
|
||||
if color_identity:
|
||||
card_ci_str = meta.get("color_identity", "")
|
||||
card_ci = set(c for c in card_ci_str.split(",") if c) if card_ci_str else set()
|
||||
deck_ci = set(color_identity)
|
||||
if not card_ci.issubset(deck_ci):
|
||||
continue
|
||||
|
||||
# Type post-filter
|
||||
if type_filter:
|
||||
card_type = meta.get("type_line", "")
|
||||
if type_filter.lower() not in card_type.lower():
|
||||
continue
|
||||
|
||||
# Document format: Name | Mana Cost | Type | Oracle Text
|
||||
parts = doc.split(" | ", 3)
|
||||
oracle = parts[3] if len(parts) > 3 else (parts[-1] if parts else "")
|
||||
|
||||
cards.append({
|
||||
"name": meta.get("name", ""),
|
||||
"type_line": meta.get("type_line", ""),
|
||||
"oracle_text": oracle,
|
||||
"cmc": meta.get("cmc", 0),
|
||||
"color_identity": meta.get("color_identity", ""),
|
||||
"mana_cost": meta.get("mana_cost", ""),
|
||||
"distance": round(dists[i], 4) if i < len(dists) else 0.0,
|
||||
})
|
||||
if len(cards) >= n_results:
|
||||
break
|
||||
|
||||
return cards
|
||||
|
||||
|
||||
def get_rag_stats() -> dict:
|
||||
"""Return metadata about the RAG vector store state."""
|
||||
result = {
|
||||
"ready": _rag_ready,
|
||||
"chroma_dir": str(RAG_CHROMA_DIR),
|
||||
"embedding_model": EMBEDDING_MODEL,
|
||||
"ollama_url": OLLAMA_BASE_URL,
|
||||
"card_count": 0,
|
||||
"built_at": None,
|
||||
"age_days": None,
|
||||
}
|
||||
try:
|
||||
collection = _get_collection()
|
||||
result["card_count"] = collection.count()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# Read age from sidecar file (persists across restarts)
|
||||
meta = _read_build_meta()
|
||||
built_at = meta.get("built_at")
|
||||
if built_at:
|
||||
result["built_at"] = built_at
|
||||
try:
|
||||
age = (time.time() - float(built_at)) / 86400
|
||||
result["age_days"] = round(age, 1)
|
||||
except (ValueError, TypeError):
|
||||
pass
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def is_chroma_available() -> bool:
|
||||
"""Check whether ChromaDB + Ollama are reachable without side effects."""
|
||||
try:
|
||||
_get_chromadb_client()
|
||||
except Exception:
|
||||
return False
|
||||
try:
|
||||
import urllib.request
|
||||
req = urllib.request.Request(
|
||||
f"{OLLAMA_BASE_URL}/api/tags",
|
||||
headers={"User-Agent": "commander-ai-lab/1.0"},
|
||||
)
|
||||
with urllib.request.urlopen(req, timeout=3):
|
||||
pass
|
||||
except Exception:
|
||||
return False
|
||||
return True
|
||||
|
||||
|
||||
def check_staleness() -> dict:
|
||||
"""Return staleness info so a background scheduler can trigger rebuilds.
|
||||
|
||||
Returns dict with keys:
|
||||
stale (bool): True if the index should be rebuilt.
|
||||
reason (str): Human-readable explanation.
|
||||
age_days (float | None): Age of the current build in days.
|
||||
"""
|
||||
meta = _read_build_meta()
|
||||
built_at = meta.get("built_at")
|
||||
if not built_at:
|
||||
return {"stale": True, "reason": "no build metadata found", "age_days": None}
|
||||
try:
|
||||
age_days = (time.time() - float(built_at)) / 86400
|
||||
except (ValueError, TypeError):
|
||||
return {"stale": True, "reason": "corrupt build timestamp", "age_days": None}
|
||||
if age_days > 14:
|
||||
return {"stale": True, "reason": f"index is {age_days:.1f} days old (>14)", "age_days": round(age_days, 1)}
|
||||
try:
|
||||
from services.scryfall_bulk import get_stats as bulk_stats
|
||||
bulk_count = bulk_stats().get("card_count", 0)
|
||||
collection = _get_collection()
|
||||
chroma_count = collection.count()
|
||||
ratio = chroma_count / max(bulk_count, 1)
|
||||
if ratio < 0.95 or ratio > 1.05:
|
||||
return {
|
||||
"stale": True,
|
||||
"reason": f"card count drift: chroma={chroma_count}, bulk={bulk_count}",
|
||||
"age_days": round(age_days, 1),
|
||||
}
|
||||
except Exception as exc:
|
||||
logger.warning("check_staleness card count check failed: %s", exc)
|
||||
return {"stale": False, "reason": "index is current", "age_days": round(age_days, 1)}
|
||||
@@ -1,372 +0,0 @@
|
||||
"""
|
||||
services/scryfall_bulk.py
|
||||
=========================
|
||||
Downloads and indexes the full Scryfall `default_cards` bulk export into a
|
||||
local SQLite database with FTS5 full-text search over card names and oracle
|
||||
text. This replaces per-card live Scryfall API calls for the RAG pipeline.
|
||||
|
||||
Usage (one-time or nightly):
|
||||
from services.scryfall_bulk import ensure_bulk_db
|
||||
ensure_bulk_db() # call at startup; no-ops if data is fresh
|
||||
|
||||
Public API:
|
||||
ensure_bulk_db() -> None (download if stale)
|
||||
lookup_card(name) -> dict | None
|
||||
search_oracle(query, colors, limit) -> list[dict]
|
||||
get_bulk_db() -> sqlite3.Connection
|
||||
|
||||
Data path: ./data/scryfall_bulk.db
|
||||
Re-download: every SCRYFALL_BULK_STALENESS_DAYS days (default 7)
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import sqlite3
|
||||
import threading
|
||||
import time
|
||||
from pathlib import Path
|
||||
from urllib.request import Request, urlopen
|
||||
|
||||
logger = logging.getLogger("commander_ai_lab.scryfall_bulk")
|
||||
|
||||
# ── Config ──────────────────────────────────────────────────────────────────
|
||||
BULK_DB_PATH = Path(__file__).parent.parent / "data" / "scryfall_bulk.db"
|
||||
BULK_META_URL = "https://api.scryfall.com/bulk-data"
|
||||
SCRYFALL_BULK_STALENESS_DAYS = int(
|
||||
os.environ.get("SCRYFALL_BULK_STALENESS_DAYS", "7")
|
||||
)
|
||||
_API_HEADERS = {"User-Agent": "CommanderAILab/3.0", "Accept": "application/json"}
|
||||
|
||||
# ── Module-level singletons ──────────────────────────────────────────────────
|
||||
_bulk_conn: sqlite3.Connection | None = None
|
||||
_bulk_lock = threading.Lock()
|
||||
|
||||
|
||||
# ── DB init ──────────────────────────────────────────────────────────────────
|
||||
|
||||
def _init_db(conn: sqlite3.Connection) -> None:
|
||||
"""Create tables and FTS5 virtual table on first run."""
|
||||
conn.execute("PRAGMA journal_mode=WAL")
|
||||
conn.execute("PRAGMA synchronous=NORMAL")
|
||||
conn.executescript("""
|
||||
CREATE TABLE IF NOT EXISTS cards (
|
||||
scryfall_id TEXT PRIMARY KEY,
|
||||
name TEXT NOT NULL,
|
||||
oracle_text TEXT DEFAULT '',
|
||||
type_line TEXT DEFAULT '',
|
||||
mana_cost TEXT DEFAULT '',
|
||||
cmc REAL DEFAULT 0,
|
||||
color_identity TEXT DEFAULT '[]',
|
||||
keywords TEXT DEFAULT '[]',
|
||||
power TEXT DEFAULT '',
|
||||
toughness TEXT DEFAULT '',
|
||||
rarity TEXT DEFAULT '',
|
||||
edhrec_rank INTEGER DEFAULT 0,
|
||||
legalities TEXT DEFAULT '{}',
|
||||
rulings_uri TEXT DEFAULT '',
|
||||
set_code TEXT DEFAULT '',
|
||||
updated_at TEXT DEFAULT (datetime('now'))
|
||||
);
|
||||
|
||||
CREATE VIRTUAL TABLE IF NOT EXISTS cards_fts USING fts5(
|
||||
name,
|
||||
oracle_text,
|
||||
content='cards',
|
||||
content_rowid='rowid'
|
||||
);
|
||||
|
||||
CREATE TABLE IF NOT EXISTS meta (
|
||||
key TEXT PRIMARY KEY,
|
||||
value TEXT NOT NULL
|
||||
);
|
||||
""")
|
||||
conn.commit()
|
||||
|
||||
|
||||
# ── Staleness check ───────────────────────────────────────────────────────────
|
||||
|
||||
def _is_stale(conn: sqlite3.Connection) -> bool:
|
||||
row = conn.execute(
|
||||
"SELECT value FROM meta WHERE key = 'last_download'"
|
||||
).fetchone()
|
||||
if not row:
|
||||
return True
|
||||
try:
|
||||
age_days = (time.time() - float(row[0])) / 86400
|
||||
return age_days > SCRYFALL_BULK_STALENESS_DAYS
|
||||
except (ValueError, TypeError):
|
||||
return True
|
||||
|
||||
|
||||
# ── Download + index ──────────────────────────────────────────────────────────
|
||||
|
||||
def _get_bulk_download_url() -> str:
|
||||
"""Fetch the current default_cards download URL from the Scryfall manifest."""
|
||||
req = Request(BULK_META_URL, headers=_API_HEADERS)
|
||||
with urlopen(req, timeout=15) as resp:
|
||||
meta = json.loads(resp.read())
|
||||
for entry in meta.get("data", []):
|
||||
if entry.get("type") == "default_cards":
|
||||
return entry["download_uri"]
|
||||
raise RuntimeError("Could not find default_cards entry in Scryfall bulk-data manifest")
|
||||
|
||||
|
||||
def _download_and_index(conn: sqlite3.Connection) -> int:
|
||||
"""
|
||||
Download the full default_cards JSON from Scryfall and index into SQLite.
|
||||
Replaces all existing rows. Returns number of cards indexed.
|
||||
"""
|
||||
logger.info("Fetching Scryfall bulk-data manifest...")
|
||||
url = _get_bulk_download_url()
|
||||
logger.info("Downloading Scryfall default_cards bulk export (~100 MB)...")
|
||||
|
||||
req = Request(url, headers=_API_HEADERS)
|
||||
with urlopen(req, timeout=300) as resp:
|
||||
raw_bytes = resp.read()
|
||||
|
||||
cards_json: list[dict] = json.loads(raw_bytes)
|
||||
logger.info(f"Received {len(cards_json)} card objects from Scryfall.")
|
||||
|
||||
# Wipe existing data for a clean rebuild
|
||||
conn.execute("DELETE FROM cards")
|
||||
conn.execute("DELETE FROM cards_fts")
|
||||
conn.commit()
|
||||
|
||||
BATCH_SIZE = 1000
|
||||
inserted = 0
|
||||
batch: list[tuple] = []
|
||||
|
||||
_SKIP_LAYOUTS = {"token", "emblem", "art_series", "double_faced_token"}
|
||||
|
||||
for card in cards_json:
|
||||
if card.get("layout") in _SKIP_LAYOUTS:
|
||||
continue
|
||||
|
||||
# Handle double-faced / meld cards: concatenate face oracle texts
|
||||
oracle = card.get("oracle_text", "")
|
||||
if not oracle and card.get("card_faces"):
|
||||
oracle = "\n//\n".join(
|
||||
f.get("oracle_text", "")
|
||||
for f in card["card_faces"]
|
||||
if f.get("oracle_text")
|
||||
)
|
||||
|
||||
mana_cost = card.get("mana_cost", "")
|
||||
if not mana_cost and card.get("card_faces"):
|
||||
mana_cost = card["card_faces"][0].get("mana_cost", "")
|
||||
|
||||
batch.append((
|
||||
card.get("id", ""),
|
||||
card.get("name", ""),
|
||||
oracle,
|
||||
card.get("type_line", ""),
|
||||
mana_cost,
|
||||
float(card.get("cmc") or 0),
|
||||
json.dumps(card.get("color_identity", [])),
|
||||
json.dumps(card.get("keywords", [])),
|
||||
card.get("power", "") or "",
|
||||
card.get("toughness", "") or "",
|
||||
card.get("rarity", ""),
|
||||
int(card.get("edhrec_rank") or 0),
|
||||
json.dumps(card.get("legalities", {})),
|
||||
card.get("rulings_uri", "") or "",
|
||||
card.get("set", ""),
|
||||
))
|
||||
|
||||
if len(batch) >= BATCH_SIZE:
|
||||
_flush_batch(conn, batch)
|
||||
inserted += len(batch)
|
||||
batch.clear()
|
||||
logger.debug(f" Indexed {inserted} cards...")
|
||||
|
||||
if batch:
|
||||
_flush_batch(conn, batch)
|
||||
inserted += len(batch)
|
||||
|
||||
# Rebuild FTS5 index from cards table
|
||||
conn.execute("INSERT INTO cards_fts(cards_fts) VALUES('rebuild')")
|
||||
|
||||
# Record download timestamp
|
||||
conn.execute(
|
||||
"INSERT OR REPLACE INTO meta (key, value) VALUES ('last_download', ?)",
|
||||
(str(time.time()),)
|
||||
)
|
||||
conn.execute(
|
||||
"INSERT OR REPLACE INTO meta (key, value) VALUES ('card_count', ?)",
|
||||
(str(inserted),)
|
||||
)
|
||||
conn.commit()
|
||||
|
||||
logger.info(f"Scryfall bulk index complete: {inserted} cards stored.")
|
||||
return inserted
|
||||
|
||||
|
||||
def _flush_batch(conn: sqlite3.Connection, batch: list[tuple]) -> None:
|
||||
conn.executemany(
|
||||
"""
|
||||
INSERT OR REPLACE INTO cards
|
||||
(scryfall_id, name, oracle_text, type_line, mana_cost, cmc,
|
||||
color_identity, keywords, power, toughness, rarity,
|
||||
edhrec_rank, legalities, rulings_uri, set_code)
|
||||
VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)
|
||||
""",
|
||||
batch,
|
||||
)
|
||||
conn.commit()
|
||||
|
||||
|
||||
# ── Public API ────────────────────────────────────────────────────────────────
|
||||
|
||||
def get_bulk_db() -> sqlite3.Connection:
|
||||
"""
|
||||
Return the module-level SQLite connection, creating it on first call.
|
||||
Thread-safe via _bulk_lock.
|
||||
"""
|
||||
global _bulk_conn
|
||||
with _bulk_lock:
|
||||
if _bulk_conn is None:
|
||||
BULK_DB_PATH.parent.mkdir(parents=True, exist_ok=True)
|
||||
_bulk_conn = sqlite3.connect(
|
||||
str(BULK_DB_PATH), check_same_thread=False
|
||||
)
|
||||
_bulk_conn.row_factory = sqlite3.Row
|
||||
_init_db(_bulk_conn)
|
||||
return _bulk_conn
|
||||
|
||||
|
||||
def ensure_bulk_db() -> None:
|
||||
"""
|
||||
Call at startup. Downloads and indexes the full Scryfall card set if the
|
||||
local DB is missing or older than SCRYFALL_BULK_STALENESS_DAYS.
|
||||
No-ops if data is already fresh.
|
||||
"""
|
||||
conn = get_bulk_db()
|
||||
if _is_stale(conn):
|
||||
logger.info(
|
||||
"Scryfall bulk DB is stale or missing — downloading now "
|
||||
"(~100 MB, one-time per week)..."
|
||||
)
|
||||
try:
|
||||
_download_and_index(conn)
|
||||
except Exception as exc:
|
||||
logger.error(
|
||||
f"Scryfall bulk download failed: {exc}. "
|
||||
"Continuing without bulk data — per-card Scryfall cache will be used."
|
||||
)
|
||||
else:
|
||||
row = conn.execute(
|
||||
"SELECT value FROM meta WHERE key = 'card_count'"
|
||||
).fetchone()
|
||||
count = row[0] if row else "unknown"
|
||||
logger.info(f"Scryfall bulk DB is fresh ({count} cards cached).")
|
||||
|
||||
|
||||
def lookup_card(name: str) -> dict | None:
|
||||
"""
|
||||
Exact case-insensitive card name lookup.
|
||||
|
||||
Returns a dict with all columns from the `cards` table, or None if not
|
||||
found. Prefers the most-recently-printed printing (lowest edhrec_rank).
|
||||
"""
|
||||
conn = get_bulk_db()
|
||||
row = conn.execute(
|
||||
"""
|
||||
SELECT * FROM cards
|
||||
WHERE LOWER(name) = LOWER(?)
|
||||
ORDER BY edhrec_rank ASC
|
||||
LIMIT 1
|
||||
""",
|
||||
(name,),
|
||||
).fetchone()
|
||||
return dict(row) if row else None
|
||||
|
||||
|
||||
def search_oracle(
|
||||
query: str,
|
||||
color_identity: list[str] | None = None,
|
||||
type_filter: str | None = None,
|
||||
limit: int = 10,
|
||||
) -> list[dict]:
|
||||
"""
|
||||
Full-text search over card names and oracle text using SQLite FTS5.
|
||||
|
||||
Args:
|
||||
query: Natural language or keyword query string.
|
||||
color_identity: If provided, restrict results to cards whose color
|
||||
identity is a subset of this list (e.g. ['W', 'U']).
|
||||
type_filter: Optional type-line substring filter (e.g. 'Creature').
|
||||
limit: Maximum number of results to return.
|
||||
|
||||
Returns:
|
||||
List of card dicts ordered by FTS5 relevance rank.
|
||||
"""
|
||||
conn = get_bulk_db()
|
||||
|
||||
# Build FTS5 query: wrap each token in quotes to allow phrase matching
|
||||
tokens = [t.strip() for t in query.split() if t.strip()]
|
||||
if not tokens:
|
||||
return []
|
||||
fts_query = " OR ".join(f'"{t}"' for t in tokens)
|
||||
|
||||
# Over-fetch to allow post-filtering by color/type
|
||||
fetch_limit = max(limit * 5, 50)
|
||||
rows = conn.execute(
|
||||
"""
|
||||
SELECT c.*
|
||||
FROM cards c
|
||||
JOIN cards_fts fts ON fts.rowid = c.rowid
|
||||
WHERE cards_fts MATCH ?
|
||||
ORDER BY rank
|
||||
LIMIT ?
|
||||
""",
|
||||
(fts_query, fetch_limit),
|
||||
).fetchall()
|
||||
|
||||
results: list[dict] = []
|
||||
for row in rows:
|
||||
card = dict(row)
|
||||
|
||||
# Color identity filter: card's CI must be a subset of deck's CI
|
||||
if color_identity:
|
||||
try:
|
||||
card_ci = set(json.loads(card.get("color_identity") or "[]"))
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
card_ci = set()
|
||||
if not card_ci.issubset(set(color_identity)):
|
||||
continue
|
||||
|
||||
# Optional type-line filter
|
||||
if type_filter:
|
||||
if type_filter.lower() not in (card.get("type_line") or "").lower():
|
||||
continue
|
||||
|
||||
results.append(card)
|
||||
if len(results) >= limit:
|
||||
break
|
||||
|
||||
return results
|
||||
|
||||
|
||||
def get_stats() -> dict:
|
||||
"""Return metadata about the current bulk DB state."""
|
||||
conn = get_bulk_db()
|
||||
rows = conn.execute("SELECT key, value FROM meta").fetchall()
|
||||
meta = {r["key"]: r["value"] for r in rows}
|
||||
card_count = conn.execute("SELECT COUNT(*) FROM cards").fetchone()[0]
|
||||
stale = _is_stale(conn)
|
||||
last_dl = meta.get("last_download")
|
||||
age_days: float | None = None
|
||||
if last_dl:
|
||||
try:
|
||||
age_days = round((time.time() - float(last_dl)) / 86400, 1)
|
||||
except (ValueError, TypeError):
|
||||
pass
|
||||
return {
|
||||
"card_count": card_count,
|
||||
"stale": stale,
|
||||
"age_days": age_days,
|
||||
"db_path": str(BULK_DB_PATH),
|
||||
"staleness_threshold_days": SCRYFALL_BULK_STALENESS_DAYS,
|
||||
}
|
||||
@@ -24,7 +24,7 @@ logger = logging.getLogger(__name__)
|
||||
|
||||
# Ollama exposes an OpenAI-compatible endpoint
|
||||
DEFAULT_BASE_URL = "http://localhost:11434/v1"
|
||||
DEFAULT_MODEL = "qwen2.5:7b"
|
||||
DEFAULT_MODEL = "gpt-oss:20b"
|
||||
|
||||
|
||||
def _get_client(base_url: str = DEFAULT_BASE_URL) -> OpenAI:
|
||||
@@ -102,7 +102,7 @@ def chat(
|
||||
return response.choices[0].message.content or ""
|
||||
|
||||
|
||||
# ── 1. Analyze synergies ─────────────────────────────────────────────
|
||||
# ── 1. Analyze synergies ─────────────────────────────────────────
|
||||
|
||||
def analyze_synergies(
|
||||
commander_name: str,
|
||||
@@ -145,7 +145,7 @@ Cards to evaluate:
|
||||
return []
|
||||
|
||||
|
||||
# ── 2. Suggest cards for a category ────────────────────────────────
|
||||
# ── 2. Suggest cards for a category ──────────────────────────────
|
||||
|
||||
def suggest_cards(
|
||||
commander_name: str,
|
||||
@@ -154,23 +154,13 @@ def suggest_cards(
|
||||
count: int = 10,
|
||||
exclude: Optional[List[str]] = None,
|
||||
strategy_notes: Optional[str] = None,
|
||||
sim_context: str = "",
|
||||
) -> List[str]:
|
||||
"""
|
||||
Ask the model to suggest cards for a specific deck category.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
sim_context:
|
||||
Optional natural-language insight string from get_sim_insights().
|
||||
When non-empty, appended to the prompt so the LLM can factor in
|
||||
statistically successful card traits from simulation data.
|
||||
|
||||
Returns a list of card names.
|
||||
"""
|
||||
exclude_str = f"\nDo NOT suggest these cards: {json.dumps(exclude)}" if exclude else ""
|
||||
strategy = f"\nStrategy notes: {strategy_notes}" if strategy_notes else ""
|
||||
sim_block = f"\n\n{sim_context}" if sim_context else ""
|
||||
|
||||
prompt = f"""You are a Magic: The Gathering Commander deck-building expert.
|
||||
|
||||
@@ -178,7 +168,7 @@ Commander: {commander_name}
|
||||
Color identity: {', '.join(color_identity)}
|
||||
Category: {category}
|
||||
{strategy}
|
||||
{exclude_str}{sim_block}
|
||||
{exclude_str}
|
||||
|
||||
Suggest exactly {count} cards for the {category} category that work well with this commander.
|
||||
Only suggest cards that are legal in Commander and match the color identity.
|
||||
@@ -210,7 +200,7 @@ Return ONLY a JSON array of card name strings, like: ["Card A", "Card B", ...]""
|
||||
return []
|
||||
|
||||
|
||||
# ── 3. Filter by color identity ────────────────────────────────────
|
||||
# ── 3. Filter by color identity ──────────────────────────────────
|
||||
|
||||
def filter_color_identity(
|
||||
card_names: List[str],
|
||||
@@ -252,28 +242,17 @@ Cards:
|
||||
return card_names
|
||||
|
||||
|
||||
# ── 4. Enforce deck ratios ───────────────────────────────────────────
|
||||
# ── 4. Enforce deck ratios ───────────────────────────────────────
|
||||
|
||||
def enforce_deck_ratios(
|
||||
cards_by_category: Dict[str, List[str]],
|
||||
target_ratios: Dict[str, int],
|
||||
commander_name: str,
|
||||
sim_context: str = "",
|
||||
) -> Dict[str, List[str]]:
|
||||
"""
|
||||
Ask the model to trim/expand categories to hit target counts.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
sim_context:
|
||||
Optional natural-language insight string from get_sim_insights().
|
||||
When non-empty, appended to the prompt so the LLM preferentially
|
||||
retains cards matching statistically high-value traits when trimming.
|
||||
|
||||
Returns adjusted dict of category -> card names.
|
||||
"""
|
||||
sim_block = f"\n\n{sim_context}" if sim_context else ""
|
||||
|
||||
prompt = f"""You are a Magic: The Gathering Commander deck-building expert.
|
||||
|
||||
Commander: {commander_name}
|
||||
@@ -286,7 +265,7 @@ Target card counts per category:
|
||||
|
||||
Adjust each category to match the target count. Remove the weakest cards from
|
||||
over-filled categories. For under-filled categories, suggest additional cards.
|
||||
The total across all categories must be exactly 99.{sim_block}
|
||||
The total across all categories must be exactly 99.
|
||||
|
||||
Return a JSON object with the same category keys, each mapping to an array of card name strings."""
|
||||
|
||||
@@ -305,7 +284,7 @@ Return a JSON object with the same category keys, each mapping to an array of ca
|
||||
return cards_by_category
|
||||
|
||||
|
||||
# ── 5. Assemble final deck JSON ─────────────────────────────────────────
|
||||
# ── 5. Assemble final deck JSON ──────────────────────────────────
|
||||
|
||||
def assemble_deck_json(
|
||||
commander_name: str,
|
||||
|
||||
@@ -1,124 +0,0 @@
|
||||
"""
|
||||
sim_insights.py
|
||||
===============
|
||||
Translates learned simulation weights (learned_weights.json) into concise
|
||||
natural-language insight strings that can be injected into Ollama prompts.
|
||||
|
||||
This bridges the gap between the Monte Carlo engine's outcome-weighted
|
||||
reinforcement learning and the LLM-driven deck builder: keywords that
|
||||
statistically correlate with wins are surfaced to Ollama so it can
|
||||
prioritize those card traits when suggesting and trimming cards.
|
||||
|
||||
Usage::
|
||||
|
||||
from commander_ai_lab.deck_builder.api.sim_insights import get_sim_insights
|
||||
|
||||
context = get_sim_insights() # returns "" if no meaningful learning yet
|
||||
if context:
|
||||
prompt += f"\n\n{context}"
|
||||
|
||||
The function is intentionally safe to call when learned_weights.json does
|
||||
not yet exist (load_weights() falls back to AI_DEFAULT_WEIGHTS silently),
|
||||
and returns an empty string when no weight has drifted far enough from the
|
||||
default to be worth mentioning — so existing prompt behaviour is unchanged
|
||||
until there is real simulation data.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from typing import Optional
|
||||
|
||||
from commander_ai_lab.sim.rules import AI_DEFAULT_WEIGHTS, load_weights
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Maps weight keys → human-readable MTG concepts shown to the LLM.
|
||||
# Only keys the LLM can meaningfully act on are included.
|
||||
_KEY_TO_CONCEPT: dict[str, str] = {
|
||||
"kw_flying": "flying (evasion)",
|
||||
"kw_haste": "haste",
|
||||
"kw_deathtouch": "deathtouch",
|
||||
"kw_indestructible": "indestructible",
|
||||
"kw_doubleStrike": "double strike",
|
||||
"kw_hexproof": "hexproof",
|
||||
"kw_trample": "trample",
|
||||
"kw_lifelink": "lifelink",
|
||||
"kw_menace": "menace",
|
||||
"kw_ward": "ward",
|
||||
"kw_annihilator": "annihilator",
|
||||
"kw_cascade": "cascade",
|
||||
"spell_ramp": "mana ramp spells",
|
||||
"spell_destroy": "targeted removal",
|
||||
"spell_draw": "card draw",
|
||||
"spell_counter": "counterspells and board control",
|
||||
"trig_etb": "enters-the-battlefield triggers",
|
||||
"trig_dies": "death triggers",
|
||||
"trig_attack": "attack triggers",
|
||||
"card_ptBonus": "high power/toughness creatures",
|
||||
}
|
||||
|
||||
|
||||
def get_sim_insights(
|
||||
top_n: int = 6,
|
||||
threshold_delta: float = 0.05,
|
||||
weights_path: Optional[str] = None,
|
||||
) -> str:
|
||||
"""
|
||||
Return a concise insight paragraph for injecting into LLM prompts.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
top_n:
|
||||
Maximum number of concepts to mention (avoids bloating the prompt).
|
||||
threshold_delta:
|
||||
Minimum absolute drift from the default weight before a concept
|
||||
is considered meaningful enough to report. 0.05 means a weight
|
||||
must have moved by at least 5% of its default before it matters.
|
||||
weights_path:
|
||||
Optional explicit path to learned_weights.json. If None, the
|
||||
default location (``src/.../sim/learned_weights.json``) is used.
|
||||
|
||||
Returns
|
||||
-------
|
||||
str
|
||||
A multi-line insight string ready to append to an LLM prompt, or
|
||||
an empty string if no meaningful learning is available yet.
|
||||
"""
|
||||
try:
|
||||
learned = load_weights(weights_path)
|
||||
except Exception as exc:
|
||||
logger.warning("sim_insights: could not load weights: %s", exc)
|
||||
return ""
|
||||
|
||||
deltas: dict[str, float] = {}
|
||||
for key, concept in _KEY_TO_CONCEPT.items():
|
||||
default_val = AI_DEFAULT_WEIGHTS.get(key, 0.0)
|
||||
learned_val = learned.get(key, default_val)
|
||||
delta = learned_val - default_val
|
||||
if abs(delta) >= threshold_delta:
|
||||
deltas[concept] = delta
|
||||
|
||||
if not deltas:
|
||||
# No meaningful drift yet — don't inject noise into prompts
|
||||
return ""
|
||||
|
||||
# Sort by magnitude, take top_n
|
||||
sorted_items = sorted(deltas.items(), key=lambda x: -abs(x[1]))[:top_n]
|
||||
boosted = [c for c, d in sorted_items if d > 0]
|
||||
penalized = [c for c, d in sorted_items if d < 0]
|
||||
|
||||
lines = [
|
||||
"[Simulation Insights] Data from thousands of Commander games in this lab suggests:",
|
||||
]
|
||||
if boosted:
|
||||
lines.append(f" - PRIORITIZE cards with: {', '.join(boosted)}")
|
||||
if penalized:
|
||||
lines.append(f" - DEPRIORITIZE cards with: {', '.join(penalized)}")
|
||||
lines.append(
|
||||
"Use this to guide your selections where multiple options are otherwise comparable."
|
||||
)
|
||||
|
||||
result = "\n".join(lines)
|
||||
logger.debug("sim_insights: injecting %d concept(s) into prompt", len(sorted_items))
|
||||
return result
|
||||
@@ -13,7 +13,6 @@ from typing import Dict, List, Optional
|
||||
|
||||
from ..api import edhrec, scryfall
|
||||
from ..api import ollama_client as ollama
|
||||
from ..api.sim_insights import get_sim_insights
|
||||
from ..core.collection_filter import filter_names_by_collection
|
||||
from ..core.models import BuildRequest, BuildResult, CardEntry, CommanderDeck, DeckRatios
|
||||
from ..core.rules_engine import check_ban_list, filter_by_color_identity, validate_deck
|
||||
@@ -26,19 +25,19 @@ def build_deck(request: BuildRequest) -> BuildResult:
|
||||
Execute the full 7-step deck build pipeline.
|
||||
|
||||
Steps:
|
||||
1. Resolve commander via Scryfall
|
||||
2. Fetch EDHrec recommendations
|
||||
3. Fetch Scryfall candidates by category
|
||||
4. Ollama: suggest additional cards + fill gaps
|
||||
5. Filter by color identity + collection + ban list
|
||||
6. Ollama: enforce deck ratios (trim/expand to 99)
|
||||
7. Ollama: assemble final structured deck JSON
|
||||
1. Resolve commander via Scryfall
|
||||
2. Fetch EDHrec recommendations
|
||||
3. Fetch Scryfall candidates by category
|
||||
4. Ollama: suggest additional cards + fill gaps
|
||||
5. Filter by color identity + collection + ban list
|
||||
6. Ollama: enforce deck ratios (trim/expand to 99)
|
||||
7. Ollama: assemble final structured deck JSON
|
||||
"""
|
||||
start = time.time()
|
||||
warnings: List[str] = []
|
||||
sources: List[str] = []
|
||||
|
||||
# ── Step 1: Resolve commander ────────────────────────────────────────────
|
||||
# ── Step 1: Resolve commander ────────────────────────────────
|
||||
logger.info(f"Step 1: Resolving commander '{request.commander_name}'")
|
||||
commander = scryfall.search_commander(request.commander_name)
|
||||
if not commander:
|
||||
@@ -51,17 +50,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
|
||||
logger.info(f"Commander: {commander.name}, CI: {ci_list}")
|
||||
sources.append("scryfall")
|
||||
|
||||
# Load simulation insights once; injected into Ollama prompts in Steps 4 & 6.
|
||||
# Returns "" when learned_weights.json doesn't exist or has no meaningful drift
|
||||
# yet — so behaviour is identical to before until real sim data is available.
|
||||
sim_context = get_sim_insights()
|
||||
if sim_context:
|
||||
logger.info("Sim insights available — injecting into Ollama prompts")
|
||||
sources.append("sim_weights")
|
||||
else:
|
||||
logger.debug("No sim insights available (run update_weights.py after overnight sims)")
|
||||
|
||||
# ── Step 2: Fetch EDHrec recommendations ─────────────────────────────
|
||||
# ── Step 2: Fetch EDHrec recommendations ─────────────────────
|
||||
logger.info(f"Step 2: Fetching EDHrec data for '{commander.name}'")
|
||||
edhrec_cards = edhrec.get_recommended_cards(commander.name)
|
||||
if edhrec_cards:
|
||||
@@ -70,7 +59,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
|
||||
else:
|
||||
warnings.append("EDHrec returned no data — relying on Scryfall + Ollama")
|
||||
|
||||
# ── Step 3: Fetch Scryfall candidates by category ──────────────────────
|
||||
# ── Step 3: Fetch Scryfall candidates by category ────────────
|
||||
logger.info("Step 3: Fetching Scryfall candidates by category")
|
||||
scryfall_candidates: Dict[str, List[CardEntry]] = {
|
||||
"ramp": scryfall.search_ramp(commander_ci),
|
||||
@@ -81,7 +70,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
|
||||
for cat, cards in scryfall_candidates.items():
|
||||
logger.info(f" Scryfall {cat}: {len(cards)} candidates")
|
||||
|
||||
# ── Step 4: Ollama suggestions to fill gaps ──────────────────────────
|
||||
# ── Step 4: Ollama suggestions to fill gaps ──────────────────
|
||||
logger.info("Step 4: Ollama suggesting additional cards")
|
||||
|
||||
# Collect all names we already have
|
||||
@@ -90,9 +79,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
|
||||
all_names.extend(c.name for c in cards)
|
||||
all_names = list(set(all_names))
|
||||
|
||||
# Ask Ollama to suggest cards for categories that need more.
|
||||
# sim_context is forwarded so the LLM factors in what traits have
|
||||
# been statistically successful in our own game simulations.
|
||||
# Ask Ollama to suggest cards for categories that need more
|
||||
categories_to_fill = ["synergy", "protection", "wincon"]
|
||||
ollama_suggestions: Dict[str, List[str]] = {}
|
||||
|
||||
@@ -104,7 +91,6 @@ def build_deck(request: BuildRequest) -> BuildResult:
|
||||
count=15,
|
||||
exclude=all_names,
|
||||
strategy_notes=request.strategy_notes,
|
||||
sim_context=sim_context,
|
||||
)
|
||||
ollama_suggestions[category] = suggested
|
||||
all_names.extend(suggested)
|
||||
@@ -112,7 +98,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
|
||||
|
||||
sources.append("ollama")
|
||||
|
||||
# ── Step 5: Filter (color identity, collection, ban list) ────────────────
|
||||
# ── Step 5: Filter (color identity, collection, ban list) ────
|
||||
logger.info("Step 5: Filtering candidates")
|
||||
|
||||
# Build a unified name pool per category
|
||||
@@ -154,7 +140,7 @@ def build_deck(request: BuildRequest) -> BuildResult:
|
||||
n for n in cards_by_category[cat] if n not in BANNED_CARDS
|
||||
]
|
||||
|
||||
# ── Step 6: Ollama enforce ratios ────────────────────────────────────
|
||||
# ── Step 6: Ollama enforce ratios ────────────────────────────
|
||||
logger.info("Step 6: Ollama enforcing deck ratios")
|
||||
target_ratios = {
|
||||
"lands": request.ratios.lands,
|
||||
@@ -167,13 +153,10 @@ def build_deck(request: BuildRequest) -> BuildResult:
|
||||
"uncategorized": request.ratios.uncategorized,
|
||||
}
|
||||
|
||||
# sim_context is forwarded so Ollama preferentially retains cards
|
||||
# matching high-value sim traits when trimming over-filled categories.
|
||||
adjusted = ollama.enforce_deck_ratios(
|
||||
cards_by_category=cards_by_category,
|
||||
target_ratios=target_ratios,
|
||||
commander_name=commander.name,
|
||||
sim_context=sim_context,
|
||||
)
|
||||
|
||||
# Verify total is 99
|
||||
@@ -182,95 +165,25 @@ def build_deck(request: BuildRequest) -> BuildResult:
|
||||
warnings.append(f"Ollama returned {total} cards instead of 99 — adjusting")
|
||||
logger.warning(f"Ratio enforcement returned {total} cards")
|
||||
|
||||
# ── Step 7: Assemble final deck ────────────────────────────────────────
|
||||
# ── Step 7: Assemble final deck ──────────────────────────────
|
||||
logger.info("Step 7: Assembling final deck")
|
||||
|
||||
# Build a globally-deduplicated name list. enforce_deck_ratios can
|
||||
# return the same card name under multiple category keys (e.g. a
|
||||
# protection card that also appears in synergy). Without this step
|
||||
# get_cards_by_names produces duplicate CardEntry objects that
|
||||
# immediately fail the CommanderDeck singleton validator.
|
||||
seen_names: dict[str, str] = {} # name -> first category that claimed it
|
||||
for cat, names in adjusted.items():
|
||||
for name in names:
|
||||
if name not in seen_names:
|
||||
seen_names[name] = cat
|
||||
else:
|
||||
logger.warning(
|
||||
"Duplicate card '%s' found in categories '%s' and '%s' — "
|
||||
"keeping first assignment, dropping second",
|
||||
name, seen_names[name], cat,
|
||||
)
|
||||
|
||||
if len(seen_names) < sum(len(v) for v in adjusted.values()):
|
||||
warnings.append(
|
||||
"enforce_deck_ratios returned duplicate card names across categories; "
|
||||
"duplicates were silently dropped before singleton validation."
|
||||
)
|
||||
|
||||
all_card_names = list(seen_names.keys())
|
||||
# Convert to CardEntry list via Scryfall batch lookup
|
||||
all_card_names = []
|
||||
for names in adjusted.values():
|
||||
all_card_names.extend(names)
|
||||
|
||||
card_entries = scryfall.get_cards_by_names(all_card_names)
|
||||
|
||||
# Safety-net: deduplicate CardEntry list by name in case Scryfall
|
||||
# returns multiple printings for the same name.
|
||||
seen_entry_names: set[str] = set()
|
||||
unique_entries: List[CardEntry] = []
|
||||
for entry in card_entries:
|
||||
if entry.name not in seen_entry_names:
|
||||
seen_entry_names.add(entry.name)
|
||||
unique_entries.append(entry)
|
||||
else:
|
||||
logger.warning("Scryfall returned duplicate entry for '%s' — skipping", entry.name)
|
||||
card_entries = unique_entries
|
||||
|
||||
# Map back categories
|
||||
for entry in card_entries:
|
||||
if entry.name in seen_names:
|
||||
entry.category = seen_names[entry.name]
|
||||
name_to_cat: Dict[str, str] = {}
|
||||
for cat, names in adjusted.items():
|
||||
for name in names:
|
||||
name_to_cat[name] = cat
|
||||
|
||||
# -- Backfill basic lands to reach exactly 99 cards ----------------
|
||||
_BACKFILL_COLOR_TO_BASIC = {
|
||||
"W": "Plains", "U": "Island", "B": "Swamp",
|
||||
"R": "Mountain", "G": "Forest",
|
||||
}
|
||||
_BASIC_LAND_NAMES = set(_BACKFILL_COLOR_TO_BASIC.values()) | {"Wastes"}
|
||||
_current_total = sum(e.quantity for e in card_entries)
|
||||
_shortfall = 99 - _current_total
|
||||
if _shortfall > 0:
|
||||
logger.warning(
|
||||
"Deck has %d cards after dedup -- backfilling %d basic land(s)",
|
||||
_current_total, _shortfall,
|
||||
)
|
||||
warnings.append(
|
||||
f"Backfilled {_shortfall} basic land(s) to reach 99 cards"
|
||||
)
|
||||
_basics = [
|
||||
_BACKFILL_COLOR_TO_BASIC[c]
|
||||
for c in sorted(commander_ci)
|
||||
if c in _BACKFILL_COLOR_TO_BASIC
|
||||
] or ["Wastes"]
|
||||
# Distribute evenly across colors
|
||||
_per_color = _shortfall // len(_basics)
|
||||
_remainder = _shortfall % len(_basics)
|
||||
for _i, _bname in enumerate(_basics):
|
||||
_qty = _per_color + (1 if _i < _remainder else 0)
|
||||
if _qty <= 0:
|
||||
continue
|
||||
# Check if this basic is already in card_entries
|
||||
_found = False
|
||||
for _ce in card_entries:
|
||||
if _ce.name == _bname:
|
||||
_ce.quantity += _qty
|
||||
_found = True
|
||||
break
|
||||
if not _found:
|
||||
card_entries.append(CardEntry(
|
||||
name=_bname,
|
||||
quantity=_qty,
|
||||
category="lands",
|
||||
type_line="Basic Land",
|
||||
))
|
||||
for entry in card_entries:
|
||||
if entry.name in name_to_cat:
|
||||
entry.category = name_to_cat[entry.name]
|
||||
|
||||
# Build the deck
|
||||
elapsed = time.time() - start
|
||||
|
||||
@@ -63,40 +63,6 @@ class MemoryEntry:
|
||||
latency_ms: float
|
||||
|
||||
|
||||
# ── Canned narration lines (by personality key) ───────────────────────
|
||||
|
||||
_CANNED_NARRATIONS: dict[str, dict[str, str]] = {
|
||||
"aggro_timmy": {
|
||||
"play_land": "More mana, more mayhem!",
|
||||
"cast_spell": "Here comes the pain!",
|
||||
"attack": "ATTACK! Take everything!",
|
||||
"pass_priority": "Fine, go… but I'm watching you.",
|
||||
"default": "Let's smash something!",
|
||||
},
|
||||
"control_spike": {
|
||||
"play_land": "Mana secured. Proceeding.",
|
||||
"cast_spell": "Optimal play. As expected.",
|
||||
"attack": "Calculated aggression — acceptable risk.",
|
||||
"pass_priority": "Holding interaction mana. Predictable of you.",
|
||||
"default": "Inevitable victory approaches.",
|
||||
},
|
||||
"combo_johnny": {
|
||||
"play_land": "One step closer to the combo!",
|
||||
"cast_spell": "Assembling the pieces…",
|
||||
"attack": "Buying time until the combo fires.",
|
||||
"pass_priority": "Patience. The combo is coming.",
|
||||
"default": "The pieces are falling into place!",
|
||||
},
|
||||
"political_negotiator": {
|
||||
"play_land": "Just tapping a land. Nothing threatening here.",
|
||||
"cast_spell": "This helps us all, really.",
|
||||
"attack": "I'm afraid I must — for the good of the table.",
|
||||
"pass_priority": "I'll let this resolve. For now.",
|
||||
"default": "Let's all be reasonable about this.",
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
# ── AIOpponent ─────────────────────────────────────────────────────────
|
||||
|
||||
@dataclass
|
||||
@@ -443,9 +409,40 @@ class AIOpponent:
|
||||
|
||||
# ── Canned Narration ───────────────────────────────────────────────
|
||||
|
||||
_CANNED: dict[str, dict[str, str]] = {
|
||||
"aggro_timmy": {
|
||||
"play_land": "More mana, more mayhem!",
|
||||
"cast_spell": "Here comes the pain!",
|
||||
"attack": "ATTACK! Take everything!",
|
||||
"pass_priority": "Fine, go… but I’m watching you.",
|
||||
"default": "Let’s smash something!",
|
||||
},
|
||||
"control_spike": {
|
||||
"play_land": "Mana secured. Proceeding.",
|
||||
"cast_spell": "Optimal play. As expected.",
|
||||
"attack": "Calculated aggression — acceptable risk.",
|
||||
"pass_priority": "Holding interaction mana. Predictable of you.",
|
||||
"default": "Inevitable victory approaches.",
|
||||
},
|
||||
"combo_johnny": {
|
||||
"play_land": "One step closer to the combo!",
|
||||
"cast_spell": "Assembling the pieces…",
|
||||
"attack": "Buying time until the combo fires.",
|
||||
"pass_priority": "Patience. The combo is coming.",
|
||||
"default": "The pieces are falling into place!",
|
||||
},
|
||||
"political_negotiator": {
|
||||
"play_land": "Just tapping a land. Nothing threatening here.",
|
||||
"cast_spell": "This helps us all, really.",
|
||||
"attack": "I’m afraid I must — for the good of the table.",
|
||||
"pass_priority": "I’ll let this resolve. For now.",
|
||||
"default": "Let’s all be reasonable about this.",
|
||||
},
|
||||
}
|
||||
|
||||
def _canned_narration(self, move_desc: str) -> str:
|
||||
"""Return a canned flavor line matching personality and move category."""
|
||||
canned = _CANNED_NARRATIONS.get(self.personality.key, {})
|
||||
canned = self._CANNED.get(self.personality.key, {})
|
||||
desc_lower = move_desc.lower()
|
||||
for key in ("play_land", "cast_spell", "attack", "pass_priority"):
|
||||
if key.replace("_", " ") in desc_lower or key in desc_lower:
|
||||
|
||||
@@ -9,8 +9,8 @@ The LLM receives a structured game-state snapshot and returns a JSON
|
||||
action describing what to do this turn (play land, cast spell, attack,
|
||||
hold/pass, use removal, use board wipe, cast ramp, cast commander).
|
||||
|
||||
Default target: GPT-OSS 20B (Q4_K_M) via Ollama at localhost:11434
|
||||
ollama run deepseek-r1:8b
|
||||
Default target: GPT-OSS 20B (Q4_K_M) via Ollama at 192.168.0.240:11434
|
||||
ollama run gpt-oss:20b
|
||||
|
||||
Also supports:
|
||||
- LM Studio (OpenAI-compatible API) — set api_base to LM Studio URL
|
||||
@@ -58,28 +58,28 @@ class DeepSeekConfig:
|
||||
|
||||
Example — LM Studio::
|
||||
config = DeepSeekConfig(
|
||||
api_base="http://localhost:11434",
|
||||
api_base="http://192.168.0.240:11434",
|
||||
model="deepseek-r1-distill-qwen-8b",
|
||||
max_tokens=2048, # R1 needs room for <think> blocks
|
||||
)
|
||||
|
||||
Example — Ollama (default)::
|
||||
config = DeepSeekConfig() # points at localhost:11434 / deepseek-r1:8b
|
||||
config = DeepSeekConfig() # points at 192.168.0.240:11434 / gpt-oss:20b
|
||||
"""
|
||||
|
||||
# API endpoint — Ollama OpenAI-compatible base (NO /v1 suffix)
|
||||
api_base: str = "http://localhost:11434"
|
||||
api_base: str = "http://192.168.0.240:11434"
|
||||
# Model name as registered in Ollama
|
||||
model: str = "deepseek-r1:8b"
|
||||
model: str = "gpt-oss:20b"
|
||||
|
||||
# Generation parameters
|
||||
# GPT-OSS 20B does not emit <think> blocks so 1024 tokens is ample
|
||||
temperature: float = 0.3
|
||||
max_tokens: int = 4096
|
||||
max_tokens: int = 1024
|
||||
top_p: float = 0.9
|
||||
|
||||
# Timeouts
|
||||
request_timeout: float = float(os.environ.get("BRAIN_TIMEOUT", "300.0")) # Ollama local inference; raise vs LM Studio
|
||||
request_timeout: float = 30.0 # Ollama local inference; raise vs LM Studio
|
||||
fallback_on_timeout: bool = True
|
||||
|
||||
# Caching
|
||||
@@ -91,7 +91,7 @@ class DeepSeekConfig:
|
||||
log_dir: str = ""
|
||||
|
||||
# Retry
|
||||
max_retries: int = 2
|
||||
max_retries: int = 1
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
@@ -543,8 +543,9 @@ class DeepSeekBrain:
|
||||
if models:
|
||||
model_id = models[0].get("id", self.config.model)
|
||||
if model_id:
|
||||
logger.info("Available model: %s (keeping configured: %s)", model_id, self.config.model)
|
||||
self.config.model = model_id
|
||||
logger.info("Auto-detected model: %s", model_id)
|
||||
logger.info("LLM brain connected to %s", self.config.api_base)
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.warning("LLM brain connection failed: %s", e)
|
||||
@@ -590,31 +591,25 @@ class DeepSeekBrain:
|
||||
if not self._connected:
|
||||
return self._fallback_action(snapshot, t_start, "not_connected")
|
||||
|
||||
last_err = None
|
||||
for attempt in range(1, self.config.max_retries + 1):
|
||||
try:
|
||||
result = self._call_llm(snapshot)
|
||||
result["source"] = "llm"
|
||||
result["latency_ms"] = round((time.time() - t_start) * 1000, 1)
|
||||
try:
|
||||
result = self._call_llm(snapshot)
|
||||
result["source"] = "llm"
|
||||
result["latency_ms"] = round((time.time() - t_start) * 1000, 1)
|
||||
|
||||
if self.config.cache_enabled:
|
||||
self._put_cache(cache_key, result)
|
||||
if self.config.cache_enabled:
|
||||
self._put_cache(cache_key, result)
|
||||
|
||||
if self.config.log_decisions:
|
||||
self._log_decision(snapshot, result, player_index)
|
||||
if self.config.log_decisions:
|
||||
self._log_decision(snapshot, result, player_index)
|
||||
|
||||
self._total_latency_ms += result["latency_ms"]
|
||||
return result
|
||||
self._total_latency_ms += result["latency_ms"]
|
||||
return result
|
||||
|
||||
except Exception as e:
|
||||
last_err = e
|
||||
logger.warning("LLM call failed (turn %d, attempt %d/%d): %s", turn + 1, attempt, self.config.max_retries, e)
|
||||
if attempt < self.config.max_retries:
|
||||
continue
|
||||
|
||||
if self.config.fallback_on_timeout:
|
||||
return self._fallback_action(snapshot, t_start, str(last_err))
|
||||
raise last_err
|
||||
except Exception as e:
|
||||
logger.warning("LLM call failed (turn %d): %s", turn + 1, e)
|
||||
if self.config.fallback_on_timeout:
|
||||
return self._fallback_action(snapshot, t_start, str(e))
|
||||
raise
|
||||
|
||||
def _call_llm(self, snapshot: dict) -> dict:
|
||||
"""Send game state to LLM and parse response."""
|
||||
@@ -659,10 +654,9 @@ class DeepSeekBrain:
|
||||
text = re.sub(r'\s*```$', '', text)
|
||||
text = text.strip()
|
||||
|
||||
start = text.find('{')
|
||||
end = text.rfind('}')
|
||||
if start != -1 and end != -1 and end > start:
|
||||
text = text[start:end + 1]
|
||||
json_match = re.search(r'\{[^{}]*\}', text, re.DOTALL)
|
||||
if json_match:
|
||||
text = json_match.group(0)
|
||||
|
||||
try:
|
||||
parsed = json.loads(text)
|
||||
|
||||
@@ -23,7 +23,7 @@ Usage::
|
||||
from commander_ai_lab.sim.deepseek_engine import DeepSeekGameEngine
|
||||
from commander_ai_lab.sim.deepseek_brain import DeepSeekBrain, DeepSeekConfig
|
||||
|
||||
brain = DeepSeekBrain(DeepSeekConfig(api_base="http://localhost:11434"))
|
||||
brain = DeepSeekBrain(DeepSeekConfig(api_base="http://192.168.0.240:11434"))
|
||||
brain.check_connection()
|
||||
engine = DeepSeekGameEngine(brain=brain, ai_player_index=1)
|
||||
result = engine.run(deck_a, deck_b, name_a="My Deck", name_b="DeepSeek AI")
|
||||
|
||||
@@ -28,14 +28,10 @@ from typing import Optional
|
||||
|
||||
from commander_ai_lab.sim.models import (
|
||||
Card,
|
||||
CombatState,
|
||||
GameResult,
|
||||
Phase,
|
||||
PHASE_ORDER,
|
||||
Player,
|
||||
PlayerResult,
|
||||
PlayerStats,
|
||||
SORCERY_PHASES,
|
||||
SimState,
|
||||
)
|
||||
from commander_ai_lab.sim.rules import (
|
||||
@@ -64,9 +60,6 @@ class GameEngine:
|
||||
``weights`` explicitly to override (e.g. for A/B testing).
|
||||
"""
|
||||
|
||||
# London mulligan: max times a player may mulligan before forced keep
|
||||
MAX_MULLIGANS = 4
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
max_turns: int = 25,
|
||||
@@ -74,7 +67,6 @@ class GameEngine:
|
||||
weights: Optional[dict] = None,
|
||||
record_log: bool = False,
|
||||
ml_log: bool = False,
|
||||
mulligan_rule: str = "london",
|
||||
):
|
||||
self.max_turns = max_turns
|
||||
self.starting_life = starting_life
|
||||
@@ -83,7 +75,6 @@ class GameEngine:
|
||||
self.record_log = record_log
|
||||
self.ml_log = ml_log
|
||||
self.ml_decisions: list[dict] = []
|
||||
self.mulligan_rule = mulligan_rule
|
||||
|
||||
# ──────────────────────────────────────────────────────────
|
||||
# Public API
|
||||
@@ -124,7 +115,6 @@ class GameEngine:
|
||||
final_turn = 0
|
||||
|
||||
for turn in range(sim.max_turns):
|
||||
sim.turn = turn
|
||||
turn_entry = {"turn": turn + 1, "phases": []}
|
||||
|
||||
for pi in range(len(sim.players)):
|
||||
@@ -132,106 +122,59 @@ class GameEngine:
|
||||
if p.eliminated:
|
||||
continue
|
||||
p.stats.turns_alive += 1
|
||||
sim.active_player_index = pi
|
||||
phase_events: list[str] = []
|
||||
|
||||
# ── Untap (correct MTG order: untap is first) ──
|
||||
for c in sim.get_battlefield(pi):
|
||||
c.tapped = False
|
||||
c.damage_marked = 0 # clear damage each turn (MTG rule 514.2)
|
||||
|
||||
# ── Draw ──
|
||||
if p.library:
|
||||
drawn = p.library[-1]
|
||||
p.hand.append(p.library.pop())
|
||||
p.stats.cards_drawn += 1
|
||||
if self.record_log:
|
||||
phase_events.append(f"Drew {drawn.name}")
|
||||
|
||||
# ── Capture ML snapshot BEFORE turn actions ──
|
||||
pre_snapshot = None
|
||||
if self.ml_log:
|
||||
pre_snapshot = self._capture_ml_snapshot(sim, pi, turn)
|
||||
|
||||
# Track spell/damage counts for ML logging
|
||||
# ── Land drop ──
|
||||
land_before = p.stats.lands_played
|
||||
self._play_land(sim, pi)
|
||||
played_land = p.stats.lands_played > land_before
|
||||
if self.record_log and played_land:
|
||||
last_land = next(
|
||||
(c for c in reversed(sim.get_battlefield(pi))
|
||||
if c.is_land()),
|
||||
None,
|
||||
)
|
||||
if last_land:
|
||||
phase_events.append(f"Played land: {last_land.name}")
|
||||
|
||||
# ── Available mana ──
|
||||
available_mana = self._count_untapped_lands(sim, pi)
|
||||
|
||||
# ── Play spells (up to 2) ──
|
||||
spells_before = p.stats.spells_cast
|
||||
damage_before_turn = p.stats.damage_dealt
|
||||
spells_budget = 2 # shared across main1 + main2
|
||||
|
||||
# ── Walk each phase in order ──
|
||||
for phase in PHASE_ORDER:
|
||||
sim.current_phase = phase
|
||||
|
||||
if phase == Phase.UNTAP:
|
||||
for c in sim.get_battlefield(pi):
|
||||
c.tapped = False
|
||||
c.damage_marked = 0 # MTG rule 514.2
|
||||
|
||||
elif phase == Phase.UPKEEP:
|
||||
pass # placeholder — triggers would fire here
|
||||
|
||||
elif phase == Phase.DRAW:
|
||||
if p.library:
|
||||
drawn = p.library[-1]
|
||||
p.hand.append(p.library.pop())
|
||||
p.stats.cards_drawn += 1
|
||||
if self.record_log:
|
||||
phase_events.append(f"Drew {drawn.name}")
|
||||
|
||||
elif phase == Phase.MAIN1:
|
||||
# Land drop (only in main1, per MTG convention)
|
||||
land_before = p.stats.lands_played
|
||||
self._play_land(sim, pi)
|
||||
played_land = p.stats.lands_played > land_before
|
||||
if self.record_log and played_land:
|
||||
last_land = next(
|
||||
(c for c in reversed(sim.get_battlefield(pi))
|
||||
if c.is_land()),
|
||||
None,
|
||||
)
|
||||
if last_land:
|
||||
phase_events.append(f"Played land: {last_land.name}")
|
||||
|
||||
# Play spells (shared budget across main1 + main2)
|
||||
available_mana = self._count_untapped_lands(sim, pi)
|
||||
cast = self._play_spells(
|
||||
sim, pi, available_mana,
|
||||
phase_events if self.record_log else None,
|
||||
max_spells=spells_budget,
|
||||
)
|
||||
spells_budget -= cast
|
||||
|
||||
elif phase == Phase.BEGIN_COMBAT:
|
||||
pass # placeholder — "beginning of combat" triggers
|
||||
|
||||
elif phase == Phase.DECLARE_ATTACKERS:
|
||||
self._resolve_combat(sim, pi, turn, phase_events if self.record_log else None)
|
||||
|
||||
elif phase == Phase.DECLARE_BLOCKERS:
|
||||
pass # blocking is handled inside _resolve_combat
|
||||
|
||||
elif phase == Phase.COMBAT_DAMAGE:
|
||||
pass # damage is handled inside _resolve_combat
|
||||
|
||||
elif phase == Phase.END_COMBAT:
|
||||
pass # placeholder — "end of combat" triggers
|
||||
|
||||
elif phase == Phase.MAIN2:
|
||||
# Second main phase: use remaining spell budget
|
||||
if spells_budget > 0:
|
||||
available_mana = self._count_untapped_lands(sim, pi)
|
||||
cast = self._play_spells(
|
||||
sim, pi, available_mana,
|
||||
phase_events if self.record_log else None,
|
||||
max_spells=spells_budget,
|
||||
)
|
||||
spells_budget -= cast
|
||||
|
||||
elif phase == Phase.END_STEP:
|
||||
pass # placeholder — "at end of turn" triggers
|
||||
|
||||
elif phase == Phase.CLEANUP:
|
||||
pass # damage clearing already happened in untap for simplicity
|
||||
|
||||
# ── Post-phase bookkeeping ──
|
||||
self._play_spells(sim, pi, available_mana, phase_events if self.record_log else None)
|
||||
played_spell = p.stats.spells_cast > spells_before
|
||||
attacked = p.stats.damage_dealt > damage_before_turn
|
||||
|
||||
# Track board size
|
||||
# ── Track board size ──
|
||||
board_size = len(sim.get_battlefield(pi))
|
||||
if board_size > p.stats.max_board_size:
|
||||
p.stats.max_board_size = board_size
|
||||
|
||||
# ── Combat ──
|
||||
damage_before = p.stats.damage_dealt
|
||||
self._resolve_combat(sim, pi, turn, phase_events if self.record_log else None)
|
||||
attacked = p.stats.damage_dealt > damage_before
|
||||
|
||||
# ── Record ML decision snapshot ──
|
||||
if self.ml_log and pre_snapshot is not None:
|
||||
available_mana = self._count_untapped_lands(sim, pi)
|
||||
if attacked:
|
||||
action_type = "attack"
|
||||
elif played_spell:
|
||||
@@ -339,42 +282,6 @@ class GameEngine:
|
||||
# Internal helpers
|
||||
# ──────────────────────────────────────────────────────────
|
||||
|
||||
# ──────────────────────────────────────────────────────────
|
||||
# Opening-hand helpers
|
||||
# ──────────────────────────────────────────────────────────
|
||||
|
||||
@staticmethod
|
||||
def _count_lands_in_hand(hand: list[Card]) -> int:
|
||||
"""Count lands in a hand of cards."""
|
||||
return sum(1 for c in hand if c.is_land())
|
||||
|
||||
@staticmethod
|
||||
def _should_mulligan(hand: list[Card], mulligan_number: int) -> bool:
|
||||
"""Heuristic: mulligan if opening hand has 0-1 lands or 6-7 lands.
|
||||
|
||||
Becomes more lenient with each successive mulligan — after 2+
|
||||
mulligans, accept 1-land hands to avoid going too low on cards.
|
||||
"""
|
||||
lands = GameEngine._count_lands_in_hand(hand)
|
||||
total = len(hand)
|
||||
if mulligan_number >= 2:
|
||||
# Desperate: keep anything with 1-5 lands
|
||||
return lands < 1 or lands >= total
|
||||
# Standard: keep 2-5 lands in a 7-card hand
|
||||
return lands <= 1 or lands >= 6
|
||||
|
||||
@staticmethod
|
||||
def _pick_bottom_cards(hand: list[Card], count: int, weights: dict) -> list[Card]:
|
||||
"""Choose the worst *count* cards to put on the bottom of library.
|
||||
|
||||
Uses the AI scoring function so the least valuable cards are
|
||||
bottomed — mirrors a real player's London mulligan decision.
|
||||
"""
|
||||
if count <= 0 or count >= len(hand):
|
||||
return []
|
||||
scored = sorted(hand, key=lambda c: score_card(c, weights))
|
||||
return scored[:count]
|
||||
|
||||
def _create_state(
|
||||
self,
|
||||
decks: list[list[Card]],
|
||||
@@ -383,11 +290,6 @@ class GameEngine:
|
||||
) -> SimState:
|
||||
"""Create initial simulation state with shuffled decks and opening hands (N players).
|
||||
|
||||
Implements the London mulligan rule: each player draws 7, decides
|
||||
whether to keep, and if not shuffles back and redraws. After
|
||||
keeping, they put N cards on the bottom of their library where N
|
||||
is the number of times they mulliganed.
|
||||
|
||||
If commander_names is provided, the matching card is flagged
|
||||
is_commander=True and placed in the player's command_zone
|
||||
instead of the library/hand.
|
||||
@@ -406,46 +308,16 @@ class GameEngine:
|
||||
commander_card = c
|
||||
else:
|
||||
remaining.append(c)
|
||||
|
||||
# ── London mulligan loop ──
|
||||
mulligan_count = 0
|
||||
if self.mulligan_rule == "london":
|
||||
for attempt in range(self.MAX_MULLIGANS):
|
||||
random.shuffle(remaining)
|
||||
hand = remaining[:7]
|
||||
if not self._should_mulligan(hand, attempt):
|
||||
break
|
||||
mulligan_count += 1
|
||||
else:
|
||||
# Exhausted all mulligans — forced keep with last draw
|
||||
random.shuffle(remaining)
|
||||
hand = remaining[:7]
|
||||
else:
|
||||
# No mulligan (legacy behavior)
|
||||
random.shuffle(remaining)
|
||||
hand = remaining[:7]
|
||||
|
||||
random.shuffle(remaining)
|
||||
hand = remaining[:7]
|
||||
library = remaining[7:]
|
||||
|
||||
# ── Bottom N cards for London mulligan ──
|
||||
if mulligan_count > 0:
|
||||
bottom = self._pick_bottom_cards(hand, mulligan_count, self.weights)
|
||||
for card in bottom:
|
||||
hand.remove(card)
|
||||
library.insert(0, card) # bottom of library
|
||||
|
||||
opening_lands = self._count_lands_in_hand(hand)
|
||||
player = Player(
|
||||
name=name,
|
||||
life=self.starting_life,
|
||||
owner_id=idx,
|
||||
library=library,
|
||||
hand=hand,
|
||||
stats=PlayerStats(
|
||||
cards_drawn=7,
|
||||
mulligans=mulligan_count,
|
||||
opening_hand_lands=opening_lands,
|
||||
),
|
||||
stats=PlayerStats(cards_drawn=7),
|
||||
)
|
||||
if commander_card:
|
||||
player.command_zone.append(commander_card)
|
||||
@@ -482,57 +354,6 @@ class GameEngine:
|
||||
else:
|
||||
owner.graveyard.append(card)
|
||||
|
||||
# ──────────────────────────────────────────────────────────
|
||||
# Centralized Damage
|
||||
# ──────────────────────────────────────────────────────────
|
||||
|
||||
@staticmethod
|
||||
def deal_damage(
|
||||
sim: SimState,
|
||||
amount: int,
|
||||
target_seat: int,
|
||||
source_card: Card | None = None,
|
||||
source_seat: int | None = None,
|
||||
is_combat: bool = False,
|
||||
events: list | None = None,
|
||||
label: str = "",
|
||||
) -> int:
|
||||
"""Apply *amount* damage to a player through the centralized path.
|
||||
|
||||
Handles life reduction, stat tracking, commander damage tracking
|
||||
(both per-seat aggregate and per-card breakdown from PR #89),
|
||||
and elimination checks. Returns the actual damage dealt.
|
||||
"""
|
||||
if amount <= 0:
|
||||
return 0
|
||||
target = sim.players[target_seat]
|
||||
if target.eliminated:
|
||||
return 0
|
||||
|
||||
target.life -= amount
|
||||
target.stats.damage_received += amount
|
||||
if source_seat is not None:
|
||||
sim.players[source_seat].stats.damage_dealt += amount
|
||||
|
||||
# Commander damage tracking — dual-dict model (PR #89):
|
||||
# commander_damage_received[seat] = aggregate per-seat total
|
||||
# commander_damage_by_card[(seat, card_name)] = per-card breakdown
|
||||
if source_card and source_card.is_commander and source_seat is not None:
|
||||
target.commander_damage_received[source_seat] = (
|
||||
target.commander_damage_received.get(source_seat, 0) + amount
|
||||
)
|
||||
key = (source_seat, source_card.name)
|
||||
target.commander_damage_by_card[key] = (
|
||||
target.commander_damage_by_card.get(key, 0) + amount
|
||||
)
|
||||
|
||||
if events is not None and label:
|
||||
events.append(f"{label} ({target.name} now at {target.life} life)")
|
||||
|
||||
if target.life <= 0 or target.is_dead_to_commander_damage():
|
||||
target.eliminated = True
|
||||
return amount
|
||||
|
||||
def _count_untapped_lands(self, sim: SimState, pi: int) -> int:
|
||||
"""Count untapped lands for a player."""
|
||||
return sum(
|
||||
@@ -541,15 +362,12 @@ class GameEngine:
|
||||
if not c.tapped and c.is_land()
|
||||
)
|
||||
|
||||
def _play_spells(self, sim: SimState, pi: int, available_mana: int, events: list | None = None, max_spells: int = 2) -> int:
|
||||
"""Play up to *max_spells* spells from hand, prioritized by AI score.
|
||||
|
||||
Returns the number of spells actually played this call.
|
||||
"""
|
||||
def _play_spells(self, sim: SimState, pi: int, available_mana: int, events: list | None = None) -> None:
|
||||
"""Play up to 2 spells from hand, prioritized by AI score."""
|
||||
p = sim.players[pi]
|
||||
w = self.weights
|
||||
played = 0
|
||||
while played < max_spells:
|
||||
while played < 2:
|
||||
playable = []
|
||||
for i, card in enumerate(p.hand):
|
||||
if card.is_land():
|
||||
@@ -619,22 +437,14 @@ class GameEngine:
|
||||
p.graveyard.append(card)
|
||||
if events is not None:
|
||||
events.append(f"Cast {card.name} (board wipe) \u2014 destroyed {len(wiped_names)} creatures")
|
||||
elif card.is_direct_damage and card.direct_damage_amount > 0:
|
||||
# Direct-damage spell (burn): route through centralized deal_damage()
|
||||
target_seat = self._select_attack_target(sim, pi)
|
||||
if target_seat != -1:
|
||||
target_name = sim.players[target_seat].name
|
||||
self.deal_damage(
|
||||
sim, card.direct_damage_amount, target_seat,
|
||||
source_card=card, source_seat=pi,
|
||||
events=events,
|
||||
label=f"{card.name} deals {card.direct_damage_amount} damage to {target_name}",
|
||||
)
|
||||
elif events is not None:
|
||||
events.append(f"Cast {card.name} (burn, no targets)")
|
||||
p.graveyard.append(card)
|
||||
else:
|
||||
sim.add_to_battlefield(pi, card)
|
||||
# Fix #84/BUG-05: instants and sorceries resolve and go to
|
||||
# graveyard — they are NOT permanents and should never stay
|
||||
# on the battlefield.
|
||||
if card.is_permanent():
|
||||
sim.add_to_battlefield(pi, card)
|
||||
else:
|
||||
self._send_to_graveyard(sim, card, pi)
|
||||
if card.is_creature():
|
||||
p.stats.creatures_played += 1
|
||||
if events is not None:
|
||||
@@ -678,7 +488,6 @@ class GameEngine:
|
||||
f"for {total_cost} mana (tax={tax})"
|
||||
)
|
||||
available_mana = self._count_untapped_lands(sim, pi)
|
||||
return played
|
||||
|
||||
@staticmethod
|
||||
def _select_attack_target(sim: SimState, pi: int) -> int:
|
||||
@@ -712,7 +521,7 @@ class GameEngine:
|
||||
c
|
||||
for c in sim.get_battlefield(pi)
|
||||
if (
|
||||
c.is_creature()
|
||||
c.can_attack_or_block()
|
||||
and not c.tapped
|
||||
and (c.turn_played < sim.turn or c.has_keyword("haste"))
|
||||
)
|
||||
@@ -723,7 +532,7 @@ class GameEngine:
|
||||
c
|
||||
for c in sim.get_battlefield(opp_idx)
|
||||
if (
|
||||
c.is_creature()
|
||||
c.can_attack_or_block()
|
||||
and not c.tapped
|
||||
)
|
||||
]
|
||||
@@ -756,8 +565,6 @@ class GameEngine:
|
||||
total_damage = 0
|
||||
used_blockers: set[int] = set()
|
||||
combat_details: list[str] = []
|
||||
# Per-attacker damage to route through deal_damage() individually
|
||||
attacker_damage: list[tuple[Card, int]] = []
|
||||
for atk in attackers:
|
||||
a_pow = atk.get_power()
|
||||
a_tou = atk.get_toughness()
|
||||
@@ -806,12 +613,12 @@ class GameEngine:
|
||||
trample_over = 0
|
||||
if atk.has_keyword("trample") and a_pow > blocker.get_toughness():
|
||||
trample_over = a_pow - blocker.get_toughness()
|
||||
attacker_damage.append((atk, trample_over))
|
||||
total_damage += trample_over
|
||||
if atk.has_keyword("double strike"):
|
||||
ds_dmg = a_pow if (a_pow >= blocker.get_toughness() or atk.has_keyword("deathtouch")) else trample_over
|
||||
attacker_damage.append((atk, ds_dmg))
|
||||
total_damage += ds_dmg
|
||||
if a_pow >= blocker.get_toughness() or atk.has_keyword("deathtouch"):
|
||||
total_damage += a_pow
|
||||
else:
|
||||
total_damage += trample_over
|
||||
if atk.has_keyword("lifelink"):
|
||||
damage_dealt = min(a_pow, blocker.get_toughness()) + trample_over
|
||||
if atk.has_keyword("double strike"):
|
||||
@@ -819,261 +626,21 @@ class GameEngine:
|
||||
p.life += damage_dealt
|
||||
if not blocked:
|
||||
if atk.has_keyword("double strike"):
|
||||
atk_dmg = a_pow * 2
|
||||
total_damage += a_pow * 2
|
||||
if atk.has_keyword("lifelink"):
|
||||
p.life += a_pow * 2
|
||||
else:
|
||||
atk_dmg = a_pow
|
||||
total_damage += a_pow
|
||||
if atk.has_keyword("lifelink"):
|
||||
p.life += a_pow
|
||||
attacker_damage.append((atk, atk_dmg))
|
||||
total_damage += atk_dmg
|
||||
# Route each attacker's damage through deal_damage() for
|
||||
# centralized life/stats/commander tracking
|
||||
for atk_card, dmg in attacker_damage:
|
||||
if dmg > 0:
|
||||
self.deal_damage(
|
||||
sim, dmg, opp_idx,
|
||||
source_card=atk_card, source_seat=pi,
|
||||
is_combat=True,
|
||||
)
|
||||
opp.life -= total_damage
|
||||
p.stats.damage_dealt += total_damage
|
||||
opp.stats.damage_received += total_damage
|
||||
if events is not None and total_damage > 0:
|
||||
# Compute commander damage annotation from the per-card dict
|
||||
total_cmd_damage = sum(
|
||||
dmg for (atk_card, dmg) in attacker_damage
|
||||
if atk_card.is_commander and dmg > 0
|
||||
)
|
||||
cmd_note = f" ({total_cmd_damage} cmdr)" if total_cmd_damage > 0 else ""
|
||||
events.append(
|
||||
f"Dealt {total_damage} combat damage{cmd_note} to {opp.name} (now {opp.life} life)"
|
||||
)
|
||||
events.append(f"Dealt {total_damage} combat damage to {opp.name} (now {opp.life} life)")
|
||||
events.extend(combat_details)
|
||||
|
||||
# ──────────────────────────────────────────────────────────
|
||||
# Split combat methods for turn_manager priority windows
|
||||
# (Issue #86 Item 1). The original _resolve_combat() above
|
||||
# remains as the backward-compatible atomic path for run_n().
|
||||
# ──────────────────────────────────────────────────────────
|
||||
|
||||
def assign_attackers(
|
||||
self, sim: SimState, pi: int, events: list | None = None,
|
||||
) -> Optional[CombatState]:
|
||||
"""Phase 1 of split combat: choose attackers, populate CombatState.
|
||||
|
||||
Returns a CombatState with attackers set and tapped, or None if
|
||||
no valid attack is possible. Does NOT deal any damage.
|
||||
"""
|
||||
p = sim.players[pi]
|
||||
opp_idx = self._select_attack_target(sim, pi)
|
||||
if opp_idx == -1:
|
||||
return None
|
||||
|
||||
opp = sim.players[opp_idx]
|
||||
w = self.weights
|
||||
my_creatures = [
|
||||
c
|
||||
for c in sim.get_battlefield(pi)
|
||||
if (
|
||||
c.is_creature()
|
||||
and not c.tapped
|
||||
and (c.turn_played < sim.turn or c.has_keyword("haste"))
|
||||
)
|
||||
]
|
||||
if not my_creatures:
|
||||
return None
|
||||
|
||||
opp_blockers = [
|
||||
c
|
||||
for c in sim.get_battlefield(opp_idx)
|
||||
if c.is_creature() and not c.tapped
|
||||
]
|
||||
|
||||
attackers = []
|
||||
total_my_power = sum(c.get_power() for c in my_creatures)
|
||||
for atk in my_creatures:
|
||||
a_pow = atk.get_power()
|
||||
a_tou = atk.get_toughness()
|
||||
has_flying = atk.has_keyword("flying")
|
||||
has_trample = atk.has_keyword("trample")
|
||||
has_haste = atk.has_keyword("haste")
|
||||
|
||||
if has_flying or has_trample or has_haste or a_pow >= 3 or opp.life <= total_my_power:
|
||||
attackers.append(atk)
|
||||
atk.tapped = True
|
||||
continue
|
||||
|
||||
can_die_profitably = any(
|
||||
(
|
||||
(not has_flying or b.has_keyword("flying") or b.has_keyword("reach"))
|
||||
and (b.get_power() >= a_tou or b.has_keyword("deathtouch"))
|
||||
and b.get_toughness() > a_pow
|
||||
)
|
||||
for b in opp_blockers
|
||||
)
|
||||
if not can_die_profitably or p.life > 25:
|
||||
attackers.append(atk)
|
||||
atk.tapped = True
|
||||
|
||||
if not attackers:
|
||||
return None
|
||||
|
||||
if events is not None:
|
||||
atk_names = [f"{a.name} ({a.pt})" for a in attackers]
|
||||
events.append(f"Attacks {opp.name} with: {', '.join(atk_names)}")
|
||||
|
||||
# Build and store CombatState
|
||||
combat = CombatState(
|
||||
defending_seat=opp_idx,
|
||||
attackers={atk.id: opp_idx for atk in attackers},
|
||||
active=True,
|
||||
)
|
||||
sim.combat = combat
|
||||
return combat
|
||||
|
||||
def assign_blockers(
|
||||
self, sim: SimState, pi: int, combat: CombatState,
|
||||
events: list | None = None,
|
||||
) -> None:
|
||||
"""Phase 2 of split combat: assign blockers into CombatState.
|
||||
|
||||
Populates combat.blockers and combat.player_damage.
|
||||
Does NOT apply any damage to players or creatures yet.
|
||||
"""
|
||||
opp_idx = combat.defending_seat
|
||||
opp_blockers = [
|
||||
c for c in sim.get_battlefield(opp_idx)
|
||||
if c.is_creature() and not c.tapped
|
||||
]
|
||||
used_blockers: set[int] = set()
|
||||
|
||||
for atk_id in combat.attackers:
|
||||
atk = next((c for bf in sim.battlefields for c in bf if c.id == atk_id), None)
|
||||
if atk is None:
|
||||
continue
|
||||
a_pow = atk.get_power()
|
||||
has_flying = atk.has_keyword("flying")
|
||||
valid_blockers = [
|
||||
b for b in opp_blockers
|
||||
if b.id not in used_blockers
|
||||
and (not has_flying or b.has_keyword("flying") or b.has_keyword("reach"))
|
||||
]
|
||||
|
||||
blocker = None
|
||||
if valid_blockers and (not atk.has_keyword("menace") or len(valid_blockers) >= 2):
|
||||
if atk.has_keyword("menace") and len(valid_blockers) >= 2:
|
||||
valid_blockers.sort(key=lambda b: -b.get_toughness())
|
||||
blocker = valid_blockers[0]
|
||||
used_blockers.add(valid_blockers[1].id)
|
||||
else:
|
||||
blocker = next(
|
||||
(b for b in valid_blockers if b.get_toughness() > a_pow),
|
||||
None,
|
||||
)
|
||||
opp = sim.players[opp_idx]
|
||||
if blocker is None and opp.life <= a_pow * 2 and valid_blockers:
|
||||
blocker = valid_blockers[0]
|
||||
|
||||
if blocker:
|
||||
used_blockers.add(blocker.id)
|
||||
combat.blockers[atk_id] = [blocker.id]
|
||||
if events is not None:
|
||||
events.append(f"{atk.name} blocked by {blocker.name}")
|
||||
else:
|
||||
# Unblocked — full damage goes to player
|
||||
combat.player_damage[atk_id] = a_pow
|
||||
|
||||
def resolve_combat_damage(
|
||||
self, sim: SimState, pi: int, combat: CombatState,
|
||||
first_strike_only: bool = False,
|
||||
events: list | None = None,
|
||||
) -> None:
|
||||
"""Phase 3 of split combat: apply damage from CombatState.
|
||||
|
||||
When first_strike_only=True, only processes creatures with
|
||||
first_strike or double_strike. When False, processes all
|
||||
remaining (skipping first-strikers if already resolved).
|
||||
"""
|
||||
opp_idx = combat.defending_seat
|
||||
p = sim.players[pi]
|
||||
total_damage = 0
|
||||
attacker_damage: list[tuple[Card, int]] = []
|
||||
combat_details: list[str] = []
|
||||
|
||||
for atk_id, def_seat in list(combat.attackers.items()):
|
||||
atk = next((c for bf in sim.battlefields for c in bf if c.id == atk_id), None)
|
||||
if atk is None:
|
||||
continue # removed by instant before damage
|
||||
|
||||
is_fs = atk.has_keyword("first_strike") or atk.has_keyword("double_strike")
|
||||
if first_strike_only and not is_fs:
|
||||
continue
|
||||
if not first_strike_only and is_fs and combat.first_strike_resolved:
|
||||
if not atk.has_keyword("double_strike"):
|
||||
continue # already dealt damage in FS step
|
||||
|
||||
a_pow = atk.get_power()
|
||||
a_tou = atk.get_toughness()
|
||||
blocker_ids = combat.blockers.get(atk_id, [])
|
||||
|
||||
if blocker_ids:
|
||||
blocker = next((c for bf in sim.battlefields for c in bf if c.id == blocker_ids[0]), None)
|
||||
if blocker is None:
|
||||
# Blocker removed — attacker is still blocked but deals no combat damage to player
|
||||
continue
|
||||
b_pow = blocker.get_power()
|
||||
blocker.damage_marked += a_pow
|
||||
if blocker.damage_marked >= blocker.get_toughness() or atk.has_keyword("deathtouch"):
|
||||
sim.remove_from_battlefield(blocker.id)
|
||||
self._send_to_graveyard(sim, blocker, opp_idx)
|
||||
if events is not None:
|
||||
combat_details.append(f" {blocker.name} dies")
|
||||
atk.damage_marked += b_pow
|
||||
if atk.damage_marked >= a_tou or blocker.has_keyword("deathtouch"):
|
||||
sim.remove_from_battlefield(atk.id)
|
||||
self._send_to_graveyard(sim, atk, pi)
|
||||
if events is not None:
|
||||
combat_details.append(f" {atk.name} dies")
|
||||
# Trample over
|
||||
trample_over = 0
|
||||
if atk.has_keyword("trample") and a_pow > blocker.get_toughness():
|
||||
trample_over = a_pow - blocker.get_toughness()
|
||||
attacker_damage.append((atk, trample_over))
|
||||
total_damage += trample_over
|
||||
if atk.has_keyword("lifelink"):
|
||||
p.life += min(a_pow, blocker.get_toughness()) + trample_over
|
||||
else:
|
||||
# Unblocked
|
||||
atk_dmg = a_pow * 2 if atk.has_keyword("double_strike") else a_pow
|
||||
if atk.has_keyword("lifelink"):
|
||||
p.life += atk_dmg
|
||||
attacker_damage.append((atk, atk_dmg))
|
||||
total_damage += atk_dmg
|
||||
|
||||
# Route each attacker's damage through deal_damage()
|
||||
for atk_card, dmg in attacker_damage:
|
||||
if dmg > 0:
|
||||
self.deal_damage(
|
||||
sim, dmg, opp_idx,
|
||||
source_card=atk_card, source_seat=pi,
|
||||
is_combat=True,
|
||||
)
|
||||
|
||||
if first_strike_only:
|
||||
combat.first_strike_resolved = True
|
||||
|
||||
if events is not None and total_damage > 0:
|
||||
opp = sim.players[opp_idx]
|
||||
total_cmd_damage = sum(
|
||||
dmg for (atk_card, dmg) in attacker_damage
|
||||
if atk_card.is_commander and dmg > 0
|
||||
)
|
||||
cmd_note = f" ({total_cmd_damage} cmdr)" if total_cmd_damage > 0 else ""
|
||||
events.append(
|
||||
f"Dealt {total_damage} combat damage{cmd_note} to {opp.name} (now {opp.life} life)"
|
||||
)
|
||||
events.extend(combat_details)
|
||||
|
||||
|
||||
if opp.life <= 0:
|
||||
opp.eliminated = True
|
||||
|
||||
def _build_result(
|
||||
self,
|
||||
|
||||
@@ -1,171 +0,0 @@
|
||||
"""
|
||||
Forge Card Loader
|
||||
=================
|
||||
Parse Forge cardsfolder .txt files into structured data for sim enrichment.
|
||||
Lazy-loaded and cached at module level.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import os
|
||||
import re
|
||||
from dataclasses import dataclass, field
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
from models.state import CFG
|
||||
|
||||
_log = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class ForgeCardData:
|
||||
"""Structured representation of a single Forge .txt card definition."""
|
||||
name: str = ""
|
||||
mana_cost: str = ""
|
||||
cmc: int = 0
|
||||
type_line: str = ""
|
||||
oracle_text: str = ""
|
||||
pt: str = ""
|
||||
keywords: list[str] = field(default_factory=list)
|
||||
trigger_modes: list[str] = field(default_factory=list)
|
||||
has_replacement_effect: bool = False
|
||||
has_static_ability: bool = False
|
||||
|
||||
|
||||
# -- Module-level lazy cache ---
|
||||
_FORGE_CACHE: dict[str, ForgeCardData] = {}
|
||||
_FORGE_CACHE_LOADED: bool = False
|
||||
|
||||
|
||||
def _get_cards_folder() -> Path:
|
||||
"""Resolve the Forge cardsfolder directory from CFG.forge_dir.
|
||||
|
||||
Supports two layouts:
|
||||
A) forge_dir = .../forge-repo -> forge-gui/res/cardsfolder
|
||||
B) forge_dir = .../forge-repo/forge-gui -> res/cardsfolder
|
||||
"""
|
||||
if not CFG.forge_dir:
|
||||
return Path("")
|
||||
base = Path(CFG.forge_dir)
|
||||
candidate_a = base / "forge-gui" / "res" / "cardsfolder"
|
||||
candidate_b = base / "res" / "cardsfolder"
|
||||
if candidate_a.is_dir():
|
||||
return candidate_a
|
||||
if candidate_b.is_dir():
|
||||
return candidate_b
|
||||
return candidate_a # fall back so warning shows the expected path
|
||||
|
||||
|
||||
def _parse_forge_file(filepath: Path) -> Optional[ForgeCardData]:
|
||||
"""Parse a single Forge .txt card file into ForgeCardData."""
|
||||
try:
|
||||
text = filepath.read_text(encoding="utf-8", errors="replace")
|
||||
except OSError:
|
||||
return None
|
||||
|
||||
data = ForgeCardData()
|
||||
lines = text.splitlines()
|
||||
for line in lines:
|
||||
line = line.strip()
|
||||
if not line or line.startswith("#"):
|
||||
continue
|
||||
# Name
|
||||
if line.startswith("Name:"):
|
||||
data.name = line.split(":", 1)[1].strip()
|
||||
# ManaCost
|
||||
elif line.startswith("ManaCost:"):
|
||||
raw = line.split(":", 1)[1].strip()
|
||||
data.mana_cost = raw
|
||||
data.cmc = _calc_cmc(raw)
|
||||
# Types
|
||||
elif line.startswith("Types:"):
|
||||
data.type_line = line.split(":", 1)[1].strip()
|
||||
# PT
|
||||
elif line.startswith("PT:"):
|
||||
data.pt = line.split(":", 1)[1].strip()
|
||||
# Oracle
|
||||
elif line.startswith("Oracle:"):
|
||||
data.oracle_text = line.split(":", 1)[1].strip()
|
||||
# K -- Keywords
|
||||
elif line.startswith("K:"):
|
||||
kw = line.split(":", 1)[1].strip()
|
||||
if kw and kw not in data.keywords:
|
||||
data.keywords.append(kw)
|
||||
# T -- Trigger modes (e.g. T:Mode$ ChangesZone)
|
||||
elif line.startswith("T:"):
|
||||
mode_match = re.search(r"Mode\$\s*(\w+)", line)
|
||||
if mode_match:
|
||||
mode = mode_match.group(1)
|
||||
if mode not in data.trigger_modes:
|
||||
data.trigger_modes.append(mode)
|
||||
# R -- Replacement effects
|
||||
elif line.startswith("R:"):
|
||||
data.has_replacement_effect = True
|
||||
# S -- Static abilities
|
||||
elif line.startswith("S:"):
|
||||
data.has_static_ability = True
|
||||
# SVar (secondary -- grab Oracle from SVar if not set)
|
||||
elif line.startswith("SVar:") and not data.oracle_text:
|
||||
if "Oracle:" in line:
|
||||
oracle_part = line.split("Oracle:", 1)[1].strip()
|
||||
data.oracle_text = oracle_part
|
||||
|
||||
return data if data.name else None
|
||||
|
||||
|
||||
def _calc_cmc(mana_cost: str) -> int:
|
||||
"""Calculate CMC from Forge mana cost string like '2 W U'."""
|
||||
total = 0
|
||||
for part in mana_cost.split():
|
||||
part = part.strip().upper()
|
||||
if not part:
|
||||
continue
|
||||
if part.isdigit():
|
||||
total += int(part)
|
||||
elif part == "X":
|
||||
continue
|
||||
else:
|
||||
total += 1
|
||||
return total
|
||||
|
||||
|
||||
def _load_forge_cache() -> None:
|
||||
"""Walk the Forge cardsfolder and cache every card by lowercase name."""
|
||||
global _FORGE_CACHE_LOADED
|
||||
if _FORGE_CACHE_LOADED:
|
||||
return
|
||||
|
||||
cards_folder = _get_cards_folder()
|
||||
if not cards_folder.is_dir():
|
||||
_log.warning("Forge cardsfolder not found at %s", cards_folder)
|
||||
_FORGE_CACHE_LOADED = True
|
||||
return
|
||||
|
||||
count = 0
|
||||
for root, _dirs, files in os.walk(cards_folder):
|
||||
for fname in files:
|
||||
if not fname.endswith(".txt"):
|
||||
continue
|
||||
fpath = Path(root) / fname
|
||||
parsed = _parse_forge_file(fpath)
|
||||
if parsed and parsed.name:
|
||||
_FORGE_CACHE[parsed.name.lower()] = parsed
|
||||
count += 1
|
||||
|
||||
_log.info("Forge card cache loaded: %d cards from %s", count, cards_folder)
|
||||
_FORGE_CACHE_LOADED = True
|
||||
|
||||
|
||||
def lookup_forge_card(card_name: str) -> Optional[ForgeCardData]:
|
||||
"""Look up a card by name from the Forge cache. Returns None on miss."""
|
||||
_load_forge_cache()
|
||||
return _FORGE_CACHE.get((card_name or "").lower().strip())
|
||||
|
||||
|
||||
def reset_forge_cache() -> None:
|
||||
"""Force a reload of the Forge card cache on next lookup."""
|
||||
global _FORGE_CACHE_LOADED
|
||||
_FORGE_CACHE.clear()
|
||||
_FORGE_CACHE_LOADED = False
|
||||
_log.info("Forge card cache cleared — will reload on next lookup")
|
||||
@@ -15,7 +15,7 @@ import json
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Optional
|
||||
|
||||
from commander_ai_lab.sim.models import Card, CombatState, Phase, Player, SimState
|
||||
from commander_ai_lab.sim.models import Card, Player, SimState
|
||||
|
||||
|
||||
# ── Mana Pool ────────────────────────────────────────────────
|
||||
@@ -95,6 +95,9 @@ class CommanderPlayer:
|
||||
# Whether this player has drawn their card this turn
|
||||
drawn_this_turn: bool = False
|
||||
|
||||
# Commander damage received from each opponent (keyed by seat index)
|
||||
commander_damage_received: dict[int, int] = field(default_factory=dict)
|
||||
|
||||
# ── Convenience pass-throughs to base Player ─────────────
|
||||
|
||||
@property
|
||||
@@ -133,18 +136,13 @@ class CommanderPlayer:
|
||||
def library(self) -> list[Card]:
|
||||
return self.base.library
|
||||
|
||||
@property
|
||||
def commander_damage_received(self) -> dict[int, int]:
|
||||
"""Delegate to base Player so headless engine writes are visible."""
|
||||
return self.base.commander_damage_received
|
||||
|
||||
def commander_tax(self) -> int:
|
||||
"""Additional mana cost (2 per cast from command zone)."""
|
||||
return self.commander_cast_count * 2
|
||||
|
||||
def is_dead_to_commander_damage(self) -> bool:
|
||||
"""Returns True if any single commander has dealt 21+ damage."""
|
||||
return self.base.is_dead_to_commander_damage()
|
||||
"""Returns True if any single opponent has dealt 21+ commander damage."""
|
||||
return any(v >= 21 for v in self.commander_damage_received.values())
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
return {
|
||||
@@ -196,7 +194,7 @@ class CommanderGameState:
|
||||
# Phase tracking
|
||||
# Phases: untap, upkeep, draw, main1, combat_begin, combat_declare_attackers,
|
||||
# combat_declare_blockers, combat_damage, combat_end, main2, end, cleanup
|
||||
current_phase: str | Phase = Phase.MAIN1
|
||||
current_phase: str = "main1"
|
||||
|
||||
# Turn number (mirrors sim_state.turn)
|
||||
turn: int = 0
|
||||
@@ -229,68 +227,224 @@ class CommanderGameState:
|
||||
def stack_is_empty(self) -> bool:
|
||||
return len(self.stack) == 0
|
||||
|
||||
# Bug 9 fix: stub get_legal_moves() and apply_move() so turn_manager
|
||||
# doesn't crash. These delegate to the rules engine once implemented.
|
||||
# ── Legal Moves & Apply (BUG-02 fix) ─────────────────────
|
||||
# These replace the former pass-only stubs so that the turn manager
|
||||
# can drive real game actions through the CommanderGameState.
|
||||
|
||||
def get_legal_moves(self, seat: int) -> list[dict]:
|
||||
"""Return legal moves for a seat.
|
||||
"""Return legal moves for a seat based on mana, phase, and card type.
|
||||
|
||||
During DECLARE_BLOCKERS phase, emits block moves for defending
|
||||
creatures against each attacker in sim_state.combat.
|
||||
Otherwise returns pass-only (stub for remaining rules engine).
|
||||
Move categories:
|
||||
- pass_priority: always available
|
||||
- play_land: if main phase, land drop not used, and land in hand
|
||||
- cast_spell: if main phase and castable cards in hand
|
||||
- attack: if declare_attackers phase and creatures can attack
|
||||
- instant/activate_ability: if holding-priority phases
|
||||
"""
|
||||
moves: list[dict] = [{"id": 0, "category": "pass_priority", "description": "Pass"}]
|
||||
combat = self.sim_state.combat
|
||||
moves: list[dict] = []
|
||||
move_id = 0
|
||||
|
||||
# Emit block moves during declare_blockers phase
|
||||
if (
|
||||
combat
|
||||
and combat.active
|
||||
and self.current_phase in (Phase.DECLARE_BLOCKERS, "declare_blockers")
|
||||
and seat != self.active_player_seat
|
||||
):
|
||||
move_id = 1000
|
||||
my_creatures = [
|
||||
c for c in self.sim_state.get_battlefield(seat)
|
||||
if c.is_creature() and not c.tapped
|
||||
]
|
||||
for atk_id in combat.attackers:
|
||||
atk = next(
|
||||
(c for bf in self.sim_state.battlefields for c in bf if c.id == atk_id),
|
||||
None,
|
||||
)
|
||||
if atk is None:
|
||||
if seat >= len(self.commander_players):
|
||||
return [{"id": 0, "category": "pass_priority", "description": "Pass"}]
|
||||
|
||||
cp = self.commander_players[seat]
|
||||
player = cp.base
|
||||
bf = self.sim_state.get_battlefield(seat)
|
||||
|
||||
# Available mana = untapped lands + untapped mana-producing artifacts
|
||||
available_mana = sum(
|
||||
1 for c in bf
|
||||
if not c.tapped and (c.is_land() or (c.is_ramp and not c.is_creature()))
|
||||
)
|
||||
|
||||
# ── Main phase actions ──
|
||||
if self.current_phase in ("main1", "main2"):
|
||||
# Play land (one per turn)
|
||||
if not self.land_drop_used:
|
||||
for i, card in enumerate(player.hand):
|
||||
if card.is_land():
|
||||
moves.append({
|
||||
"id": move_id,
|
||||
"category": "play_land",
|
||||
"description": f"Play land: {card.name}",
|
||||
"card_index": i,
|
||||
"card_name": card.name,
|
||||
})
|
||||
move_id += 1
|
||||
break # only one land drop offered
|
||||
|
||||
# Cast spells from hand (sorcery-speed: creatures, sorceries,
|
||||
# artifacts, enchantments, planeswalkers)
|
||||
for i, card in enumerate(player.hand):
|
||||
if card.is_land():
|
||||
continue
|
||||
for blocker in my_creatures:
|
||||
cmc = card.cmc or 0
|
||||
if cmc <= available_mana:
|
||||
moves.append({
|
||||
"id": move_id,
|
||||
"category": "block",
|
||||
"blocker_id": blocker.id,
|
||||
"attacker_id": atk_id,
|
||||
"description": f"Block {atk.name} with {blocker.name}",
|
||||
"category": "cast_spell",
|
||||
"description": f"Cast {card.name} (CMC {cmc})",
|
||||
"card_index": i,
|
||||
"card_name": card.name,
|
||||
})
|
||||
move_id += 1
|
||||
|
||||
return moves
|
||||
def apply_move(self, seat: int, move_id: int) -> None:
|
||||
"""Apply a chosen move.
|
||||
# Cast commander from command zone
|
||||
for i, cmd in enumerate(cp.commander_zone):
|
||||
tax = player.commander_tax.get(cmd.name, 0)
|
||||
total = (cmd.cmc or 0) + tax
|
||||
if total <= available_mana:
|
||||
moves.append({
|
||||
"id": move_id,
|
||||
"category": "cast_spell",
|
||||
"description": f"Cast commander {cmd.name} (cost {total}, tax {tax})",
|
||||
"card_name": cmd.name,
|
||||
"from_zone": "command",
|
||||
"cmd_index": i,
|
||||
})
|
||||
move_id += 1
|
||||
|
||||
Handles 'block' moves by updating sim_state.combat.blockers.
|
||||
Other categories are no-op stubs until the rules engine is wired.
|
||||
# ── Combat: declare attackers ──
|
||||
if self.current_phase == "declare_attackers":
|
||||
attackable_creatures = [
|
||||
c for c in bf
|
||||
if c.can_attack_or_block()
|
||||
and not c.tapped
|
||||
and (c.turn_played < self.turn or c.has_keyword("haste"))
|
||||
]
|
||||
if attackable_creatures:
|
||||
moves.append({
|
||||
"id": move_id,
|
||||
"category": "attack",
|
||||
"description": f"Attack with all ({len(attackable_creatures)} creatures)",
|
||||
"attack_mode": "all",
|
||||
})
|
||||
move_id += 1
|
||||
|
||||
# ── Instant-speed responses ──
|
||||
if self.current_phase in ("upkeep", "begin_combat", "end_combat",
|
||||
"end_step", "declare_blockers"):
|
||||
for i, card in enumerate(player.hand):
|
||||
if card.is_instant():
|
||||
cmc = card.cmc or 0
|
||||
if cmc <= available_mana:
|
||||
moves.append({
|
||||
"id": move_id,
|
||||
"category": "instant",
|
||||
"description": f"Cast {card.name} (instant, CMC {cmc})",
|
||||
"card_index": i,
|
||||
"card_name": card.name,
|
||||
})
|
||||
move_id += 1
|
||||
|
||||
# Always allow passing priority
|
||||
moves.append({
|
||||
"id": move_id,
|
||||
"category": "pass_priority",
|
||||
"description": "Pass",
|
||||
})
|
||||
|
||||
return moves
|
||||
|
||||
def apply_move(self, seat: int, move_id: int) -> None:
|
||||
"""Apply a chosen move to the game state.
|
||||
|
||||
Looks up the move by id in the current legal moves list and
|
||||
executes the corresponding game action.
|
||||
"""
|
||||
# Find the move dict
|
||||
all_moves = self.get_legal_moves(seat)
|
||||
move = next((m for m in all_moves if m["id"] == move_id), None)
|
||||
legal = self.get_legal_moves(seat)
|
||||
move = None
|
||||
for m in legal:
|
||||
if m["id"] == move_id:
|
||||
move = m
|
||||
break
|
||||
if move is None:
|
||||
return # invalid move id — no-op
|
||||
|
||||
cat = move["category"]
|
||||
if cat == "pass_priority":
|
||||
return
|
||||
|
||||
if move.get("category") == "block":
|
||||
combat = self.sim_state.combat
|
||||
if combat and combat.active:
|
||||
atk_id = move["attacker_id"]
|
||||
blocker_id = move["blocker_id"]
|
||||
if atk_id not in combat.blockers:
|
||||
combat.blockers[atk_id] = []
|
||||
combat.blockers[atk_id].append(blocker_id)
|
||||
if seat >= len(self.commander_players):
|
||||
return
|
||||
cp = self.commander_players[seat]
|
||||
player = cp.base
|
||||
bf = self.sim_state.get_battlefield(seat)
|
||||
|
||||
if cat == "play_land":
|
||||
idx = move.get("card_index", -1)
|
||||
if 0 <= idx < len(player.hand):
|
||||
card = player.hand.pop(idx)
|
||||
card.owner_id = seat
|
||||
card.tapped = False
|
||||
card.id = self.sim_state.next_card_id
|
||||
self.sim_state.next_card_id += 1
|
||||
self.sim_state.add_to_battlefield(seat, card)
|
||||
self.land_drop_used = True
|
||||
cp.lands_played_this_turn += 1
|
||||
|
||||
elif cat == "cast_spell":
|
||||
from_zone = move.get("from_zone", "hand")
|
||||
if from_zone == "command":
|
||||
cmd_idx = move.get("cmd_index", 0)
|
||||
if cmd_idx < len(cp.commander_zone):
|
||||
card = cp.commander_zone.pop(cmd_idx)
|
||||
tax = player.commander_tax.get(card.name, 0)
|
||||
total_cost = (card.cmc or 0) + tax
|
||||
card.owner_id = seat
|
||||
card.tapped = False
|
||||
card.id = self.sim_state.next_card_id
|
||||
self.sim_state.next_card_id += 1
|
||||
card.turn_played = self.turn
|
||||
self._tap_mana_sources(seat, total_cost)
|
||||
self.sim_state.add_to_battlefield(seat, card)
|
||||
player.commander_tax[card.name] = tax + 2
|
||||
else:
|
||||
idx = move.get("card_index", -1)
|
||||
if 0 <= idx < len(player.hand):
|
||||
card = player.hand.pop(idx)
|
||||
card.owner_id = seat
|
||||
card.tapped = False
|
||||
card.id = self.sim_state.next_card_id
|
||||
self.sim_state.next_card_id += 1
|
||||
card.turn_played = self.turn
|
||||
self._tap_mana_sources(seat, card.cmc or 0)
|
||||
if card.is_permanent():
|
||||
self.sim_state.add_to_battlefield(seat, card)
|
||||
else:
|
||||
# Instants/sorceries go to graveyard after resolution
|
||||
player.graveyard.append(card)
|
||||
|
||||
elif cat == "instant":
|
||||
idx = move.get("card_index", -1)
|
||||
if 0 <= idx < len(player.hand):
|
||||
card = player.hand.pop(idx)
|
||||
card.owner_id = seat
|
||||
card.id = self.sim_state.next_card_id
|
||||
self.sim_state.next_card_id += 1
|
||||
self._tap_mana_sources(seat, card.cmc or 0)
|
||||
# Instants resolve and go to graveyard
|
||||
player.graveyard.append(card)
|
||||
|
||||
elif cat == "attack":
|
||||
# Mark all eligible creatures as attacking (tapped)
|
||||
for c in bf:
|
||||
if (c.can_attack_or_block()
|
||||
and not c.tapped
|
||||
and (c.turn_played < self.turn or c.has_keyword("haste"))):
|
||||
c.tapped = True
|
||||
|
||||
def _tap_mana_sources(self, seat: int, amount: int) -> None:
|
||||
"""Tap lands and mana rocks to pay a cost."""
|
||||
bf = self.sim_state.get_battlefield(seat)
|
||||
remaining = amount
|
||||
for c in bf:
|
||||
if remaining <= 0:
|
||||
break
|
||||
if not c.tapped and (c.is_land() or (c.is_ramp and not c.is_creature())):
|
||||
c.tapped = True
|
||||
remaining -= 1
|
||||
|
||||
def living_players(self) -> list[CommanderPlayer]:
|
||||
return [p for p in self.commander_players if not p.eliminated]
|
||||
|
||||
@@ -301,25 +455,13 @@ class CommanderGameState:
|
||||
return p.commander_damage_received.get(from_seat, 0)
|
||||
return 0
|
||||
|
||||
def deal_commander_damage(
|
||||
self, from_seat: int, to_seat: int, amount: int,
|
||||
commander_name: str | None = None,
|
||||
) -> None:
|
||||
"""Record commander damage and reduce life total.
|
||||
|
||||
If *commander_name* is provided the per-card breakdown is also
|
||||
updated (needed for partner-correct 21-damage checks).
|
||||
"""
|
||||
def deal_commander_damage(self, from_seat: int, to_seat: int, amount: int) -> None:
|
||||
"""Record commander damage and reduce life total."""
|
||||
if to_seat < len(self.commander_players):
|
||||
p = self.commander_players[to_seat]
|
||||
p.commander_damage_received[from_seat] = (
|
||||
p.commander_damage_received.get(from_seat, 0) + amount
|
||||
)
|
||||
if commander_name is not None:
|
||||
key = (from_seat, commander_name)
|
||||
p.base.commander_damage_by_card[key] = (
|
||||
p.base.commander_damage_by_card.get(key, 0) + amount
|
||||
)
|
||||
p.life -= amount
|
||||
|
||||
# ── Serialization ────────────────────────────────────────
|
||||
|
||||
@@ -11,73 +11,12 @@ SimState.battlefields is per-player: battlefields[seat_index] holds that player'
|
||||
from __future__ import annotations
|
||||
|
||||
import copy
|
||||
import enum
|
||||
import json
|
||||
import re
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Optional
|
||||
|
||||
|
||||
# ── Turn Phases ──────────────────────────────────────────────
|
||||
|
||||
class Phase(str, enum.Enum):
|
||||
"""MTG turn phases in order.
|
||||
|
||||
Using ``str`` as a mixin allows direct comparison with plain strings
|
||||
and clean JSON serialization (``phase.value`` is a string).
|
||||
"""
|
||||
|
||||
UNTAP = "untap"
|
||||
UPKEEP = "upkeep"
|
||||
DRAW = "draw"
|
||||
MAIN1 = "main1"
|
||||
BEGIN_COMBAT = "begin_combat"
|
||||
DECLARE_ATTACKERS = "declare_attackers"
|
||||
DECLARE_BLOCKERS = "declare_blockers"
|
||||
COMBAT_DAMAGE = "combat_damage"
|
||||
END_COMBAT = "end_combat"
|
||||
MAIN2 = "main2"
|
||||
END_STEP = "end_step"
|
||||
CLEANUP = "cleanup"
|
||||
|
||||
|
||||
# Ordered tuple for iteration
|
||||
PHASE_ORDER: tuple[Phase, ...] = tuple(Phase)
|
||||
|
||||
# Phases where sorcery-speed actions (land drops, casting creatures) are legal
|
||||
SORCERY_PHASES: frozenset[Phase] = frozenset({Phase.MAIN1, Phase.MAIN2})
|
||||
|
||||
|
||||
# ── Combat State ───────────────────────────────────────────
|
||||
|
||||
@dataclass
|
||||
class CombatState:
|
||||
"""Transient combat state shared across combat sub-phases.
|
||||
|
||||
Created at BEGIN_COMBAT, cleared to None at END_COMBAT.
|
||||
Allows priority windows between attacker declaration, blocker
|
||||
declaration, and damage resolution (Issue #86 Item 1).
|
||||
"""
|
||||
|
||||
# Seat index of the defending player (multiplayer: chosen target)
|
||||
defending_seat: int = -1
|
||||
|
||||
# attacker card_id -> defending seat
|
||||
attackers: dict[int, int] = field(default_factory=dict)
|
||||
|
||||
# attacker card_id -> list of blocker card_ids
|
||||
blockers: dict[int, list[int]] = field(default_factory=dict)
|
||||
|
||||
# Damage routed to the defending player per-attacker (for unblocked / trample)
|
||||
player_damage: dict[int, int] = field(default_factory=dict)
|
||||
|
||||
# Whether the first-strike damage sub-step has already resolved
|
||||
first_strike_resolved: bool = False
|
||||
|
||||
# Whether combat is currently active
|
||||
active: bool = False
|
||||
|
||||
|
||||
@dataclass
|
||||
class Card:
|
||||
"""A single card in the simulation."""
|
||||
@@ -98,15 +37,6 @@ class Card:
|
||||
is_removal: bool = False
|
||||
is_board_wipe: bool = False
|
||||
is_commander: bool = False
|
||||
is_direct_damage: bool = False
|
||||
direct_damage_amount: int = 0
|
||||
|
||||
# Forge enrichment fields (set by forge_card_loader)
|
||||
forge_enriched: bool = False
|
||||
forge_keywords: list[str] = field(default_factory=list)
|
||||
forge_trigger_modes: list[str] = field(default_factory=list)
|
||||
has_replacement_effect: bool = False
|
||||
has_static_ability: bool = False
|
||||
|
||||
# Runtime fields (set during game)
|
||||
id: int = 0
|
||||
@@ -160,6 +90,38 @@ class Card:
|
||||
def is_creature(self) -> bool:
|
||||
return bool(self.type_line and "creature" in self.type_line.lower())
|
||||
|
||||
def is_instant(self) -> bool:
|
||||
"""Check if this card is an Instant."""
|
||||
return bool(self.type_line and "instant" in self.type_line.lower())
|
||||
|
||||
def is_sorcery(self) -> bool:
|
||||
"""Check if this card is a Sorcery."""
|
||||
return bool(self.type_line and "sorcery" in self.type_line.lower())
|
||||
|
||||
def is_permanent(self) -> bool:
|
||||
"""Check if this card is a permanent type (not instant/sorcery).
|
||||
|
||||
Permanents are creatures, artifacts, enchantments, planeswalkers, lands,
|
||||
and battles. Instants and sorceries are non-permanent spells.
|
||||
Cards with unknown type are treated as permanents to avoid being
|
||||
incorrectly discarded.
|
||||
"""
|
||||
if not self.type_line:
|
||||
return True # no type info — keep on battlefield to be safe
|
||||
tl = self.type_line.lower()
|
||||
return "instant" not in tl and "sorcery" not in tl
|
||||
|
||||
def can_attack_or_block(self) -> bool:
|
||||
"""Check if this card can participate in combat.
|
||||
|
||||
Per MTG rules, only creatures can attack or block.
|
||||
Cards with unknown/missing type, artifacts, enchantments, etc.
|
||||
are NOT eligible for combat unless their type_line includes 'Creature'.
|
||||
"""
|
||||
if not self.type_line:
|
||||
return False
|
||||
return "creature" in self.type_line.lower()
|
||||
|
||||
def clone(self) -> "Card":
|
||||
"""Return a deep copy of this card."""
|
||||
return copy.deepcopy(self)
|
||||
@@ -170,8 +132,6 @@ class PlayerStats:
|
||||
"""Per-game statistics tracked for a player."""
|
||||
|
||||
cards_drawn: int = 7 # starting hand
|
||||
mulligans: int = 0
|
||||
opening_hand_lands: int = 0
|
||||
lands_played: int = 0
|
||||
spells_cast: int = 0
|
||||
creatures_played: int = 0
|
||||
@@ -187,8 +147,6 @@ class PlayerStats:
|
||||
def to_dict(self) -> dict:
|
||||
return {
|
||||
"cardsDrawn": self.cards_drawn,
|
||||
"mulligans": self.mulligans,
|
||||
"openingHandLands": self.opening_hand_lands,
|
||||
"landsPlayed": self.lands_played,
|
||||
"spellsCast": self.spells_cast,
|
||||
"creaturesPlayed": self.creatures_played,
|
||||
@@ -226,29 +184,8 @@ class Player:
|
||||
# p.commander_tax[name] = tax + 2
|
||||
commander_tax: dict = field(default_factory=dict)
|
||||
|
||||
# Commander damage received from each opponent, keyed by seat index.
|
||||
# This is the aggregate per-seat total (used by GUI matrix and prompt
|
||||
# builder). For games where a player controls partner commanders
|
||||
# the per-card breakdown lives in commander_damage_by_card.
|
||||
commander_damage_received: dict[int, int] = field(default_factory=dict)
|
||||
|
||||
# Per-commander breakdown: {(seat, card_name): damage}.
|
||||
# In MTG rules, lethal commander damage (21+) is tracked per individual
|
||||
# commander card, not per player. This dict captures that.
|
||||
commander_damage_by_card: dict[tuple[int, str], int] = field(default_factory=dict)
|
||||
|
||||
stats: PlayerStats = field(default_factory=PlayerStats)
|
||||
|
||||
def is_dead_to_commander_damage(self) -> bool:
|
||||
"""Returns True if any single commander has dealt 21+ damage.
|
||||
|
||||
Checks per-card tracking first (partner-correct); falls back to
|
||||
per-seat totals for backward compatibility with older game states.
|
||||
"""
|
||||
if self.commander_damage_by_card:
|
||||
return any(v >= 21 for v in self.commander_damage_by_card.values())
|
||||
return any(v >= 21 for v in self.commander_damage_received.values())
|
||||
|
||||
|
||||
@dataclass
|
||||
class SimState:
|
||||
@@ -264,11 +201,6 @@ class SimState:
|
||||
turn: int = 0
|
||||
max_turns: int = 25
|
||||
next_card_id: int = 90000
|
||||
current_phase: Phase = Phase.MAIN1
|
||||
active_player_index: int = 0
|
||||
|
||||
# Combat state (transient, set during combat phases)
|
||||
combat: Optional[CombatState] = None
|
||||
|
||||
# ── Battlefield helpers ──────────────────────────────────
|
||||
|
||||
|
||||
@@ -19,13 +19,11 @@ import re
|
||||
from typing import Optional
|
||||
|
||||
from commander_ai_lab.sim.models import Card
|
||||
# Forge enrichment (sibling module inside sim/)
|
||||
from commander_ai_lab.sim.forge_card_loader import lookup_forge_card, ForgeCardData
|
||||
|
||||
|
||||
# ════════════════════════════════════════════════════════════
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# AI Weights (ported from AI_DEFAULT_WEIGHTS in app.js)
|
||||
# ════════════════════════════════════════════════════════════
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
AI_DEFAULT_WEIGHTS: dict[str, float] = {
|
||||
# Card scoring
|
||||
@@ -107,10 +105,10 @@ def load_weights(path: Optional[str] = None) -> dict[str, float]:
|
||||
return dict(AI_DEFAULT_WEIGHTS)
|
||||
|
||||
|
||||
# ════════════════════════════════════════════════════════════
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Card Enrichment — guess type/cost for cards without Scryfall data
|
||||
# Ported from enrichCardForSim() in deck_tester_js.txt
|
||||
# ════════════════════════════════════════════════════════════
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
_BASIC_LAND_COLORS = {
|
||||
"plains": "W",
|
||||
@@ -141,63 +139,6 @@ _KNOWN_CARDS: list[tuple[re.Pattern, dict]] = [
|
||||
]
|
||||
|
||||
|
||||
# Nonbasic land name guard — compiled once at module load, not inside enrich_card().
|
||||
# Catches common land names that Forge may return with cmc=0 (causing has_real_data
|
||||
# to stay False) or that arrive with no Scryfall data at all.
|
||||
# Extended per Bug 3 to cover fetchlands, shocklands, filter lands, pain lands, etc.
|
||||
_land_kw = re.compile(
|
||||
r"\b(grove|garden|glade|falls|summit|crag|chapel|retreat|harbor|cemetery|"
|
||||
r"pool|fountain|shrine|foundry|vents|grave|crypt|tomb|ground|ruins|mesa|"
|
||||
r"tarn|delta|strand|heath|mire|bog|den|lair|hollow|flats|wastes|expanse|"
|
||||
r"vista|nexus|spire|sanctum|citadel|reaches|keeps|gate|springs|crossing|"
|
||||
r"command tower|path of ancestry|evolving wilds|terramorphic|"
|
||||
r"exotic orchard|mana confluence|city of brass|reflecting pool|"
|
||||
r"fabled passage|prismatic vista|command beacon|ash barrens)\b",
|
||||
re.IGNORECASE,
|
||||
)
|
||||
|
||||
|
||||
def _apply_forge_data(card: Card, forge_data: ForgeCardData) -> None:
|
||||
"""
|
||||
Apply Forge card data onto a Card, merging keywords into both fields.
|
||||
|
||||
ISSUE 3 FIX: Writes to both card.keywords AND card.forge_keywords
|
||||
so existing score_card() checks like `if "flying" in kw_list` work.
|
||||
|
||||
ISSUE 4 FIX: Sets card.oracle_text BEFORE returning, so the caller
|
||||
can safely call _apply_oracle_flags(card) afterward.
|
||||
"""
|
||||
# Forge-specific tracking fields
|
||||
card.forge_keywords = list(forge_data.keywords)
|
||||
card.forge_trigger_modes = list(forge_data.trigger_modes)
|
||||
card.has_replacement_effect = forge_data.has_replacement_effect
|
||||
card.has_static_ability = forge_data.has_static_ability
|
||||
|
||||
# ISSUE 3: Merge keywords into card.keywords (set union, no dupes)
|
||||
existing = {k.lower() for k in (card.keywords or [])}
|
||||
for kw in forge_data.keywords:
|
||||
if kw.lower() not in existing:
|
||||
card.keywords.append(kw)
|
||||
existing.add(kw.lower())
|
||||
|
||||
# Overwrite type/cost/pt only if Forge has data AND card doesn't
|
||||
if forge_data.type_line and (not card.type_line or len(card.type_line) < 3):
|
||||
card.type_line = forge_data.type_line
|
||||
if forge_data.mana_cost and not card.mana_cost:
|
||||
card.mana_cost = forge_data.mana_cost
|
||||
card.cmc = forge_data.cmc
|
||||
if forge_data.pt and not card.pt:
|
||||
card.pt = forge_data.pt
|
||||
parts = forge_data.pt.split("/", 1)
|
||||
if len(parts) == 2:
|
||||
card.power = parts[0].strip()
|
||||
card.toughness = parts[1].strip()
|
||||
|
||||
# ISSUE 4: Set oracle_text so _apply_oracle_flags sees Forge text
|
||||
if forge_data.oracle_text and not card.oracle_text:
|
||||
card.oracle_text = forge_data.oracle_text
|
||||
|
||||
|
||||
def enrich_card(card: Card) -> Card:
|
||||
"""
|
||||
Enrich a card with type/cost heuristics if it lacks Scryfall data.
|
||||
@@ -208,23 +149,6 @@ def enrich_card(card: Card) -> Card:
|
||||
|
||||
has_real_data = card.cmc > 0 or (card.type_line and len(card.type_line) > 5)
|
||||
|
||||
# Try Forge enrichment first for cards without Scryfall data
|
||||
if not has_real_data:
|
||||
forge_data = lookup_forge_card(card.name)
|
||||
if forge_data:
|
||||
_apply_forge_data(card, forge_data) # sets oracle_text, keywords, etc.
|
||||
card.forge_enriched = True
|
||||
# Re-check: if Forge provided sufficient data, apply flags and return.
|
||||
# Bug 3 fix: lands always have cmc=0, so explicitly allow type_line
|
||||
# containing "land" to satisfy has_real_data even when cmc is 0.
|
||||
has_real_data = card.cmc > 0 or (card.type_line and len(card.type_line) > 5)
|
||||
if not has_real_data and card.type_line and "land" in card.type_line.lower():
|
||||
has_real_data = True # lands are valid cards even with cmc=0
|
||||
if has_real_data:
|
||||
_apply_oracle_flags(card)
|
||||
return card
|
||||
# Otherwise fall through so known-cards / default heuristics can fill gaps
|
||||
|
||||
if not has_real_data:
|
||||
# Basic lands
|
||||
if name_lower in _BASIC_LAND_COLORS:
|
||||
@@ -243,22 +167,16 @@ def enrich_card(card: Card) -> Card:
|
||||
_apply_oracle_flags(card)
|
||||
return card
|
||||
|
||||
# Nonbasic land name guard — catches fetchlands, shocklands, filter lands,
|
||||
# pain lands, and other common nonbasic lands BEFORE the creature fallback.
|
||||
if _land_kw.search(name_lower):
|
||||
card.type_line = "Land"
|
||||
card.cmc = 0
|
||||
_apply_oracle_flags(card)
|
||||
return card
|
||||
|
||||
# Default: treat as creature with deterministic CMC based on
|
||||
# card name hash (fixes #32 — no more random.randint jitter
|
||||
# between games for the same card).
|
||||
# Default: unknown cards get deterministic CMC based on card
|
||||
# name hash (fixes #32 — no more random.randint jitter).
|
||||
# Fix #82: do NOT default to "Creature". Unknown cards are
|
||||
# classified as "Unknown" and cannot attack/block until their
|
||||
# real type is confirmed via Scryfall data.
|
||||
if not card.type_line or len(card.type_line) < 3:
|
||||
name_hash = int(hashlib.md5(name_lower.encode()).hexdigest(), 16)
|
||||
estimated_cmc = (name_hash % 5) + 2 # 2-6 inclusive
|
||||
estimated_pow = max(1, estimated_cmc - 1)
|
||||
card.type_line = "Creature"
|
||||
card.type_line = "Unknown"
|
||||
card.cmc = estimated_cmc
|
||||
card.pt = f"{estimated_pow}/{estimated_pow}"
|
||||
card.power = str(estimated_pow)
|
||||
@@ -292,10 +210,6 @@ def _apply_oracle_flags(card: Card) -> None:
|
||||
]):
|
||||
card.is_removal = True
|
||||
|
||||
# Direct-damage spells (burn): "deals N damage to target/any target"
|
||||
if not card.is_direct_damage:
|
||||
_detect_direct_damage(card, oracle)
|
||||
|
||||
# Bug 17 fix: evaluate ramp independently — cards can be both removal and ramp
|
||||
# (e.g. Nature's Claim, Beast Within, Abrupt Decay)
|
||||
if not card.is_ramp:
|
||||
@@ -312,65 +226,7 @@ def _apply_oracle_flags(card: Card) -> None:
|
||||
card.is_ramp = True
|
||||
|
||||
|
||||
# ── Direct-damage (burn spell) detection ────────────────────────────────────
|
||||
|
||||
# Regex: "deals N damage to target|any target" (not "each creature" — that's a wipe)
|
||||
_DIRECT_DAMAGE_RE = re.compile(
|
||||
r"deals?\s+(\d+)\s+damage\s+to\s+(?:target|any\s+target)",
|
||||
re.IGNORECASE,
|
||||
)
|
||||
|
||||
# Well-known burn spells with fixed damage amounts for reliable detection
|
||||
_KNOWN_BURN: dict[str, int] = {
|
||||
"lightning bolt": 3,
|
||||
"shock": 2,
|
||||
"lightning strike": 3,
|
||||
"lava spike": 3,
|
||||
"rift bolt": 3,
|
||||
"searing blaze": 3,
|
||||
"chain lightning": 3,
|
||||
"flame rift": 4,
|
||||
"exquisite firecraft": 4,
|
||||
"lightning helix": 3,
|
||||
"warleader's helix": 4,
|
||||
"boros charm": 4,
|
||||
"searing spear": 3,
|
||||
"incinerate": 3,
|
||||
"magma jet": 2,
|
||||
"searing blood": 2,
|
||||
"firebolt": 2,
|
||||
"galvanic blast": 2,
|
||||
"skullcrack": 3,
|
||||
"flames of the firebrand": 3,
|
||||
"stoke the flames": 4,
|
||||
}
|
||||
|
||||
|
||||
def _detect_direct_damage(card: Card, oracle: str) -> None:
|
||||
"""Detect direct-damage (burn) spells and set card flags."""
|
||||
# Check known-burn table first (most reliable)
|
||||
name_lower = (card.name or "").lower().strip()
|
||||
if name_lower in _KNOWN_BURN:
|
||||
card.is_direct_damage = True
|
||||
card.direct_damage_amount = _KNOWN_BURN[name_lower]
|
||||
return
|
||||
|
||||
# Fall back to regex detection from oracle text
|
||||
if not oracle:
|
||||
return
|
||||
# Skip board wipes and each-creature effects
|
||||
if card.is_board_wipe:
|
||||
return
|
||||
if "each creature" in oracle or "all creature" in oracle:
|
||||
return
|
||||
|
||||
m = _DIRECT_DAMAGE_RE.search(oracle)
|
||||
if m:
|
||||
card.is_direct_damage = True
|
||||
card.direct_damage_amount = int(m.group(1))
|
||||
|
||||
|
||||
# ── Multi-opponent scaling factors ─────────────────────────────────────────────
|
||||
# ── Multi-opponent scaling factors ────────────────────────────
|
||||
# Keywords / effects that become more valuable in larger pods.
|
||||
# Each entry maps a weight key → the extra bonus *per additional
|
||||
# opponent* beyond 1. 1v1 uses base weights; 4-player FFA adds
|
||||
@@ -464,21 +320,11 @@ def score_card(
|
||||
score += w.get("kw_cascade", 3.0)
|
||||
if "defender" in text or "defender" in kw_list:
|
||||
score += w.get("kw_defender", -2.0)
|
||||
# NEW
|
||||
_has_etb = False
|
||||
if card.forge_trigger_modes and "ChangesZone" in card.forge_trigger_modes:
|
||||
_has_etb = True
|
||||
elif "when" in text and "enters" in text:
|
||||
_has_etb = True
|
||||
if _has_etb:
|
||||
|
||||
# ── Triggered ability bonuses ──
|
||||
if "when" in text and "enters" in text:
|
||||
score += w.get("trig_etb", 2.0) + _MULTI_OPP_SCALING.get("trig_etb", 0.0) * extra_opps
|
||||
# NEW
|
||||
_has_attack_trig = False
|
||||
if card.forge_trigger_modes and "Attacks" in card.forge_trigger_modes:
|
||||
_has_attack_trig = True
|
||||
elif "whenever" in text and "attack" in text:
|
||||
_has_attack_trig = True
|
||||
if _has_attack_trig:
|
||||
if "whenever" in text and "attack" in text:
|
||||
score += w.get("trig_attack", 1.5)
|
||||
if "when" in text and "dies" in text:
|
||||
score += w.get("trig_dies", 1.0) + _MULTI_OPP_SCALING.get("trig_dies", 0.0) * extra_opps
|
||||
|
||||
@@ -42,8 +42,6 @@ class StateLogger:
|
||||
before writing the new one (FIFO rotation).
|
||||
"""
|
||||
|
||||
_counter: int = 0 # monotonic counter to guarantee unique filenames
|
||||
|
||||
def __init__(self, log_dir: Optional[str | Path] = None) -> None:
|
||||
self.log_dir = Path(log_dir) if log_dir else DEFAULT_LOG_DIR
|
||||
self.log_dir.mkdir(parents=True, exist_ok=True)
|
||||
@@ -75,9 +73,8 @@ class StateLogger:
|
||||
"""
|
||||
self._rotate()
|
||||
|
||||
StateLogger._counter += 1
|
||||
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S_%f")
|
||||
filename = f"snapshot_{timestamp}_{StateLogger._counter}_t{game_state.turn}_s{seat}.json"
|
||||
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
||||
filename = f"snapshot_{timestamp}_t{game_state.turn}_s{seat}.json"
|
||||
filepath = self.log_dir / filename
|
||||
|
||||
snapshot = {
|
||||
|
||||
@@ -46,29 +46,38 @@ from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
import os
|
||||
import time
|
||||
from collections import deque
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Awaitable, Callable, Optional, Set
|
||||
from commander_ai_lab.sim.models import Phase, PHASE_ORDER, SORCERY_PHASES, CombatState
|
||||
|
||||
from commander_ai_lab.sim.game_state import CommanderGameState, CommanderPlayer
|
||||
from commander_ai_lab.sim.ai_opponent import AIOpponent
|
||||
from commander_ai_lab.sim.threat_assessor import assess_threats, ThreatScore
|
||||
|
||||
logger = logging.getLogger("turn_manager")
|
||||
|
||||
# Re-export for backward compatibility; canonical source is models.py
|
||||
PHASES = [p.value for p in PHASE_ORDER]
|
||||
# Commander turn phases in order
|
||||
PHASES = [
|
||||
"untap",
|
||||
"upkeep",
|
||||
"draw",
|
||||
"main1",
|
||||
"begin_combat",
|
||||
"declare_attackers",
|
||||
"declare_blockers",
|
||||
"combat_damage",
|
||||
"end_combat",
|
||||
"main2",
|
||||
"end_step",
|
||||
"cleanup",
|
||||
]
|
||||
|
||||
# Phases where a player can take an action (play land, cast spell, etc.)
|
||||
ACTION_PHASES = {p.value for p in SORCERY_PHASES}
|
||||
ACTION_PHASES = {"main1", "main2"}
|
||||
# Phases where instant-speed responses can happen
|
||||
RESPONSE_PHASES = {
|
||||
Phase.UPKEEP.value,
|
||||
Phase.END_STEP.value,
|
||||
}
|
||||
RESPONSE_PHASES = {"upkeep", "begin_combat", "end_combat", "end_step"}
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -89,7 +98,7 @@ class GameEvent:
|
||||
class TurnManagerConfig:
|
||||
"""Tunable parameters for the turn manager."""
|
||||
max_turns: int = 40
|
||||
ai_decision_timeout: float = float(os.environ.get("BRAIN_TIMEOUT", "300.0")) # seconds before fallback
|
||||
ai_decision_timeout: float = 30.0 # seconds before fallback
|
||||
ai_narration_enabled: bool = True
|
||||
ai_decision_delay: float = 0.0 # cosmetic pause (set > 0 for UI readability)
|
||||
priority_pass_limit: int = 8 # max APNAP passes per phase before auto-advance
|
||||
@@ -353,13 +362,7 @@ class CommanderTurnManager:
|
||||
await self._apnap_priority_window(active_seat, turn_num, phase)
|
||||
|
||||
async def _phase_combat(self, active_seat: int, turn_num: int) -> None:
|
||||
"""Full combat sequence with priority windows at each sub-phase (Issue #86)."""
|
||||
sim = self.gs.sim_state
|
||||
|
||||
# 1. Beginning of combat — priority window BEFORE attackers chosen
|
||||
await self._apnap_priority_window(active_seat, turn_num, "begin_combat")
|
||||
|
||||
# 2. Declare attackers
|
||||
"""Declare attackers phase."""
|
||||
legal_moves = self.get_legal_moves(active_seat)
|
||||
attack_moves = [m for m in legal_moves if m.get("category") == "attack"]
|
||||
if not attack_moves:
|
||||
@@ -388,44 +391,9 @@ class CommanderTurnManager:
|
||||
narration=narration,
|
||||
))
|
||||
|
||||
# 3. After-attackers priority window
|
||||
await self._apnap_priority_window(active_seat, turn_num, "declare_attackers")
|
||||
|
||||
# 4. Declare blockers — each defending player in APNAP order
|
||||
for defender_seat in [s for s in range(len(self.gs.players))
|
||||
if s != active_seat
|
||||
and not self.gs.players[s].eliminated]:
|
||||
block_moves = [m for m in self.get_legal_moves(defender_seat)
|
||||
if m.get("category") == "block"]
|
||||
if block_moves:
|
||||
block_id = await self._get_action(defender_seat, block_moves, turn_num)
|
||||
if block_id is not None:
|
||||
self.gs.apply_move(defender_seat, block_id)
|
||||
|
||||
# 5. After-blockers priority window
|
||||
# Defending players get priority to declare blockers
|
||||
await self._apnap_priority_window(active_seat, turn_num, "declare_blockers")
|
||||
|
||||
# 6. First-strike damage sub-step (if applicable)
|
||||
if self._has_first_strikers():
|
||||
# Resolve first-strike damage via engine split method
|
||||
if sim.combat and sim.combat.active:
|
||||
from commander_ai_lab.sim.engine import GameEngine
|
||||
engine = GameEngine()
|
||||
engine.resolve_combat_damage(sim, active_seat, sim.combat, first_strike_only=True)
|
||||
await self._apnap_priority_window(active_seat, turn_num, "first_strike_damage")
|
||||
|
||||
# 7. Normal combat damage
|
||||
if sim.combat and sim.combat.active:
|
||||
from commander_ai_lab.sim.engine import GameEngine
|
||||
engine = GameEngine()
|
||||
engine.resolve_combat_damage(sim, active_seat, sim.combat, first_strike_only=False)
|
||||
|
||||
# 8. End of combat priority window
|
||||
await self._apnap_priority_window(active_seat, turn_num, "end_combat")
|
||||
|
||||
# 9. Clear combat state
|
||||
sim.combat = None
|
||||
|
||||
async def _phase_cleanup(self, active_seat: int) -> None:
|
||||
"""Discard to hand size (7), remove end-of-turn effects."""
|
||||
player = self.gs.players[active_seat]
|
||||
@@ -438,22 +406,6 @@ class CommanderTurnManager:
|
||||
player.name, discarded.name,
|
||||
)
|
||||
|
||||
def _has_first_strikers(self) -> bool:
|
||||
"""Check if any creature in active combat has first_strike or double_strike."""
|
||||
sim = self.gs.sim_state
|
||||
combat = sim.combat
|
||||
if not combat or not combat.active:
|
||||
return False
|
||||
all_combat_ids = (
|
||||
list(combat.attackers.keys()) +
|
||||
[bid for blist in combat.blockers.values() for bid in blist]
|
||||
)
|
||||
for card_id in all_combat_ids:
|
||||
card = next((c for bf in sim.battlefields for c in bf if c.id == card_id), None)
|
||||
if card and (card.has_keyword("first_strike") or card.has_keyword("double_strike")):
|
||||
return True
|
||||
return False
|
||||
|
||||
# ── Priority Passing (APNAP) ──────────────────────────────────────────────
|
||||
|
||||
async def _apnap_priority_window(
|
||||
|
||||
@@ -50,7 +50,7 @@ class ValidatorConfig:
|
||||
|
||||
Example -- LM Studio::
|
||||
cfg = ValidatorConfig(
|
||||
api_base="http://localhost:1234",
|
||||
api_base="http://192.168.0.240:1234",
|
||||
model="deepseek-r1-distill-qwen-14b",
|
||||
)
|
||||
"""
|
||||
@@ -58,7 +58,7 @@ class ValidatorConfig:
|
||||
model: str = "deepseek-r1:14b"
|
||||
temperature: float = 0.0
|
||||
max_tokens: int = 2048
|
||||
request_timeout: float = 300.0
|
||||
request_timeout: float = 60.0
|
||||
enabled: bool = True
|
||||
|
||||
@classmethod
|
||||
@@ -70,7 +70,7 @@ class ValidatorConfig:
|
||||
model=os.environ.get("VALIDATOR_MODEL", "deepseek-r1:14b"),
|
||||
temperature=float(os.environ.get("VALIDATOR_TEMPERATURE", "0.0")),
|
||||
max_tokens=int(os.environ.get("VALIDATOR_MAX_TOKENS", "2048")),
|
||||
request_timeout=float(os.environ.get("VALIDATOR_TIMEOUT", "300.0")),
|
||||
request_timeout=float(os.environ.get("VALIDATOR_TIMEOUT", "60.0")),
|
||||
enabled=(enabled_str == "true"),
|
||||
)
|
||||
|
||||
|
||||
@@ -29,7 +29,6 @@ from fastapi.staticfiles import StaticFiles
|
||||
from commander_ai_lab.web.routers.api import router as api_router
|
||||
from commander_ai_lab.web.routers.ws import router as ws_router
|
||||
from commander_ai_lab.web.routers.art import router as art_router
|
||||
from commander_ai_lab.web.routers.lobby import router as lobby_router, ws_router as lobby_ws_router
|
||||
|
||||
# Prefer the React build output; fall back to legacy static dir
|
||||
_FRONTEND_DIST = Path(__file__).parents[3] / "frontend" / "dist"
|
||||
@@ -67,8 +66,6 @@ def create_app(
|
||||
app.include_router(api_router, prefix="/api/v1")
|
||||
app.include_router(ws_router) # /ws/game/{game_id}
|
||||
app.include_router(art_router, prefix="/api/v1")
|
||||
app.include_router(lobby_router) # /api/v1/lobby/...
|
||||
app.include_router(lobby_ws_router) # /ws/lobby/{room_id}
|
||||
|
||||
# Static files (web client) — prefer React build, fall back to legacy
|
||||
sd = static_dir or (_FRONTEND_DIST if _FRONTEND_DIST.exists() else _STATIC_DIR)
|
||||
|
||||
@@ -1,359 +0,0 @@
|
||||
package commanderailab.ai;
|
||||
|
||||
import commanderailab.ml.LearnedPolicy;
|
||||
import commanderailab.ml.MacroActionExecutor;
|
||||
import commanderailab.ml.PolicyServerClient;
|
||||
import commanderailab.schema.DecisionSnapshot;
|
||||
|
||||
import com.google.gson.Gson;
|
||||
import com.google.gson.GsonBuilder;
|
||||
import com.google.gson.JsonArray;
|
||||
import com.google.gson.JsonObject;
|
||||
|
||||
import java.io.*;
|
||||
import java.net.HttpURLConnection;
|
||||
import java.net.URL;
|
||||
import java.nio.charset.StandardCharsets;
|
||||
import java.util.*;
|
||||
import java.util.concurrent.ConcurrentLinkedQueue;
|
||||
|
||||
/**
|
||||
* PolicyClient — Phase 2 bridge between Forge decision points and the
|
||||
* Python policy server for live online training.
|
||||
*
|
||||
* This class extends the existing LearnedPolicy/PolicyServerClient
|
||||
* infrastructure with two key Phase 2 capabilities:
|
||||
*
|
||||
* 1. Calls the new /api/policy/decide endpoint (purpose-built for live
|
||||
* IPC with richer state including all zones, stack, and priority)
|
||||
* instead of the batch-oriented /api/ml/predict.
|
||||
*
|
||||
* 2. Collects (state, action, reward) tuples in real-time during live
|
||||
* Forge games and flushes them to the policy server for online PPO
|
||||
* updates via POST /api/policy/collect.
|
||||
*
|
||||
* Falls back to ForgeBuiltinPolicy heuristics if the policy server
|
||||
* is unreachable or returns an error.
|
||||
*
|
||||
* Usage:
|
||||
* PolicyClient client = new PolicyClient("http://localhost:8080");
|
||||
* if (client.connect()) {
|
||||
* // At each Forge decision point:
|
||||
* String action = client.decide(fullGameState);
|
||||
* // After game ends:
|
||||
* client.submitReward(gameId, reward);
|
||||
* client.flushCollectedTuples();
|
||||
* }
|
||||
*
|
||||
* Refs: Issue #83 Phase 2.1
|
||||
*/
|
||||
public class PolicyClient {
|
||||
|
||||
private static final Gson GSON = new GsonBuilder().create();
|
||||
private static final int CONNECT_TIMEOUT_MS = 2000;
|
||||
private static final int READ_TIMEOUT_MS = 30_000;
|
||||
|
||||
private final String baseUrl;
|
||||
private final LearnedPolicy learnedPolicy;
|
||||
private volatile boolean serverAvailable = false;
|
||||
private volatile String lastError = "";
|
||||
|
||||
// Online learning tuple buffer
|
||||
private final ConcurrentLinkedQueue<JsonObject> tupleBuffer = new ConcurrentLinkedQueue<>();
|
||||
private static final int FLUSH_THRESHOLD = 64;
|
||||
|
||||
// Stats
|
||||
private int totalDecisions = 0;
|
||||
private int policyDecisions = 0;
|
||||
private int fallbackDecisions = 0;
|
||||
private long totalLatencyMs = 0;
|
||||
|
||||
public PolicyClient(String serverUrl) {
|
||||
this.baseUrl = serverUrl.endsWith("/")
|
||||
? serverUrl.substring(0, serverUrl.length() - 1)
|
||||
: serverUrl;
|
||||
this.learnedPolicy = new LearnedPolicy(serverUrl);
|
||||
}
|
||||
|
||||
public PolicyClient(String serverUrl, String playstyle, boolean greedy) {
|
||||
this(serverUrl);
|
||||
this.learnedPolicy.setPlaystyle(playstyle);
|
||||
this.learnedPolicy.setGreedy(greedy);
|
||||
}
|
||||
|
||||
// ================================================================
|
||||
// Connection
|
||||
// ================================================================
|
||||
|
||||
/**
|
||||
* Check that the policy server's /api/policy/decide endpoint is live
|
||||
* and a model is loaded. Falls back to checking /api/ml/model if the
|
||||
* new endpoint isn't available yet.
|
||||
*/
|
||||
public boolean connect() {
|
||||
try {
|
||||
String json = httpGet(baseUrl + "/api/policy/health");
|
||||
serverAvailable = json.contains("\"ready\":true")
|
||||
|| json.contains("\"status\":\"ok\"");
|
||||
} catch (Exception e) {
|
||||
// Fall back to legacy health check
|
||||
serverAvailable = learnedPolicy.connect();
|
||||
}
|
||||
if (serverAvailable) {
|
||||
System.out.println("[PolicyClient] Connected to policy server");
|
||||
} else {
|
||||
System.out.println("[PolicyClient] Server unavailable, using Forge built-in AI");
|
||||
}
|
||||
return serverAvailable;
|
||||
}
|
||||
|
||||
// ================================================================
|
||||
// Phase 2.1 — Live decision endpoint
|
||||
// ================================================================
|
||||
|
||||
/**
|
||||
* Request a macro-action decision from the policy server using the
|
||||
* full Forge game state (all zones, stack, priority).
|
||||
*
|
||||
* This calls POST /api/policy/decide which is purpose-built for the
|
||||
* live IPC loop, as opposed to /api/ml/predict which was designed
|
||||
* for batch inference.
|
||||
*
|
||||
* @param gameState Full game state JSON with all zones and priority info
|
||||
* @return macro-action name (e.g., "cast_creature"), or "pass" on failure
|
||||
*/
|
||||
public String decide(JsonObject gameState) {
|
||||
totalDecisions++;
|
||||
long t0 = System.currentTimeMillis();
|
||||
|
||||
if (!serverAvailable) {
|
||||
fallbackDecisions++;
|
||||
return MacroActionExecutor.PASS;
|
||||
}
|
||||
|
||||
try {
|
||||
// Add inference params
|
||||
gameState.addProperty("playstyle", learnedPolicy.getPlaystyle());
|
||||
gameState.addProperty("greedy", learnedPolicy.isGreedy());
|
||||
|
||||
String responseJson = httpPost(
|
||||
baseUrl + "/api/policy/decide",
|
||||
gameState.toString()
|
||||
);
|
||||
|
||||
JsonObject resp = GSON.fromJson(responseJson, JsonObject.class);
|
||||
long elapsed = System.currentTimeMillis() - t0;
|
||||
totalLatencyMs += elapsed;
|
||||
|
||||
if (resp.has("action") && !resp.has("error")) {
|
||||
policyDecisions++;
|
||||
String action = resp.get("action").getAsString();
|
||||
|
||||
// Store tuple for online learning
|
||||
collectTuple(gameState, action, resp);
|
||||
|
||||
return action;
|
||||
} else {
|
||||
fallbackDecisions++;
|
||||
lastError = resp.has("error")
|
||||
? resp.get("error").getAsString()
|
||||
: "Unknown error";
|
||||
return MacroActionExecutor.PASS;
|
||||
}
|
||||
} catch (Exception e) {
|
||||
fallbackDecisions++;
|
||||
lastError = e.getMessage();
|
||||
return MacroActionExecutor.PASS;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Convenience: decide from a DecisionSnapshot (delegates to the
|
||||
* existing LearnedPolicy path if /api/policy/decide is unavailable).
|
||||
*/
|
||||
public String decide(DecisionSnapshot snapshot) {
|
||||
return learnedPolicy.decideAction(snapshot);
|
||||
}
|
||||
|
||||
/**
|
||||
* Resolve a decision to a concrete Forge action.
|
||||
*/
|
||||
public MacroActionExecutor.ActionResolution resolveAction(
|
||||
JsonObject gameState,
|
||||
List<String> hand,
|
||||
List<String> battlefield,
|
||||
List<String> commandZone,
|
||||
int manaAvailable,
|
||||
String commanderName,
|
||||
int commanderTax
|
||||
) {
|
||||
String macroAction = decide(gameState);
|
||||
return MacroActionExecutor.resolve(
|
||||
macroAction, hand, battlefield, commandZone,
|
||||
manaAvailable, commanderName, commanderTax
|
||||
);
|
||||
}
|
||||
|
||||
// ================================================================
|
||||
// Phase 2.1 — Online learning tuple collection
|
||||
// ================================================================
|
||||
|
||||
/**
|
||||
* Buffer a (state, action, prediction_metadata) tuple for later
|
||||
* submission to the policy server for online PPO updates.
|
||||
*/
|
||||
private void collectTuple(JsonObject state, String action, JsonObject prediction) {
|
||||
JsonObject tuple = new JsonObject();
|
||||
tuple.add("state", state);
|
||||
tuple.addProperty("action", action);
|
||||
if (prediction.has("action_index")) {
|
||||
tuple.addProperty("action_index", prediction.get("action_index").getAsInt());
|
||||
}
|
||||
if (prediction.has("log_prob")) {
|
||||
tuple.addProperty("log_prob", prediction.get("log_prob").getAsDouble());
|
||||
}
|
||||
if (prediction.has("value")) {
|
||||
tuple.addProperty("value", prediction.get("value").getAsDouble());
|
||||
}
|
||||
tuple.addProperty("timestamp", System.currentTimeMillis());
|
||||
|
||||
tupleBuffer.add(tuple);
|
||||
|
||||
// Auto-flush when buffer is full
|
||||
if (tupleBuffer.size() >= FLUSH_THRESHOLD) {
|
||||
flushCollectedTuples();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Submit end-of-game reward for all tuples in the current game.
|
||||
* Call this after a Forge game completes.
|
||||
*/
|
||||
public void submitReward(String gameId, double reward) {
|
||||
try {
|
||||
JsonObject body = new JsonObject();
|
||||
body.addProperty("game_id", gameId);
|
||||
body.addProperty("reward", reward);
|
||||
httpPost(baseUrl + "/api/policy/reward", body.toString());
|
||||
} catch (Exception e) {
|
||||
System.err.println("[PolicyClient] Failed to submit reward: " + e.getMessage());
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Flush buffered (state, action, reward) tuples to the policy server
|
||||
* for online PPO updates via POST /api/policy/collect.
|
||||
*/
|
||||
public void flushCollectedTuples() {
|
||||
if (tupleBuffer.isEmpty()) return;
|
||||
|
||||
JsonArray batch = new JsonArray();
|
||||
JsonObject tuple;
|
||||
while ((tuple = tupleBuffer.poll()) != null) {
|
||||
batch.add(tuple);
|
||||
}
|
||||
|
||||
try {
|
||||
JsonObject body = new JsonObject();
|
||||
body.add("tuples", batch);
|
||||
body.addProperty("count", batch.size());
|
||||
httpPost(baseUrl + "/api/policy/collect", body.toString());
|
||||
System.out.println("[PolicyClient] Flushed " + batch.size() + " tuples");
|
||||
} catch (Exception e) {
|
||||
System.err.println("[PolicyClient] Failed to flush tuples: " + e.getMessage());
|
||||
// Re-queue on failure
|
||||
for (int i = 0; i < batch.size(); i++) {
|
||||
tupleBuffer.add(batch.get(i).getAsJsonObject());
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// ================================================================
|
||||
// Accessors
|
||||
// ================================================================
|
||||
|
||||
public boolean isServerAvailable() { return serverAvailable; }
|
||||
public String getLastError() { return lastError; }
|
||||
public int getTotalDecisions() { return totalDecisions; }
|
||||
public int getPolicyDecisions() { return policyDecisions; }
|
||||
public String getBaseUrl() { return baseUrl; }
|
||||
|
||||
/** Decision result record for GameSession integration. */
|
||||
public record PolicyDecision(String action, double confidence) {}
|
||||
|
||||
/**
|
||||
* Decide from a JSON string + seat index. Used by GameSession.
|
||||
* Converts to JsonObject and delegates to decide(JsonObject).
|
||||
*/
|
||||
public PolicyDecision decide(String stateJson, int seat) {
|
||||
JsonObject state = GSON.fromJson(stateJson, JsonObject.class);
|
||||
state.addProperty("seat", seat);
|
||||
String action = decide(state);
|
||||
return new PolicyDecision(action, 1.0);
|
||||
}
|
||||
|
||||
public int getFallbackDecisions() { return fallbackDecisions; }
|
||||
public int getPendingTuples() { return tupleBuffer.size(); }
|
||||
|
||||
public double getAverageLatencyMs() {
|
||||
return policyDecisions > 0
|
||||
? (double) totalLatencyMs / policyDecisions
|
||||
: 0;
|
||||
}
|
||||
|
||||
public String getStatsSummary() {
|
||||
return String.format(
|
||||
"PolicyClient[decisions=%d, policy=%d, fallback=%d, avg=%.1fms, pending=%d]",
|
||||
totalDecisions, policyDecisions, fallbackDecisions,
|
||||
getAverageLatencyMs(), tupleBuffer.size()
|
||||
);
|
||||
}
|
||||
|
||||
// ================================================================
|
||||
// HTTP helpers
|
||||
// ================================================================
|
||||
|
||||
private String httpGet(String url) throws IOException {
|
||||
HttpURLConnection conn = (HttpURLConnection) new URL(url).openConnection();
|
||||
conn.setRequestMethod("GET");
|
||||
conn.setConnectTimeout(CONNECT_TIMEOUT_MS);
|
||||
conn.setReadTimeout(READ_TIMEOUT_MS);
|
||||
conn.setRequestProperty("Accept", "application/json");
|
||||
int code = conn.getResponseCode();
|
||||
if (code != 200) {
|
||||
throw new IOException("HTTP " + code + ": " + readStream(conn.getErrorStream()));
|
||||
}
|
||||
return readStream(conn.getInputStream());
|
||||
}
|
||||
|
||||
private String httpPost(String url, String jsonBody) throws IOException {
|
||||
HttpURLConnection conn = (HttpURLConnection) new URL(url).openConnection();
|
||||
conn.setRequestMethod("POST");
|
||||
conn.setConnectTimeout(CONNECT_TIMEOUT_MS);
|
||||
conn.setReadTimeout(READ_TIMEOUT_MS);
|
||||
conn.setDoOutput(true);
|
||||
conn.setRequestProperty("Content-Type", "application/json");
|
||||
conn.setRequestProperty("Accept", "application/json");
|
||||
try (OutputStream os = conn.getOutputStream()) {
|
||||
os.write(jsonBody.getBytes(StandardCharsets.UTF_8));
|
||||
}
|
||||
int code = conn.getResponseCode();
|
||||
if (code != 200) {
|
||||
throw new IOException("HTTP " + code + ": " + readStream(conn.getErrorStream()));
|
||||
}
|
||||
return readStream(conn.getInputStream());
|
||||
}
|
||||
|
||||
private String readStream(InputStream stream) throws IOException {
|
||||
if (stream == null) return "";
|
||||
try (BufferedReader reader = new BufferedReader(
|
||||
new InputStreamReader(stream, StandardCharsets.UTF_8))) {
|
||||
StringBuilder sb = new StringBuilder();
|
||||
String line;
|
||||
while ((line = reader.readLine()) != null) {
|
||||
sb.append(line);
|
||||
}
|
||||
return sb.toString();
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -17,12 +17,6 @@ import java.util.concurrent.atomic.AtomicLong;
|
||||
* - Issue #5: Auto-detects optimal thread count, configurable cap,
|
||||
* real-time sims/sec reporting, graceful backpressure
|
||||
*
|
||||
* Phase 3 (Issue #83): Persistent JVM worker pool — eliminates per-game
|
||||
* JVM startup overhead by reusing GameRules and CardDb across games.
|
||||
* - Workers are pre-warmed at construction time
|
||||
* - Pool size matches numThreads (one warm worker per thread slot)
|
||||
* - Target throughput: 10-50 games/sec per thread
|
||||
*
|
||||
* Each thread gets its own BatchRunner instance and a per-thread RNG seed
|
||||
* derived from the master seed. Results are merged after all threads complete.
|
||||
*/
|
||||
@@ -49,17 +43,6 @@ public class MultiThreadBatchRunner {
|
||||
private boolean useSimplifiedAi = false;
|
||||
private int aiThinkTimeMs = -1;
|
||||
|
||||
// ── ML Decision Logging ──────────────────────────────────────
|
||||
private boolean mlLogEnabled = false;
|
||||
private String mlOutputDir = "results";
|
||||
private String mlBatchId;
|
||||
|
||||
// ── Phase 3: Persistent JVM worker pool ──────────────────────
|
||||
// Pre-warmed BatchRunner instances — one per thread slot.
|
||||
// Reusing them avoids per-game JVM startup cost (GameRules, CardDb init).
|
||||
private final List<BatchRunner> workerPool = new ArrayList<>();
|
||||
private boolean poolWarmed = false;
|
||||
|
||||
public MultiThreadBatchRunner(String forgeJarPath, String forgeWorkDir,
|
||||
List<DeckInfo> decks, AiPolicy policy, int numThreads) {
|
||||
this(forgeJarPath, forgeWorkDir, decks, policy, numThreads, true, 120, "java");
|
||||
@@ -84,104 +67,65 @@ public class MultiThreadBatchRunner {
|
||||
this.javaPath = (javaPath != null && !javaPath.isEmpty()) ? javaPath : "java";
|
||||
}
|
||||
|
||||
// ── Configuration setters ────────────────────────────────────
|
||||
|
||||
/**
|
||||
* Set progress callback for real-time reporting (Issue #5).
|
||||
*/
|
||||
public void setProgressCallback(BatchRunner.ProgressCallback callback) {
|
||||
this.progressCallback = callback;
|
||||
}
|
||||
|
||||
/**
|
||||
* Set max subprocess queue depth for backpressure (Issue #5).
|
||||
* If the number of running Forge subprocesses exceeds this limit,
|
||||
* new game spawns are throttled until slots free up.
|
||||
*
|
||||
* @param maxDepth Max concurrent subprocesses (-1 for unlimited)
|
||||
*/
|
||||
public void setMaxQueueDepth(int maxDepth) {
|
||||
this.maxQueueDepth = maxDepth;
|
||||
}
|
||||
|
||||
/**
|
||||
* Configure AI optimization flags (Issue #4).
|
||||
*/
|
||||
public void setAiOptimization(boolean simplified, int thinkTimeMs) {
|
||||
this.useSimplifiedAi = simplified;
|
||||
this.aiThinkTimeMs = thinkTimeMs;
|
||||
}
|
||||
|
||||
public void enableMlLogging(String outputDir, String batchId) {
|
||||
this.mlLogEnabled = true;
|
||||
this.mlOutputDir = outputDir;
|
||||
this.mlBatchId = batchId;
|
||||
}
|
||||
|
||||
// ── Phase 3: Worker pool management ─────────────────────────
|
||||
|
||||
/**
|
||||
* Pre-warm the JVM worker pool. Creates one BatchRunner per thread slot
|
||||
* and runs a single no-op warm-up pass so that GameRules and CardDb are
|
||||
* loaded and cached before the first real game batch begins.
|
||||
*
|
||||
* Call this once after construction, before runBatch(). If not called
|
||||
* explicitly, runBatch() will warm the pool automatically on first use.
|
||||
*
|
||||
* Target: eliminates ~2-5s per-game JVM startup overhead, enabling
|
||||
* 10-50 games/sec per thread (Phase 3 success criterion).
|
||||
*/
|
||||
public synchronized void warmPool() {
|
||||
if (poolWarmed) return;
|
||||
|
||||
int effective = numThreads <= 0 ? detectOptimalThreads() : numThreads;
|
||||
System.out.printf("[POOL] Pre-warming %d JVM worker(s)...%n", effective);
|
||||
long warmStart = System.currentTimeMillis();
|
||||
|
||||
workerPool.clear();
|
||||
for (int i = 0; i < effective; i++) {
|
||||
BatchRunner worker = createWorker(i);
|
||||
workerPool.add(worker);
|
||||
}
|
||||
|
||||
long warmMs = System.currentTimeMillis() - warmStart;
|
||||
System.out.printf("[POOL] Worker pool ready (%d workers) in %.1fs%n",
|
||||
effective, warmMs / 1000.0);
|
||||
poolWarmed = true;
|
||||
}
|
||||
|
||||
/**
|
||||
* Shut down the worker pool and release resources.
|
||||
* Call after all runBatch() calls are complete.
|
||||
*/
|
||||
public synchronized void shutdownPool() {
|
||||
for (BatchRunner worker : workerPool) {
|
||||
try {
|
||||
worker.closeMlLogger();
|
||||
} catch (Exception ignored) {}
|
||||
}
|
||||
workerPool.clear();
|
||||
poolWarmed = false;
|
||||
System.out.println("[POOL] Worker pool shut down.");
|
||||
}
|
||||
|
||||
private BatchRunner createWorker(int threadId) {
|
||||
BatchRunner worker = new BatchRunner(
|
||||
forgeJarPath, forgeWorkDir, decks, policy, mlLogEnabled ? false : quiet, clockSeconds, javaPath);
|
||||
worker.setAiOptimization(useSimplifiedAi, aiThinkTimeMs);
|
||||
if (mlLogEnabled) {
|
||||
String threadBatchId = mlBatchId + "-t" + threadId;
|
||||
worker.enableMlLogging(mlOutputDir, threadBatchId);
|
||||
}
|
||||
return worker;
|
||||
}
|
||||
|
||||
// ── Phase 3: Thread count auto-detection ─────────────────────
|
||||
|
||||
/**
|
||||
* Auto-detect optimal thread count based on available CPU cores (Issue #5).
|
||||
*
|
||||
* Uses physical core count (not logical/hyperthreaded) when possible.
|
||||
* Each Forge subprocess is CPU-intensive with little I/O wait, so
|
||||
* hyperthreading provides minimal benefit and may increase contention.
|
||||
*
|
||||
* @return Recommended thread count for this machine
|
||||
*/
|
||||
public static int detectOptimalThreads() {
|
||||
int availableProcessors = Runtime.getRuntime().availableProcessors();
|
||||
|
||||
// On most systems, availableProcessors includes hyperthreads.
|
||||
// For CPU-bound Forge sims, physical cores are what matter.
|
||||
// Heuristic: assume HT gives 2x logical cores on Intel/AMD
|
||||
int estimatedPhysical = availableProcessors;
|
||||
|
||||
// Try to detect if hyperthreading is active
|
||||
// On Windows, we can check if logical > physical
|
||||
try {
|
||||
String os = System.getProperty("os.name", "").toLowerCase();
|
||||
if (os.contains("win")) {
|
||||
// Windows: NUMBER_OF_PROCESSORS env var = logical processors
|
||||
// For a more accurate count, we'd need WMI or /proc — but the
|
||||
// simple heuristic of logical/2 works for most desktop systems
|
||||
// Only apply if > 4 logical cores (small systems likely don't have HT)
|
||||
if (availableProcessors > 4) {
|
||||
estimatedPhysical = availableProcessors / 2;
|
||||
}
|
||||
} else if (os.contains("linux")) {
|
||||
java.io.File topology = new java.io.File(
|
||||
"/sys/devices/system/cpu/cpu0/topology/thread_siblings_list");
|
||||
// Linux: try reading /sys/devices/system/cpu/cpu0/topology/thread_siblings_list
|
||||
// If the file exists and shows 2 threads per core, halve the count
|
||||
java.io.File topology = new java.io.File("/sys/devices/system/cpu/cpu0/topology/thread_siblings_list");
|
||||
if (topology.exists()) {
|
||||
String content = java.nio.file.Files.readString(topology.toPath()).trim();
|
||||
if (content.contains(",") || content.contains("-")) {
|
||||
@@ -193,54 +137,47 @@ public class MultiThreadBatchRunner {
|
||||
// Ignore — use availableProcessors as-is
|
||||
}
|
||||
|
||||
// Reserve 1 core for the OS/JVM overhead, minimum 1 worker
|
||||
int optimal = Math.max(1, estimatedPhysical - 1);
|
||||
|
||||
System.out.printf("[THREADS] Detected: %d logical processors, ~%d physical cores → using %d threads%n",
|
||||
availableProcessors, estimatedPhysical, optimal);
|
||||
|
||||
return optimal;
|
||||
}
|
||||
|
||||
// ── Main batch runner ─────────────────────────────────────────
|
||||
|
||||
/**
|
||||
* Run totalGames across numThreads workers.
|
||||
*
|
||||
* Phase 3: Uses the persistent worker pool if available (warmPool() called
|
||||
* beforehand), otherwise falls back to creating per-run workers. Pool reuse
|
||||
* eliminates per-game JVM startup cost for GameRules and CardDb.
|
||||
* v24: Real-time progress reporting, backpressure, per-game sims/sec (Issue #5).
|
||||
*/
|
||||
public List<GameResult> runBatch(int totalGames, Long masterSeed)
|
||||
throws InterruptedException, ExecutionException {
|
||||
|
||||
// Auto-detect if threads=0 or threads=-1
|
||||
public List<GameResult> runBatch(int totalGames, Long masterSeed) throws InterruptedException, ExecutionException {
|
||||
// Issue #5: Auto-detect if threads=0 or threads=-1 (auto mode)
|
||||
if (numThreads <= 0) {
|
||||
numThreads = detectOptimalThreads();
|
||||
}
|
||||
|
||||
// Phase 3: auto-warm pool on first runBatch() if not already warmed
|
||||
if (!poolWarmed) {
|
||||
warmPool();
|
||||
}
|
||||
|
||||
int gamesPerThread = totalGames / numThreads;
|
||||
int remainder = totalGames % numThreads;
|
||||
|
||||
// Issue #5: Backpressure — limit concurrent subprocesses if configured
|
||||
ExecutorService executor;
|
||||
if (maxQueueDepth > 0) {
|
||||
// Use a bounded thread pool to prevent RAM exhaustion from too many Forge JVMs
|
||||
int effectiveThreads = Math.min(numThreads, maxQueueDepth);
|
||||
executor = Executors.newFixedThreadPool(effectiveThreads);
|
||||
System.out.printf("[BACKPRESSURE] Limiting to %d concurrent Forge processes " +
|
||||
"(requested %d threads, max queue %d)%n",
|
||||
System.out.printf("[BACKPRESSURE] Limiting to %d concurrent Forge processes (requested %d threads, max queue %d)%n",
|
||||
effectiveThreads, numThreads, maxQueueDepth);
|
||||
} else {
|
||||
executor = Executors.newFixedThreadPool(numThreads);
|
||||
}
|
||||
|
||||
List<Future<List<GameResult>>> futures = new ArrayList<>();
|
||||
|
||||
totalCompleted.set(0);
|
||||
batchStartMs.set(System.currentTimeMillis());
|
||||
|
||||
System.out.printf("[BATCH] Starting %d games across %d pooled workers " +
|
||||
"(%.1f games/worker avg)%n",
|
||||
System.out.printf("[BATCH] Starting %d games across %d threads (%.1f games/thread avg)%n",
|
||||
totalGames, numThreads, (double) totalGames / numThreads);
|
||||
|
||||
int gameOffset = 0;
|
||||
@@ -248,37 +185,36 @@ public class MultiThreadBatchRunner {
|
||||
int chunkSize = gamesPerThread + (t < remainder ? 1 : 0);
|
||||
if (chunkSize == 0) continue;
|
||||
|
||||
Long threadSeed = (masterSeed != null)
|
||||
? masterSeed + (long) gameOffset * 1000L : null;
|
||||
Long threadSeed = (masterSeed != null) ? masterSeed + (long) gameOffset * 1000L : null;
|
||||
int startIndex = gameOffset;
|
||||
int threadId = t;
|
||||
|
||||
// Phase 3: retrieve pre-warmed worker from pool
|
||||
BatchRunner worker = (threadId < workerPool.size())
|
||||
? workerPool.get(threadId)
|
||||
: createWorker(threadId);
|
||||
BatchRunner runner = new BatchRunner(forgeJarPath, forgeWorkDir, decks, policy, quiet, clockSeconds, javaPath);
|
||||
|
||||
// Per-thread progress callback that aggregates across all threads
|
||||
worker.setProgressCallback((completed, total, pct, simsPerSec, lastResult) -> {
|
||||
// Issue #4: Forward AI optimization settings
|
||||
runner.setAiOptimization(useSimplifiedAi, aiThinkTimeMs);
|
||||
|
||||
// Issue #5: Per-thread progress callback that aggregates across all threads
|
||||
runner.setProgressCallback((completed, total, pct, simsPerSec, lastResult) -> {
|
||||
int globalCompleted = totalCompleted.incrementAndGet();
|
||||
long elapsed = System.currentTimeMillis() - batchStartMs.get();
|
||||
double globalSimsPerSec = elapsed > 0
|
||||
? (double) globalCompleted / (elapsed / 1000.0) : 0.0;
|
||||
? (double) globalCompleted / (elapsed / 1000.0)
|
||||
: 0.0;
|
||||
int globalPct = (int) ((double) globalCompleted * 100.0 / totalGames);
|
||||
|
||||
System.out.printf("[PROGRESS] %d/%d games (%.1f%%) — %.3f sims/sec " +
|
||||
"(worker %d: %d/%d)%n",
|
||||
System.out.printf("[PROGRESS] %d/%d games (%.1f%%) — %.3f sims/sec (thread %d: %d/%d)%n",
|
||||
globalCompleted, totalGames, (double) globalPct,
|
||||
globalSimsPerSec, threadId, completed, total);
|
||||
|
||||
// Forward to external callback if set
|
||||
if (progressCallback != null) {
|
||||
progressCallback.onProgress(globalCompleted, totalGames,
|
||||
globalPct, globalSimsPerSec, lastResult);
|
||||
progressCallback.onProgress(globalCompleted, totalGames, globalPct, globalSimsPerSec, lastResult);
|
||||
}
|
||||
});
|
||||
|
||||
futures.add(executor.submit(() -> {
|
||||
List<GameResult> results = worker.runBatchSingleThread(chunkSize, threadSeed);
|
||||
List<GameResult> results = runner.runBatchSingleThread(chunkSize, threadSeed);
|
||||
for (int i = 0; i < results.size(); i++) {
|
||||
results.get(i).gameIndex = startIndex + i;
|
||||
}
|
||||
@@ -304,10 +240,8 @@ public class MultiThreadBatchRunner {
|
||||
|
||||
// Final throughput report
|
||||
long totalElapsed = System.currentTimeMillis() - batchStartMs.get();
|
||||
double finalSimsPerSec = totalElapsed > 0
|
||||
? (double) merged.size() / (totalElapsed / 1000.0) : 0.0;
|
||||
System.out.printf("[BATCH] Completed %d games in %.1fs — %.3f sims/sec " +
|
||||
"(across %d pooled workers)%n",
|
||||
double finalSimsPerSec = totalElapsed > 0 ? (double) merged.size() / (totalElapsed / 1000.0) : 0.0;
|
||||
System.out.printf("[BATCH] Completed %d games in %.1fs — %.3f sims/sec (across %d threads)%n",
|
||||
merged.size(), totalElapsed / 1000.0, finalSimsPerSec, numThreads);
|
||||
|
||||
return merged;
|
||||
|
||||
@@ -4,7 +4,6 @@ import com.google.gson.Gson;
|
||||
import com.google.gson.GsonBuilder;
|
||||
import com.google.gson.JsonObject;
|
||||
import com.google.gson.JsonParser;
|
||||
import commanderailab.ai.PolicyClient;
|
||||
|
||||
import java.util.*;
|
||||
import java.util.concurrent.BlockingQueue;
|
||||
@@ -14,11 +13,10 @@ import java.util.function.Consumer;
|
||||
/**
|
||||
* GameSession — holds state for one live interactive Commander game.
|
||||
*
|
||||
* PHASE 2: integrates PolicyClient for bidirectional sync between
|
||||
* the Java game loop and the Python policy server.
|
||||
* PHASE 1 STUB: generates synthetic game state so you can verify the full
|
||||
* WebSocket contract round-trips correctly before wiring in real Forge IPC.
|
||||
*
|
||||
* AI turns now consult the policy server for macro-action decisions
|
||||
* instead of using random stub logic.
|
||||
* Replace run() in Phase 2 once the contract is verified end-to-end.
|
||||
*/
|
||||
public class GameSession {
|
||||
|
||||
@@ -29,7 +27,6 @@ public class GameSession {
|
||||
private final String forgeJarPath;
|
||||
private final String forgeWorkDir;
|
||||
private final BlockingQueue<String> humanActionQueue;
|
||||
private final PolicyClient policyClient;
|
||||
|
||||
private volatile boolean running = false;
|
||||
private volatile int turnNumber = 1;
|
||||
@@ -59,21 +56,11 @@ public class GameSession {
|
||||
public GameSession(List<String> deckNames, Long seed,
|
||||
String forgeJarPath, String forgeWorkDir,
|
||||
BlockingQueue<String> humanActionQueue) {
|
||||
this(deckNames, seed, forgeJarPath, forgeWorkDir, humanActionQueue,
|
||||
new PolicyClient("http://localhost:8080"));
|
||||
}
|
||||
|
||||
@SuppressWarnings("unchecked")
|
||||
public GameSession(List<String> deckNames, Long seed,
|
||||
String forgeJarPath, String forgeWorkDir,
|
||||
BlockingQueue<String> humanActionQueue,
|
||||
PolicyClient policyClient) {
|
||||
this.deckNames = deckNames;
|
||||
this.seed = seed;
|
||||
this.forgeJarPath = forgeJarPath;
|
||||
this.forgeWorkDir = forgeWorkDir;
|
||||
this.humanActionQueue = humanActionQueue;
|
||||
this.policyClient = policyClient;
|
||||
|
||||
int seats = Math.min(deckNames.size(), 4);
|
||||
life = new int[seats];
|
||||
@@ -87,8 +74,8 @@ public class GameSession {
|
||||
for (int i = 0; i < seats; i++) {
|
||||
life[i] = 40;
|
||||
hands[i] = new ArrayList<>(List.of(
|
||||
"card_stub_1", "card_stub_2", "card_stub_3",
|
||||
"card_stub_4", "card_stub_5", "card_stub_6", "card_stub_7"
|
||||
"card_stub_1", "card_stub_2", "card_stub_3",
|
||||
"card_stub_4", "card_stub_5", "card_stub_6", "card_stub_7"
|
||||
));
|
||||
battlefields[i] = new ArrayList<>();
|
||||
graveyards[i] = new ArrayList<>();
|
||||
@@ -98,27 +85,28 @@ public class GameSession {
|
||||
|
||||
public boolean isRunning() { return running; }
|
||||
public int getTurnNumber() { return turnNumber; }
|
||||
public void stop() { running = false; }
|
||||
|
||||
public void stop() {
|
||||
running = false;
|
||||
}
|
||||
|
||||
/**
|
||||
* Run the game loop. Calls onStateChange after every action resolves.
|
||||
* Blocks until the game ends or stop() is called.
|
||||
*
|
||||
* PHASE 2: AI turns now consult the PolicyClient for decisions.
|
||||
* The policy server returns a macro-action which is applied to game state.
|
||||
* Falls back to PASS_PRIORITY if the policy server is unreachable.
|
||||
* PHASE 1 STUB: advances through phases automatically; on MAIN1 of seat 0's
|
||||
* turn, pauses and waits for the human client to send an action.
|
||||
*/
|
||||
public void run(Consumer<Map<String, Object>> onStateChange) throws InterruptedException {
|
||||
public void run(Consumer<Object> onStateChange) throws InterruptedException {
|
||||
running = true;
|
||||
Random rng = seed != null ? new Random(seed) : new Random();
|
||||
|
||||
System.out.println("[Session] Game started. Decks: " + deckNames);
|
||||
System.out.println("[Session] PolicyClient endpoint: " + policyClient.getBaseUrl());
|
||||
|
||||
while (running && !isGameOver()) {
|
||||
String currentPhase = PHASES[phaseIndex];
|
||||
phase = currentPhase;
|
||||
activePlayer = (turnNumber - 1) % deckNames.size();
|
||||
|
||||
boolean isHumanTurn = (activePlayer == 0);
|
||||
boolean isInteractivePhase = currentPhase.equals("MAIN1") || currentPhase.equals("MAIN2");
|
||||
|
||||
@@ -129,6 +117,7 @@ public class GameSession {
|
||||
|
||||
System.out.println("[Session] Awaiting human action for " + currentPhase + "...");
|
||||
String actionJson = humanActionQueue.poll(120, TimeUnit.SECONDS);
|
||||
|
||||
if (actionJson == null) {
|
||||
System.out.println("[Session] Human timed out — auto passing.");
|
||||
} else {
|
||||
@@ -136,18 +125,13 @@ public class GameSession {
|
||||
System.out.println("[Session] Human action applied: " + actionJson);
|
||||
}
|
||||
awaitingHumanInput = false;
|
||||
|
||||
} else if (!isHumanTurn && isInteractivePhase) {
|
||||
// Phase 2: consult PolicyClient for AI decision
|
||||
priorityPlayer = activePlayer;
|
||||
Map<String, Object> snapshot = buildStateSnapshot();
|
||||
String policyAction = consultPolicy(activePlayer, snapshot);
|
||||
applyPolicyAction(activePlayer, policyAction, rng);
|
||||
System.out.println("[Session] AI-" + activePlayer + " policy action: " + policyAction);
|
||||
|
||||
} else {
|
||||
// Non-interactive phase — small delay for readability
|
||||
// AI turn — small delay for readability
|
||||
Thread.sleep(300);
|
||||
// Simulate AI occasionally dealing damage to human
|
||||
if (!isHumanTurn && currentPhase.equals("DAMAGE") && life[0] > 5) {
|
||||
life[0] -= rng.nextInt(4);
|
||||
}
|
||||
}
|
||||
|
||||
// Advance phase
|
||||
@@ -156,6 +140,7 @@ public class GameSession {
|
||||
phaseIndex = 0;
|
||||
turnNumber++;
|
||||
}
|
||||
|
||||
onStateChange.accept(buildStateSnapshot());
|
||||
}
|
||||
|
||||
@@ -163,70 +148,11 @@ public class GameSession {
|
||||
System.out.println("[Session] Game ended after " + turnNumber + " turns.");
|
||||
}
|
||||
|
||||
// ---------------------------------------------------------
|
||||
// Policy integration (Phase 2)
|
||||
// ---------------------------------------------------------
|
||||
|
||||
/**
|
||||
* Consult the Python policy server for an AI decision.
|
||||
* Sends the current game snapshot and returns the recommended macro-action.
|
||||
* Falls back to PASS_PRIORITY on error.
|
||||
*/
|
||||
private String consultPolicy(int seat, Map<String, Object> snapshot) {
|
||||
try {
|
||||
String stateJson = GSON.toJson(snapshot);
|
||||
PolicyClient.PolicyDecision decision = policyClient.decide(stateJson, seat);
|
||||
if (decision != null && decision.action() != null) {
|
||||
System.out.println("[Session] Policy decision for seat " + seat
|
||||
+ ": " + decision.action()
|
||||
+ " (confidence=" + String.format("%.2f", decision.confidence()) + ")");
|
||||
return decision.action();
|
||||
}
|
||||
} catch (Exception e) {
|
||||
System.err.println("[Session] Policy server error for seat " + seat + ": " + e.getMessage());
|
||||
}
|
||||
return "PASS_PRIORITY";
|
||||
}
|
||||
|
||||
/**
|
||||
* Apply a policy-recommended macro-action for an AI player.
|
||||
*/
|
||||
private void applyPolicyAction(int seat, String action, Random rng) {
|
||||
switch (action) {
|
||||
case "CAST_SPELL" -> {
|
||||
if (!hands[seat].isEmpty()) {
|
||||
String card = hands[seat].remove(0);
|
||||
battlefields[seat].add(card);
|
||||
System.out.println("[Session] AI-" + seat + " cast: " + card);
|
||||
}
|
||||
}
|
||||
case "PLAY_LAND" -> {
|
||||
if (!hands[seat].isEmpty()) {
|
||||
String card = hands[seat].remove(hands[seat].size() - 1);
|
||||
battlefields[seat].add(card);
|
||||
}
|
||||
}
|
||||
case "ATTACK" -> {
|
||||
int target = (seat + 1) % life.length;
|
||||
if (life[target] > 0) {
|
||||
int dmg = rng.nextInt(3) + 1;
|
||||
life[target] -= dmg;
|
||||
System.out.println("[Session] AI-" + seat + " attacks player " + target + " for " + dmg);
|
||||
}
|
||||
}
|
||||
case "PASS_PRIORITY" -> { /* no-op */ }
|
||||
default -> System.out.println("[Session] Unknown policy action: " + action);
|
||||
}
|
||||
}
|
||||
|
||||
// ---------------------------------------------------------
|
||||
// Human action handling
|
||||
// ---------------------------------------------------------
|
||||
|
||||
private void applyAction(String actionJson) {
|
||||
try {
|
||||
JsonObject action = JsonParser.parseString(actionJson).getAsJsonObject();
|
||||
String type = action.has("type") ? action.get("type").getAsString() : "PASS_PRIORITY";
|
||||
|
||||
switch (type) {
|
||||
case "PLAY_LAND", "CAST_SPELL" -> {
|
||||
String cardId = action.has("cardId") ? action.get("cardId").getAsString() : null;
|
||||
@@ -246,6 +172,7 @@ public class GameSession {
|
||||
private boolean isGameOver() {
|
||||
int alive = 0;
|
||||
for (int lp : life) if (lp > 0) alive++;
|
||||
// Phase 1 stub: end after 50 turns or only 1 player alive
|
||||
return alive <= 1 || turnNumber > 50;
|
||||
}
|
||||
|
||||
@@ -283,7 +210,7 @@ public class GameSession {
|
||||
p.put("poison", poison[i]);
|
||||
p.put("commanderTax", commanderTax[i]);
|
||||
p.put("handCount", hands[i].size());
|
||||
p.put("hand", i == 0 ? hands[i] : List.of());
|
||||
p.put("hand", i == 0 ? hands[i] : List.of()); // hide opponent hands
|
||||
p.put("battlefield", battlefields[i]);
|
||||
p.put("graveyard", graveyards[i]);
|
||||
p.put("commandZone", commandZones[i]);
|
||||
|
||||
@@ -90,7 +90,7 @@ public class LabCli implements Callable<Integer> {
|
||||
description = "Master RNG seed for reproducibility (blank for random)")
|
||||
private String seed;
|
||||
|
||||
@Option(names = {"--output", "-o"}, defaultValue = "results/ml-decision-latest.json",
|
||||
@Option(names = {"--output", "-o"}, defaultValue = "results/batch-latest.json",
|
||||
description = "Output JSON file path")
|
||||
private String outputPath;
|
||||
|
||||
@@ -344,12 +344,6 @@ public class LabCli implements Callable<Integer> {
|
||||
mtRunner.setAiOptimization(aiSimplified, aiThinkTimeMs);
|
||||
if (maxQueueDepth > 0) {
|
||||
mtRunner.setMaxQueueDepth(maxQueueDepth);
|
||||
}
|
||||
// v4: Enable ML decision logging if requested
|
||||
if (mlLog) {
|
||||
String batchId = UUID.randomUUID().toString().substring(0, 8);
|
||||
mtRunner.enableMlLogging("results", batchId);
|
||||
System.out.println("[ML] Decision logging enabled (multi-thread) — data will be saved to results/");
|
||||
}
|
||||
games = mtRunner.runBatch(numGames, masterSeed);
|
||||
} else {
|
||||
|
||||
@@ -33,7 +33,7 @@ public class PolicyServerClient {
|
||||
|
||||
private static final Gson GSON = new GsonBuilder().create();
|
||||
private static final int CONNECT_TIMEOUT_MS = 2000;
|
||||
private static final int READ_TIMEOUT_MS = 300_000;
|
||||
private static final int READ_TIMEOUT_MS = 5000;
|
||||
|
||||
private final String baseUrl;
|
||||
private volatile boolean available = false;
|
||||
|
||||
@@ -31,7 +31,7 @@ public class JsonExporter {
|
||||
* Write a BatchResult to a JSON file.
|
||||
*
|
||||
* @param result The batch result to export
|
||||
* @param filePath Output file path (e.g., "results/ml-decision-20260306-001.json")
|
||||
* @param filePath Output file path (e.g., "results/batch-20260306-001.json")
|
||||
* @throws IOException if file cannot be written
|
||||
*/
|
||||
public static void writeToFile(BatchResult result, String filePath) throws IOException {
|
||||
|
||||
+44
-42
@@ -1,110 +1,112 @@
|
||||
@echo off
|
||||
REM ═══════════════════════════════════════════════════════════
|
||||
REM Commander AI Lab — One-Click Launcher (Windows)
|
||||
REM Commander AI Lab — One-Click Launcher (Windows)
|
||||
REM ═══════════════════════════════════════════════════════════
|
||||
REM
|
||||
REM Starts the Python FastAPI server + serves the web UI.
|
||||
REM Prerequisites:
|
||||
REM - Python 3.10+ with: pip install fastapi uvicorn
|
||||
REM - Java 17+
|
||||
REM - commander-ai-lab built: mvn package "-DskipTests"
|
||||
REM Starts the Python FastAPI server + serves the web UI.
|
||||
REM Prerequisites:
|
||||
REM - Python 3.10+ with: pip install fastapi uvicorn
|
||||
REM - Java 17+
|
||||
REM - commander-ai-lab built: mvn package "-DskipTests"
|
||||
REM
|
||||
REM Edit the paths below to match your system.
|
||||
REM Edit the paths below to match your system.
|
||||
REM ═══════════════════════════════════════════════════════════
|
||||
|
||||
REM ── Your Forge paths (EDIT THESE) ──────────────────────────
|
||||
set FORGE_JAR=D:\ForgeCommander\forge-repo\forge-gui-desktop\target\forge-gui-desktop-2.0.12-SNAPSHOT-jar-with-dependencies.jar
|
||||
set FORGE_DIR=D:\ForgeCommander\forge-repo
|
||||
set FORGE_DIR=D:\ForgeCommander\forge-repo\forge-gui
|
||||
set FORGE_DECKS_DIR=%APPDATA%\Forge\decks\commander
|
||||
REM ── Lab JAR (auto-detected from target/) ─────────────────────
|
||||
|
||||
REM ── Lab JAR (auto-detected from target/) ───────────────────
|
||||
set LAB_PORT=8080
|
||||
|
||||
REM ── API Keys (set via environment variables or .env file) ──
|
||||
REM If not already set in your environment, create a .env file
|
||||
REM in this directory (see .env.example) or set them manually:
|
||||
REM set XIMILAR_API_KEY=your-ximilar-key-here
|
||||
REM set ANTHROPIC_API_KEY=your-anthropic-api-key-here
|
||||
REM If not already set in your environment, create a .env file
|
||||
REM in this directory (see .env.example) or set them manually:
|
||||
REM set XIMILAR_API_KEY=your-ximilar-key-here
|
||||
REM set PPLX_API_KEY=your-perplexity-key-here
|
||||
REM
|
||||
REM Load from .env file if it exists and vars aren't already set
|
||||
REM Load from .env file if it exists and vars aren't already set
|
||||
if not defined XIMILAR_API_KEY (
|
||||
if exist "%~dp0.env" (
|
||||
for /f "usebackq tokens=1,* delims==" %%A in ("%~dp0.env") do (
|
||||
if "%%A"=="XIMILAR_API_KEY" set XIMILAR_API_KEY=%%B
|
||||
if "%%A"=="ANTHROPIC_API_KEY" set ANTHROPIC_API_KEY=%%B
|
||||
if "%%A"=="PPLX_API_KEY" set PPLX_API_KEY=%%B
|
||||
)
|
||||
)
|
||||
)
|
||||
|
||||
echo.
|
||||
echo ╔══════════════════════════════════════════════════╗
|
||||
echo ║ Commander AI Lab — Launcher ║
|
||||
echo ╚══════════════════════════════════════════════════╝
|
||||
echo ╔══════════════════════════════════════════════════╗
|
||||
echo ║ Commander AI Lab — Launcher ║
|
||||
echo ╚══════════════════════════════════════════════════╝
|
||||
echo.
|
||||
echo Forge JAR: %FORGE_JAR%
|
||||
echo Forge Dir: %FORGE_DIR%
|
||||
echo Decks Dir: %FORGE_DECKS_DIR%
|
||||
echo Port: %LAB_PORT%
|
||||
echo Ximilar: Configured
|
||||
if defined ANTHROPIC_API_KEY (
|
||||
echo Claude Opus: Configured
|
||||
echo Forge JAR: %FORGE_JAR%
|
||||
echo Forge Dir: %FORGE_DIR%
|
||||
echo Decks Dir: %FORGE_DECKS_DIR%
|
||||
echo Port: %LAB_PORT%
|
||||
echo Ximilar: Configured
|
||||
if defined PPLX_API_KEY (
|
||||
echo Perplexity: Configured
|
||||
) else (
|
||||
echo Claude Opus: Not configured ^(set ANTHROPIC_API_KEY env var for AI features^)
|
||||
echo Perplexity: Not configured ^(set PPLX_API_KEY env var for AI features^)
|
||||
)
|
||||
echo.
|
||||
|
||||
REM ── Check prerequisites ────────────────────────────────────
|
||||
where python >nul 2>&1
|
||||
if %ERRORLEVEL% neq 0 (
|
||||
echo ERROR: Python not found in PATH
|
||||
echo ERROR: Python not found in PATH
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
where java >nul 2>&1
|
||||
if %ERRORLEVEL% neq 0 (
|
||||
echo ERROR: Java not found in PATH
|
||||
echo ERROR: Java not found in PATH
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
if not exist "%FORGE_JAR%" (
|
||||
echo ERROR: Forge JAR not found at: %FORGE_JAR%
|
||||
echo Run Forge build first:
|
||||
echo cd D:\ForgeCommander\forge-repo
|
||||
echo mvn package -pl forge-gui-desktop "-DskipTests" "-Drevision=2.0.12-SNAPSHOT" -am
|
||||
echo ERROR: Forge JAR not found at: %FORGE_JAR%
|
||||
echo Run Forge build first:
|
||||
echo cd D:\ForgeCommander\forge-repo
|
||||
echo mvn package -pl forge-gui-desktop "-DskipTests" "-Drevision=2.0.12-SNAPSHOT" -am
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
REM ── Check if lab_api.py exists ─────────────────────────────
|
||||
if not exist "%~dp0lab_api.py" (
|
||||
echo ERROR: lab_api.py not found in %~dp0
|
||||
echo ERROR: lab_api.py not found in %~dp0
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
REM ── Install Python deps if needed ───────────────────────────
|
||||
REM ── Install Python deps if needed ──────────────────────────
|
||||
python -c "import fastapi" >nul 2>&1
|
||||
if %ERRORLEVEL% neq 0 (
|
||||
echo Installing FastAPI + Uvicorn...
|
||||
echo Installing FastAPI + Uvicorn...
|
||||
pip install fastapi uvicorn
|
||||
)
|
||||
|
||||
REM ── Launch the server ───────────────────────────────────────
|
||||
REM ── Launch the server ──────────────────────────────────────
|
||||
echo.
|
||||
echo Starting Commander AI Lab server...
|
||||
echo Web UI: http://localhost:%LAB_PORT%
|
||||
echo API: http://localhost:%LAB_PORT%/docs
|
||||
echo Press Ctrl+C to stop.
|
||||
echo Starting Commander AI Lab server...
|
||||
echo Web UI: http://localhost:%LAB_PORT%
|
||||
echo API: http://localhost:%LAB_PORT%/docs
|
||||
echo Press Ctrl+C to stop.
|
||||
echo.
|
||||
|
||||
if defined ANTHROPIC_API_KEY (
|
||||
if defined PPLX_API_KEY (
|
||||
python "%~dp0lab_api.py" ^
|
||||
--forge-jar "%FORGE_JAR%" ^
|
||||
--forge-dir "%FORGE_DIR%" ^
|
||||
--forge-decks-dir "%FORGE_DECKS_DIR%" ^
|
||||
--port %LAB_PORT% ^
|
||||
--ximilar-key "%XIMILAR_API_KEY%" ^
|
||||
--anthropic-key "%ANTHROPIC_API_KEY%"
|
||||
--pplx-key "%PPLX_API_KEY%"
|
||||
) else (
|
||||
python "%~dp0lab_api.py" ^
|
||||
--forge-jar "%FORGE_JAR%" ^
|
||||
|
||||
+11
-111
@@ -26,56 +26,11 @@ os.environ.setdefault("SDL_AUDIODRIVER", "dummy")
|
||||
class StubCard:
|
||||
name: str
|
||||
type: str = "creature"
|
||||
type_line: str = ""
|
||||
pt: Optional[str] = "2/2"
|
||||
cmc: int = 3
|
||||
tapped: bool = False
|
||||
is_commander: bool = False
|
||||
oracle: str = ""
|
||||
oracle_text: str = ""
|
||||
power: str = ""
|
||||
toughness: str = ""
|
||||
keywords: list = field(default_factory=list)
|
||||
|
||||
def get_power(self) -> int:
|
||||
if self.power:
|
||||
try:
|
||||
return int(self.power)
|
||||
except ValueError:
|
||||
return 0
|
||||
if not self.pt:
|
||||
return 0
|
||||
parts = self.pt.split("/")
|
||||
try:
|
||||
return int(parts[0])
|
||||
except (ValueError, IndexError):
|
||||
return 0
|
||||
|
||||
def get_toughness(self) -> int:
|
||||
if self.toughness:
|
||||
try:
|
||||
return int(self.toughness)
|
||||
except ValueError:
|
||||
return 0
|
||||
if not self.pt:
|
||||
return 0
|
||||
parts = self.pt.split("/")
|
||||
try:
|
||||
return int(parts[1])
|
||||
except (ValueError, IndexError):
|
||||
return 0
|
||||
|
||||
def is_land(self) -> bool:
|
||||
return bool(self.type_line and "land" in self.type_line.lower())
|
||||
|
||||
def is_creature(self) -> bool:
|
||||
return bool(self.type_line and "creature" in self.type_line.lower())
|
||||
|
||||
def has_keyword(self, kw: str) -> bool:
|
||||
kw_lower = kw.lower()
|
||||
if self.keywords and any(k.lower() == kw_lower for k in self.keywords):
|
||||
return True
|
||||
return kw_lower in (self.oracle_text or "").lower()
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
return {
|
||||
@@ -92,7 +47,7 @@ class StubCard:
|
||||
@dataclass
|
||||
class StubPlayer:
|
||||
name: str
|
||||
seat: int = 0
|
||||
seat: int
|
||||
life: int = 40
|
||||
eliminated: bool = False
|
||||
hand: list = field(default_factory=list)
|
||||
@@ -120,28 +75,7 @@ class StubPlayer:
|
||||
}
|
||||
|
||||
|
||||
class _StubSimState:
|
||||
"""Minimal SimState-compatible stub — delegates to player battlefields."""
|
||||
|
||||
def __init__(self, players: list) -> None:
|
||||
self._players = players
|
||||
|
||||
def get_battlefield(self, seat: int) -> list:
|
||||
if 0 <= seat < len(self._players):
|
||||
return self._players[seat].battlefield
|
||||
return []
|
||||
|
||||
def add_to_battlefield(self, seat: int, card) -> None:
|
||||
if 0 <= seat < len(self._players):
|
||||
self._players[seat].battlefield.append(card)
|
||||
|
||||
|
||||
class StubGameState:
|
||||
"""
|
||||
Shared test stub that implements the CommanderGameState interface
|
||||
used by ThreatAssessor, TurnManager, and other subsystems.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
num_players: int = 4,
|
||||
@@ -152,27 +86,11 @@ class StubGameState:
|
||||
self.turn = 1
|
||||
self.current_phase = "main1"
|
||||
self.active_player_seat = 0
|
||||
self.priority_seat = 0
|
||||
self.stack: list = []
|
||||
self.stack = []
|
||||
self.game_over = False
|
||||
self.winner = None
|
||||
self.commander_damage: dict[tuple, int] = {}
|
||||
|
||||
# SimState-compatible sub-object for turn_manager._phase_untap() etc.
|
||||
self.sim_state = _StubSimState(self.players)
|
||||
|
||||
# -- CommanderGameState interface methods --
|
||||
|
||||
def battlefield(self, seat: int) -> list:
|
||||
"""Return the battlefield for *seat* (delegates to sim_state)."""
|
||||
return self.sim_state.get_battlefield(seat)
|
||||
|
||||
def stack_is_empty(self) -> bool:
|
||||
return len(self.stack) == 0
|
||||
|
||||
def living_players(self) -> list:
|
||||
return [p for p in self.players if not p.eliminated]
|
||||
|
||||
def get_legal_moves(self, seat: int) -> list[dict]:
|
||||
return [
|
||||
{"id": 1, "category": "pass_priority", "description": "Pass priority"},
|
||||
@@ -188,14 +106,6 @@ class StubGameState:
|
||||
if self.active_player_seat == 0:
|
||||
self.turn += 1
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
return {
|
||||
"turn": self.turn,
|
||||
"current_phase": self.current_phase,
|
||||
"active_player_seat": self.active_player_seat,
|
||||
"players": [p.to_dict() for p in self.players],
|
||||
}
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Pytest fixtures
|
||||
@@ -211,20 +121,6 @@ def game_state_2p():
|
||||
return StubGameState(num_players=2, names=["Alice", "Bob"])
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def basic_creature():
|
||||
"""A simple Card instance for clone and attribute tests."""
|
||||
from commander_ai_lab.sim.models import Card
|
||||
return Card(
|
||||
name="Grizzly Bears",
|
||||
type_line="Creature — Bear",
|
||||
cmc=2,
|
||||
pt="2/2",
|
||||
power="2",
|
||||
toughness="2",
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def targeting_memory():
|
||||
from commander_ai_lab.sim.politics.memory import TargetingMemory
|
||||
@@ -261,12 +157,8 @@ def fresh_app():
|
||||
"""FastAPI test app with a clean session store."""
|
||||
from commander_ai_lab.web.session_store import SessionStore
|
||||
SessionStore._instance = None
|
||||
import commander_ai_lab.web.routers.api as api_mod
|
||||
api_mod._store = SessionStore()
|
||||
from commander_ai_lab.web.app import create_app
|
||||
app = create_app()
|
||||
yield app
|
||||
SessionStore._instance = None
|
||||
return create_app()
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
@@ -275,6 +167,14 @@ def http_client(fresh_app):
|
||||
return TestClient(fresh_app)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def basic_creature():
|
||||
"""A simple creature Card for model tests."""
|
||||
from commander_ai_lab.sim.models import Card
|
||||
return Card(name="Grizzly Bears", type_line="Creature — Bear",
|
||||
cmc=2, pt="2/2", power="2", toughness="2")
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def event_loop():
|
||||
"""Provide a fresh event loop for async tests."""
|
||||
|
||||
@@ -77,7 +77,7 @@ class TestDeckRatios:
|
||||
assert total == 99
|
||||
|
||||
def test_bad_total_raises(self):
|
||||
with pytest.raises(ValidationError, match="less_than_equal|must sum to 99"):
|
||||
with pytest.raises(ValidationError, match="must sum to 99"):
|
||||
DeckRatios(lands=50)
|
||||
|
||||
def test_out_of_range_raises(self):
|
||||
|
||||
@@ -1,539 +0,0 @@
|
||||
"""Regression tests for direct-damage spell routing (Issue #86).
|
||||
|
||||
Tests that burn spells and similar direct-damage effects are routed
|
||||
through the centralized deal_damage() path, correctly update
|
||||
life totals / stats, and integrate with commander damage tracking.
|
||||
|
||||
Adapted to work with the dual-dict commander damage model from PR #89:
|
||||
- commander_damage_received[seat] = per-seat aggregate
|
||||
- commander_damage_by_card[(seat, card_name)] = per-card breakdown
|
||||
"""
|
||||
import pytest
|
||||
from commander_ai_lab.sim.models import Card, Player, PlayerStats, SimState
|
||||
from commander_ai_lab.sim.rules import enrich_card
|
||||
from commander_ai_lab.sim.engine import GameEngine
|
||||
|
||||
|
||||
# ── Helpers ──────────────────────────────────────────────────
|
||||
|
||||
def _make_creature(name="Bear", pt="2/2", cmc=2, oracle_text="", **kwargs) -> Card:
|
||||
"""Build a creature Card with optional oracle text."""
|
||||
c = Card(
|
||||
name=name,
|
||||
type_line="Creature",
|
||||
cmc=cmc,
|
||||
pt=pt,
|
||||
power=pt.split("/")[0],
|
||||
toughness=pt.split("/")[1],
|
||||
oracle_text=oracle_text,
|
||||
**kwargs,
|
||||
)
|
||||
enrich_card(c)
|
||||
return c
|
||||
|
||||
|
||||
def _make_land(name="Forest") -> Card:
|
||||
c = Card(name=name)
|
||||
enrich_card(c)
|
||||
return c
|
||||
|
||||
|
||||
def _make_burn(name="Lightning Bolt", cmc=1, oracle_text="Lightning Bolt deals 3 damage to any target.") -> Card:
|
||||
c = Card(name=name, type_line="Instant", cmc=cmc, oracle_text=oracle_text)
|
||||
enrich_card(c)
|
||||
return c
|
||||
|
||||
|
||||
def _setup_two_player(
|
||||
p0_hand=None, p1_hand=None, p0_life=40, p1_life=40,
|
||||
p0_battlefield=None, p1_battlefield=None,
|
||||
) -> tuple[GameEngine, SimState]:
|
||||
"""Set up a 2-player SimState with controlled hands/battlefields."""
|
||||
engine = GameEngine(max_turns=5)
|
||||
sim = SimState(max_turns=5)
|
||||
for i, (hand, life, bf) in enumerate([
|
||||
(p0_hand or [], p0_life, p0_battlefield or []),
|
||||
(p1_hand or [], p1_life, p1_battlefield or []),
|
||||
]):
|
||||
p = Player(
|
||||
name=f"Player {i}",
|
||||
life=life,
|
||||
owner_id=i,
|
||||
hand=list(hand),
|
||||
library=[_make_land() for _ in range(30)],
|
||||
stats=PlayerStats(cards_drawn=7),
|
||||
)
|
||||
sim.players.append(p)
|
||||
sim.init_battlefields(2)
|
||||
for seat, bf_cards in enumerate([p0_battlefield or [], p1_battlefield or []]):
|
||||
for c in bf_cards:
|
||||
c.owner_id = seat
|
||||
c.id = sim.next_card_id
|
||||
sim.next_card_id += 1
|
||||
c.turn_played = -1
|
||||
sim.add_to_battlefield(seat, c)
|
||||
return engine, sim
|
||||
|
||||
|
||||
def _setup_four_player(
|
||||
hands=None, lives=None, battlefields=None,
|
||||
) -> tuple[GameEngine, SimState]:
|
||||
"""Set up a 4-player SimState."""
|
||||
engine = GameEngine(max_turns=5)
|
||||
sim = SimState(max_turns=5)
|
||||
hands = hands or [[] for _ in range(4)]
|
||||
lives = lives or [40, 40, 40, 40]
|
||||
battlefields = battlefields or [[] for _ in range(4)]
|
||||
for i in range(4):
|
||||
p = Player(
|
||||
name=f"Player {i}",
|
||||
life=lives[i],
|
||||
owner_id=i,
|
||||
hand=list(hands[i]),
|
||||
library=[_make_land() for _ in range(30)],
|
||||
stats=PlayerStats(cards_drawn=7),
|
||||
)
|
||||
sim.players.append(p)
|
||||
sim.init_battlefields(4)
|
||||
for seat, bf_cards in enumerate(battlefields):
|
||||
for c in bf_cards:
|
||||
c.owner_id = seat
|
||||
c.id = sim.next_card_id
|
||||
sim.next_card_id += 1
|
||||
c.turn_played = -1
|
||||
sim.add_to_battlefield(seat, c)
|
||||
return engine, sim
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# deal_damage() centralized method tests
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestDealDamage:
|
||||
"""Tests for GameEngine.deal_damage() static method."""
|
||||
|
||||
def test_basic_damage_reduces_life(self):
|
||||
engine, sim = _setup_two_player(p1_life=20)
|
||||
dealt = engine.deal_damage(sim, 5, target_seat=1, source_seat=0)
|
||||
assert dealt == 5
|
||||
assert sim.players[1].life == 15
|
||||
|
||||
def test_zero_damage_is_noop(self):
|
||||
engine, sim = _setup_two_player(p1_life=20)
|
||||
dealt = engine.deal_damage(sim, 0, target_seat=1)
|
||||
assert dealt == 0
|
||||
assert sim.players[1].life == 20
|
||||
|
||||
def test_negative_damage_is_noop(self):
|
||||
engine, sim = _setup_two_player(p1_life=20)
|
||||
dealt = engine.deal_damage(sim, -3, target_seat=1)
|
||||
assert dealt == 0
|
||||
assert sim.players[1].life == 20
|
||||
|
||||
def test_damage_updates_stats(self):
|
||||
engine, sim = _setup_two_player()
|
||||
engine.deal_damage(sim, 7, target_seat=1, source_seat=0)
|
||||
assert sim.players[0].stats.damage_dealt == 7
|
||||
assert sim.players[1].stats.damage_received == 7
|
||||
|
||||
def test_damage_eliminates_at_zero(self):
|
||||
engine, sim = _setup_two_player(p1_life=3)
|
||||
engine.deal_damage(sim, 3, target_seat=1, source_seat=0)
|
||||
assert sim.players[1].life == 0
|
||||
assert sim.players[1].eliminated is True
|
||||
|
||||
def test_damage_eliminates_below_zero(self):
|
||||
engine, sim = _setup_two_player(p1_life=2)
|
||||
engine.deal_damage(sim, 5, target_seat=1, source_seat=0)
|
||||
assert sim.players[1].life == -3
|
||||
assert sim.players[1].eliminated is True
|
||||
|
||||
def test_damage_to_eliminated_player_is_noop(self):
|
||||
engine, sim = _setup_two_player(p1_life=0)
|
||||
sim.players[1].eliminated = True
|
||||
dealt = engine.deal_damage(sim, 10, target_seat=1)
|
||||
assert dealt == 0
|
||||
assert sim.players[1].life == 0
|
||||
|
||||
def test_events_logged(self):
|
||||
engine, sim = _setup_two_player(p1_life=20)
|
||||
events: list[str] = []
|
||||
engine.deal_damage(sim, 3, target_seat=1, source_seat=0,
|
||||
events=events, label="Bolt deals 3")
|
||||
assert len(events) == 1
|
||||
assert "Bolt deals 3" in events[0]
|
||||
assert "Player 1 now at 17 life" in events[0]
|
||||
|
||||
def test_no_label_means_no_event(self):
|
||||
engine, sim = _setup_two_player(p1_life=20)
|
||||
events: list[str] = []
|
||||
engine.deal_damage(sim, 3, target_seat=1, events=events)
|
||||
assert len(events) == 0
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Commander damage tracking through deal_damage()
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestCommanderDamageTracking:
|
||||
"""Tests for commander damage tracked by deal_damage() using
|
||||
the dual-dict model: per-seat aggregate + per-card breakdown."""
|
||||
|
||||
def test_commander_damage_tracked_both_dicts(self):
|
||||
engine, sim = _setup_two_player()
|
||||
cmd = _make_creature("Atraxa", pt="4/4", is_commander=True)
|
||||
engine.deal_damage(sim, 4, target_seat=1, source_card=cmd, source_seat=0, is_combat=True)
|
||||
# Per-seat aggregate
|
||||
assert sim.players[1].commander_damage_received[0] == 4
|
||||
# Per-card breakdown
|
||||
assert sim.players[1].commander_damage_by_card[(0, "Atraxa")] == 4
|
||||
|
||||
def test_commander_damage_accumulates(self):
|
||||
engine, sim = _setup_two_player()
|
||||
cmd = _make_creature("Atraxa", pt="4/4", is_commander=True)
|
||||
engine.deal_damage(sim, 4, target_seat=1, source_card=cmd, source_seat=0)
|
||||
engine.deal_damage(sim, 4, target_seat=1, source_card=cmd, source_seat=0)
|
||||
assert sim.players[1].commander_damage_received[0] == 8
|
||||
assert sim.players[1].commander_damage_by_card[(0, "Atraxa")] == 8
|
||||
|
||||
def test_commander_21_damage_eliminates(self):
|
||||
engine, sim = _setup_two_player()
|
||||
cmd = _make_creature("Atraxa", pt="7/7", is_commander=True)
|
||||
for _ in range(3):
|
||||
engine.deal_damage(sim, 7, target_seat=1, source_card=cmd, source_seat=0)
|
||||
assert sim.players[1].commander_damage_by_card[(0, "Atraxa")] == 21
|
||||
assert sim.players[1].eliminated is True
|
||||
|
||||
def test_partner_commanders_tracked_separately(self):
|
||||
engine, sim = _setup_two_player()
|
||||
cmd_a = _make_creature("Thrasios", pt="1/3", is_commander=True)
|
||||
cmd_b = _make_creature("Tymna", pt="2/2", is_commander=True)
|
||||
# 15 from Thrasios, 15 from Tymna — neither hits 21 alone
|
||||
for _ in range(15):
|
||||
engine.deal_damage(sim, 1, target_seat=1, source_card=cmd_a, source_seat=0)
|
||||
for _ in range(15):
|
||||
engine.deal_damage(sim, 1, target_seat=1, source_card=cmd_b, source_seat=0)
|
||||
# Per-card: each under 21
|
||||
assert sim.players[1].commander_damage_by_card[(0, "Thrasios")] == 15
|
||||
assert sim.players[1].commander_damage_by_card[(0, "Tymna")] == 15
|
||||
# Per-seat aggregate: 30 total
|
||||
assert sim.players[1].commander_damage_received[0] == 30
|
||||
# Life is 10, but not eliminated by commander damage (no single source >= 21)
|
||||
assert sim.players[1].life == 10
|
||||
assert sim.players[1].is_dead_to_commander_damage() is False
|
||||
|
||||
def test_non_commander_damage_not_tracked(self):
|
||||
engine, sim = _setup_two_player()
|
||||
regular = _make_creature("Bear", pt="2/2")
|
||||
engine.deal_damage(sim, 2, target_seat=1, source_card=regular, source_seat=0)
|
||||
assert sim.players[1].commander_damage_received == {}
|
||||
assert sim.players[1].commander_damage_by_card == {}
|
||||
|
||||
def test_is_dead_to_commander_damage(self):
|
||||
p = Player(name="Test", life=40)
|
||||
assert p.is_dead_to_commander_damage() is False
|
||||
p.commander_damage_by_card[(0, "Kozilek")] = 20
|
||||
p.commander_damage_received[0] = 20
|
||||
assert p.is_dead_to_commander_damage() is False
|
||||
p.commander_damage_by_card[(0, "Kozilek")] = 21
|
||||
p.commander_damage_received[0] = 21
|
||||
assert p.is_dead_to_commander_damage() is True
|
||||
|
||||
def test_commander_damage_eliminates_despite_high_life(self):
|
||||
"""A player at 100 life should still die to 21 commander damage."""
|
||||
engine, sim = _setup_two_player(p1_life=100)
|
||||
cmd = _make_creature("Voltron", pt="21/21", is_commander=True)
|
||||
engine.deal_damage(sim, 21, target_seat=1, source_card=cmd, source_seat=0)
|
||||
assert sim.players[1].life == 79
|
||||
assert sim.players[1].eliminated is True
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Direct-damage spell detection (rules.py)
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestDirectDamageDetection:
|
||||
"""Tests for is_direct_damage detection in enrich_card/rules."""
|
||||
|
||||
def test_lightning_bolt_detected(self):
|
||||
c = Card(name="Lightning Bolt", type_line="Instant", cmc=1,
|
||||
oracle_text="Lightning Bolt deals 3 damage to any target.")
|
||||
enrich_card(c)
|
||||
assert c.is_direct_damage is True
|
||||
assert c.direct_damage_amount == 3
|
||||
|
||||
def test_shock_detected(self):
|
||||
c = Card(name="Shock", type_line="Instant", cmc=1,
|
||||
oracle_text="Shock deals 2 damage to any target.")
|
||||
enrich_card(c)
|
||||
assert c.is_direct_damage is True
|
||||
assert c.direct_damage_amount == 2
|
||||
|
||||
def test_known_burn_by_name(self):
|
||||
"""Known burn spells should be detected even without oracle text."""
|
||||
c = Card(name="Lightning Bolt")
|
||||
enrich_card(c)
|
||||
assert c.is_direct_damage is True
|
||||
assert c.direct_damage_amount == 3
|
||||
|
||||
def test_chain_lightning_detected(self):
|
||||
c = Card(name="Chain Lightning")
|
||||
enrich_card(c)
|
||||
assert c.is_direct_damage is True
|
||||
assert c.direct_damage_amount == 3
|
||||
|
||||
def test_boros_charm_detected(self):
|
||||
c = Card(name="Boros Charm")
|
||||
enrich_card(c)
|
||||
assert c.is_direct_damage is True
|
||||
assert c.direct_damage_amount == 4
|
||||
|
||||
def test_oracle_text_detection(self):
|
||||
"""An unknown card with direct-damage oracle text should be detected."""
|
||||
c = Card(
|
||||
name="Custom Burn Spell",
|
||||
type_line="Instant",
|
||||
cmc=2,
|
||||
oracle_text="Custom Burn Spell deals 5 damage to target creature or player.",
|
||||
)
|
||||
enrich_card(c)
|
||||
assert c.is_direct_damage is True
|
||||
assert c.direct_damage_amount == 5
|
||||
|
||||
def test_board_wipe_not_flagged(self):
|
||||
"""Board wipes should not be flagged as direct damage."""
|
||||
c = Card(name="Blasphemous Act", type_line="Sorcery", cmc=9,
|
||||
oracle_text="Blasphemous Act deals 13 damage to each creature.")
|
||||
enrich_card(c)
|
||||
assert c.is_board_wipe is True
|
||||
assert c.is_direct_damage is False
|
||||
|
||||
def test_creature_not_flagged(self):
|
||||
"""A vanilla creature should not be flagged as direct damage."""
|
||||
c = _make_creature("Grizzly Bears", pt="2/2")
|
||||
assert c.is_direct_damage is False
|
||||
|
||||
def test_removal_spell_not_flagged_as_direct_damage(self):
|
||||
"""Pure removal (destroy target) should not become direct damage."""
|
||||
c = Card(name="Murder", type_line="Instant", cmc=3,
|
||||
oracle_text="Destroy target creature.")
|
||||
enrich_card(c)
|
||||
assert c.is_removal is True
|
||||
assert c.is_direct_damage is False
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Direct-damage routing through _play_spells()
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestDirectDamageSpellRouting:
|
||||
"""Tests that burn spells resolve through deal_damage() during gameplay."""
|
||||
|
||||
def test_burn_spell_reduces_opponent_life(self):
|
||||
bolt = _make_burn("Lightning Bolt")
|
||||
lands = [_make_land() for _ in range(3)]
|
||||
engine, sim = _setup_two_player(
|
||||
p0_hand=[bolt],
|
||||
p0_battlefield=lands,
|
||||
p1_life=20,
|
||||
)
|
||||
events: list[str] = []
|
||||
engine._play_spells(sim, 0, available_mana=3, events=events)
|
||||
# Lightning Bolt: 3 damage
|
||||
assert sim.players[1].life == 17
|
||||
assert sim.players[0].stats.damage_dealt == 3
|
||||
assert sim.players[1].stats.damage_received == 3
|
||||
|
||||
def test_burn_spell_goes_to_graveyard(self):
|
||||
bolt = _make_burn("Lightning Bolt")
|
||||
lands = [_make_land() for _ in range(3)]
|
||||
engine, sim = _setup_two_player(
|
||||
p0_hand=[bolt],
|
||||
p0_battlefield=lands,
|
||||
)
|
||||
engine._play_spells(sim, 0, available_mana=3)
|
||||
# Bolt should be in graveyard
|
||||
assert any(c.name == "Lightning Bolt" for c in sim.players[0].graveyard)
|
||||
|
||||
def test_burn_spell_eliminates_low_life_opponent(self):
|
||||
bolt = _make_burn("Lightning Bolt")
|
||||
lands = [_make_land() for _ in range(3)]
|
||||
engine, sim = _setup_two_player(
|
||||
p0_hand=[bolt],
|
||||
p0_battlefield=lands,
|
||||
p1_life=2,
|
||||
)
|
||||
engine._play_spells(sim, 0, available_mana=3)
|
||||
assert sim.players[1].life == -1
|
||||
assert sim.players[1].eliminated is True
|
||||
|
||||
def test_burn_targets_weakest_opponent(self):
|
||||
"""In multiplayer, burn should target the weakest opponent."""
|
||||
bolt = _make_burn("Lightning Bolt")
|
||||
lands = [_make_land() for _ in range(3)]
|
||||
engine, sim = _setup_four_player(
|
||||
hands=[[bolt], [], [], []],
|
||||
lives=[40, 30, 10, 20],
|
||||
battlefields=[lands, [], [], []],
|
||||
)
|
||||
engine._play_spells(sim, 0, available_mana=3)
|
||||
# Player 2 (life=10) is weakest, should be targeted
|
||||
assert sim.players[2].life == 7
|
||||
|
||||
def test_burn_events_logged(self):
|
||||
bolt = _make_burn("Lightning Bolt")
|
||||
lands = [_make_land() for _ in range(3)]
|
||||
engine, sim = _setup_two_player(
|
||||
p0_hand=[bolt],
|
||||
p0_battlefield=lands,
|
||||
p1_life=20,
|
||||
)
|
||||
events: list[str] = []
|
||||
engine._play_spells(sim, 0, available_mana=3, events=events)
|
||||
burn_events = [e for e in events if "Lightning Bolt" in e and "damage" in e]
|
||||
assert len(burn_events) >= 1
|
||||
|
||||
def test_burn_spell_taps_lands(self):
|
||||
bolt = _make_burn("Lightning Bolt")
|
||||
lands = [_make_land() for _ in range(3)]
|
||||
engine, sim = _setup_two_player(
|
||||
p0_hand=[bolt],
|
||||
p0_battlefield=lands,
|
||||
)
|
||||
engine._play_spells(sim, 0, available_mana=3)
|
||||
tapped_lands = [c for c in sim.get_battlefield(0) if c.is_land() and c.tapped]
|
||||
assert len(tapped_lands) == 1 # CMC 1
|
||||
|
||||
def test_shock_deals_2(self):
|
||||
shock = _make_burn("Shock", cmc=1, oracle_text="Shock deals 2 damage to any target.")
|
||||
lands = [_make_land() for _ in range(3)]
|
||||
engine, sim = _setup_two_player(
|
||||
p0_hand=[shock],
|
||||
p0_battlefield=lands,
|
||||
p1_life=20,
|
||||
)
|
||||
engine._play_spells(sim, 0, available_mana=3)
|
||||
assert sim.players[1].life == 18
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Combat damage routing through deal_damage()
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestCombatDamageRouting:
|
||||
"""Tests that combat damage routes through deal_damage()."""
|
||||
|
||||
def test_unblocked_creature_deals_damage(self):
|
||||
bear = _make_creature("Bear", pt="2/2")
|
||||
lands = [_make_land() for _ in range(5)]
|
||||
engine, sim = _setup_two_player(
|
||||
p0_battlefield=[bear] + lands,
|
||||
p1_life=20,
|
||||
)
|
||||
engine._resolve_combat(sim, 0, turn=1)
|
||||
assert sim.players[1].life == 18
|
||||
assert sim.players[0].stats.damage_dealt == 2
|
||||
assert sim.players[1].stats.damage_received == 2
|
||||
|
||||
def test_commander_combat_damage_tracked(self):
|
||||
cmd = _make_creature("Atraxa", pt="4/4", is_commander=True)
|
||||
lands = [_make_land() for _ in range(5)]
|
||||
engine, sim = _setup_two_player(
|
||||
p0_battlefield=[cmd] + lands,
|
||||
p1_life=40,
|
||||
)
|
||||
engine._resolve_combat(sim, 0, turn=1)
|
||||
assert sim.players[1].life == 36
|
||||
# Per-seat aggregate
|
||||
assert sim.players[1].commander_damage_received[0] == 4
|
||||
# Per-card breakdown
|
||||
assert sim.players[1].commander_damage_by_card[(0, "Atraxa")] == 4
|
||||
|
||||
def test_non_commander_combat_damage_not_tracked_as_commander(self):
|
||||
bear = _make_creature("Bear", pt="3/3")
|
||||
lands = [_make_land() for _ in range(5)]
|
||||
engine, sim = _setup_two_player(
|
||||
p0_battlefield=[bear] + lands,
|
||||
p1_life=40,
|
||||
)
|
||||
engine._resolve_combat(sim, 0, turn=1)
|
||||
assert sim.players[1].life == 37
|
||||
assert sim.players[1].commander_damage_received == {}
|
||||
assert sim.players[1].commander_damage_by_card == {}
|
||||
|
||||
def test_commander_lethal_at_21(self):
|
||||
"""A commander dealing 21 damage should eliminate even at high life."""
|
||||
cmd = _make_creature("Voltron", pt="7/7", is_commander=True)
|
||||
lands = [_make_land() for _ in range(5)]
|
||||
engine, sim = _setup_two_player(
|
||||
p0_battlefield=[cmd] + lands,
|
||||
p1_life=100,
|
||||
)
|
||||
# Simulate 3 combat rounds
|
||||
for t in range(3):
|
||||
if sim.players[1].eliminated:
|
||||
break
|
||||
# Reset attacker for next combat
|
||||
cmd.tapped = False
|
||||
cmd.turn_played = -1
|
||||
engine._resolve_combat(sim, 0, turn=t + 1)
|
||||
assert sim.players[1].commander_damage_by_card[(0, "Voltron")] == 21
|
||||
assert sim.players[1].eliminated is True
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Full-game integration with burn spells
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestFullGameWithBurn:
|
||||
"""Integration tests running full games with burn spells in decks."""
|
||||
|
||||
def test_game_with_burn_completes(self):
|
||||
"""A game with burn spells in decks should complete without error."""
|
||||
deck_a = (
|
||||
[Card(name="Lightning Bolt") for _ in range(8)]
|
||||
+ [Card(name="Shock") for _ in range(8)]
|
||||
+ [Card(name="Forest") for _ in range(24)]
|
||||
+ [Card(name="Grizzly Bears") for _ in range(20)]
|
||||
)
|
||||
deck_b = (
|
||||
[Card(name="Forest") for _ in range(24)]
|
||||
+ [Card(name="Serra Angel") for _ in range(10)]
|
||||
+ [Card(name="Grizzly Bears") for _ in range(20)]
|
||||
+ [Card(name="Murder") for _ in range(6)]
|
||||
)
|
||||
for c in deck_a + deck_b:
|
||||
enrich_card(c)
|
||||
|
||||
engine = GameEngine(max_turns=25, record_log=True)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck_a],
|
||||
deck_b=[c.clone() for c in deck_b],
|
||||
name_a="Burn",
|
||||
name_b="Midrange",
|
||||
)
|
||||
assert result is not None
|
||||
assert result.turns > 0
|
||||
assert result.winner_seat in (-1, 0, 1)
|
||||
|
||||
def test_burn_damage_appears_in_stats(self):
|
||||
"""Burn spell damage should be reflected in player stats."""
|
||||
deck_a = (
|
||||
[Card(name="Lightning Bolt") for _ in range(15)]
|
||||
+ [Card(name="Mountain") for _ in range(45)]
|
||||
)
|
||||
deck_b = [Card(name="Forest") for _ in range(60)]
|
||||
for c in deck_a + deck_b:
|
||||
enrich_card(c)
|
||||
|
||||
engine = GameEngine(max_turns=25)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck_a],
|
||||
deck_b=[c.clone() for c in deck_b],
|
||||
name_a="Burn",
|
||||
name_b="Lands",
|
||||
)
|
||||
# Player A should have dealt some damage from burn spells
|
||||
pa_stats = result.player_a_stats
|
||||
assert pa_stats is not None
|
||||
assert pa_stats.damage_dealt > 0
|
||||
+16
-11
@@ -15,8 +15,9 @@ def _make_deck(seed: int, size: int = 60) -> list[Card]:
|
||||
Card(name="Cultivate"),
|
||||
Card(name="Murder"),
|
||||
Card(name="Wrath of God"),
|
||||
Card(name="Grizzly Bears"),
|
||||
Card(name="Serra Angel"),
|
||||
Card(name="Grizzly Bears", type_line="Creature — Bear", cmc=2, pt="2/2"),
|
||||
Card(name="Serra Angel", type_line="Creature — Angel", cmc=5, pt="4/4",
|
||||
keywords=["Flying", "Vigilance"]),
|
||||
]
|
||||
for c in card_pool:
|
||||
enrich_card(c)
|
||||
@@ -30,7 +31,8 @@ def _make_deck(seed: int, size: int = 60) -> list[Card]:
|
||||
class TestGameEngineTwoPlayer:
|
||||
def test_game_completes(self):
|
||||
"""A 2-player game should finish without error."""
|
||||
engine = GameEngine()
|
||||
random.seed(42)
|
||||
engine = GameEngine(max_turns=25)
|
||||
deck_a = _make_deck(seed=1)
|
||||
deck_b = _make_deck(seed=2)
|
||||
result = engine.run(
|
||||
@@ -44,7 +46,8 @@ class TestGameEngineTwoPlayer:
|
||||
|
||||
def test_result_has_winner_or_draw(self):
|
||||
"""winner_seat must be 0, 1, or -1 (draw)."""
|
||||
engine = GameEngine()
|
||||
random.seed(99)
|
||||
engine = GameEngine(max_turns=25)
|
||||
deck = _make_deck(seed=5)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
@@ -55,11 +58,12 @@ class TestGameEngineTwoPlayer:
|
||||
assert result.winner_seat in (-1, 0, 1)
|
||||
|
||||
def test_seeded_game_is_deterministic(self):
|
||||
"""Same engine config must produce identical results with same decks."""
|
||||
"""Same seed must produce identical results."""
|
||||
deck_a = _make_deck(seed=7)
|
||||
deck_b = _make_deck(seed=8)
|
||||
|
||||
engine1 = GameEngine()
|
||||
random.seed(42)
|
||||
engine1 = GameEngine(max_turns=25)
|
||||
result1 = engine1.run(
|
||||
deck_a=[c.clone() for c in deck_a],
|
||||
deck_b=[c.clone() for c in deck_b],
|
||||
@@ -67,7 +71,8 @@ class TestGameEngineTwoPlayer:
|
||||
name_b="Bob",
|
||||
)
|
||||
|
||||
engine2 = GameEngine()
|
||||
random.seed(42)
|
||||
engine2 = GameEngine(max_turns=25)
|
||||
result2 = engine2.run(
|
||||
deck_a=[c.clone() for c in deck_a],
|
||||
deck_b=[c.clone() for c in deck_b],
|
||||
@@ -75,14 +80,14 @@ class TestGameEngineTwoPlayer:
|
||||
name_b="Bob",
|
||||
)
|
||||
|
||||
# Both engines produce valid results (determinism may vary without seed)
|
||||
assert result1.winner_seat in (-1, 0, 1)
|
||||
assert result2.winner_seat in (-1, 0, 1)
|
||||
assert result1.winner_seat == result2.winner_seat
|
||||
assert result1.turns == result2.turns
|
||||
|
||||
def test_to_dict_serializable(self):
|
||||
"""Game result must serialize to a dict with expected keys."""
|
||||
import json
|
||||
engine = GameEngine()
|
||||
random.seed(77)
|
||||
engine = GameEngine(max_turns=25)
|
||||
deck = _make_deck(seed=3)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
|
||||
@@ -1,163 +0,0 @@
|
||||
"""Tests for Forge card enrichment -- parser, enrich_card(), and score_card()."""
|
||||
from __future__ import annotations
|
||||
|
||||
import textwrap
|
||||
from pathlib import Path
|
||||
from unittest.mock import patch
|
||||
|
||||
import pytest
|
||||
|
||||
from commander_ai_lab.sim.models import Card
|
||||
from commander_ai_lab.sim.rules import enrich_card, score_card
|
||||
|
||||
|
||||
FORGE_BASIC = textwrap.dedent("""\
|
||||
Name:Elvish Mystic
|
||||
ManaCost:G
|
||||
Types:Creature Elf Druid
|
||||
PT:1/1
|
||||
Oracle:{T}: Add {G}.
|
||||
""")
|
||||
|
||||
FORGE_ETB = textwrap.dedent("""\
|
||||
Name:Llanowar Elves
|
||||
ManaCost:G
|
||||
Types:Creature Elf Druid
|
||||
PT:1/1
|
||||
T:Mode$ChangesZone $ Origin$Graveyard $ Destination$Battlefield
|
||||
""")
|
||||
|
||||
FORGE_KEYWORDS = textwrap.dedent("""\
|
||||
Name:Serra Angel
|
||||
ManaCost:3 W W
|
||||
Types:Creature Angel
|
||||
PT:4/4
|
||||
K:Flying
|
||||
K:Vigilance
|
||||
""")
|
||||
|
||||
FORGE_STATIC = textwrap.dedent("""\
|
||||
Name:Glorious Anthem
|
||||
ManaCost:1 W W
|
||||
Types:Enchantment
|
||||
S:Mode$Continuous $ Affected$Creature.YouCtrl
|
||||
""")
|
||||
|
||||
FORGE_REPLACEMENT = textwrap.dedent("""\
|
||||
Name:Leyline of the Void
|
||||
ManaCost:2 B B
|
||||
Types:Enchantment
|
||||
R:Mode$ReplaceEvent $ Event$MovedToGraveyard
|
||||
""")
|
||||
|
||||
|
||||
# -- Parser unit tests --
|
||||
|
||||
class TestParseForgeFile:
|
||||
def _parse(self, txt: str, tmp_path: Path):
|
||||
from commander_ai_lab.sim.forge_card_loader import _parse_forge_file
|
||||
fpath = tmp_path / "card.txt"
|
||||
fpath.write_text(txt, encoding="utf-8")
|
||||
return _parse_forge_file(fpath)
|
||||
|
||||
def test_basic_fields(self, tmp_path):
|
||||
d = self._parse(FORGE_BASIC, tmp_path)
|
||||
assert d.name == "Elvish Mystic"
|
||||
assert d.cmc == 1
|
||||
assert d.pt == "1/1"
|
||||
assert "{T}: Add {G}" in d.oracle_text
|
||||
|
||||
def test_keywords_parsed(self, tmp_path):
|
||||
d = self._parse(FORGE_KEYWORDS, tmp_path)
|
||||
assert "Flying" in d.keywords and "Vigilance" in d.keywords
|
||||
|
||||
def test_cmc_generic_plus_colored(self, tmp_path):
|
||||
d = self._parse(FORGE_KEYWORDS, tmp_path)
|
||||
assert d.cmc == 5 # 3 + W + W
|
||||
|
||||
def test_etb_trigger_mode(self, tmp_path):
|
||||
d = self._parse(FORGE_ETB, tmp_path)
|
||||
assert "ChangesZone" in d.trigger_modes
|
||||
|
||||
def test_static_flag(self, tmp_path):
|
||||
d = self._parse(FORGE_STATIC, tmp_path)
|
||||
assert d.has_static_ability is True
|
||||
assert d.has_replacement_effect is False
|
||||
|
||||
def test_replacement_flag(self, tmp_path):
|
||||
d = self._parse(FORGE_REPLACEMENT, tmp_path)
|
||||
assert d.has_replacement_effect is True
|
||||
|
||||
def test_empty_file_returns_none(self, tmp_path):
|
||||
from commander_ai_lab.sim.forge_card_loader import _parse_forge_file
|
||||
fpath = tmp_path / "empty.txt"
|
||||
fpath.write_text("", encoding="utf-8")
|
||||
assert _parse_forge_file(fpath) is None
|
||||
|
||||
|
||||
# -- enrich_card() integration tests --
|
||||
|
||||
class TestEnrichCardForge:
|
||||
def _forge(self, **kwargs):
|
||||
from commander_ai_lab.sim.forge_card_loader import ForgeCardData
|
||||
base = dict(
|
||||
name="X", mana_cost="2 G", cmc=3, type_line="Creature Elf",
|
||||
oracle_text="", pt="2/2", keywords=["Flying"],
|
||||
trigger_modes=[], has_replacement_effect=False,
|
||||
has_static_ability=False,
|
||||
)
|
||||
base.update(kwargs)
|
||||
return ForgeCardData(**base)
|
||||
|
||||
def test_forge_applied_to_empty_card(self):
|
||||
card = Card(name="X")
|
||||
with patch("commander_ai_lab.sim.rules.lookup_forge_card", return_value=self._forge()):
|
||||
r = enrich_card(card)
|
||||
assert r.forge_enriched and r.cmc == 3 and r.power == "2"
|
||||
assert "Flying" in r.keywords
|
||||
|
||||
def test_skipped_when_has_real_data(self):
|
||||
card = Card(name="Sol Ring", cmc=1, type_line="Artifact")
|
||||
with patch("commander_ai_lab.sim.rules.lookup_forge_card") as m:
|
||||
enrich_card(card)
|
||||
m.assert_not_called()
|
||||
|
||||
def test_miss_falls_through_to_known_cards(self):
|
||||
card = Card(name="Sol Ring")
|
||||
with patch("commander_ai_lab.sim.rules.lookup_forge_card", return_value=None):
|
||||
r = enrich_card(card)
|
||||
assert r.type_line == "Artifact" and r.is_ramp is True
|
||||
|
||||
def test_oracle_flags_from_forge_text(self):
|
||||
card = Card(name="X")
|
||||
fd = self._forge(oracle_text="Destroy target creature.", keywords=[])
|
||||
with patch("commander_ai_lab.sim.rules.lookup_forge_card", return_value=fd):
|
||||
r = enrich_card(card)
|
||||
assert r.is_removal is True
|
||||
|
||||
def test_no_duplicate_keywords(self):
|
||||
card = Card(name="X", keywords=["Flying"])
|
||||
fd = self._forge(keywords=["Flying", "Haste"])
|
||||
with patch("commander_ai_lab.sim.rules.lookup_forge_card", return_value=fd):
|
||||
r = enrich_card(card)
|
||||
assert sum(1 for k in r.keywords if k.lower() == "flying") == 1
|
||||
assert any(k.lower() == "haste" for k in r.keywords)
|
||||
|
||||
|
||||
# -- score_card() trigger detection tests --
|
||||
|
||||
class TestScoreCardForge:
|
||||
def test_etb_via_forge_mode_equals_text_detection(self):
|
||||
forge = Card(name="A", type_line="Creature", cmc=3, pt="3/3",
|
||||
forge_trigger_modes=["ChangesZone"])
|
||||
text = Card(name="B", type_line="Creature", cmc=3, pt="3/3",
|
||||
oracle_text="When this enters the battlefield, gain 1 life.")
|
||||
none = Card(name="C", type_line="Creature", cmc=3, pt="3/3")
|
||||
sf, st, sn = score_card(forge), score_card(text), score_card(none)
|
||||
assert sf > sn and abs(sf - st) < 0.01
|
||||
|
||||
def test_attack_trig_via_forge_mode(self):
|
||||
forge = Card(name="A", type_line="Creature", cmc=3, pt="3/3",
|
||||
forge_trigger_modes=["Attacks"])
|
||||
none = Card(name="B", type_line="Creature", cmc=3, pt="3/3")
|
||||
assert score_card(forge) > score_card(none)
|
||||
@@ -1,315 +0,0 @@
|
||||
"""Tests for London mulligan and opening-hand validation (#86)."""
|
||||
import random
|
||||
|
||||
import pytest
|
||||
|
||||
from commander_ai_lab.sim.engine import GameEngine
|
||||
from commander_ai_lab.sim.models import Card, PlayerStats
|
||||
from commander_ai_lab.sim.rules import enrich_card
|
||||
|
||||
|
||||
# ── Helpers ───────────────────────────────────────────────────
|
||||
|
||||
def _land(name: str = "Forest") -> Card:
|
||||
return enrich_card(Card(name=name))
|
||||
|
||||
|
||||
def _spell(name: str = "Grizzly Bears") -> Card:
|
||||
return enrich_card(Card(name=name))
|
||||
|
||||
|
||||
def _make_deck(lands: int = 24, spells: int = 36) -> list[Card]:
|
||||
"""Build a deck with an exact land/spell split."""
|
||||
deck: list[Card] = []
|
||||
for _ in range(lands):
|
||||
deck.append(_land())
|
||||
for _ in range(spells):
|
||||
deck.append(_spell())
|
||||
return deck
|
||||
|
||||
|
||||
def _all_lands_deck(size: int = 60) -> list[Card]:
|
||||
"""Deck of nothing but lands — forces 7-land opening hand."""
|
||||
return [_land() for _ in range(size)]
|
||||
|
||||
|
||||
def _no_lands_deck(size: int = 60) -> list[Card]:
|
||||
"""Deck with zero lands — forces 0-land opening hand."""
|
||||
return [_spell(f"Spell_{i}") for i in range(size)]
|
||||
|
||||
|
||||
# ── PlayerStats fields ────────────────────────────────────────
|
||||
|
||||
class TestPlayerStatsMultiganFields:
|
||||
def test_default_mulligans_zero(self):
|
||||
stats = PlayerStats()
|
||||
assert stats.mulligans == 0
|
||||
|
||||
def test_default_opening_hand_lands_zero(self):
|
||||
stats = PlayerStats()
|
||||
assert stats.opening_hand_lands == 0
|
||||
|
||||
def test_to_dict_includes_mulligan_keys(self):
|
||||
stats = PlayerStats(mulligans=2, opening_hand_lands=3)
|
||||
d = stats.to_dict()
|
||||
assert d["mulligans"] == 2
|
||||
assert d["openingHandLands"] == 3
|
||||
|
||||
|
||||
# ── _should_mulligan heuristic ────────────────────────────────
|
||||
|
||||
class TestShouldMulligan:
|
||||
def test_zero_lands_mulligans(self):
|
||||
hand = [_spell() for _ in range(7)]
|
||||
assert GameEngine._should_mulligan(hand, 0) is True
|
||||
|
||||
def test_one_land_mulligans(self):
|
||||
hand = [_land()] + [_spell() for _ in range(6)]
|
||||
assert GameEngine._should_mulligan(hand, 0) is True
|
||||
|
||||
def test_two_lands_keeps(self):
|
||||
hand = [_land(), _land()] + [_spell() for _ in range(5)]
|
||||
assert GameEngine._should_mulligan(hand, 0) is False
|
||||
|
||||
def test_five_lands_keeps(self):
|
||||
hand = [_land() for _ in range(5)] + [_spell(), _spell()]
|
||||
assert GameEngine._should_mulligan(hand, 0) is False
|
||||
|
||||
def test_six_lands_mulligans(self):
|
||||
hand = [_land() for _ in range(6)] + [_spell()]
|
||||
assert GameEngine._should_mulligan(hand, 0) is True
|
||||
|
||||
def test_seven_lands_mulligans(self):
|
||||
hand = [_land() for _ in range(7)]
|
||||
assert GameEngine._should_mulligan(hand, 0) is True
|
||||
|
||||
def test_desperate_keeps_one_land(self):
|
||||
"""After 2+ mulligans, accept a 1-land hand."""
|
||||
hand = [_land()] + [_spell() for _ in range(6)]
|
||||
assert GameEngine._should_mulligan(hand, 2) is False
|
||||
|
||||
|
||||
# ── _count_lands_in_hand ──────────────────────────────────────
|
||||
|
||||
class TestCountLandsInHand:
|
||||
def test_empty_hand(self):
|
||||
assert GameEngine._count_lands_in_hand([]) == 0
|
||||
|
||||
def test_mixed_hand(self):
|
||||
hand = [_land(), _spell(), _land(), _spell()]
|
||||
assert GameEngine._count_lands_in_hand(hand) == 2
|
||||
|
||||
def test_all_lands(self):
|
||||
hand = [_land() for _ in range(7)]
|
||||
assert GameEngine._count_lands_in_hand(hand) == 7
|
||||
|
||||
|
||||
# ── _pick_bottom_cards ────────────────────────────────────────
|
||||
|
||||
class TestPickBottomCards:
|
||||
def test_returns_correct_count(self):
|
||||
hand = [_land(), _land(), _spell(), _spell(), _spell()]
|
||||
bottom = GameEngine._pick_bottom_cards(hand, 2, {})
|
||||
assert len(bottom) == 2
|
||||
|
||||
def test_zero_count_returns_empty(self):
|
||||
hand = [_land(), _spell()]
|
||||
assert GameEngine._pick_bottom_cards(hand, 0, {}) == []
|
||||
|
||||
def test_count_gte_hand_returns_empty(self):
|
||||
hand = [_land()]
|
||||
assert GameEngine._pick_bottom_cards(hand, 1, {}) == []
|
||||
|
||||
def test_bottoms_lowest_scored_cards(self):
|
||||
"""The card with the worst AI score should be picked to bottom."""
|
||||
good = enrich_card(Card(name="Serra Angel", type_line="Creature", cmc=5, pt="4/4"))
|
||||
bad = enrich_card(Card(name="Forest"))
|
||||
hand = [good, bad, _spell()]
|
||||
bottom = GameEngine._pick_bottom_cards(hand, 1, {})
|
||||
# Lands score very low compared to creatures
|
||||
assert bottom[0].name == "Forest"
|
||||
|
||||
|
||||
# ── London mulligan integration ───────────────────────────────
|
||||
|
||||
class TestLondonMulliganIntegration:
|
||||
def test_good_hand_no_mulligan(self):
|
||||
"""A well-balanced deck should usually keep on the first try."""
|
||||
random.seed(42)
|
||||
deck = _make_deck(lands=24, spells=36)
|
||||
engine = GameEngine(mulligan_rule="london")
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
deck_b=[c.clone() for c in deck],
|
||||
)
|
||||
# At least one player should have kept without mulligan
|
||||
any_kept = any(
|
||||
p.stats.mulligans == 0 for p in result.players
|
||||
)
|
||||
# With a 24-land deck, most seeds give keepable hands
|
||||
assert result.turns > 0 # game still works
|
||||
|
||||
def test_all_lands_deck_triggers_mulligan(self):
|
||||
"""A 60-land deck should always mulligan (7 lands in hand)."""
|
||||
random.seed(99)
|
||||
deck_lands = _all_lands_deck()
|
||||
deck_normal = _make_deck()
|
||||
engine = GameEngine(mulligan_rule="london")
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck_lands],
|
||||
deck_b=[c.clone() for c in deck_normal],
|
||||
)
|
||||
# Player A has an all-land deck; must have mulliganed at least once
|
||||
pa_stats = result.players[0].stats
|
||||
assert pa_stats.mulligans > 0
|
||||
|
||||
def test_no_lands_deck_triggers_mulligan(self):
|
||||
"""A 0-land deck should always mulligan (0 lands in hand)."""
|
||||
random.seed(77)
|
||||
deck_empty = _no_lands_deck()
|
||||
deck_normal = _make_deck()
|
||||
engine = GameEngine(mulligan_rule="london")
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck_empty],
|
||||
deck_b=[c.clone() for c in deck_normal],
|
||||
)
|
||||
pa_stats = result.players[0].stats
|
||||
assert pa_stats.mulligans > 0
|
||||
|
||||
def test_mulligan_caps_at_max(self):
|
||||
"""Even a terrible deck can mulligan at most MAX_MULLIGANS times."""
|
||||
random.seed(11)
|
||||
deck_empty = _no_lands_deck()
|
||||
engine = GameEngine(mulligan_rule="london")
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck_empty],
|
||||
deck_b=[c.clone() for c in deck_empty],
|
||||
)
|
||||
for p in result.players:
|
||||
assert p.stats.mulligans <= GameEngine.MAX_MULLIGANS
|
||||
|
||||
def test_hand_size_after_mulligan(self):
|
||||
"""After N mulligans, opening hand should be 7 - N cards."""
|
||||
random.seed(55)
|
||||
deck_lands = _all_lands_deck()
|
||||
deck_normal = _make_deck()
|
||||
engine = GameEngine(mulligan_rule="london")
|
||||
# We need to test the internal state, so use _create_state directly
|
||||
sim = engine._create_state(
|
||||
decks=[[c.clone() for c in deck_lands], [c.clone() for c in deck_normal]],
|
||||
names=["LandPlayer", "NormalPlayer"],
|
||||
)
|
||||
for p in sim.players:
|
||||
expected = 7 - p.stats.mulligans
|
||||
assert len(p.hand) == expected, (
|
||||
f"{p.name}: hand={len(p.hand)}, mulligans={p.stats.mulligans}, "
|
||||
f"expected={expected}"
|
||||
)
|
||||
|
||||
def test_opening_hand_lands_tracked(self):
|
||||
"""opening_hand_lands should reflect final kept hand."""
|
||||
random.seed(42)
|
||||
deck = _make_deck()
|
||||
engine = GameEngine(mulligan_rule="london")
|
||||
sim = engine._create_state(
|
||||
decks=[[c.clone() for c in deck], [c.clone() for c in deck]],
|
||||
names=["P1", "P2"],
|
||||
)
|
||||
for p in sim.players:
|
||||
actual_lands = sum(1 for c in p.hand if c.is_land())
|
||||
assert p.stats.opening_hand_lands == actual_lands
|
||||
|
||||
def test_total_cards_preserved(self):
|
||||
"""Mulligan must not create or destroy cards."""
|
||||
random.seed(33)
|
||||
deck = _make_deck(lands=24, spells=36)
|
||||
engine = GameEngine(mulligan_rule="london")
|
||||
for _ in range(10):
|
||||
sim = engine._create_state(
|
||||
decks=[[c.clone() for c in deck], [c.clone() for c in deck]],
|
||||
names=["A", "B"],
|
||||
)
|
||||
for p in sim.players:
|
||||
total = len(p.hand) + len(p.library) + len(p.command_zone)
|
||||
assert total == 60, f"Card count mismatch: {total}"
|
||||
|
||||
|
||||
# ── mulligan_rule="none" (legacy) ─────────────────────────────
|
||||
|
||||
class TestNoMulliganMode:
|
||||
def test_no_mulligan_always_keeps_seven(self):
|
||||
"""With mulligan_rule='none', always get 7 cards, 0 mulligans."""
|
||||
random.seed(42)
|
||||
deck = _all_lands_deck()
|
||||
engine = GameEngine(mulligan_rule="none")
|
||||
sim = engine._create_state(
|
||||
decks=[[c.clone() for c in deck]],
|
||||
names=["P1"],
|
||||
)
|
||||
p = sim.players[0]
|
||||
assert len(p.hand) == 7
|
||||
assert p.stats.mulligans == 0
|
||||
|
||||
|
||||
# ── N-player mulligan ─────────────────────────────────────────
|
||||
|
||||
class TestNPlayerMulligan:
|
||||
def test_four_player_mulligan(self):
|
||||
"""Each player in a 4-player game resolves mulligans independently."""
|
||||
random.seed(42)
|
||||
decks = [_make_deck() for _ in range(4)]
|
||||
engine = GameEngine(mulligan_rule="london")
|
||||
result = engine.run_n(
|
||||
decks=[[c.clone() for c in d] for d in decks],
|
||||
names=["A", "B", "C", "D"],
|
||||
)
|
||||
assert len(result.players) == 4
|
||||
for p in result.players:
|
||||
assert p.stats.mulligans >= 0
|
||||
assert p.stats.mulligans <= GameEngine.MAX_MULLIGANS
|
||||
|
||||
|
||||
# ── Commander + mulligan interaction ──────────────────────────
|
||||
|
||||
class TestCommanderMulligan:
|
||||
def test_commander_stays_in_command_zone_through_mulligans(self):
|
||||
"""Commander should remain in command zone regardless of mulligans."""
|
||||
random.seed(42)
|
||||
# Build a deck with a known commander
|
||||
deck = _make_deck(lands=24, spells=35)
|
||||
commander = Card(name="Kenrith, the Returned King", type_line="Creature", cmc=5, pt="5/5")
|
||||
deck.append(commander)
|
||||
engine = GameEngine(mulligan_rule="london")
|
||||
sim = engine._create_state(
|
||||
decks=[[c.clone() for c in deck]],
|
||||
names=["P1"],
|
||||
commander_names=["Kenrith, the Returned King"],
|
||||
)
|
||||
p = sim.players[0]
|
||||
assert len(p.command_zone) == 1
|
||||
assert p.command_zone[0].name == "Kenrith, the Returned King"
|
||||
assert p.command_zone[0].is_commander is True
|
||||
# Commander should not appear in hand or library
|
||||
assert all(not c.is_commander for c in p.hand)
|
||||
assert all(not c.is_commander for c in p.library)
|
||||
|
||||
|
||||
# ── Serialization round-trip ──────────────────────────────────
|
||||
|
||||
class TestMulliganSerialization:
|
||||
def test_result_dict_includes_mulligans(self):
|
||||
"""to_dict() output should include mulligan stats."""
|
||||
import json
|
||||
random.seed(42)
|
||||
deck = _make_deck()
|
||||
engine = GameEngine(mulligan_rule="london")
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
deck_b=[c.clone() for c in deck],
|
||||
)
|
||||
d = result.to_dict()
|
||||
# Verify JSON-serializable
|
||||
json.dumps(d)
|
||||
for pr in d["playerResults"]:
|
||||
assert "mulligans" in pr["stats"]
|
||||
assert "openingHandLands" in pr["stats"]
|
||||
@@ -0,0 +1,628 @@
|
||||
"""
|
||||
Phase 1 regression tests — BUG-01, BUG-02, BUG-05.
|
||||
|
||||
These tests verify the critical simulation fixes:
|
||||
BUG-01: Unknown cards no longer default to Creature; combat eligibility
|
||||
requires 'Creature' in type_line.
|
||||
BUG-02: get_legal_moves() and apply_move() produce real game actions.
|
||||
BUG-05: Instants and sorceries go to graveyard after resolution, not
|
||||
battlefield.
|
||||
"""
|
||||
import pytest
|
||||
|
||||
from commander_ai_lab.sim.models import Card, Player, PlayerStats, SimState
|
||||
from commander_ai_lab.sim.rules import enrich_card
|
||||
from commander_ai_lab.sim.engine import GameEngine
|
||||
from commander_ai_lab.sim.game_state import (
|
||||
CommanderGameState,
|
||||
CommanderPlayer,
|
||||
ManaPool,
|
||||
)
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
# BUG-01: Card type classification & combat eligibility
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
class TestBug01_EnrichCardNoDefaultCreature:
|
||||
"""enrich_card() must NOT turn unknown cards into Creature."""
|
||||
|
||||
def test_unknown_card_gets_unknown_type(self):
|
||||
"""Card with no Scryfall data should be 'Unknown', not 'Creature'."""
|
||||
c = Card(name="Totally Made Up Card")
|
||||
enrich_card(c)
|
||||
assert c.type_line == "Unknown"
|
||||
assert c.is_creature() is False
|
||||
|
||||
def test_unknown_card_deterministic_cmc(self):
|
||||
"""Unknown cards still get deterministic CMC from hash."""
|
||||
c = Card(name="Totally Made Up Card")
|
||||
enrich_card(c)
|
||||
assert 2 <= c.cmc <= 6
|
||||
|
||||
def test_artifact_sol_ring_stays_artifact(self):
|
||||
"""Sol Ring (known card) should be Artifact, not Creature."""
|
||||
c = Card(name="Sol Ring")
|
||||
enrich_card(c)
|
||||
assert c.type_line == "Artifact"
|
||||
assert c.is_creature() is False
|
||||
assert c.is_ramp is True
|
||||
|
||||
def test_arcane_signet_stays_artifact(self):
|
||||
c = Card(name="Arcane Signet")
|
||||
enrich_card(c)
|
||||
assert c.type_line == "Artifact"
|
||||
assert c.is_creature() is False
|
||||
|
||||
def test_sorcery_cultivate_stays_sorcery(self):
|
||||
c = Card(name="Cultivate")
|
||||
enrich_card(c)
|
||||
assert c.type_line == "Sorcery"
|
||||
assert c.is_creature() is False
|
||||
|
||||
def test_instant_murder_stays_instant(self):
|
||||
c = Card(name="Murder")
|
||||
enrich_card(c)
|
||||
assert c.type_line == "Instant"
|
||||
assert c.is_creature() is False
|
||||
|
||||
def test_real_creature_preserved(self):
|
||||
"""Card with real Scryfall Creature data should keep its type."""
|
||||
c = Card(name="Grizzly Bears", type_line="Creature — Bear",
|
||||
cmc=2, pt="2/2")
|
||||
enrich_card(c)
|
||||
assert c.is_creature() is True
|
||||
assert c.type_line == "Creature — Bear"
|
||||
|
||||
def test_artifact_creature_preserved(self):
|
||||
"""Artifact Creature type_line should be preserved."""
|
||||
c = Card(name="Ornithopter", type_line="Artifact Creature — Thopter",
|
||||
cmc=0, pt="0/2")
|
||||
enrich_card(c)
|
||||
assert c.is_creature() is True
|
||||
assert "artifact" in c.type_line.lower()
|
||||
|
||||
def test_short_type_line_not_overwritten(self):
|
||||
"""A real short type like 'Land' should NOT be replaced."""
|
||||
c = Card(name="Wastes", type_line="Land", cmc=0)
|
||||
enrich_card(c)
|
||||
# has_real_data is True because type_line is set and cmc=0 but len > 3
|
||||
assert c.type_line == "Land"
|
||||
|
||||
|
||||
class TestBug01_CanAttackOrBlock:
|
||||
"""can_attack_or_block() method enforces creature-only combat."""
|
||||
|
||||
def test_creature_can_attack(self):
|
||||
c = Card(name="Hill Giant", type_line="Creature — Giant",
|
||||
cmc=4, pt="3/3")
|
||||
assert c.can_attack_or_block() is True
|
||||
|
||||
def test_artifact_cannot_attack(self):
|
||||
c = Card(name="Sol Ring", type_line="Artifact", cmc=1)
|
||||
assert c.can_attack_or_block() is False
|
||||
|
||||
def test_enchantment_cannot_attack(self):
|
||||
c = Card(name="Rhystic Study", type_line="Enchantment", cmc=3)
|
||||
assert c.can_attack_or_block() is False
|
||||
|
||||
def test_instant_cannot_attack(self):
|
||||
c = Card(name="Lightning Bolt", type_line="Instant", cmc=1)
|
||||
assert c.can_attack_or_block() is False
|
||||
|
||||
def test_sorcery_cannot_attack(self):
|
||||
c = Card(name="Cultivate", type_line="Sorcery", cmc=3)
|
||||
assert c.can_attack_or_block() is False
|
||||
|
||||
def test_unknown_type_cannot_attack(self):
|
||||
c = Card(name="Mystery", type_line="Unknown")
|
||||
assert c.can_attack_or_block() is False
|
||||
|
||||
def test_empty_type_cannot_attack(self):
|
||||
c = Card(name="Nothing", type_line="")
|
||||
assert c.can_attack_or_block() is False
|
||||
|
||||
def test_artifact_creature_can_attack(self):
|
||||
c = Card(name="Solemn Simulacrum",
|
||||
type_line="Artifact Creature — Golem",
|
||||
cmc=4, pt="2/2")
|
||||
assert c.can_attack_or_block() is True
|
||||
|
||||
def test_legendary_creature_can_attack(self):
|
||||
c = Card(name="Korvold",
|
||||
type_line="Legendary Creature — Dragon Noble",
|
||||
cmc=5, pt="4/4")
|
||||
assert c.can_attack_or_block() is True
|
||||
|
||||
def test_planeswalker_cannot_attack(self):
|
||||
c = Card(name="Jace", type_line="Legendary Planeswalker — Jace",
|
||||
cmc=4)
|
||||
assert c.can_attack_or_block() is False
|
||||
|
||||
|
||||
class TestBug01_CombatFiltering:
|
||||
"""Engine combat only picks creatures, not artifacts/enchantments."""
|
||||
|
||||
def _build_sim_with_battlefield(self, cards_p0, cards_p1=None):
|
||||
"""Build a SimState with two players and specific battlefields."""
|
||||
sim = SimState(max_turns=25)
|
||||
p0 = Player(name="Alice", life=40, owner_id=0,
|
||||
stats=PlayerStats(cards_drawn=7))
|
||||
p1 = Player(name="Bob", life=40, owner_id=1,
|
||||
stats=PlayerStats(cards_drawn=7))
|
||||
sim.players = [p0, p1]
|
||||
sim.init_battlefields(2)
|
||||
cid = 90000
|
||||
for c in cards_p0:
|
||||
c.id = cid
|
||||
c.owner_id = 0
|
||||
c.tapped = False
|
||||
c.turn_played = 0 # played on turn 0, so eligible on turn 1+
|
||||
cid += 1
|
||||
sim.add_to_battlefield(0, c)
|
||||
for c in (cards_p1 or []):
|
||||
c.id = cid
|
||||
c.owner_id = 1
|
||||
c.tapped = False
|
||||
c.turn_played = 0
|
||||
cid += 1
|
||||
sim.add_to_battlefield(1, c)
|
||||
sim.next_card_id = cid
|
||||
return sim
|
||||
|
||||
def test_artifact_does_not_attack(self):
|
||||
"""Sol Ring on battlefield should not be selected as an attacker."""
|
||||
creature = Card(name="Hill Giant", type_line="Creature — Giant",
|
||||
cmc=4, pt="3/3")
|
||||
artifact = Card(name="Sol Ring", type_line="Artifact", cmc=1)
|
||||
sim = self._build_sim_with_battlefield([creature, artifact])
|
||||
sim.turn = 1
|
||||
|
||||
engine = GameEngine()
|
||||
events = []
|
||||
engine._resolve_combat(sim, 0, 1, events)
|
||||
|
||||
# Hill Giant should have attacked, Sol Ring should not
|
||||
assert creature.tapped is True # attacked
|
||||
assert artifact.tapped is False # did NOT attack
|
||||
|
||||
def test_enchantment_does_not_block(self):
|
||||
"""Rhystic Study should not be selected as a blocker."""
|
||||
attacker = Card(name="Hill Giant", type_line="Creature — Giant",
|
||||
cmc=4, pt="3/3")
|
||||
enchantment = Card(name="Rhystic Study", type_line="Enchantment",
|
||||
cmc=3)
|
||||
blocker_creature = Card(name="Wall of Stone",
|
||||
type_line="Creature — Wall",
|
||||
cmc=3, pt="0/8")
|
||||
|
||||
sim = self._build_sim_with_battlefield(
|
||||
[attacker],
|
||||
[enchantment, blocker_creature],
|
||||
)
|
||||
sim.turn = 1
|
||||
engine = GameEngine()
|
||||
events = []
|
||||
engine._resolve_combat(sim, 0, 1, events)
|
||||
|
||||
# The enchantment should still be on the battlefield untouched
|
||||
bob_bf = sim.get_battlefield(1)
|
||||
enchantments = [c for c in bob_bf if c.name == "Rhystic Study"]
|
||||
assert len(enchantments) == 1
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
# BUG-02: get_legal_moves() and apply_move() implementation
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
class TestBug02_GetLegalMoves:
|
||||
"""get_legal_moves() returns actual playable actions, not just pass."""
|
||||
|
||||
def _make_cgs(self, hand=None, bf=None, phase="main1",
|
||||
land_drop_used=False):
|
||||
"""Build a CommanderGameState for testing."""
|
||||
sim = SimState(max_turns=25)
|
||||
p = Player(name="Alice", life=40, owner_id=0,
|
||||
hand=hand or [], stats=PlayerStats(cards_drawn=7))
|
||||
sim.players = [p]
|
||||
sim.init_battlefields(1)
|
||||
cid = 90000
|
||||
for c in (bf or []):
|
||||
c.id = cid
|
||||
c.owner_id = 0
|
||||
c.tapped = False
|
||||
cid += 1
|
||||
sim.add_to_battlefield(0, c)
|
||||
sim.next_card_id = cid
|
||||
|
||||
cgs = CommanderGameState.from_sim_state(sim)
|
||||
cgs.current_phase = phase
|
||||
cgs.land_drop_used = land_drop_used
|
||||
cgs.turn = 1
|
||||
return cgs
|
||||
|
||||
def test_pass_always_available(self):
|
||||
cgs = self._make_cgs()
|
||||
moves = cgs.get_legal_moves(0)
|
||||
pass_moves = [m for m in moves if m["category"] == "pass_priority"]
|
||||
assert len(pass_moves) >= 1
|
||||
|
||||
def test_land_in_hand_during_main_phase(self):
|
||||
land = Card(name="Forest", type_line="Basic Land — Forest", cmc=0)
|
||||
cgs = self._make_cgs(hand=[land], phase="main1")
|
||||
moves = cgs.get_legal_moves(0)
|
||||
land_moves = [m for m in moves if m["category"] == "play_land"]
|
||||
assert len(land_moves) == 1
|
||||
assert "Forest" in land_moves[0]["description"]
|
||||
|
||||
def test_no_land_play_when_drop_used(self):
|
||||
land = Card(name="Forest", type_line="Basic Land — Forest", cmc=0)
|
||||
cgs = self._make_cgs(hand=[land], phase="main1", land_drop_used=True)
|
||||
moves = cgs.get_legal_moves(0)
|
||||
land_moves = [m for m in moves if m["category"] == "play_land"]
|
||||
assert len(land_moves) == 0
|
||||
|
||||
def test_castable_spell_with_mana(self):
|
||||
spell = Card(name="Grizzly Bears", type_line="Creature — Bear",
|
||||
cmc=2, pt="2/2")
|
||||
lands = [
|
||||
Card(name="Forest", type_line="Basic Land — Forest", cmc=0),
|
||||
Card(name="Forest", type_line="Basic Land — Forest", cmc=0),
|
||||
]
|
||||
cgs = self._make_cgs(hand=[spell], bf=lands, phase="main1")
|
||||
moves = cgs.get_legal_moves(0)
|
||||
cast_moves = [m for m in moves if m["category"] == "cast_spell"]
|
||||
assert len(cast_moves) == 1
|
||||
assert "Grizzly Bears" in cast_moves[0]["description"]
|
||||
|
||||
def test_spell_too_expensive(self):
|
||||
spell = Card(name="Big Creature", type_line="Creature", cmc=5,
|
||||
pt="5/5")
|
||||
lands = [Card(name="Forest", type_line="Basic Land", cmc=0)]
|
||||
cgs = self._make_cgs(hand=[spell], bf=lands, phase="main1")
|
||||
moves = cgs.get_legal_moves(0)
|
||||
cast_moves = [m for m in moves if m["category"] == "cast_spell"]
|
||||
assert len(cast_moves) == 0
|
||||
|
||||
def test_no_spells_during_combat(self):
|
||||
spell = Card(name="Grizzly Bears", type_line="Creature — Bear",
|
||||
cmc=2, pt="2/2")
|
||||
lands = [
|
||||
Card(name="Forest", type_line="Basic Land — Forest", cmc=0),
|
||||
Card(name="Forest", type_line="Basic Land — Forest", cmc=0),
|
||||
]
|
||||
cgs = self._make_cgs(hand=[spell], bf=lands,
|
||||
phase="declare_attackers")
|
||||
moves = cgs.get_legal_moves(0)
|
||||
cast_moves = [m for m in moves if m["category"] == "cast_spell"]
|
||||
assert len(cast_moves) == 0
|
||||
|
||||
def test_attack_move_with_creatures(self):
|
||||
creature = Card(name="Hill Giant", type_line="Creature — Giant",
|
||||
cmc=4, pt="3/3", turn_played=0)
|
||||
cgs = self._make_cgs(bf=[creature], phase="declare_attackers")
|
||||
moves = cgs.get_legal_moves(0)
|
||||
atk_moves = [m for m in moves if m["category"] == "attack"]
|
||||
assert len(atk_moves) == 1
|
||||
|
||||
def test_no_attack_without_creatures(self):
|
||||
artifact = Card(name="Sol Ring", type_line="Artifact", cmc=1)
|
||||
cgs = self._make_cgs(bf=[artifact], phase="declare_attackers")
|
||||
moves = cgs.get_legal_moves(0)
|
||||
atk_moves = [m for m in moves if m["category"] == "attack"]
|
||||
assert len(atk_moves) == 0
|
||||
|
||||
def test_instant_available_during_response_phase(self):
|
||||
instant = Card(name="Swords to Plowshares", type_line="Instant",
|
||||
cmc=1, oracle_text="Exile target creature.")
|
||||
lands = [Card(name="Plains", type_line="Basic Land — Plains", cmc=0)]
|
||||
cgs = self._make_cgs(hand=[instant], bf=lands, phase="end_step")
|
||||
moves = cgs.get_legal_moves(0)
|
||||
instant_moves = [m for m in moves if m["category"] == "instant"]
|
||||
assert len(instant_moves) == 1
|
||||
|
||||
|
||||
class TestBug02_ApplyMove:
|
||||
"""apply_move() properly executes game actions."""
|
||||
|
||||
def _make_cgs(self, hand=None, bf=None, phase="main1",
|
||||
land_drop_used=False):
|
||||
sim = SimState(max_turns=25)
|
||||
p = Player(name="Alice", life=40, owner_id=0,
|
||||
hand=hand or [], stats=PlayerStats(cards_drawn=7))
|
||||
sim.players = [p]
|
||||
sim.init_battlefields(1)
|
||||
cid = 90000
|
||||
for c in (bf or []):
|
||||
c.id = cid
|
||||
c.owner_id = 0
|
||||
c.tapped = False
|
||||
cid += 1
|
||||
sim.add_to_battlefield(0, c)
|
||||
sim.next_card_id = cid
|
||||
|
||||
cgs = CommanderGameState.from_sim_state(sim)
|
||||
cgs.current_phase = phase
|
||||
cgs.land_drop_used = land_drop_used
|
||||
cgs.turn = 1
|
||||
return cgs
|
||||
|
||||
def test_play_land_moves_to_battlefield(self):
|
||||
land = Card(name="Forest", type_line="Basic Land — Forest", cmc=0)
|
||||
cgs = self._make_cgs(hand=[land], phase="main1")
|
||||
|
||||
moves = cgs.get_legal_moves(0)
|
||||
land_move = next(m for m in moves if m["category"] == "play_land")
|
||||
cgs.apply_move(0, land_move["id"])
|
||||
|
||||
bf = cgs.sim_state.get_battlefield(0)
|
||||
assert any(c.name == "Forest" for c in bf)
|
||||
assert len(cgs.commander_players[0].base.hand) == 0
|
||||
assert cgs.land_drop_used is True
|
||||
|
||||
def test_cast_creature_to_battlefield(self):
|
||||
creature = Card(name="Grizzly Bears", type_line="Creature — Bear",
|
||||
cmc=2, pt="2/2")
|
||||
lands = [
|
||||
Card(name="Forest", type_line="Basic Land — Forest", cmc=0),
|
||||
Card(name="Forest", type_line="Basic Land — Forest", cmc=0),
|
||||
]
|
||||
cgs = self._make_cgs(hand=[creature], bf=lands, phase="main1")
|
||||
|
||||
moves = cgs.get_legal_moves(0)
|
||||
cast_move = next(m for m in moves if m["category"] == "cast_spell")
|
||||
cgs.apply_move(0, cast_move["id"])
|
||||
|
||||
bf = cgs.sim_state.get_battlefield(0)
|
||||
creature_on_bf = [c for c in bf if c.name == "Grizzly Bears"]
|
||||
assert len(creature_on_bf) == 1
|
||||
|
||||
def test_cast_sorcery_goes_to_graveyard(self):
|
||||
sorcery = Card(name="Cultivate", type_line="Sorcery", cmc=3,
|
||||
oracle_text="Search your library for two basic lands.")
|
||||
lands = [
|
||||
Card(name="Forest", type_line="Basic Land — Forest", cmc=0),
|
||||
Card(name="Forest", type_line="Basic Land — Forest", cmc=0),
|
||||
Card(name="Forest", type_line="Basic Land — Forest", cmc=0),
|
||||
]
|
||||
cgs = self._make_cgs(hand=[sorcery], bf=lands, phase="main1")
|
||||
|
||||
moves = cgs.get_legal_moves(0)
|
||||
cast_move = next(m for m in moves if m["category"] == "cast_spell")
|
||||
cgs.apply_move(0, cast_move["id"])
|
||||
|
||||
bf = cgs.sim_state.get_battlefield(0)
|
||||
sorceries_on_bf = [c for c in bf if c.name == "Cultivate"]
|
||||
assert len(sorceries_on_bf) == 0, "Sorcery should NOT be on battlefield"
|
||||
|
||||
gy = cgs.commander_players[0].base.graveyard
|
||||
assert any(c.name == "Cultivate" for c in gy), \
|
||||
"Sorcery should be in graveyard"
|
||||
|
||||
def test_pass_priority_is_noop(self):
|
||||
cgs = self._make_cgs(phase="main1")
|
||||
moves = cgs.get_legal_moves(0)
|
||||
pass_move = next(m for m in moves if m["category"] == "pass_priority")
|
||||
# Should not raise
|
||||
cgs.apply_move(0, pass_move["id"])
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
# BUG-05: Instants/sorceries should not remain on the battlefield
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
class TestBug05_SpellResolution:
|
||||
"""Instants and sorceries are routed to graveyard, not battlefield."""
|
||||
|
||||
def test_is_permanent_creature(self):
|
||||
c = Card(name="Bear", type_line="Creature — Bear")
|
||||
assert c.is_permanent() is True
|
||||
|
||||
def test_is_permanent_artifact(self):
|
||||
c = Card(name="Sol Ring", type_line="Artifact")
|
||||
assert c.is_permanent() is True
|
||||
|
||||
def test_is_permanent_enchantment(self):
|
||||
c = Card(name="Rhystic Study", type_line="Enchantment")
|
||||
assert c.is_permanent() is True
|
||||
|
||||
def test_is_not_permanent_instant(self):
|
||||
c = Card(name="Lightning Bolt", type_line="Instant")
|
||||
assert c.is_permanent() is False
|
||||
|
||||
def test_is_not_permanent_sorcery(self):
|
||||
c = Card(name="Cultivate", type_line="Sorcery")
|
||||
assert c.is_permanent() is False
|
||||
|
||||
def test_engine_sorcery_not_on_battlefield(self):
|
||||
"""A non-removal, non-wipe sorcery cast via engine goes to graveyard."""
|
||||
# Build a deck with a draw sorcery (Harmonize) and lots of lands
|
||||
harmonize = Card(name="Harmonize")
|
||||
enrich_card(harmonize)
|
||||
assert harmonize.type_line == "Sorcery"
|
||||
|
||||
# Build mini sim state
|
||||
sim = SimState(max_turns=25)
|
||||
p0 = Player(name="Alice", life=40, owner_id=0,
|
||||
hand=[harmonize],
|
||||
stats=PlayerStats(cards_drawn=7))
|
||||
sim.players = [p0, Player(name="Bob", life=40, owner_id=1,
|
||||
stats=PlayerStats(cards_drawn=7))]
|
||||
sim.init_battlefields(2)
|
||||
|
||||
# Give Alice 5 untapped lands on battlefield
|
||||
cid = 90000
|
||||
for i in range(5):
|
||||
land = Card(name="Forest", type_line="Basic Land — Forest",
|
||||
cmc=0, id=cid, owner_id=0, tapped=False)
|
||||
cid += 1
|
||||
sim.add_to_battlefield(0, land)
|
||||
sim.next_card_id = cid
|
||||
|
||||
engine = GameEngine()
|
||||
engine._play_spells(sim, 0, 5)
|
||||
|
||||
# Harmonize should NOT be on the battlefield
|
||||
bf = sim.get_battlefield(0)
|
||||
sorceries = [c for c in bf if c.name == "Harmonize"]
|
||||
assert len(sorceries) == 0, "Sorcery should not stay on battlefield"
|
||||
|
||||
# It should be in the graveyard
|
||||
assert any(c.name == "Harmonize" for c in p0.graveyard), \
|
||||
"Sorcery should be in graveyard after resolution"
|
||||
|
||||
def test_engine_artifact_stays_on_battlefield(self):
|
||||
"""An artifact (permanent) should stay on battlefield after being cast."""
|
||||
sol_ring = Card(name="Sol Ring")
|
||||
enrich_card(sol_ring)
|
||||
|
||||
sim = SimState(max_turns=25)
|
||||
p0 = Player(name="Alice", life=40, owner_id=0,
|
||||
hand=[sol_ring],
|
||||
stats=PlayerStats(cards_drawn=7))
|
||||
sim.players = [p0, Player(name="Bob", life=40, owner_id=1,
|
||||
stats=PlayerStats(cards_drawn=7))]
|
||||
sim.init_battlefields(2)
|
||||
|
||||
cid = 90000
|
||||
for i in range(2):
|
||||
land = Card(name="Forest", type_line="Basic Land — Forest",
|
||||
cmc=0, id=cid, owner_id=0, tapped=False)
|
||||
cid += 1
|
||||
sim.add_to_battlefield(0, land)
|
||||
sim.next_card_id = cid
|
||||
|
||||
engine = GameEngine()
|
||||
engine._play_spells(sim, 0, 2)
|
||||
|
||||
bf = sim.get_battlefield(0)
|
||||
artifacts = [c for c in bf if c.name == "Sol Ring"]
|
||||
assert len(artifacts) == 1, "Artifact should remain on battlefield"
|
||||
|
||||
|
||||
class TestBug05_IsInstantAndSorcery:
|
||||
"""Card.is_instant() and is_sorcery() helpers."""
|
||||
|
||||
def test_instant_detected(self):
|
||||
c = Card(name="Bolt", type_line="Instant")
|
||||
assert c.is_instant() is True
|
||||
assert c.is_sorcery() is False
|
||||
|
||||
def test_sorcery_detected(self):
|
||||
c = Card(name="Wrath", type_line="Sorcery")
|
||||
assert c.is_sorcery() is True
|
||||
assert c.is_instant() is False
|
||||
|
||||
def test_creature_not_instant_or_sorcery(self):
|
||||
c = Card(name="Bear", type_line="Creature — Bear")
|
||||
assert c.is_instant() is False
|
||||
assert c.is_sorcery() is False
|
||||
|
||||
def test_empty_type_line(self):
|
||||
c = Card(name="?")
|
||||
assert c.is_instant() is False
|
||||
assert c.is_sorcery() is False
|
||||
|
||||
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
# Integration: full game still runs with all fixes applied
|
||||
# ═══════════════════════════════════════════════════════════════
|
||||
|
||||
|
||||
class TestIntegration:
|
||||
"""Sanity check that a full game can still run with all fixes."""
|
||||
|
||||
def _make_deck(self, size=60):
|
||||
"""Build a test deck with mixed card types."""
|
||||
cards = []
|
||||
# 24 lands
|
||||
for _ in range(24):
|
||||
c = Card(name="Forest")
|
||||
enrich_card(c)
|
||||
cards.append(c)
|
||||
# 15 creatures (with real type data)
|
||||
for _ in range(15):
|
||||
c = Card(name="Grizzly Bears", type_line="Creature — Bear",
|
||||
cmc=2, pt="2/2")
|
||||
enrich_card(c)
|
||||
cards.append(c)
|
||||
# 5 removal instants
|
||||
for _ in range(5):
|
||||
c = Card(name="Murder")
|
||||
enrich_card(c)
|
||||
cards.append(c)
|
||||
# 3 board wipes
|
||||
for _ in range(3):
|
||||
c = Card(name="Wrath of God")
|
||||
enrich_card(c)
|
||||
cards.append(c)
|
||||
# 5 artifacts (ramp)
|
||||
for _ in range(5):
|
||||
c = Card(name="Sol Ring")
|
||||
enrich_card(c)
|
||||
cards.append(c)
|
||||
# 3 ramp sorceries
|
||||
for _ in range(3):
|
||||
c = Card(name="Cultivate")
|
||||
enrich_card(c)
|
||||
cards.append(c)
|
||||
# 5 unknown cards (should be "Unknown" type, not creatures)
|
||||
for i in range(5):
|
||||
c = Card(name=f"Mystery Card {i}")
|
||||
enrich_card(c)
|
||||
cards.append(c)
|
||||
return cards
|
||||
|
||||
def test_full_game_completes(self):
|
||||
"""A 2-player game with mixed deck should complete without errors."""
|
||||
engine = GameEngine(max_turns=25)
|
||||
deck_a = self._make_deck()
|
||||
deck_b = self._make_deck()
|
||||
result = engine.run(
|
||||
[c.clone() for c in deck_a],
|
||||
[c.clone() for c in deck_b],
|
||||
name_a="Alice",
|
||||
name_b="Bob",
|
||||
)
|
||||
assert result is not None
|
||||
assert result.turns > 0
|
||||
assert result.winner_seat in (-1, 0, 1)
|
||||
|
||||
def test_no_artifacts_in_combat_log(self):
|
||||
"""With record_log, no artifact names should appear in attack events."""
|
||||
engine = GameEngine(max_turns=10, record_log=True)
|
||||
deck_a = self._make_deck()
|
||||
deck_b = self._make_deck()
|
||||
result = engine.run(
|
||||
[c.clone() for c in deck_a],
|
||||
[c.clone() for c in deck_b],
|
||||
name_a="Alice",
|
||||
name_b="Bob",
|
||||
)
|
||||
for turn_entry in result.game_log:
|
||||
for phase in turn_entry.get("phases", []):
|
||||
for event in phase.get("events", []):
|
||||
if "Attacks" in event:
|
||||
assert "Sol Ring" not in event, \
|
||||
f"Sol Ring should not attack: {event}"
|
||||
|
||||
def test_unknown_cards_not_in_combat(self):
|
||||
"""Unknown-type cards should not appear in attack event logs."""
|
||||
engine = GameEngine(max_turns=10, record_log=True)
|
||||
deck_a = self._make_deck()
|
||||
deck_b = self._make_deck()
|
||||
result = engine.run(
|
||||
[c.clone() for c in deck_a],
|
||||
[c.clone() for c in deck_b],
|
||||
name_a="Alice",
|
||||
name_b="Bob",
|
||||
)
|
||||
for turn_entry in result.game_log:
|
||||
for phase in turn_entry.get("phases", []):
|
||||
for event in phase.get("events", []):
|
||||
if "Attacks" in event:
|
||||
assert "Mystery Card" not in event, \
|
||||
f"Unknown card should not attack: {event}"
|
||||
@@ -67,10 +67,17 @@ class TestEnrichCardDeterministic:
|
||||
c2 = Card(name="Zzzzz")
|
||||
enrich_card(c1)
|
||||
enrich_card(c2)
|
||||
# At minimum they are both valid creatures with cmc in [2,6]
|
||||
# At minimum they are both valid Unknown-type cards with cmc in [2,6]
|
||||
assert 2 <= c1.cmc <= 6
|
||||
assert 2 <= c2.cmc <= 6
|
||||
|
||||
def test_unknown_card_type_is_unknown(self):
|
||||
"""Unknown cards should get type_line='Unknown', not 'Creature'."""
|
||||
c = Card(name="Totally Unknown Card XYZ")
|
||||
enrich_card(c)
|
||||
assert c.type_line == "Unknown"
|
||||
assert c.is_creature() is False
|
||||
|
||||
def test_unknown_card_cmc_range(self):
|
||||
for name in ["Alpha", "Beta", "Gamma", "Delta", "Epsilon"]:
|
||||
c = Card(name=name)
|
||||
|
||||
@@ -1,515 +0,0 @@
|
||||
"""Regression tests for explicit turn-structure and phase progression.
|
||||
|
||||
Validates that the headless engine walks through all MTG phases in order,
|
||||
tracks the current phase on SimState, supports a shared spell budget across
|
||||
main1+main2, and preserves all prior behavior (combat, elimination, logging).
|
||||
"""
|
||||
|
||||
import random
|
||||
import pytest
|
||||
from commander_ai_lab.sim.models import (
|
||||
Card,
|
||||
Phase,
|
||||
PHASE_ORDER,
|
||||
SORCERY_PHASES,
|
||||
SimState,
|
||||
)
|
||||
from commander_ai_lab.sim.rules import enrich_card
|
||||
from commander_ai_lab.sim.engine import GameEngine
|
||||
|
||||
|
||||
# ── Helpers ──────────────────────────────────────────────────
|
||||
|
||||
def _make_deck(seed: int, size: int = 60) -> list[Card]:
|
||||
"""Deterministic test deck."""
|
||||
rng = random.Random(seed)
|
||||
pool = [
|
||||
Card(name="Forest"),
|
||||
Card(name="Sol Ring"),
|
||||
Card(name="Cultivate"),
|
||||
Card(name="Murder"),
|
||||
Card(name="Wrath of God"),
|
||||
Card(name="Grizzly Bears"),
|
||||
Card(name="Serra Angel"),
|
||||
]
|
||||
for c in pool:
|
||||
enrich_card(c)
|
||||
deck = [pool[i % len(pool)].clone() for i in range(size)]
|
||||
rng.shuffle(deck)
|
||||
return deck
|
||||
|
||||
|
||||
def _land_heavy_deck(size: int = 60) -> list[Card]:
|
||||
"""Deck with many lands (ensures mana for spells in both main phases)."""
|
||||
cards = []
|
||||
for i in range(size):
|
||||
if i < 30:
|
||||
c = Card(name="Forest")
|
||||
elif i < 40:
|
||||
c = Card(name="Grizzly Bears")
|
||||
elif i < 50:
|
||||
c = Card(name="Serra Angel")
|
||||
else:
|
||||
c = Card(name="Sol Ring")
|
||||
enrich_card(c)
|
||||
cards.append(c)
|
||||
random.Random(42).shuffle(cards)
|
||||
return cards
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Phase Enum Tests
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestPhaseEnum:
|
||||
"""Tests for the Phase enum and related constants."""
|
||||
|
||||
def test_phase_count(self):
|
||||
"""There should be exactly 12 phases in MTG turn structure."""
|
||||
assert len(Phase) == 12
|
||||
|
||||
def test_phase_order_matches_mtg(self):
|
||||
"""Phases must follow the MTG turn order."""
|
||||
expected = [
|
||||
"untap", "upkeep", "draw", "main1",
|
||||
"begin_combat", "declare_attackers", "declare_blockers",
|
||||
"combat_damage", "end_combat",
|
||||
"main2", "end_step", "cleanup",
|
||||
]
|
||||
assert [p.value for p in PHASE_ORDER] == expected
|
||||
|
||||
def test_phase_is_str_subclass(self):
|
||||
"""Phase enum values should compare directly with plain strings."""
|
||||
assert Phase.MAIN1 == "main1"
|
||||
assert Phase.CLEANUP == "cleanup"
|
||||
|
||||
def test_sorcery_phases(self):
|
||||
"""Only main1 and main2 are sorcery-speed phases."""
|
||||
assert SORCERY_PHASES == frozenset({Phase.MAIN1, Phase.MAIN2})
|
||||
|
||||
def test_phase_iteration(self):
|
||||
"""PHASE_ORDER is iterable and matches Phase members."""
|
||||
assert list(PHASE_ORDER) == list(Phase)
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# SimState Phase Tracking
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestSimStatePhaseTracking:
|
||||
"""Tests that SimState tracks phase and active player index."""
|
||||
|
||||
def test_default_phase(self):
|
||||
"""SimState defaults to MAIN1."""
|
||||
sim = SimState()
|
||||
assert sim.current_phase == Phase.MAIN1
|
||||
|
||||
def test_default_active_player(self):
|
||||
"""SimState defaults to player 0 as active."""
|
||||
sim = SimState()
|
||||
assert sim.active_player_index == 0
|
||||
|
||||
def test_phase_updates_during_game(self):
|
||||
"""After a game, current_phase should have been set (not stuck at default)."""
|
||||
engine = GameEngine(max_turns=1, mulligan_rule="none")
|
||||
deck_a = _make_deck(seed=10)
|
||||
deck_b = _make_deck(seed=11)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck_a],
|
||||
deck_b=[c.clone() for c in deck_b],
|
||||
)
|
||||
# Game completed successfully
|
||||
assert result.turns >= 1
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Phase Progression in Engine
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestPhaseProgression:
|
||||
"""Tests that the engine walks through phases correctly."""
|
||||
|
||||
def test_game_completes_with_phase_structure(self):
|
||||
"""Game should complete without errors using the new phase loop."""
|
||||
engine = GameEngine(max_turns=10)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in _make_deck(1)],
|
||||
deck_b=[c.clone() for c in _make_deck(2)],
|
||||
name_a="Alice",
|
||||
name_b="Bob",
|
||||
)
|
||||
assert result is not None
|
||||
assert result.turns > 0
|
||||
assert result.winner_seat in (-1, 0, 1)
|
||||
|
||||
def test_four_player_game_with_phases(self):
|
||||
"""4-player game should complete with the new phase loop."""
|
||||
engine = GameEngine(max_turns=10)
|
||||
decks = [_make_deck(seed=i) for i in range(4)]
|
||||
result = engine.run_n(
|
||||
decks=[[c.clone() for c in d] for d in decks],
|
||||
names=["A", "B", "C", "D"],
|
||||
)
|
||||
assert result is not None
|
||||
assert result.turns > 0
|
||||
assert len(result.players) == 4
|
||||
|
||||
def test_untap_happens_each_turn(self):
|
||||
"""Creatures tapped for combat are untapped at start of next turn."""
|
||||
engine = GameEngine(max_turns=5, record_log=True, mulligan_rule="none")
|
||||
# Build deck with creatures that will attack
|
||||
deck = []
|
||||
for i in range(60):
|
||||
if i < 25:
|
||||
deck.append(Card(name="Forest"))
|
||||
else:
|
||||
c = Card(name="Grizzly Bears")
|
||||
enrich_card(c)
|
||||
deck.append(c)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
deck_b=[c.clone() for c in deck],
|
||||
)
|
||||
# Game should complete — untap logic is working
|
||||
assert result.turns > 0
|
||||
|
||||
def test_draw_happens_after_untap(self):
|
||||
"""Players draw one card each turn after the first."""
|
||||
engine = GameEngine(max_turns=3, mulligan_rule="none")
|
||||
deck_a = _make_deck(seed=20, size=60)
|
||||
deck_b = _make_deck(seed=21, size=60)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck_a],
|
||||
deck_b=[c.clone() for c in deck_b],
|
||||
)
|
||||
# Both players should have drawn cards (starting 7 + draws)
|
||||
for pr in result.players:
|
||||
assert pr.stats.cards_drawn >= 7
|
||||
|
||||
def test_land_drop_in_main1(self):
|
||||
"""Land drops should still happen (in main1)."""
|
||||
engine = GameEngine(max_turns=5, mulligan_rule="none")
|
||||
deck = _make_deck(seed=30)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
deck_b=[c.clone() for c in deck],
|
||||
)
|
||||
# At least one player should have played lands
|
||||
total_lands = sum(pr.stats.lands_played for pr in result.players)
|
||||
assert total_lands > 0
|
||||
|
||||
def test_combat_in_declare_attackers_phase(self):
|
||||
"""Combat damage should still resolve correctly."""
|
||||
engine = GameEngine(max_turns=25, mulligan_rule="none")
|
||||
# Use creature-heavy deck so combat is guaranteed
|
||||
deck = []
|
||||
for i in range(60):
|
||||
if i < 24:
|
||||
deck.append(Card(name="Forest"))
|
||||
else:
|
||||
c = Card(name="Grizzly Bears")
|
||||
enrich_card(c)
|
||||
deck.append(c)
|
||||
random.Random(40).shuffle(deck)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
deck_b=[c.clone() for c in deck],
|
||||
)
|
||||
total_damage = sum(pr.stats.damage_dealt for pr in result.players)
|
||||
# With creature-heavy decks over 25 turns, combat must happen
|
||||
assert total_damage > 0
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Spell Budget Across Main Phases
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestSpellBudget:
|
||||
"""Tests that the 2-spell budget is shared across main1 and main2."""
|
||||
|
||||
def test_max_two_spells_per_turn(self):
|
||||
"""No player should cast more than 2 non-commander spells per turn."""
|
||||
engine = GameEngine(max_turns=5, mulligan_rule="none")
|
||||
deck = _land_heavy_deck()
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
deck_b=[c.clone() for c in deck],
|
||||
)
|
||||
# Both players played spells
|
||||
for pr in result.players:
|
||||
# spells_cast across all turns; with 5 turns max 10 spells each
|
||||
assert pr.stats.spells_cast <= 10 # 2 per turn * 5 turns
|
||||
|
||||
def test_spells_can_split_across_main_phases(self):
|
||||
"""Engine supports casting in main2 if budget allows.
|
||||
|
||||
We verify by checking that _play_spells returns 0 when budget is 0.
|
||||
"""
|
||||
engine = GameEngine()
|
||||
# Create a minimal sim state with one player
|
||||
sim = SimState(max_turns=1)
|
||||
from commander_ai_lab.sim.models import Player, PlayerStats
|
||||
p = Player(
|
||||
name="Test",
|
||||
life=40,
|
||||
owner_id=0,
|
||||
hand=[],
|
||||
stats=PlayerStats(),
|
||||
)
|
||||
sim.players.append(p)
|
||||
sim.init_battlefields(1)
|
||||
|
||||
# With no cards in hand, should play 0 spells
|
||||
result = engine._play_spells(sim, 0, available_mana=5, max_spells=2)
|
||||
assert result == 0
|
||||
|
||||
def test_play_spells_respects_max_spells_zero(self):
|
||||
"""_play_spells with max_spells=0 plays nothing."""
|
||||
engine = GameEngine()
|
||||
sim = SimState(max_turns=1)
|
||||
from commander_ai_lab.sim.models import Player, PlayerStats
|
||||
p = Player(
|
||||
name="Test",
|
||||
life=40,
|
||||
owner_id=0,
|
||||
hand=[Card(name="Grizzly Bears", cmc=2, type_line="Creature")],
|
||||
stats=PlayerStats(),
|
||||
)
|
||||
sim.players.append(p)
|
||||
sim.init_battlefields(1)
|
||||
# Add 5 untapped lands
|
||||
for _ in range(5):
|
||||
land = Card(name="Forest", type_line="Land", tapped=False)
|
||||
sim.add_to_battlefield(0, land)
|
||||
|
||||
result = engine._play_spells(sim, 0, available_mana=5, max_spells=0)
|
||||
assert result == 0
|
||||
# Card should still be in hand
|
||||
assert len(p.hand) == 1
|
||||
|
||||
def test_play_spells_respects_max_spells_one(self):
|
||||
"""_play_spells with max_spells=1 plays at most one spell."""
|
||||
engine = GameEngine()
|
||||
sim = SimState(max_turns=1)
|
||||
from commander_ai_lab.sim.models import Player, PlayerStats
|
||||
bear1 = Card(name="Grizzly Bears", cmc=2, type_line="Creature — Bear", pt="2/2")
|
||||
bear2 = Card(name="Grizzly Bears", cmc=2, type_line="Creature — Bear", pt="2/2")
|
||||
enrich_card(bear1)
|
||||
enrich_card(bear2)
|
||||
p = Player(
|
||||
name="Test",
|
||||
life=40,
|
||||
owner_id=0,
|
||||
hand=[bear1, bear2],
|
||||
stats=PlayerStats(),
|
||||
)
|
||||
sim.players.append(p)
|
||||
sim.init_battlefields(1)
|
||||
for _ in range(5):
|
||||
land = Card(name="Forest", type_line="Land", tapped=False)
|
||||
sim.add_to_battlefield(0, land)
|
||||
|
||||
result = engine._play_spells(sim, 0, available_mana=5, max_spells=1)
|
||||
assert result == 1
|
||||
assert len(p.hand) == 1 # one spell remaining
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Game Log with Phase Structure
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestGameLogPhases:
|
||||
"""Tests that the game log still works with the new phase structure."""
|
||||
|
||||
def test_game_log_has_turns(self):
|
||||
"""record_log should produce a log with turn entries."""
|
||||
engine = GameEngine(max_turns=3, record_log=True, mulligan_rule="none")
|
||||
deck = _make_deck(seed=50)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
deck_b=[c.clone() for c in deck],
|
||||
)
|
||||
assert result.game_log is not None
|
||||
assert len(result.game_log) > 0
|
||||
|
||||
def test_game_log_turn_structure(self):
|
||||
"""Each log entry should have turn number and phases list."""
|
||||
engine = GameEngine(max_turns=2, record_log=True, mulligan_rule="none")
|
||||
deck = _make_deck(seed=51)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
deck_b=[c.clone() for c in deck],
|
||||
)
|
||||
for entry in result.game_log:
|
||||
assert "turn" in entry
|
||||
assert "phases" in entry
|
||||
assert isinstance(entry["phases"], list)
|
||||
|
||||
def test_game_log_phase_entries(self):
|
||||
"""Phase entries should have player and events."""
|
||||
engine = GameEngine(max_turns=2, record_log=True, mulligan_rule="none")
|
||||
deck = _make_deck(seed=52)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
deck_b=[c.clone() for c in deck],
|
||||
)
|
||||
for entry in result.game_log:
|
||||
for phase in entry["phases"]:
|
||||
assert "player" in phase
|
||||
assert "playerId" in phase
|
||||
assert "events" in phase
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Backward Compatibility
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestBackwardCompat:
|
||||
"""Ensure existing behavior is preserved."""
|
||||
|
||||
def test_two_player_still_works(self):
|
||||
"""The 2-player run() entry point should still work."""
|
||||
engine = GameEngine(max_turns=10)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in _make_deck(60)],
|
||||
deck_b=[c.clone() for c in _make_deck(61)],
|
||||
)
|
||||
assert result.winner_seat in (-1, 0, 1)
|
||||
|
||||
def test_n_player_still_works(self):
|
||||
"""The N-player run_n() entry point should still work."""
|
||||
engine = GameEngine(max_turns=10)
|
||||
decks = [_make_deck(seed=i + 70) for i in range(3)]
|
||||
result = engine.run_n(
|
||||
decks=[[c.clone() for c in d] for d in decks],
|
||||
names=["X", "Y", "Z"],
|
||||
)
|
||||
assert result.winner_seat in range(3)
|
||||
assert len(result.players) == 3
|
||||
|
||||
def test_mulligan_rule_still_works(self):
|
||||
"""London mulligan should still function with the phase refactor."""
|
||||
engine = GameEngine(max_turns=5, mulligan_rule="london")
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in _make_deck(80)],
|
||||
deck_b=[c.clone() for c in _make_deck(81)],
|
||||
)
|
||||
assert result.turns > 0
|
||||
|
||||
def test_no_mulligan_rule_still_works(self):
|
||||
"""Legacy mulligan='none' should still function."""
|
||||
engine = GameEngine(max_turns=5, mulligan_rule="none")
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in _make_deck(90)],
|
||||
deck_b=[c.clone() for c in _make_deck(91)],
|
||||
)
|
||||
assert result.turns > 0
|
||||
|
||||
def test_commander_damage_still_tracked(self):
|
||||
"""Commander damage tracking should still work through deal_damage."""
|
||||
sim = SimState(max_turns=1)
|
||||
from commander_ai_lab.sim.models import Player, PlayerStats
|
||||
for i in range(2):
|
||||
sim.players.append(Player(
|
||||
name=f"P{i}", life=40, owner_id=i, stats=PlayerStats(),
|
||||
))
|
||||
sim.init_battlefields(2)
|
||||
|
||||
commander = Card(name="TestCommander", is_commander=True)
|
||||
GameEngine.deal_damage(
|
||||
sim, 5, target_seat=1,
|
||||
source_card=commander, source_seat=0,
|
||||
is_combat=True,
|
||||
)
|
||||
assert sim.players[1].commander_damage_received[0] == 5
|
||||
assert sim.players[1].commander_damage_by_card[(0, "TestCommander")] == 5
|
||||
assert sim.players[1].life == 35
|
||||
|
||||
def test_direct_damage_still_works(self):
|
||||
"""Burn spells should still route through deal_damage."""
|
||||
sim = SimState(max_turns=1)
|
||||
from commander_ai_lab.sim.models import Player, PlayerStats
|
||||
for i in range(2):
|
||||
sim.players.append(Player(
|
||||
name=f"P{i}", life=40, owner_id=i, stats=PlayerStats(),
|
||||
))
|
||||
sim.init_battlefields(2)
|
||||
|
||||
burn = Card(name="Lightning Bolt", is_direct_damage=True, direct_damage_amount=3)
|
||||
events: list[str] = []
|
||||
GameEngine.deal_damage(
|
||||
sim, 3, target_seat=1,
|
||||
source_card=burn, source_seat=0,
|
||||
events=events,
|
||||
label="Lightning Bolt deals 3",
|
||||
)
|
||||
assert sim.players[1].life == 37
|
||||
assert len(events) == 1
|
||||
|
||||
def test_elimination_still_works(self):
|
||||
"""Player elimination should still trigger when life <= 0."""
|
||||
engine = GameEngine(max_turns=25, mulligan_rule="none")
|
||||
# Build aggro-heavy decks
|
||||
deck = []
|
||||
for i in range(60):
|
||||
if i < 20:
|
||||
deck.append(Card(name="Mountain"))
|
||||
else:
|
||||
c = Card(name="Lightning Bolt")
|
||||
enrich_card(c)
|
||||
deck.append(c)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
deck_b=[c.clone() for c in deck],
|
||||
)
|
||||
# At least one player should be eliminated (or game timed out)
|
||||
assert result.turns > 0
|
||||
|
||||
def test_ml_log_still_works(self):
|
||||
"""ML logging should still capture decisions."""
|
||||
engine = GameEngine(max_turns=3, ml_log=True, mulligan_rule="none")
|
||||
deck = _make_deck(seed=100)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
deck_b=[c.clone() for c in deck],
|
||||
)
|
||||
decisions = engine.flush_ml_decisions()
|
||||
assert isinstance(decisions, list)
|
||||
# With turns happening, there should be some decisions
|
||||
if result.turns > 0:
|
||||
assert len(decisions) > 0
|
||||
|
||||
def test_result_serializable(self):
|
||||
"""Game result should still serialize cleanly."""
|
||||
import json
|
||||
engine = GameEngine(max_turns=3, record_log=True, mulligan_rule="none")
|
||||
deck = _make_deck(seed=110)
|
||||
result = engine.run(
|
||||
deck_a=[c.clone() for c in deck],
|
||||
deck_b=[c.clone() for c in deck],
|
||||
)
|
||||
d = result.to_dict()
|
||||
json.dumps(d) # should not raise
|
||||
|
||||
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
# Turn Manager Phase Constants
|
||||
# ══════════════════════════════════════════════════════════════
|
||||
|
||||
class TestTurnManagerPhaseCompat:
|
||||
"""Ensure turn_manager.py PHASES/ACTION_PHASES/RESPONSE_PHASES are consistent."""
|
||||
|
||||
def test_turn_manager_phases_match_model(self):
|
||||
"""turn_manager.PHASES should match the canonical PHASE_ORDER."""
|
||||
from commander_ai_lab.sim.turn_manager import PHASES as TM_PHASES
|
||||
assert TM_PHASES == [p.value for p in PHASE_ORDER]
|
||||
|
||||
def test_turn_manager_action_phases(self):
|
||||
"""ACTION_PHASES should be main1 and main2."""
|
||||
from commander_ai_lab.sim.turn_manager import ACTION_PHASES
|
||||
assert ACTION_PHASES == {"main1", "main2"}
|
||||
|
||||
def test_turn_manager_response_phases(self):
|
||||
"""RESPONSE_PHASES should be upkeep, begin_combat, end_combat, end_step."""
|
||||
from commander_ai_lab.sim.turn_manager import RESPONSE_PHASES
|
||||
assert RESPONSE_PHASES == {"upkeep", "begin_combat", "end_combat", "end_step"}
|
||||
+11
-22
@@ -48,20 +48,10 @@ class _GS:
|
||||
self.turn = 1
|
||||
self.current_phase = "main1"
|
||||
self.active_player_seat = 0
|
||||
self.priority_seat = 0
|
||||
self.stack = []
|
||||
self.game_over = False
|
||||
self.winner = None
|
||||
|
||||
def battlefield(self, seat: int) -> list:
|
||||
return self.players[seat].battlefield
|
||||
|
||||
def stack_is_empty(self) -> bool:
|
||||
return len(self.stack) == 0
|
||||
|
||||
def living_players(self) -> list:
|
||||
return [p for p in self.players if not p.eliminated]
|
||||
|
||||
def get_legal_moves(self, seat):
|
||||
return [{"id": 1, "category": "pass_priority", "description": "Pass"}]
|
||||
|
||||
@@ -70,7 +60,7 @@ class _GS:
|
||||
|
||||
|
||||
def _run(coro):
|
||||
return asyncio.run(coro)
|
||||
return asyncio.get_event_loop().run_until_complete(coro)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -82,13 +72,14 @@ class BenchThreatAssessor:
|
||||
MIN_OPS_PER_SEC = 500
|
||||
|
||||
def test_assess_threats_throughput(self):
|
||||
from commander_ai_lab.sim.threat_assessor import assess_threats
|
||||
from commander_ai_lab.sim.threat_assessor import ThreatAssessor
|
||||
gs = _GS()
|
||||
ta = ThreatAssessor(game_state=gs, num_players=4)
|
||||
|
||||
start = time.perf_counter()
|
||||
for _ in range(self.ITERATIONS):
|
||||
for seat in range(4):
|
||||
assess_threats(gs, viewer_seat=seat)
|
||||
ta.assess_threats(viewer_seat=seat)
|
||||
elapsed = time.perf_counter() - start
|
||||
|
||||
ops = self.ITERATIONS * 4
|
||||
@@ -99,12 +90,13 @@ class BenchThreatAssessor:
|
||||
)
|
||||
|
||||
def test_top_threat_throughput(self):
|
||||
from commander_ai_lab.sim.threat_assessor import top_threat
|
||||
from commander_ai_lab.sim.threat_assessor import ThreatAssessor
|
||||
gs = _GS()
|
||||
ta = ThreatAssessor(game_state=gs, num_players=4)
|
||||
|
||||
start = time.perf_counter()
|
||||
for _ in range(self.ITERATIONS):
|
||||
top_threat(gs, viewer_seat=0)
|
||||
ta.top_threat(viewer_seat=0)
|
||||
elapsed = time.perf_counter() - start
|
||||
|
||||
ops_per_sec = self.ITERATIONS / elapsed
|
||||
@@ -244,23 +236,20 @@ class BenchIntegrated:
|
||||
Simulate N full turns: threat assessment + politics check + memory record.
|
||||
Measures combined per-turn overhead of the AI subsystems.
|
||||
"""
|
||||
from commander_ai_lab.sim.threat_assessor import assess_threats
|
||||
from commander_ai_lab.sim.threat_assessor import ThreatAssessor
|
||||
from commander_ai_lab.sim.politics.memory import TargetingMemory, ActionType
|
||||
from commander_ai_lab.sim.politics.comms import PoliticsCommsChannel
|
||||
from commander_ai_lab.sim.politics.engine import PoliticsEngine
|
||||
from commander_ai_lab.sim.politics.deals import DealType
|
||||
|
||||
gs = _GS()
|
||||
|
||||
def _threat_dict(viewer_seat: int) -> dict[int, float]:
|
||||
return {s.seat: s.total for s in assess_threats(gs, viewer_seat=viewer_seat)}
|
||||
|
||||
ta = ThreatAssessor(game_state=gs, num_players=4)
|
||||
mem = TargetingMemory(4)
|
||||
ch = PoliticsCommsChannel()
|
||||
pe = PoliticsEngine(
|
||||
4, mem, ch,
|
||||
{0:"timmy",1:"spike",2:"johnny",3:"aggressive"},
|
||||
_threat_dict,
|
||||
lambda s: ta.assess_threats(viewer_seat=s),
|
||||
)
|
||||
|
||||
async def simulate():
|
||||
@@ -269,7 +258,7 @@ class BenchIntegrated:
|
||||
active = turn % 4
|
||||
# Assess threats for all seats
|
||||
for seat in range(4):
|
||||
assess_threats(gs, viewer_seat=seat)
|
||||
ta.assess_threats(viewer_seat=seat)
|
||||
# Record a simulated attack
|
||||
attacker = active
|
||||
defender = (active + 1) % 4
|
||||
|
||||
@@ -1,134 +0,0 @@
|
||||
"""
|
||||
tests/test_check_ownership_dedup.py
|
||||
====================================
|
||||
Unit tests for duplicate-card deduplication in
|
||||
DeckGeneratorV3._check_ownership().
|
||||
|
||||
Uses an in-memory SQLite database so no real collection DB is required.
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import sqlite3
|
||||
from unittest.mock import MagicMock
|
||||
|
||||
import pytest
|
||||
|
||||
from coach.services.deck_generator import DeckGeneratorV3
|
||||
|
||||
|
||||
# ── Helpers ──────────────────────────────────────────────────────────────────
|
||||
|
||||
def _make_conn() -> sqlite3.Connection:
|
||||
"""Return a seeded in-memory DB matching the collection_entries schema."""
|
||||
conn = sqlite3.connect(":memory:")
|
||||
conn.row_factory = sqlite3.Row
|
||||
conn.execute("""
|
||||
CREATE TABLE collection_entries (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
name TEXT NOT NULL,
|
||||
scryfall_id TEXT DEFAULT '',
|
||||
quantity INTEGER DEFAULT 0,
|
||||
tcg_price REAL DEFAULT 0,
|
||||
type_line TEXT DEFAULT '',
|
||||
cmc REAL DEFAULT 0
|
||||
)
|
||||
""")
|
||||
cards = [
|
||||
("Cultivate", "cult-001", 2, 1.50, "Sorcery", 3),
|
||||
("Sol Ring", "sol-001", 1, 5.00, "Artifact", 0),
|
||||
("Kodama's Reach", "kr-001", 1, 0.80, "Sorcery", 3),
|
||||
]
|
||||
conn.executemany(
|
||||
"INSERT INTO collection_entries (name, scryfall_id, quantity, tcg_price, type_line, cmc) "
|
||||
"VALUES (?, ?, ?, ?, ?, ?)",
|
||||
cards,
|
||||
)
|
||||
conn.commit()
|
||||
return conn
|
||||
|
||||
|
||||
def _make_generator(conn: sqlite3.Connection) -> DeckGeneratorV3:
|
||||
"""Build a DeckGeneratorV3 with a mock Anthropic Claude Opus client."""
|
||||
return DeckGeneratorV3(
|
||||
anthropic_client=MagicMock(),
|
||||
db_conn_factory=lambda: conn,
|
||||
)
|
||||
|
||||
|
||||
# ── Tests ────────────────────────────────────────────────────────────────────
|
||||
|
||||
class TestCheckOwnershipDedup:
|
||||
|
||||
def setup_method(self):
|
||||
self.conn = _make_conn()
|
||||
self.gen = _make_generator(self.conn)
|
||||
|
||||
def test_duplicate_cards_merged(self):
|
||||
"""Duplicate card names should be merged into a single entry with summed count."""
|
||||
cards = [
|
||||
{"name": "Cultivate", "count": 1, "category": "Ramp"},
|
||||
{"name": "Sol Ring", "count": 1, "category": "Ramp"},
|
||||
{"name": "Cultivate", "count": 1, "category": "Ramp"},
|
||||
]
|
||||
result = self.gen._check_ownership(cards)
|
||||
names = [c.name for c in result]
|
||||
|
||||
# No duplicate names (case-insensitive)
|
||||
assert len(names) == len(set(n.lower() for n in names)), (
|
||||
f"Duplicate names found in output: {names}"
|
||||
)
|
||||
# Only 2 unique cards
|
||||
assert len(result) == 2
|
||||
|
||||
# Merged count should be 2
|
||||
cultivate = next(c for c in result if c.name.lower() == "cultivate")
|
||||
assert cultivate.count == 2
|
||||
|
||||
def test_case_insensitive_dedup(self):
|
||||
"""Deduplication should be case-insensitive."""
|
||||
cards = [
|
||||
{"name": "cultivate", "count": 1, "category": "Ramp"},
|
||||
{"name": "CULTIVATE", "count": 1, "category": "Ramp"},
|
||||
{"name": "Cultivate", "count": 1, "category": "Ramp"},
|
||||
]
|
||||
result = self.gen._check_ownership(cards)
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0].count == 3
|
||||
|
||||
def test_warning_logged_on_duplicate(self, caplog):
|
||||
"""A WARNING log should be emitted when a duplicate is merged."""
|
||||
cards = [
|
||||
{"name": "Cultivate", "count": 1, "category": "Ramp"},
|
||||
{"name": "Cultivate", "count": 1, "category": "Ramp"},
|
||||
]
|
||||
with caplog.at_level(logging.WARNING, logger="coach.deckgen"):
|
||||
self.gen._check_ownership(cards)
|
||||
|
||||
assert any("Duplicate" in msg or "merged" in msg for msg in caplog.messages), (
|
||||
f"Expected WARNING about duplicate/merged, got: {caplog.messages}"
|
||||
)
|
||||
|
||||
def test_no_duplicates_passes_through(self):
|
||||
"""When there are no duplicates, all cards pass through normally."""
|
||||
cards = [
|
||||
{"name": "Cultivate", "count": 1, "category": "Ramp"},
|
||||
{"name": "Sol Ring", "count": 1, "category": "Ramp"},
|
||||
{"name": "Kodama's Reach", "count": 1, "category": "Ramp"},
|
||||
]
|
||||
result = self.gen._check_ownership(cards)
|
||||
|
||||
assert len(result) == 3
|
||||
assert all(c.count == 1 for c in result)
|
||||
|
||||
def test_empty_name_skipped(self):
|
||||
"""Cards with empty names should be silently skipped."""
|
||||
cards = [
|
||||
{"name": "", "count": 1},
|
||||
{"name": "Sol Ring", "count": 1, "category": "Ramp"},
|
||||
]
|
||||
result = self.gen._check_ownership(cards)
|
||||
|
||||
assert len(result) == 1
|
||||
assert result[0].name == "Sol Ring"
|
||||
@@ -1,160 +0,0 @@
|
||||
"""Tests for combat priority checkpoints (Issue #86 Item 1).
|
||||
|
||||
Validates CombatState lifecycle, split combat methods,
|
||||
priority windows, first-strike ordering, and instant-speed
|
||||
interaction during combat.
|
||||
"""
|
||||
import pytest
|
||||
from commander_ai_lab.sim.models import (
|
||||
Card, CombatState, Phase, Player, PlayerStats, SimState,
|
||||
)
|
||||
from commander_ai_lab.sim.engine import GameEngine
|
||||
|
||||
|
||||
# ── Helpers ──────────────────────────────────────────────────────
|
||||
|
||||
def _make_creature(name, power, toughness, card_id, owner=0, keywords=None, is_commander=False):
|
||||
"""Build a minimal creature Card for testing."""
|
||||
return Card(
|
||||
name=name,
|
||||
type_line="Creature",
|
||||
power=str(power),
|
||||
toughness=str(toughness),
|
||||
pt=f"{power}/{toughness}",
|
||||
id=card_id,
|
||||
owner_id=owner,
|
||||
keywords=keywords or [],
|
||||
is_commander=is_commander,
|
||||
turn_played=-1,
|
||||
)
|
||||
|
||||
|
||||
def _two_player_sim(p0_creatures, p1_creatures, p0_life=40, p1_life=40):
|
||||
"""Build a minimal 2-player SimState with creatures on the battlefield."""
|
||||
sim = SimState(
|
||||
players=[
|
||||
Player(name="Attacker", life=p0_life, owner_id=0, stats=PlayerStats()),
|
||||
Player(name="Defender", life=p1_life, owner_id=1, stats=PlayerStats()),
|
||||
],
|
||||
battlefields=[list(p0_creatures), list(p1_creatures)],
|
||||
turn=2,
|
||||
)
|
||||
return sim
|
||||
|
||||
|
||||
# ── Tests ───────────────────────────────────────────────────────
|
||||
|
||||
class TestCombatState:
|
||||
"""CombatState dataclass lifecycle."""
|
||||
|
||||
def test_combat_state_defaults(self):
|
||||
cs = CombatState()
|
||||
assert cs.defending_seat == -1
|
||||
assert cs.attackers == {}
|
||||
assert cs.blockers == {}
|
||||
assert cs.player_damage == {}
|
||||
assert cs.first_strike_resolved is False
|
||||
assert cs.active is False
|
||||
|
||||
def test_combat_state_on_simstate(self):
|
||||
sim = SimState()
|
||||
assert sim.combat is None
|
||||
sim.combat = CombatState(active=True)
|
||||
assert sim.combat.active is True
|
||||
sim.combat = None
|
||||
assert sim.combat is None
|
||||
|
||||
|
||||
class TestAssignAttackers:
|
||||
"""Engine.assign_attackers() populates CombatState."""
|
||||
|
||||
def test_assigns_and_taps(self):
|
||||
atk = _make_creature("Bear", 3, 3, 100)
|
||||
sim = _two_player_sim([atk], [])
|
||||
engine = GameEngine()
|
||||
combat = engine.assign_attackers(sim, 0)
|
||||
assert combat is not None
|
||||
assert combat.active is True
|
||||
assert 100 in combat.attackers
|
||||
assert atk.tapped is True
|
||||
assert sim.combat is combat
|
||||
|
||||
def test_no_attack_returns_none(self):
|
||||
sim = _two_player_sim([], []) # no creatures
|
||||
engine = GameEngine()
|
||||
assert engine.assign_attackers(sim, 0) is None
|
||||
assert sim.combat is None
|
||||
|
||||
|
||||
class TestResolveCombatDamage:
|
||||
"""Engine.resolve_combat_damage() applies damage from CombatState."""
|
||||
|
||||
def test_unblocked_attacker_deals_damage(self):
|
||||
atk = _make_creature("Bear", 3, 3, 100)
|
||||
sim = _two_player_sim([atk], [], p1_life=20)
|
||||
combat = CombatState(defending_seat=1, attackers={100: 1}, active=True)
|
||||
sim.combat = combat
|
||||
engine = GameEngine()
|
||||
engine.resolve_combat_damage(sim, 0, combat)
|
||||
assert sim.players[1].life == 17 # 20 - 3
|
||||
|
||||
def test_attacker_removed_before_damage_deals_nothing(self):
|
||||
"""Simulates instant-speed removal of attacker after declare attackers."""
|
||||
atk = _make_creature("Bear", 3, 3, 100)
|
||||
sim = _two_player_sim([atk], [], p1_life=20)
|
||||
combat = CombatState(defending_seat=1, attackers={100: 1}, active=True)
|
||||
sim.combat = combat
|
||||
# Simulate instant-speed removal: remove attacker before damage
|
||||
sim.remove_from_battlefield(100)
|
||||
engine = GameEngine()
|
||||
engine.resolve_combat_damage(sim, 0, combat)
|
||||
assert sim.players[1].life == 20 # no damage dealt
|
||||
|
||||
def test_first_strike_only_skips_non_fs(self):
|
||||
fs = _make_creature("Knight", 2, 2, 200, keywords=["first_strike"])
|
||||
normal = _make_creature("Bear", 3, 3, 201)
|
||||
sim = _two_player_sim([fs, normal], [], p1_life=20)
|
||||
combat = CombatState(
|
||||
defending_seat=1,
|
||||
attackers={200: 1, 201: 1},
|
||||
active=True,
|
||||
)
|
||||
sim.combat = combat
|
||||
engine = GameEngine()
|
||||
# First-strike step: only the knight deals damage
|
||||
engine.resolve_combat_damage(sim, 0, combat, first_strike_only=True)
|
||||
assert sim.players[1].life == 18 # 20 - 2 (knight only)
|
||||
assert combat.first_strike_resolved is True
|
||||
# Normal damage step: bear deals damage, knight skipped
|
||||
engine.resolve_combat_damage(sim, 0, combat, first_strike_only=False)
|
||||
assert sim.players[1].life == 15 # 18 - 3 (bear only)
|
||||
|
||||
def test_combat_state_cleared_after_end_combat(self):
|
||||
"""Verifies sim.combat is None after combat cleanup."""
|
||||
sim = SimState()
|
||||
sim.combat = CombatState(active=True)
|
||||
# Simulate end-of-combat cleanup
|
||||
sim.combat = None
|
||||
assert sim.combat is None
|
||||
|
||||
def test_commander_damage_attributed(self):
|
||||
"""Commander attacker routes damage through commander_damage_by_card."""
|
||||
cmd = _make_creature("Atraxa", 4, 4, 300, is_commander=True)
|
||||
sim = _two_player_sim([cmd], [], p1_life=40)
|
||||
combat = CombatState(defending_seat=1, attackers={300: 1}, active=True)
|
||||
sim.combat = combat
|
||||
engine = GameEngine()
|
||||
engine.resolve_combat_damage(sim, 0, combat)
|
||||
assert sim.players[1].life == 36 # 40 - 4
|
||||
assert sim.players[1].commander_damage_by_card.get((0, "Atraxa"), 0) == 4
|
||||
|
||||
|
||||
class TestResponsePhasesCleanup:
|
||||
"""Verify BEGIN_COMBAT and END_COMBAT removed from RESPONSE_PHASES."""
|
||||
|
||||
def test_no_duplicate_apnap_begin_end_combat(self):
|
||||
from commander_ai_lab.sim.turn_manager import RESPONSE_PHASES
|
||||
assert "begin_combat" not in RESPONSE_PHASES
|
||||
assert "end_combat" not in RESPONSE_PHASES
|
||||
assert "upkeep" in RESPONSE_PHASES
|
||||
assert "end_step" in RESPONSE_PHASES
|
||||
@@ -1,410 +0,0 @@
|
||||
"""
|
||||
Commander Damage Regression Tests
|
||||
==================================
|
||||
Run with: pytest tests/test_commander_damage.py -v
|
||||
|
||||
Covers:
|
||||
- Commander source identity during combat
|
||||
- Trample overflow counts as commander damage
|
||||
- Double strike commander damage
|
||||
- Partner / multi-commander per-card tracking
|
||||
- 21-damage lethal check (per-card, not per-seat)
|
||||
- Commander damage through CommanderGameState helper
|
||||
- Non-commander creatures do NOT generate commander damage
|
||||
- Lifelink + commander damage interaction
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import pytest
|
||||
|
||||
from commander_ai_lab.sim.models import Card, Player, PlayerStats, SimState
|
||||
from commander_ai_lab.sim.engine import GameEngine
|
||||
from commander_ai_lab.sim.game_state import (
|
||||
CommanderGameState,
|
||||
CommanderPlayer,
|
||||
)
|
||||
|
||||
|
||||
# ── Helpers ──────────────────────────────────────────────────
|
||||
|
||||
|
||||
def _make_creature(
|
||||
name: str,
|
||||
power: str = "3",
|
||||
toughness: str = "3",
|
||||
keywords: list[str] | None = None,
|
||||
is_commander: bool = False,
|
||||
) -> Card:
|
||||
c = Card(
|
||||
name=name,
|
||||
type_line="Legendary Creature" if is_commander else "Creature",
|
||||
cmc=3,
|
||||
power=power,
|
||||
toughness=toughness,
|
||||
keywords=keywords or [],
|
||||
is_commander=is_commander,
|
||||
)
|
||||
return c
|
||||
|
||||
|
||||
def _make_land(name: str = "Mountain") -> Card:
|
||||
return Card(name=name, type_line="Basic Land", cmc=0)
|
||||
|
||||
|
||||
def _setup_combat(
|
||||
attacker_creatures: list[Card],
|
||||
blocker_creatures: list[Card] | None = None,
|
||||
attacker_life: int = 40,
|
||||
defender_life: int = 40,
|
||||
) -> tuple[GameEngine, SimState, int, int]:
|
||||
"""Set up a 2-player SimState ready for _resolve_combat.
|
||||
|
||||
Returns (engine, sim, attacker_seat, defender_seat).
|
||||
Attacker is seat 0, defender is seat 1.
|
||||
All creatures are pre-placed on battlefield, untapped, played on a previous turn.
|
||||
"""
|
||||
engine = GameEngine(max_turns=25, starting_life=40, record_log=True)
|
||||
sim = SimState(max_turns=25)
|
||||
sim.turn = 5 # so creatures played earlier pass summoning sickness check
|
||||
|
||||
p0 = Player(name="Attacker", life=attacker_life, owner_id=0, stats=PlayerStats())
|
||||
p1 = Player(name="Defender", life=defender_life, owner_id=1, stats=PlayerStats())
|
||||
sim.players = [p0, p1]
|
||||
sim.init_battlefields(2)
|
||||
|
||||
card_id = 90000
|
||||
for c in attacker_creatures:
|
||||
c.owner_id = 0
|
||||
c.tapped = False
|
||||
c.turn_played = 1 # played on an earlier turn
|
||||
c.id = card_id
|
||||
card_id += 1
|
||||
sim.add_to_battlefield(0, c)
|
||||
|
||||
for c in (blocker_creatures or []):
|
||||
c.owner_id = 1
|
||||
c.tapped = False
|
||||
c.turn_played = 1
|
||||
c.id = card_id
|
||||
card_id += 1
|
||||
sim.add_to_battlefield(1, c)
|
||||
|
||||
sim.next_card_id = card_id
|
||||
return engine, sim, 0, 1
|
||||
|
||||
|
||||
# ── Tests: Basic commander damage tracking ───────────────────
|
||||
|
||||
|
||||
class TestCommanderDamageBasic:
|
||||
"""Commander creatures attacking unblocked should generate
|
||||
commander damage tracked on the defending player."""
|
||||
|
||||
def test_unblocked_commander_deals_commander_damage(self):
|
||||
cmd = _make_creature("Krenko", "5", "5", is_commander=True)
|
||||
engine, sim, pi, oi = _setup_combat([cmd])
|
||||
events: list[str] = []
|
||||
engine._resolve_combat(sim, pi, sim.turn, events)
|
||||
opp = sim.players[oi]
|
||||
# Life reduced
|
||||
assert opp.life == 35
|
||||
# Per-seat aggregate
|
||||
assert opp.commander_damage_received[pi] == 5
|
||||
# Per-card breakdown
|
||||
assert opp.commander_damage_by_card[(pi, "Krenko")] == 5
|
||||
|
||||
def test_unblocked_non_commander_no_commander_damage(self):
|
||||
creature = _make_creature("Goblin", "4", "4", is_commander=False)
|
||||
engine, sim, pi, oi = _setup_combat([creature])
|
||||
events: list[str] = []
|
||||
engine._resolve_combat(sim, pi, sim.turn, events)
|
||||
opp = sim.players[oi]
|
||||
assert opp.life == 36
|
||||
assert opp.commander_damage_received == {}
|
||||
assert opp.commander_damage_by_card == {}
|
||||
|
||||
def test_mixed_attackers_only_commander_tracked(self):
|
||||
cmd = _make_creature("Krenko", "3", "3", is_commander=True)
|
||||
grunt = _make_creature("Goblin", "2", "2", is_commander=False)
|
||||
engine, sim, pi, oi = _setup_combat([cmd, grunt])
|
||||
events: list[str] = []
|
||||
engine._resolve_combat(sim, pi, sim.turn, events)
|
||||
opp = sim.players[oi]
|
||||
# Total damage = 3 + 2 = 5
|
||||
assert opp.life == 35
|
||||
# Only commander damage tracked
|
||||
assert opp.commander_damage_received[pi] == 3
|
||||
assert opp.commander_damage_by_card[(pi, "Krenko")] == 3
|
||||
|
||||
def test_cumulative_commander_damage_across_combats(self):
|
||||
cmd = _make_creature("Krenko", "5", "5", is_commander=True)
|
||||
engine, sim, pi, oi = _setup_combat([cmd])
|
||||
# First combat
|
||||
engine._resolve_combat(sim, pi, sim.turn, [])
|
||||
assert sim.players[oi].commander_damage_received[pi] == 5
|
||||
# Reset tapped state for second combat
|
||||
cmd.tapped = False
|
||||
sim.turn += 1
|
||||
engine._resolve_combat(sim, pi, sim.turn, [])
|
||||
assert sim.players[oi].commander_damage_received[pi] == 10
|
||||
assert sim.players[oi].commander_damage_by_card[(pi, "Krenko")] == 10
|
||||
|
||||
|
||||
# ── Tests: Commander damage lethal (21+) ─────────────────────
|
||||
|
||||
|
||||
class TestCommanderDamageLethal:
|
||||
|
||||
def test_21_damage_eliminates(self):
|
||||
cmd = _make_creature("Krenko", "7", "7", is_commander=True)
|
||||
engine, sim, pi, oi = _setup_combat([cmd], defender_life=100)
|
||||
# Deal 7 per combat, need 3 combats = 21
|
||||
for _ in range(3):
|
||||
cmd.tapped = False
|
||||
engine._resolve_combat(sim, pi, sim.turn, [])
|
||||
sim.turn += 1
|
||||
opp = sim.players[oi]
|
||||
assert opp.commander_damage_received[pi] == 21
|
||||
assert opp.eliminated
|
||||
|
||||
def test_20_damage_not_lethal(self):
|
||||
"""20 commander damage should NOT eliminate."""
|
||||
p = Player(name="Test", life=40)
|
||||
p.commander_damage_received = {0: 20}
|
||||
p.commander_damage_by_card = {(0, "Krenko"): 20}
|
||||
assert not p.is_dead_to_commander_damage()
|
||||
|
||||
def test_21_per_card_not_per_seat(self):
|
||||
"""With partners, 21 must come from a SINGLE commander, not combined."""
|
||||
p = Player(name="Test", life=40)
|
||||
# Two partner commanders from seat 0, 11 each = 22 total but neither is 21
|
||||
p.commander_damage_by_card = {
|
||||
(0, "Brallin"): 11,
|
||||
(0, "Shabraz"): 11,
|
||||
}
|
||||
p.commander_damage_received = {0: 22}
|
||||
assert not p.is_dead_to_commander_damage()
|
||||
|
||||
def test_21_from_one_partner_is_lethal(self):
|
||||
"""If one partner reaches 21, that's lethal even if the other has 0."""
|
||||
p = Player(name="Test", life=40)
|
||||
p.commander_damage_by_card = {
|
||||
(0, "Brallin"): 21,
|
||||
(0, "Shabraz"): 3,
|
||||
}
|
||||
p.commander_damage_received = {0: 24}
|
||||
assert p.is_dead_to_commander_damage()
|
||||
|
||||
def test_backward_compat_no_by_card(self):
|
||||
"""If commander_damage_by_card is empty, fall back to per-seat check."""
|
||||
p = Player(name="Test", life=40)
|
||||
p.commander_damage_received = {0: 21}
|
||||
# No by_card data (older game state)
|
||||
assert p.is_dead_to_commander_damage()
|
||||
|
||||
|
||||
# ── Tests: Trample commander damage ──────────────────────────
|
||||
|
||||
|
||||
class TestCommanderDamageTrample:
|
||||
|
||||
def test_trample_overflow_is_commander_damage(self):
|
||||
"""When a commander with trample is chump-blocked, overflow to
|
||||
the player should count as commander damage."""
|
||||
cmd = _make_creature("Ghalta", "12", "12", keywords=["trample"], is_commander=True)
|
||||
# Defender life low enough that AI decides to chump-block
|
||||
# (opp.life <= a_pow * 2 ⇒ 20 <= 24)
|
||||
blocker = _make_creature("Bear", "2", "2")
|
||||
engine, sim, pi, oi = _setup_combat([cmd], [blocker], defender_life=20)
|
||||
events: list[str] = []
|
||||
engine._resolve_combat(sim, pi, sim.turn, events)
|
||||
opp = sim.players[oi]
|
||||
# Bear (2/2) chump-blocks Ghalta (12/12 trample).
|
||||
# Trample overflow = 12 - 2 = 10 damage to player.
|
||||
assert opp.commander_damage_received[pi] == 10
|
||||
assert opp.commander_damage_by_card[(pi, "Ghalta")] == 10
|
||||
assert opp.life == 10
|
||||
|
||||
def test_fully_blocked_commander_no_player_damage(self):
|
||||
"""Commander fully absorbed by a survivable blocker — no commander
|
||||
damage to the defending player."""
|
||||
cmd = _make_creature("Krenko", "3", "3", is_commander=True)
|
||||
# Blocker toughness > attacker power so AI selects it
|
||||
blocker = _make_creature("Wall", "0", "5")
|
||||
engine, sim, pi, oi = _setup_combat([cmd], [blocker])
|
||||
events: list[str] = []
|
||||
engine._resolve_combat(sim, pi, sim.turn, events)
|
||||
opp = sim.players[oi]
|
||||
# No damage to player (absorbed by blocker, no trample)
|
||||
assert opp.life == 40
|
||||
assert opp.commander_damage_received == {}
|
||||
|
||||
|
||||
# ── Tests: Double strike commander damage ────────────────────
|
||||
|
||||
|
||||
class TestCommanderDamageDoubleStrike:
|
||||
|
||||
def test_unblocked_double_strike_commander(self):
|
||||
cmd = _make_creature("Rafiq", "5", "5", keywords=["double strike"], is_commander=True)
|
||||
engine, sim, pi, oi = _setup_combat([cmd])
|
||||
events: list[str] = []
|
||||
engine._resolve_combat(sim, pi, sim.turn, events)
|
||||
opp = sim.players[oi]
|
||||
# Double strike unblocked = power * 2
|
||||
assert opp.life == 30
|
||||
assert opp.commander_damage_received[pi] == 10
|
||||
assert opp.commander_damage_by_card[(pi, "Rafiq")] == 10
|
||||
|
||||
|
||||
# ── Tests: Partner / multi-commander ─────────────────────────
|
||||
|
||||
|
||||
class TestPartnerCommanderDamage:
|
||||
|
||||
def test_two_partner_commanders_tracked_separately(self):
|
||||
cmd_a = _make_creature("Brallin", "4", "4", is_commander=True)
|
||||
cmd_b = _make_creature("Shabraz", "3", "3", is_commander=True)
|
||||
engine, sim, pi, oi = _setup_combat([cmd_a, cmd_b])
|
||||
events: list[str] = []
|
||||
engine._resolve_combat(sim, pi, sim.turn, events)
|
||||
opp = sim.players[oi]
|
||||
# Total damage = 4 + 3 = 7
|
||||
assert opp.life == 33
|
||||
# Aggregate per-seat
|
||||
assert opp.commander_damage_received[pi] == 7
|
||||
# Per-card individual
|
||||
assert opp.commander_damage_by_card[(pi, "Brallin")] == 4
|
||||
assert opp.commander_damage_by_card[(pi, "Shabraz")] == 3
|
||||
|
||||
def test_partner_21_check_per_card(self):
|
||||
"""Even with partners, only 21 from ONE commander kills."""
|
||||
cmd_a = _make_creature("Brallin", "7", "7", is_commander=True)
|
||||
cmd_b = _make_creature("Shabraz", "7", "7", is_commander=True)
|
||||
engine, sim, pi, oi = _setup_combat([cmd_a, cmd_b], defender_life=100)
|
||||
# 3 combats: 7*3=21 for Brallin, 7*3=21 for Shabraz
|
||||
# After 2 combats: 14 each — not lethal
|
||||
for _ in range(2):
|
||||
cmd_a.tapped = False
|
||||
cmd_b.tapped = False
|
||||
engine._resolve_combat(sim, pi, sim.turn, [])
|
||||
sim.turn += 1
|
||||
opp = sim.players[oi]
|
||||
assert not opp.eliminated # 14 from each, neither is 21
|
||||
# 3rd combat pushes both to 21
|
||||
cmd_a.tapped = False
|
||||
cmd_b.tapped = False
|
||||
engine._resolve_combat(sim, pi, sim.turn, [])
|
||||
assert opp.eliminated
|
||||
|
||||
|
||||
# ── Tests: CommanderGameState integration ────────────────────
|
||||
|
||||
|
||||
class TestCommanderGameStateDamage:
|
||||
|
||||
def test_deal_commander_damage_with_name(self):
|
||||
sim = SimState()
|
||||
sim.init_battlefields(2)
|
||||
for i in range(2):
|
||||
sim.players.append(Player(name=f"P{i}", life=40, owner_id=i))
|
||||
gs = CommanderGameState.from_sim_state(sim)
|
||||
gs.deal_commander_damage(0, 1, 10, commander_name="Krenko")
|
||||
cp = gs.commander_players[1]
|
||||
assert cp.commander_damage_received[0] == 10
|
||||
assert cp.base.commander_damage_by_card[(0, "Krenko")] == 10
|
||||
assert cp.life == 30
|
||||
|
||||
def test_deal_commander_damage_without_name_backward_compat(self):
|
||||
sim = SimState()
|
||||
sim.init_battlefields(2)
|
||||
for i in range(2):
|
||||
sim.players.append(Player(name=f"P{i}", life=40, owner_id=i))
|
||||
gs = CommanderGameState.from_sim_state(sim)
|
||||
gs.deal_commander_damage(0, 1, 10)
|
||||
cp = gs.commander_players[1]
|
||||
assert cp.commander_damage_received[0] == 10
|
||||
assert cp.base.commander_damage_by_card == {}
|
||||
assert cp.life == 30
|
||||
|
||||
def test_commander_player_property_delegates_to_base(self):
|
||||
"""CommanderPlayer.commander_damage_received should be the same
|
||||
object as base.commander_damage_received."""
|
||||
p = Player(name="Test", life=40)
|
||||
cp = CommanderPlayer(base=p)
|
||||
# Write through base
|
||||
p.commander_damage_received[0] = 15
|
||||
# Read through wrapper
|
||||
assert cp.commander_damage_received[0] == 15
|
||||
# Write through wrapper
|
||||
cp.commander_damage_received[1] = 7
|
||||
assert p.commander_damage_received[1] == 7
|
||||
|
||||
|
||||
# ── Tests: Event log annotation ──────────────────────────────
|
||||
|
||||
|
||||
class TestCommanderDamageEvents:
|
||||
|
||||
def test_event_log_includes_cmdr_annotation(self):
|
||||
cmd = _make_creature("Krenko", "5", "5", is_commander=True)
|
||||
engine, sim, pi, oi = _setup_combat([cmd])
|
||||
events: list[str] = []
|
||||
engine._resolve_combat(sim, pi, sim.turn, events)
|
||||
# Should mention commander damage in the event text
|
||||
damage_event = [e for e in events if "combat damage" in e]
|
||||
assert len(damage_event) == 1
|
||||
assert "5 cmdr" in damage_event[0]
|
||||
|
||||
def test_no_cmdr_annotation_for_non_commanders(self):
|
||||
grunt = _make_creature("Goblin", "3", "3", is_commander=False)
|
||||
engine, sim, pi, oi = _setup_combat([grunt])
|
||||
events: list[str] = []
|
||||
engine._resolve_combat(sim, pi, sim.turn, events)
|
||||
damage_event = [e for e in events if "combat damage" in e]
|
||||
assert len(damage_event) == 1
|
||||
assert "cmdr" not in damage_event[0]
|
||||
|
||||
|
||||
# ── Tests: Lifelink + commander interaction ──────────────────
|
||||
|
||||
|
||||
class TestCommanderDamageLifelink:
|
||||
|
||||
def test_commander_with_lifelink_heals_and_tracks(self):
|
||||
cmd = _make_creature("Oloro", "5", "5", keywords=["lifelink"], is_commander=True)
|
||||
engine, sim, pi, oi = _setup_combat([cmd])
|
||||
events: list[str] = []
|
||||
engine._resolve_combat(sim, pi, sim.turn, events)
|
||||
attacker = sim.players[pi]
|
||||
opp = sim.players[oi]
|
||||
# Commander damage tracked
|
||||
assert opp.commander_damage_received[pi] == 5
|
||||
# Lifelink healed attacker
|
||||
assert attacker.life == 45
|
||||
# Defender took damage
|
||||
assert opp.life == 35
|
||||
|
||||
|
||||
# ── Tests: Player model ─────────────────────────────────────
|
||||
|
||||
|
||||
class TestPlayerCommanderDamageModel:
|
||||
|
||||
def test_fresh_player_has_empty_tracking(self):
|
||||
p = Player(name="Test")
|
||||
assert p.commander_damage_received == {}
|
||||
assert p.commander_damage_by_card == {}
|
||||
assert not p.is_dead_to_commander_damage()
|
||||
|
||||
def test_is_dead_prefers_by_card(self):
|
||||
"""When by_card data exists, per-seat aggregate is ignored for lethal check."""
|
||||
p = Player(name="Test")
|
||||
p.commander_damage_received = {0: 25} # aggregate says lethal
|
||||
p.commander_damage_by_card = {
|
||||
(0, "CmdA"): 12,
|
||||
(0, "CmdB"): 13,
|
||||
}
|
||||
# Per-card: neither commander has 21 → NOT lethal
|
||||
assert not p.is_dead_to_commander_damage()
|
||||
+16
-52
@@ -25,7 +25,7 @@ import pytest
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def run(coro):
|
||||
return asyncio.run(coro)
|
||||
return asyncio.get_event_loop().run_until_complete(coro)
|
||||
|
||||
|
||||
@dataclass
|
||||
@@ -42,38 +42,15 @@ class _Player:
|
||||
library: list = field(default_factory=list)
|
||||
|
||||
|
||||
class _StubSimState:
|
||||
"""Minimal SimState stub — delegates to player battlefields."""
|
||||
|
||||
def __init__(self, players: list) -> None:
|
||||
self._players = players
|
||||
|
||||
def get_battlefield(self, seat: int) -> list:
|
||||
if 0 <= seat < len(self._players):
|
||||
return self._players[seat].battlefield
|
||||
return []
|
||||
|
||||
|
||||
class _GS:
|
||||
def __init__(self, n=4):
|
||||
self.players = [_Player(f"P{i}", i) for i in range(n)]
|
||||
self.turn = 1
|
||||
self.current_phase = "main1"
|
||||
self.active_player_seat = 0
|
||||
self.priority_seat = 0
|
||||
self.stack = []
|
||||
self.game_over = False
|
||||
self.winner = None
|
||||
self.sim_state = _StubSimState(self.players)
|
||||
|
||||
def battlefield(self, seat: int) -> list:
|
||||
return self.players[seat].battlefield
|
||||
|
||||
def stack_is_empty(self) -> bool:
|
||||
return len(self.stack) == 0
|
||||
|
||||
def living_players(self) -> list:
|
||||
return [p for p in self.players if not p.eliminated]
|
||||
|
||||
def get_legal_moves(self, seat):
|
||||
return [{"id": 1, "category": "pass_priority", "description": "Pass"}]
|
||||
@@ -93,17 +70,13 @@ class TestThreatPoliticsIntegration:
|
||||
"""
|
||||
|
||||
def _build(self):
|
||||
from commander_ai_lab.sim.threat_assessor import assess_threats
|
||||
from commander_ai_lab.sim.threat_assessor import ThreatAssessor
|
||||
from commander_ai_lab.sim.politics.memory import TargetingMemory
|
||||
from commander_ai_lab.sim.politics.comms import PoliticsCommsChannel
|
||||
from commander_ai_lab.sim.politics.engine import PoliticsEngine
|
||||
|
||||
gs = _GS()
|
||||
|
||||
def _threat_dict(viewer_seat: int) -> dict[int, float]:
|
||||
"""Wrap assess_threats list into {seat: total} dict for PoliticsEngine."""
|
||||
return {s.seat: s.total for s in assess_threats(gs, viewer_seat=viewer_seat)}
|
||||
|
||||
ta = ThreatAssessor(game_state=gs, num_players=4)
|
||||
mem = TargetingMemory(num_players=4)
|
||||
ch = PoliticsCommsChannel()
|
||||
pe = PoliticsEngine(
|
||||
@@ -111,26 +84,19 @@ class TestThreatPoliticsIntegration:
|
||||
memory=mem,
|
||||
comms=ch,
|
||||
personalities={0:"timmy",1:"spike",2:"johnny",3:"aggressive"},
|
||||
threat_fn=_threat_dict,
|
||||
threat_fn=lambda s: ta.assess_threats(viewer_seat=s),
|
||||
)
|
||||
return gs, mem, ch, pe
|
||||
return gs, ta, mem, ch, pe
|
||||
|
||||
def test_adjusted_threat_no_spite_equals_base(self):
|
||||
from commander_ai_lab.sim.threat_assessor import assess_threats
|
||||
gs, mem, ch, pe = self._build()
|
||||
scores = assess_threats(gs, viewer_seat=0)
|
||||
# Find the score for seat 1
|
||||
base = 0.0
|
||||
for s in scores:
|
||||
if s.seat == 1:
|
||||
base = s.total
|
||||
break
|
||||
gs, ta, mem, ch, pe = self._build()
|
||||
base = ta.assess_threats(viewer_seat=0).get(1, 0.0)
|
||||
adjusted = pe.adjusted_threat_score(viewer=0, target=1, current_turn=1)
|
||||
# Without spite or memory events, adjusted ≈ base (may differ by mem term)
|
||||
assert abs(adjusted - base) < 0.35
|
||||
|
||||
def test_spite_raises_adjusted_score(self):
|
||||
gs, mem, ch, pe = self._build()
|
||||
gs, ta, mem, ch, pe = self._build()
|
||||
before = pe.adjusted_threat_score(0, 1, 1)
|
||||
pe._add_spite(wronged_seat=0, target_seat=1, current_turn=1, intensity=0.5)
|
||||
after = pe.adjusted_threat_score(0, 1, 1)
|
||||
@@ -138,7 +104,7 @@ class TestThreatPoliticsIntegration:
|
||||
|
||||
def test_memory_aggression_raises_adjusted_score(self):
|
||||
from commander_ai_lab.sim.politics.memory import ActionType
|
||||
gs, mem, ch, pe = self._build()
|
||||
gs, ta, mem, ch, pe = self._build()
|
||||
before = pe.adjusted_threat_score(0, 2, 1)
|
||||
for _ in range(5):
|
||||
mem.record(1, 2, 0, ActionType.ATTACKED)
|
||||
@@ -146,14 +112,12 @@ class TestThreatPoliticsIntegration:
|
||||
assert after > before
|
||||
|
||||
def test_top_threat_matches_assessor(self):
|
||||
from commander_ai_lab.sim.threat_assessor import assess_threats
|
||||
gs, mem, ch, pe = self._build()
|
||||
gs, ta, mem, ch, pe = self._build()
|
||||
# Give seat 3 a huge life lead to inflate threat
|
||||
gs.players[3].life = 5 # low life — looks like they need a kill
|
||||
threats = assess_threats(gs, viewer_seat=0)
|
||||
# assess_threats returns a ThreatScore per non-eliminated seat excluding none
|
||||
# With 4 players, viewer seat 0 is included → 4 scores
|
||||
assert len(threats) == 4
|
||||
threats = ta.assess_threats(viewer_seat=0)
|
||||
# Just confirm assess_threats returns 3 keys for a 4-player game
|
||||
assert len(threats) == 3
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -315,7 +279,7 @@ class TestTurnManagerIntegration:
|
||||
on_thinking=on_thinking,
|
||||
config=TurnManagerConfig(ai_decision_delay=0.0, max_turns=2),
|
||||
)
|
||||
asyncio.run(tm.run_game())
|
||||
asyncio.get_event_loop().run_until_complete(tm.run_game())
|
||||
# Game should have fired at least one event
|
||||
assert len(events) >= 1
|
||||
|
||||
@@ -343,7 +307,7 @@ class TestTurnManagerIntegration:
|
||||
on_thinking=on_thinking,
|
||||
config=TurnManagerConfig(ai_decision_delay=0.0, max_turns=1),
|
||||
)
|
||||
asyncio.run(tm.run_game())
|
||||
asyncio.get_event_loop().run_until_complete(tm.run_game())
|
||||
# If phases were emitted, they should start with untap
|
||||
if phases_seen:
|
||||
assert phases_seen[0] in ("untap", "upkeep", "draw", "main1")
|
||||
@@ -373,7 +337,7 @@ class TestTurnManagerIntegration:
|
||||
on_thinking=on_thinking,
|
||||
config=TurnManagerConfig(ai_decision_delay=0.0, max_turns=3),
|
||||
)
|
||||
asyncio.run(tm.run_game())
|
||||
asyncio.get_event_loop().run_until_complete(tm.run_game())
|
||||
assert game_over_fired[0] is True
|
||||
|
||||
|
||||
|
||||
@@ -92,9 +92,9 @@ class TestCommanderPlayer:
|
||||
|
||||
def test_commander_damage_death(self):
|
||||
cp = CommanderPlayer(base=Player(name="Test"))
|
||||
cp.base.commander_damage_received = {0: 20, 1: 5}
|
||||
cp.commander_damage_received = {0: 20, 1: 5}
|
||||
assert not cp.is_dead_to_commander_damage()
|
||||
cp.base.commander_damage_received[0] = 21
|
||||
cp.commander_damage_received[0] = 21
|
||||
assert cp.is_dead_to_commander_damage()
|
||||
|
||||
def test_to_dict_json_serializable(self):
|
||||
|
||||
+4
-65
@@ -39,34 +39,6 @@ class _StubPlayer:
|
||||
library: list = field(default_factory=list)
|
||||
graveyard: list = field(default_factory=list)
|
||||
battlefield: list = field(default_factory=list)
|
||||
exile: list = field(default_factory=list)
|
||||
command_zone: list = field(default_factory=list)
|
||||
commander_zone: list = field(default_factory=list)
|
||||
commander_cast_count: int = 0
|
||||
commander_damage_received: dict = field(default_factory=dict)
|
||||
|
||||
def commander_tax(self) -> int:
|
||||
return self.commander_cast_count * 2
|
||||
|
||||
class mana_pool:
|
||||
"""Stub mana pool."""
|
||||
W = U = B = R = G = C = 0
|
||||
def total(self) -> int: return 0
|
||||
def to_dict(self) -> dict: return {"W":0,"U":0,"B":0,"R":0,"G":0,"C":0,"total":0}
|
||||
|
||||
mana_pool = mana_pool()
|
||||
|
||||
|
||||
class _StubSimState:
|
||||
"""Minimal SimState stub — delegates to player battlefields."""
|
||||
|
||||
def __init__(self, players: list) -> None:
|
||||
self._players = players
|
||||
|
||||
def get_battlefield(self, seat: int) -> list:
|
||||
if 0 <= seat < len(self._players):
|
||||
return self._players[seat].battlefield
|
||||
return []
|
||||
|
||||
|
||||
class _StubGameState:
|
||||
@@ -74,35 +46,11 @@ class _StubGameState:
|
||||
|
||||
def __init__(self, num_players: int = 4):
|
||||
self.players = [_StubPlayer(name=f"P{i}", life=40) for i in range(num_players)]
|
||||
self.commander_players = self.players # prompt_builder iterates this
|
||||
self.turn = 0
|
||||
self.current_phase = "main1"
|
||||
self.active_player_seat = 0
|
||||
self.priority_seat = 0
|
||||
self.land_drop_used = False
|
||||
self._move_counter = 0
|
||||
self.stack: list = []
|
||||
self.sim_state = _StubSimState(self.players)
|
||||
|
||||
def active_player(self):
|
||||
if 0 <= self.active_player_seat < len(self.players):
|
||||
return self.players[self.active_player_seat]
|
||||
return None
|
||||
|
||||
def priority_player(self):
|
||||
if 0 <= self.priority_seat < len(self.players):
|
||||
return self.players[self.priority_seat]
|
||||
return None
|
||||
|
||||
def battlefield(self, seat: int) -> list:
|
||||
"""Return the battlefield for the given seat."""
|
||||
return self.players[seat].battlefield
|
||||
|
||||
def stack_is_empty(self) -> bool:
|
||||
return len(self.stack) == 0
|
||||
|
||||
def living_players(self) -> list:
|
||||
return [p for p in self.players if not p.eliminated]
|
||||
|
||||
def get_legal_moves(self, seat: int) -> list[dict]:
|
||||
"""Always return one pass move per seat."""
|
||||
@@ -114,14 +62,6 @@ class _StubGameState:
|
||||
def apply_move(self, seat: int, move_id: int) -> None:
|
||||
self._move_counter += 1
|
||||
|
||||
def to_dict(self) -> dict:
|
||||
return {
|
||||
"turn": self.turn,
|
||||
"current_phase": self.current_phase,
|
||||
"active_player_seat": self.active_player_seat,
|
||||
"players": [{"name": p.name, "life": p.life} for p in self.players],
|
||||
}
|
||||
|
||||
|
||||
def _stub_gs(num_players: int = 4) -> _StubGameState:
|
||||
return _StubGameState(num_players=num_players)
|
||||
@@ -160,13 +100,12 @@ def _make_tm(
|
||||
class TestThreatAssessor:
|
||||
def _gs_with_creatures(self) -> _StubGameState:
|
||||
gs = _stub_gs(4)
|
||||
# Give seat 0 a big creature — use Card from sim.models for full API compat
|
||||
from commander_ai_lab.sim.models import Card
|
||||
# Give seat 0 a big creature
|
||||
gs.players[0].battlefield = [
|
||||
Card(name="Dragon", type_line="Creature — Dragon", pt="6/6", power="6", toughness="6"),
|
||||
Card(name="Forest", type_line="Basic Land — Forest"),
|
||||
{"name": "Dragon", "type": "creature", "pt": "6/6", "oracle": ""},
|
||||
{"name": "Forest", "type": "land", "pt": "", "oracle": ""},
|
||||
]
|
||||
gs.players[1].hand = [Card(name=f"Card{i}") for i in range(7)]
|
||||
gs.players[1].hand = [{"name": f"Card{i}"} for i in range(7)]
|
||||
return gs
|
||||
|
||||
def test_returns_score_per_non_eliminated_player(self):
|
||||
|
||||
+3
-12
@@ -15,21 +15,12 @@ import pytest
|
||||
# Fixtures
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _reset_session_store():
|
||||
"""Reset SessionStore singleton and api module _store before/after each test."""
|
||||
from commander_ai_lab.web.session_store import SessionStore
|
||||
SessionStore._instance = None
|
||||
# Also reset the module-level _store in the API router
|
||||
import commander_ai_lab.web.routers.api as api_mod
|
||||
api_mod._store = SessionStore()
|
||||
yield
|
||||
SessionStore._instance = None
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def app():
|
||||
"""Create a fresh FastAPI app for each test."""
|
||||
# Reset singleton so tests don't share session state
|
||||
from commander_ai_lab.web.session_store import SessionStore
|
||||
SessionStore._instance = None
|
||||
from commander_ai_lab.web.app import create_app
|
||||
return create_app()
|
||||
|
||||
|
||||
@@ -1,291 +0,0 @@
|
||||
"""
|
||||
Phase 5 Architecture Follow-Up — Unit Tests
|
||||
============================================
|
||||
Tests for the three approved decisions:
|
||||
1. Zone embedding boundary is explicit (docs + code + assertion)
|
||||
2. SQLite WAL-backed online learning store
|
||||
3. Forge-only default weights + mixed-mode presets
|
||||
|
||||
Run with: pytest tests/test_phase5_followup.py -v
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import os
|
||||
import sqlite3
|
||||
import tempfile
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
|
||||
# ====================================================================
|
||||
# Decision 1: Zone Embedding Boundary
|
||||
# ====================================================================
|
||||
|
||||
class TestZoneEmbeddingBoundary:
|
||||
"""Verify that the zone embedding contract is explicit and enforced."""
|
||||
|
||||
def test_state_dims_total_zone_dim(self):
|
||||
from ml.config.scope import STATE_DIMS
|
||||
# 4 zones × 2 players × 768 = 6144
|
||||
assert STATE_DIMS.total_zone_dim == 4 * 2 * 768 == 6144
|
||||
|
||||
def test_state_dims_total_state_dim(self):
|
||||
from ml.config.scope import STATE_DIMS
|
||||
# 29 global + 6144 zone + 4 playstyle = 6177
|
||||
assert STATE_DIMS.total_state_dim == 6177
|
||||
|
||||
def test_zone_pool_dim_matches_card_embedding_dim(self):
|
||||
from ml.config.scope import STATE_DIMS
|
||||
# Zone pool output is same size as card embedding input
|
||||
assert STATE_DIMS.zone_pool_dim == STATE_DIMS.card_embedding_dim == 768
|
||||
|
||||
def test_empty_zone_produces_zero_vector(self):
|
||||
"""Empty zone must produce a zero vector of exactly zone_pool_dim."""
|
||||
from ml.config.scope import STATE_DIMS
|
||||
from ml.encoder.state_encoder import CardEmbeddingIndex
|
||||
|
||||
idx = CardEmbeddingIndex()
|
||||
# Even without loading, mean_pool_zone returns a zero vec
|
||||
vec = idx.mean_pool_zone([])
|
||||
assert vec.shape == (STATE_DIMS.zone_pool_dim,)
|
||||
assert np.all(vec == 0.0)
|
||||
|
||||
def test_encode_zones_shape_with_empty_players(self):
|
||||
"""_encode_zones must always return exactly total_zone_dim floats."""
|
||||
from ml.config.scope import STATE_DIMS
|
||||
from ml.encoder.state_encoder import CardEmbeddingIndex, StateEncoder
|
||||
|
||||
idx = CardEmbeddingIndex()
|
||||
enc = StateEncoder(idx)
|
||||
|
||||
# Two players with empty zones
|
||||
players = [
|
||||
{"hand": [], "battlefield": [], "graveyard": [], "command_zone": []},
|
||||
{"hand": [], "battlefield": [], "graveyard": [], "command_zone": []},
|
||||
]
|
||||
zone_vec = enc._encode_zones(players)
|
||||
assert zone_vec.shape == (STATE_DIMS.total_zone_dim,)
|
||||
# All zeros because all zones are empty
|
||||
assert np.all(zone_vec == 0.0)
|
||||
|
||||
def test_full_encode_shape(self):
|
||||
"""Full state vector must be exactly total_state_dim."""
|
||||
from ml.config.scope import STATE_DIMS
|
||||
from ml.encoder.state_encoder import CardEmbeddingIndex, StateEncoder
|
||||
|
||||
idx = CardEmbeddingIndex()
|
||||
enc = StateEncoder(idx)
|
||||
|
||||
decision = {
|
||||
"turn": 3,
|
||||
"phase": "main_1",
|
||||
"active_seat": 0,
|
||||
"players": [
|
||||
{
|
||||
"seat": 0, "life": 40, "cmdr_dmg": 0, "mana": 4,
|
||||
"cmdr_tax": 0, "creatures": 2, "lands": 4,
|
||||
"hand": ["Island", "Counterspell"],
|
||||
"battlefield": ["Tundra"],
|
||||
"graveyard": [],
|
||||
"command_zone": [],
|
||||
},
|
||||
{
|
||||
"seat": 1, "life": 38, "cmdr_dmg": 0, "mana": 3,
|
||||
"cmdr_tax": 0, "creatures": 1, "lands": 3,
|
||||
"hand": [],
|
||||
"battlefield": [],
|
||||
"graveyard": [],
|
||||
"command_zone": [],
|
||||
},
|
||||
],
|
||||
}
|
||||
state = enc.encode(decision, playstyle="control")
|
||||
assert state.shape == (STATE_DIMS.total_state_dim,)
|
||||
assert state.dtype == np.float32
|
||||
|
||||
def test_boundary_docstring_present(self):
|
||||
"""StateDimensions must document the zone embedding boundary."""
|
||||
from ml.config.scope import StateDimensions
|
||||
assert "zone embedding boundary" in StateDimensions.__doc__.lower()
|
||||
|
||||
|
||||
# ====================================================================
|
||||
# Decision 2: SQLite WAL Online Learning Store
|
||||
# ====================================================================
|
||||
|
||||
class TestOnlineLearningStore:
|
||||
"""Verify the SQLite WAL-backed online learning store."""
|
||||
|
||||
@pytest.fixture
|
||||
def store(self, tmp_path):
|
||||
from ml.serving.online_learning_store import OnlineLearningStore
|
||||
db_path = str(tmp_path / "test_online.db")
|
||||
s = OnlineLearningStore(db_path=db_path)
|
||||
s.init_db()
|
||||
return s
|
||||
|
||||
def test_init_creates_db(self, store):
|
||||
assert os.path.exists(store.db_path)
|
||||
|
||||
def test_wal_mode_enabled(self, store):
|
||||
conn = store._get_conn()
|
||||
mode = conn.execute("PRAGMA journal_mode").fetchone()[0]
|
||||
assert mode == "wal"
|
||||
|
||||
def test_record_and_fetch(self, store):
|
||||
snapshot = {"turn": 1, "phase": "main_1", "players": []}
|
||||
row_id = store.record_decision(
|
||||
snapshot=snapshot,
|
||||
action_idx=3,
|
||||
confidence=0.85,
|
||||
playstyle="control",
|
||||
temperature=0.8,
|
||||
greedy=False,
|
||||
)
|
||||
assert row_id >= 1
|
||||
|
||||
decisions = store.fetch_decisions()
|
||||
assert len(decisions) == 1
|
||||
d = decisions[0]
|
||||
assert d["action_idx"] == 3
|
||||
assert d["confidence"] == pytest.approx(0.85)
|
||||
assert d["playstyle"] == "control"
|
||||
assert d["temperature"] == pytest.approx(0.8)
|
||||
assert d["greedy"] == 0
|
||||
assert d["snapshot"]["turn"] == 1
|
||||
|
||||
def test_count(self, store):
|
||||
assert store.count() == 0
|
||||
store.record_decision({"t": 1}, 0, 0.5)
|
||||
store.record_decision({"t": 2}, 1, 0.6)
|
||||
assert store.count() == 2
|
||||
assert store.count(only_unexported=True) == 2
|
||||
|
||||
def test_mark_exported(self, store):
|
||||
store.record_decision({"t": 1}, 0, 0.5)
|
||||
store.record_decision({"t": 2}, 1, 0.6)
|
||||
store.record_decision({"t": 3}, 2, 0.7)
|
||||
|
||||
# Mark first two as exported
|
||||
updated = store.mark_exported(up_to_rowid=2)
|
||||
assert updated == 2
|
||||
assert store.count(only_unexported=True) == 1
|
||||
|
||||
# Fetch only unexported
|
||||
remaining = store.fetch_decisions(only_unexported=True)
|
||||
assert len(remaining) == 1
|
||||
assert remaining[0]["action_idx"] == 2
|
||||
|
||||
def test_fetch_since_rowid(self, store):
|
||||
ids = []
|
||||
for i in range(5):
|
||||
ids.append(store.record_decision({"t": i}, i, 0.5))
|
||||
|
||||
# Fetch only rows after id 3
|
||||
results = store.fetch_decisions(since_rowid=ids[2], only_unexported=False)
|
||||
assert len(results) == 2 # ids[3] and ids[4]
|
||||
assert results[0]["action_idx"] == 3
|
||||
|
||||
def test_fetch_limit(self, store):
|
||||
for i in range(10):
|
||||
store.record_decision({"t": i}, i % 8, 0.5)
|
||||
results = store.fetch_decisions(limit=3)
|
||||
assert len(results) == 3
|
||||
|
||||
def test_close_and_reopen(self, store):
|
||||
store.record_decision({"t": 1}, 0, 0.5)
|
||||
store.close()
|
||||
# Re-open by calling _get_conn again
|
||||
assert store.count() == 1
|
||||
|
||||
def test_snapshot_stored_as_compact_json(self, store):
|
||||
"""Snapshots should be stored as compact JSON (no extra whitespace)."""
|
||||
store.record_decision({"key": "value", "num": 42}, 0, 0.5)
|
||||
conn = store._get_conn()
|
||||
raw = conn.execute(
|
||||
"SELECT snapshot FROM online_decisions WHERE id=1"
|
||||
).fetchone()[0]
|
||||
# Compact JSON has no spaces after separators
|
||||
assert " " not in raw
|
||||
assert json.loads(raw) == {"key": "value", "num": 42}
|
||||
|
||||
|
||||
# ====================================================================
|
||||
# Decision 3: Forge-Only Defaults + Mixed-Mode Presets
|
||||
# ====================================================================
|
||||
|
||||
class TestForgeOnlyDefaults:
|
||||
"""Verify default weights are Forge-only (ppo_weight=0.0)."""
|
||||
|
||||
def test_distillation_defaults_forge_only(self):
|
||||
from ml.config.scope import DISTILLATION_DEFAULTS
|
||||
assert DISTILLATION_DEFAULTS.forge_weight == 1.0
|
||||
assert DISTILLATION_DEFAULTS.ppo_weight == 0.0
|
||||
|
||||
def test_distillation_config_forge_only(self):
|
||||
from ml.training.distillation_loop import DistillationConfig
|
||||
cfg = DistillationConfig()
|
||||
assert cfg.forge_weight == 1.0
|
||||
assert cfg.ppo_weight == 0.0
|
||||
|
||||
def test_dataset_config_forge_only(self):
|
||||
from ml.data.dataset_builder import DatasetConfig
|
||||
cfg = DatasetConfig()
|
||||
assert cfg.source_weights["forge"] == 1.0
|
||||
assert cfg.source_weights["ppo"] == 0.0
|
||||
|
||||
|
||||
class TestMixedModePresets:
|
||||
"""Verify mixed-mode weight presets exist and are correct."""
|
||||
|
||||
def test_presets_dict_exists(self):
|
||||
from ml.config.scope import MIXED_MODE_PRESETS
|
||||
assert isinstance(MIXED_MODE_PRESETS, dict)
|
||||
assert len(MIXED_MODE_PRESETS) == 3
|
||||
|
||||
def test_forge_only_preset(self):
|
||||
from ml.config.scope import MIXED_MODE_PRESETS
|
||||
p = MIXED_MODE_PRESETS["forge_only"]
|
||||
assert p["forge_weight"] == 1.0
|
||||
assert p["ppo_weight"] == 0.0
|
||||
|
||||
def test_forge_90_10_preset(self):
|
||||
from ml.config.scope import MIXED_MODE_PRESETS
|
||||
p = MIXED_MODE_PRESETS["forge_90_10"]
|
||||
assert p["forge_weight"] == 1.0
|
||||
# ppo_weight ~0.11 gives approximately 10% PPO in the mix
|
||||
assert 0.1 <= p["ppo_weight"] <= 0.15
|
||||
|
||||
def test_forge_80_20_preset(self):
|
||||
from ml.config.scope import MIXED_MODE_PRESETS
|
||||
p = MIXED_MODE_PRESETS["forge_80_20"]
|
||||
assert p["forge_weight"] == 1.0
|
||||
# ppo_weight ~0.25 gives approximately 20% PPO
|
||||
assert 0.2 <= p["ppo_weight"] <= 0.3
|
||||
|
||||
def test_get_preset_weights_valid(self):
|
||||
from ml.config.scope import get_preset_weights
|
||||
w = get_preset_weights("forge_90_10")
|
||||
assert "forge_weight" in w
|
||||
assert "ppo_weight" in w
|
||||
|
||||
def test_get_preset_weights_returns_copy(self):
|
||||
"""get_preset_weights must return a copy, not the original dict."""
|
||||
from ml.config.scope import get_preset_weights, MIXED_MODE_PRESETS
|
||||
w = get_preset_weights("forge_only")
|
||||
w["forge_weight"] = 999
|
||||
assert MIXED_MODE_PRESETS["forge_only"]["forge_weight"] == 1.0
|
||||
|
||||
def test_get_preset_weights_invalid(self):
|
||||
from ml.config.scope import get_preset_weights
|
||||
with pytest.raises(KeyError, match="Unknown preset"):
|
||||
get_preset_weights("nonexistent")
|
||||
|
||||
def test_all_presets_have_both_keys(self):
|
||||
from ml.config.scope import MIXED_MODE_PRESETS
|
||||
for name, preset in MIXED_MODE_PRESETS.items():
|
||||
assert "forge_weight" in preset, f"Preset '{name}' missing forge_weight"
|
||||
assert "ppo_weight" in preset, f"Preset '{name}' missing ppo_weight"
|
||||
@@ -36,7 +36,7 @@ def _engine(personalities=None):
|
||||
|
||||
|
||||
def _run(coro):
|
||||
return asyncio.run(coro)
|
||||
return asyncio.get_event_loop().run_until_complete(coro)
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -217,7 +217,7 @@ class TestPoliticsCommsChannel:
|
||||
async def h(msg): received_seats.append(s)
|
||||
return h
|
||||
import asyncio
|
||||
h = asyncio.run(make_handler())
|
||||
h = asyncio.get_event_loop().run_until_complete(make_handler())
|
||||
channel.register_handler(seat=seat, handler=h)
|
||||
|
||||
msg = ThreatBroadcast(speaker=0, audience=-1,
|
||||
|
||||
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Reference in new issue
Block a user