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ClaudeandClaude Opus 4.6 77ded23aef fix: Phase 1 critical sim fixes — BUG-01, BUG-02, BUG-05 (#82, #84)
BUG-01: Unknown cards no longer default to "Creature". enrich_card() now
sets type_line="Unknown" for cards without Scryfall data. Added
can_attack_or_block() method to Card — only cards with "Creature" in
type_line can participate in combat. Engine combat uses
can_attack_or_block() instead of is_creature().

BUG-02: Implemented get_legal_moves() and apply_move() in
CommanderGameState with actual game logic — land drops, spell casting
(with mana checking), commander casting from command zone, attack
declarations, and instant-speed responses. Replaces the former
pass-only stubs.

BUG-05: Instants and sorceries now go to graveyard after resolution
instead of being placed on the battlefield as permanents. Added
is_permanent(), is_instant(), is_sorcery() helpers to Card model.

Includes 48 new regression tests covering all three bugs plus
integration tests verifying artifacts/unknown cards never appear in
combat. Fixed existing test_engine.py to match current engine API.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-22 17:00:11 +00:00
343 changed files with 5254 additions and 104898 deletions

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# Commander AI Lab — Environment Variables
# Copy this file to .env and fill in your values.
# start-lab.bat will auto-load .env if it exists.
# Commander AI Lab - Environment Variables
# Copy this file to .env and fill in your API keys.
# .env is gitignored and will NOT be committed.
# ── API Keys ──────────────────────────────────────────────────────
ANTHROPIC_API_KEY=your-anthropic-api-key-here
XIMILAR_API_KEY=your-ximilar-key-here
# Ximilar API Key (card scanner / visual AI recognition)
# Get yours at: https://app.ximilar.com/
XIMILAR_API_KEY=your-ximilar-api-key-here
# ── Forge JAR Path ────────────────────────────────────────────────
# Point this to your Forge GUI desktop fat JAR.
FORGE_JAR_PATH=D:/ForgeCommander/forge-repo/forge-gui-desktop/target/forge-gui-desktop-2.0.12-SNAPSHOT-jar-with-dependencies.jar
# Perplexity API Key (AI deck research & generation)
# Get yours at: https://www.perplexity.ai/settings/api
PPLX_API_KEY=your-perplexity-api-key-here
# IMPORTANT: Forge MUST be launched from the forge-gui directory (not forge-gui-desktop/target).
# The JAR looks for res/ relative to its working directory. Without this, you get
# ExceptionInInitializerError on startup.
FORGE_WORKING_DIR=D:/ForgeCommander/forge-repo/forge-gui
# CORS allowed origins (comma-separated)
# Default: http://localhost:5173,http://localhost:8080
# Add your LAN IP if accessing from another machine on your network
ALLOWED_ORIGINS=http://localhost:5173,http://localhost:8080
# ── Deck Paths ────────────────────────────────────────────────────
# Directory containing your precon .dck files.
# Forge reads deck files directly from this folder.
PRECON_DECKS_DIR=D:\ForgeCommander\commander-ai-lab\precon-decks
FORGE_DECKS_DIR=D:\ForgeCommander\commander-ai-lab\precon-decks
# ── Dual-Model AI Brain ─────────────────────────────────────
# Primary brain: GPT-OSS 20B (turn planner / decision maker)
BRAIN_API_BASE=http://localhost:11434
BRAIN_MODEL=gpt-oss:20b
BRAIN_TEMPERATURE=0.3
BRAIN_MAX_TOKENS=1024
BRAIN_TIMEOUT=120.0
# Validator brain: DeepSeek-R1-Distill-Qwen-14B (legality + explanation)
VALIDATOR_ENABLED=true
VALIDATOR_API_BASE=http://localhost:11434
VALIDATOR_MODEL=deepseek-r1:14b
VALIDATOR_TEMPERATURE=0.0
VALIDATOR_MAX_TOKENS=2048
VALIDATOR_TIMEOUT=120.0
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- name: Run tests
run: pytest -v --tb=short tests/ || true
frontend:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: '20'
- name: Build frontend
working-directory: frontend
run: |
npm ci
npm run build
- name: Run frontend tests
working-directory: frontend
run: npx vitest run
java-tests:
runs-on: ubuntu-latest
steps:
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# Commander AI Lab
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.
## What It Does
| Layer | What it is |
|---|---|
| **Monte Carlo Engine** | Pure-Python headless sim — runs thousands of games in minutes, no JVM needed |
| **Forge Engine** | Java/Forge rules-complete sim for ground-truth validation |
| **Overnight Runner** | Unattended batch runner — runs sims, updates sim weights, trains neural net |
| **ML Pipeline** | Outcome-weighted RL nudges card scoring weights; neural net trains on decision logs |
| **Deck Builder** | 7-step LLM pipeline (EDHrec → Scryfall → Ollama) now injected with sim-learned insights |
| **AI Coach** | LLM-powered coaching sessions (Anthropic/Ollama) with streaming support |
| **Web UI** | React + FastAPI dashboard for decks, sims, training, and deck building |
Headless batch simulation environment for 3-AI MTG Commander pods.
Run 100+ games, analyze win rates, and stress-test your decks — all from a web UI or CLI.
## Architecture
```
┌─────────────────────────────────────────────────────────────────┐
│ Web UI (React/TypeScript — frontend/) │
│ Deck Builder · Sim Dashboard · Training · Coach │
└────────────────────────┬────────────────────────────────────────┘
│ HTTP/REST + WebSocket
┌────────────────────────┴────────────────────────────────────────┐
│ FastAPI Server (lab_api.py / routes/ — port 8080) │
│ /api/lab/* /api/ml/* /api/coach/* /api/deck-builder/* │
└────────┬──────────────────┬──────────────────┬──────────────────┘
│ │ │
Java subprocess Python sim engine Ollama (local LLM)
(Forge rules) (Monte Carlo) qwen2.5:7b + others
│ │
┌────────┴───────┐ ┌───────┴────────────────────────────────────┐
│ Forge Engine │ │ src/commander_ai_lab/ │
│ (rules- │ │ sim/ — engine, models, rules │
│ complete) │ │ deck_builder/ — 7-step LLM pipeline │
└────────────────┘ │ coach/ — streaming LLM coach │
└────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────┐
│ Web Browser (ai-lab.js + ai-lab.css) │
│ Select decks → Start batch → Poll progress → View stats │
└─────────────────────┬───────────────────────────────────────┘
│ HTTP (REST)
┌─────────────────────┴───────────────────────────────────────┐
│ Python FastAPI Server (lab_api.py, port 8080) │
│ /api/lab/start — spawn Java batch runner subprocess │
│ /api/lab/status — poll progress (parses stdout) │
│ /api/lab/result — return completed JSON results │
│ /api/lab/decks — list decks from Forge user data │
│ /api/lab/history— browse past batch runs │
│ /api/lab/log — stream live console output │
└─────────────────────┬───────────────────────────────────────┘
│ subprocess (java -jar)
┌─────────────────────┴───────────────────────────────────────┐
│ Java CLI (LabCli.java + BatchRunner + MultiThreadRunner) │
│ Parses Forge sim output → GameResult objects → JSON │
└─────────────────────┬───────────────────────────────────────┘
│ subprocess per game
┌─────────────────────┴───────────────────────────────────────┐
│ Card Forge Engine (forge-gui-desktop sim mode) │
│ java -jar forge.jar sim -d "deck1" "deck2" "deck3" │
│ -f commander -n 1 -q │
└─────────────────────────────────────────────────────────────┘
```
## Quick Start (Windows)
**Prerequisites:** Java 17+, Python 3.10+, Maven 3.8+, [Forge](https://github.com/Card-Forge/forge) built at `D:\ForgeCommander\forge-repo`
### Prerequisites
- **Java 17+** (`java -version`)
- **Python 3.10+** (`python --version`)
- **Maven 3.8+** (`mvn --version`)
- **Forge repo** cloned and built at `D:\ForgeCommander\forge-repo`
### 1. Build Forge (one-time)
```powershell
# 1. Build Forge (one-time)
cd D:\ForgeCommander\forge-repo
mvn package -pl forge-gui-desktop "-DskipTests" "-Drevision=2.0.12-SNAPSHOT" -am
```
# 2. Build Commander AI Lab
### 2. Build Commander AI Lab
```powershell
cd D:\ForgeCommander\commander-ai-lab
mvn package "-DskipTests"
```
This produces `target/commander-ai-lab-1.0.0-SNAPSHOT.jar` (shaded fat JAR).
# 3. Install Python deps
pip install -e .
### 3. Install Python dependencies
```powershell
pip install fastapi uvicorn
```
# 4. Launch
### 4. Launch the Web UI
**Option A — One-click launcher:**
```powershell
.\start-lab.bat
# → open http://localhost:8080
```
Edit the paths at the top of `start-lab.bat` if needed.
## Overnight AFK Runner
Runs batch sims unattended, then updates card weights and trains the neural net:
**Option B — Manual launch:**
```powershell
python overnight-run.py # default: 11.5h DeepSeek sims
python overnight-run.py --batches 20 --games 50 # fixed batch count
python overnight-run.py --no-update-weights # skip weight update
python overnight-run.py --no-train # skip neural net training
python lab_api.py `
--forge-jar "D:\ForgeCommander\forge-repo\forge-gui-desktop\target\forge-gui-desktop-2.0.12-SNAPSHOT-jar-with-dependencies.jar" `
--forge-dir "D:\ForgeCommander\forge-repo\forge-gui" `
--port 8080
```
**What happens after sims complete:**
1. `update_weights.py` — nudges `learned_weights.json` from decision logs (feeds deck builder)
2. `/api/ml/train` — trains the neural net on the full decision dataset
## Sim → Deck Builder Feedback Loop
Simulation outcomes automatically improve deck recommendations:
```
Overnight sims → decisions_*.jsonl
↓
update_weights.py → learned_weights.json
↓
sim_insights.py → natural-language insight block
↓
Ollama prompts (suggest_cards + enforce_deck_ratios)
↓
Better card recommendations
```
When active, `BuildResult.sources_consulted` includes `"sim_weights"`. No-op until real sim data exists.
## Deck Builder Pipeline
The `POST /api/deck-builder/build` endpoint runs 7 steps:
1. Resolve commander via Scryfall
2. Fetch EDHrec recommendations
3. Fetch Scryfall candidates by category (ramp, removal, draw, lands)
4. Ollama suggests synergy/protection/wincon cards ← **sim insights injected here**
5. Filter by color identity, collection, ban list
6. Ollama enforces ratios (trim/expand to 99) ← **sim insights injected here**
7. Assemble final deck
## ML Pipeline
Open `http://localhost:8080` — select 3 decks, set game count, click **Run AI Sims**.
### 5. CLI-only usage (no web server)
```powershell
# Update sim card weights from decision logs (runs automatically in overnight-run.py)
python -m ml.scripts.update_weights --min-games 10 --lr 0.05 --dry-run
cd D:\ForgeCommander\forge-repo\forge-gui
# Reset weights to defaults
python -m ml.scripts.update_weights --reset
# Generate synthetic training data
python ml/scripts/generate_synthetic_data.py
java -jar "D:\ForgeCommander\commander-ai-lab\target\commander-ai-lab-1.0.0-SNAPSHOT.jar" `
--forge-jar "..\forge-gui-desktop\target\forge-gui-desktop-2.0.12-SNAPSHOT-jar-with-dependencies.jar" `
--forge-dir "." `
--deck1 "Edgar Markov" `
--deck2 "Grimgrin" `
--deck3 "Xyris" `
--games 100 `
--threads 4 `
--output results/batch-100.json
```
Learned weights are clamped to `[-20.0, 20.0]` and stored in `src/commander_ai_lab/sim/learned_weights.json`.
## Scaling Tests
## Python Simulator API
```python
from commander_ai_lab.lab.experiments import build_deck, run_simulation
deck = build_deck(["Sol Ring", "Cultivate", "Lightning Bolt"] + ["Forest"] * 36)
stats = run_simulation(deck, num_games=100, name_a="My Deck")
print(f"Win rate: {stats['win_rate']:.1%}, Avg turns: {stats['avg_turns']:.1f}")
### Single-threaded baseline (10 games)
```powershell
java -jar target\commander-ai-lab-1.0.0-SNAPSHOT.jar `
--forge-jar "..." --forge-dir "..." `
--deck1 "Edgar Markov" --deck2 "Grimgrin" --deck3 "Xyris" `
--games 10 --threads 1 --output results/baseline-10.json
```
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
java -jar target\commander-ai-lab-1.0.0-SNAPSHOT.jar `
--forge-jar "..." --forge-dir "..." `
--deck1 "Edgar Markov" --deck2 "Grimgrin" --deck3 "Xyris" `
--games 10 --threads 2 --output results/mt-10-t2.json
```
### Scale to 100 games (4 threads)
```powershell
java -jar target\commander-ai-lab-1.0.0-SNAPSHOT.jar `
--forge-jar "..." --forge-dir "..." `
--deck1 "Edgar Markov" --deck2 "Grimgrin" --deck3 "Xyris" `
--games 100 --threads 4 --output results/scale-100-t4.json
```
### Maximum throughput test (100 games, 8 threads)
```powershell
java -jar target\commander-ai-lab-1.0.0-SNAPSHOT.jar `
--forge-jar "..." --forge-dir "..." `
--deck1 "Edgar Markov" --deck2 "Grimgrin" --deck3 "Xyris" `
--games 100 --threads 8 --seed 42 --output results/scale-100-t8-seed42.json
```
### Performance comparison script
Run different thread counts and compare sims/sec:
```powershell
# Baseline: 1 thread
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
# 2 threads
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
# 4 threads
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
# 8 threads
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
```
Then compare the `simsPerSecond` values in each output JSON to see scaling behavior.
## API Reference
| Endpoint | Method | Description |
|---|---|---|
| `/api/lab/decks` | GET | List available Commander decks |
| `/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"],
"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
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# Coach clients — Anthropic Claude, LM Studio
# Coach clients — Perplexity, LM Studio
-401
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@@ -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
+64 -342
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@@ -5,11 +5,10 @@ Main orchestrator: loads deck reports, identifies underperformers,
finds replacement candidates via embeddings, builds prompts,
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
@@ -17,16 +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
@@ -34,18 +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:
"""
@@ -64,18 +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)
@@ -90,59 +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
@@ -155,14 +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 = []
@@ -184,23 +123,23 @@ class CoachService:
continue
return sessions
# ── Main Coaching Pipeline ───────────────────────
async def run_coaching_session(
self,
deck_id: str,
goals: Optional[CoachGoals] = None,
fallback_report: Optional[DeckReport] = None,
) -> CoachSession:
# ── Main Coaching Pipeline ─────────────────────────────────
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:
@@ -212,6 +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
@@ -219,17 +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 [])
@@ -248,81 +196,17 @@ class CoachService:
else:
logger.warning("Embeddings not loaded — skipping candidate search")
# Phase 4a: behavior-aware RAG — primary + replacement-effect secondary query
rag_cards: List[dict] = []
try:
from services.rag_store import query_cards
# Primary: commander synergy context
base_query = f"{report.commander} {' '.join(report.colorIdentity)} commander deck"
rag_cards = query_cards(base_query, n_results=10, color_identity=report.colorIdentity)
# Secondary: replacement effects / graveyard hate / protection
if len(rag_cards) < 15:
repl_cards = query_cards(
f"replacement effect graveyard {' '.join(report.colorIdentity)}",
n_results=5,
color_identity=report.colorIdentity,
require_replacement=True,
)
# Deduplicate by name before merging
existing_names = {c["name"] for c in rag_cards}
rag_cards += [c for c in repl_cards if c["name"] not in existing_names]
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)
# Phase 4b: rules context for grounding the coach prompt
rules_context: List[dict] = []
try:
from services.rag_store import query_rules
rules_context = query_rules(
f"Commander rules {report.commander} {' '.join(report.colorIdentity)}",
n_results=3,
)
except Exception:
pass
# 4. Build prompts
system_prompt = build_system_prompt(report, goals)
user_prompt = build_user_prompt(report, candidates, rag_cards=rag_cards, rules_context=rules_context)
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)
user_prompt = build_user_prompt(report, candidates)
# 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,
@@ -332,109 +216,31 @@ class CoachService:
completionTokens=llm_response.completion_tokens,
goals=goals,
)
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 4a: light RAG query for quick digest
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) # 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(
@@ -442,6 +248,8 @@ class CoachService:
reason=cut_data.get("reason", ""),
replacementOptions=cut_data.get("replacementOptions", []),
))
# Suggested adds
for add_data in data.get("suggestedAdds", []):
if isinstance(add_data, dict):
session.suggestedAdds.append(SuggestedAdd(
@@ -450,112 +258,26 @@ class CoachService:
reason=add_data.get("reason", ""),
synergyWith=add_data.get("synergyWith", []),
))
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", ""),
)
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"]
})
rq = data.get("rampQuality")
if isinstance(rq, dict):
session.rampQuality = RampQuality(**{
k: rq.get(k, "") for k in ["manaRocks", "landFetch", "manaDorks", "costReducers", "fragility", "canReachFourByTurnThree"]
})
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", ""),
)
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", ""),
))
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", ""),
))
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", ""),
)
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", ""),
)
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
View File
@@ -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
View File
@@ -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
View File
@@ -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
View File
@@ -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):
+41 -375
View File
@@ -4,24 +4,18 @@ Commander AI Lab — Coach Prompt Template
Constructs system and user prompts for the LLM coach.
Injects deck report data, underperformer analysis, and
candidate replacement cards into a structured template.
Phase 1 additions (#108):
- Sim Insights section: deck-level opening hand quality, curve velocity,
synergy outliers, and archetype weak spots surfaced directly in the
user prompt so Claude reasons from numbers, not vibes.
- _format_archetypes() annotates weak spots and strengths inline.
- _format_top_cards() adds keptInOpeningHandRate per card.
"""
import json
from typing import List, Dict, Optional
from .models import DeckReport, CoachGoals, CardPerformance
from .config import MAX_CANDIDATES_PER_UNDERPERFORMER, MAX_UNDERPERFORMERS
# ════════════════════════════════════════════════════════════
# ══════════════════════════════════════════════════════════════
# System Prompt
# ════════════════════════════════════════════════════════════
# ══════════════════════════════════════════════════════════════
SYSTEM_PROMPT_TEMPLATE = """You are an expert Magic: The Gathering Commander deck coach.
You analyze deck performance reports from simulation data and provide specific,
@@ -33,197 +27,44 @@ 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.
- The Sim Insights section shows pre-computed deck-level signals — use these directly in your reasoning.
- Cards flagged as [OPENING HAND TRAP] have keptInOpeningHandRate below the deck average — treat as mulligan liabilities.
- Cards flagged as [LATE CASTER] have avgTurnCast > 6 — consider whether they fit the deck's tempo.
- Cards flagged as [ISOLATED] have synergyScore in the bottom 3 of the deck — they may not support the gameplan.
- Archetypes flagged as [WEAK SPOT] in the Archetype Win Rates section are where this deck loses most — prioritize fixes for those matchups.
- 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 the [WEAK SPOT] archetypes flagged in Sim Insights, 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}.
- Cards flagged [OPENING HAND TRAP] have low keptInOpeningHandRate — prime cut candidates.
- Cards flagged [WEAK SPOT] in archetype win rates show where the deck loses most.
{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 Template
# ════════════════════════════════════════════════════════════
# ══════════════════════════════════════════════════════════════
# User Prompt Builder
# ══════════════════════════════════════════════════════════════
USER_PROMPT_TEMPLATE = """## Deck Report: {deck_name}
Commander: {commander}
@@ -238,29 +79,19 @@ Avg Game Length: {avg_game_length:.1f} turns
- Card Types: {type_summary}
- Functional Roles: {role_summary}
### Sim Insights (pre-computed deck-level signals)
{sim_insights_section}
### 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."""
@@ -268,6 +99,7 @@ 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.")
@@ -294,148 +126,42 @@ def _format_curve(buckets: List[int]) -> str:
def _format_top_cards(cards: List[CardPerformance], top_n: int = 10) -> str:
"""Format the best performing cards with extended stats.
Phase 1: adds keptInOpeningHandRate so Claude sees hand quality for
the good cards too, not just the underperformers.
"""
"""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 ""
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}, "
f"keptInOpeningHand={c.keptInOpeningHandRate:.1%}"
f"{turn_str}{tags}"
)
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."""
"""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:
turn_str = f", avgTurnCast={c.avgTurnCast:.1f}" if c.avgTurnCast is not None else ""
flags = []
if c.keptInOpeningHandRate < 0.25:
flags.append("OPENING HAND TRAP")
if c.avgTurnCast is not None and c.avgTurnCast > 6:
flags.append("LATE CASTER")
if c.synergyScore < 0.1:
flags.append("ISOLATED")
flag_str = f" [{', '.join(flags)}]" if flags else ""
lines.append(
f"- {c.name}{flag_str}: 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}"
)
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_sim_insights(cards: List[CardPerformance],
archetype_rates: Dict[str, float]) -> str:
"""Compute and format deck-level sim signals for the Sim Insights section.
Phase 1 (#108): surfaces pre-computed per-card stats as deck-level
aggregates so Claude reasons from numbers directly.
Signals produced:
1. Opening hand quality — deck avg keptInOpeningHandRate + worst offenders
2. Curve velocity — castRate-weighted avg avgTurnCast + late-caster flags
3. Synergy outliers — bottom-3 synergyScore cards flagged as [ISOLATED]
4. Archetype weak spots — archetypes < 40% win rate flagged [WEAK SPOT]
"""
if not cards:
return "No simulation data available."
lines = []
# ── 1. Opening hand quality ───────────────────────────────────────────
hand_rates = [c.keptInOpeningHandRate for c in cards if c.keptInOpeningHandRate > 0]
if hand_rates:
avg_keep = sum(hand_rates) / len(hand_rates)
lines.append(f"Opening Hand Quality: deck avg keptInOpeningHandRate = {avg_keep:.1%}")
# Worst offenders: cards significantly below the deck average
threshold = avg_keep * 0.6 # >40% below avg is an outlier
offenders = sorted(
[c for c in cards if c.keptInOpeningHandRate > 0 and c.keptInOpeningHandRate < threshold],
key=lambda c: c.keptInOpeningHandRate
)[:3]
if offenders:
lines.append(" Opening hand traps (keptInOpeningHandRate far below deck avg):")
for c in offenders:
lines.append(f" - {c.name}: {c.keptInOpeningHandRate:.1%} [OPENING HAND TRAP]")
else:
lines.append("Opening Hand Quality: no keptInOpeningHandRate data available")
# ── 2. Curve velocity ───────────────────────────────────────────────
cast_cards = [c for c in cards if c.avgTurnCast is not None and c.castRate > 0]
if cast_cards:
total_weight = sum(c.castRate for c in cast_cards)
if total_weight > 0:
weighted_avg_turn = sum(
c.avgTurnCast * c.castRate for c in cast_cards
) / total_weight
lines.append(f"Curve Velocity: castRate-weighted avg avgTurnCast = {weighted_avg_turn:.1f}")
late_casters = sorted(
[c for c in cast_cards if c.avgTurnCast > 6],
key=lambda c: c.avgTurnCast,
reverse=True
)[:3]
if late_casters:
lines.append(" Late casters (avgTurnCast > 6 — may not fit the curve):")
for c in late_casters:
lines.append(f" - {c.name}: avgTurnCast={c.avgTurnCast:.1f} [LATE CASTER]")
else:
lines.append("Curve Velocity: no avgTurnCast data available")
# ── 3. Synergy outliers ──────────────────────────────────────────────
synergy_cards = sorted(
[c for c in cards if c.castRate > 0.05], # ignore near-never-cast cards
key=lambda c: c.synergyScore
)
if synergy_cards:
bottom3 = synergy_cards[:3]
lines.append("Synergy Outliers (lowest synergyScore among cast cards):")
for c in bottom3:
lines.append(f" - {c.name}: synergyScore={c.synergyScore:.3f} [ISOLATED]")
# ── 4. Archetype weak spots ──────────────────────────────────────────
if archetype_rates:
weak = {k: v for k, v in archetype_rates.items() if v < 0.40}
if weak:
lines.append("Archetype Weak Spots (win rate < 40%):")
for arch, wr in sorted(weak.items(), key=lambda x: x[1]):
lines.append(f" - vs {arch}: {wr:.1%} [WEAK SPOT]")
else:
lines.append("Archetype Weak Spots: none (all matchups >= 40% win rate)")
return "\n".join(lines) if lines else "No sim insights available."
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)."
)
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}':")
@@ -453,55 +179,14 @@ def _format_candidates(candidates: Dict[str, List[dict]]) -> str:
return "\n".join(lines)
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}")
return "\n".join(lines)
def _format_matchups(report: DeckReport) -> str:
"""Format per-opponent matchup data."""
"""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_archetypes(report: DeckReport) -> str:
"""Format per-archetype win rates from DeckMeta.
Phase 1: annotates weak spots ([WEAK SPOT] < 40%) and strengths
([STRENGTH] >= 55%) so Claude sees the signal immediately.
"""
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]):
if wr < 0.40:
tag = " [WEAK SPOT]"
elif wr >= 0.55:
tag = " [STRENGTH]"
else:
tag = ""
lines.append(f"- vs {archetype}: {wr:.1%}{tag}")
lines.append(f"- vs {m.opponentDeck}: {m.winRate:.1%} "
f"({m.gamesPlayed} games)")
return "\n".join(lines)
@@ -512,16 +197,14 @@ def _format_combos(report: DeckReport) -> str:
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%}"
)
lines.append(f"- {cards}: winRate={combo.winRateWhenAssembled:.1%}, "
f"assemblyRate={combo.assemblyRate:.1%}")
return "\n".join(lines)
# ════════════════════════════════════════════════════════════
# ══════════════════════════════════════════════════════════════
# Main Builder Functions
# ════════════════════════════════════════════════════════════
# ══════════════════════════════════════════════════════════════
def build_system_prompt(report: DeckReport,
goals: Optional[CoachGoals] = None) -> str:
@@ -534,29 +217,16 @@ def build_system_prompt(report: DeckReport,
)
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),
)
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.
Phase 1: adds sim_insights_section computed from card-level stats.
"""
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,
@@ -568,14 +238,10 @@ def build_user_prompt(report: DeckReport,
curve_summary=_format_curve(report.structure.curveBuckets),
type_summary=", ".join(type_parts),
role_summary=", ".join(role_parts),
sim_insights_section=_format_sim_insights(
report.cards, report.meta.perArchetypeWinRates),
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),
)
-11
View File
@@ -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
+14 -43
View File
@@ -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 -1
View File
@@ -1,7 +1,7 @@
"""
Commander AI Lab — Substitution Prompt Templates
═════════════════════════════════════════════════
Prompts for the Claude Opus substitution pass.
Prompts for the Perplexity fallback substitution pass.
"""
+2 -2
View File
@@ -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))
+2 -2
View File
@@ -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 = {
+5 -21
View File
@@ -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
View File
@@ -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"
-785
View File
@@ -1,785 +0,0 @@
# Commander-AI-Lab — Unity TCGEngine Commander Board: Implementation Plan (v5)
> **Architecture Principle:** Forge = Rules Authority · FastAPI = Hub · TCGEngine Unity = Renderer · Dual-Brain AI = Decision Engine
---
## System Architecture Overview
```
┌─────────────────────────────────────────────────────────────────┐
│ UNITY (TCGEngine — 2D Board) │
│ PlayerArea x4: Hand | Library | Graveyard | Exile | Command │
│ Battlefield zones per player · Card art from local cache │
│ GameNetworkManager.cs ←── WebSocket ──► FastAPI │
└─────────────────────────────────────────────────────────────────┘
▲ ▼
┌─────────────────────────────────────────────────────────────────┐
│ FASTAPI (commander-ai-lab) │
│ /ws/game — WebSocket relay │
│ /game/action — receive player/AI action, forward to Forge │
│ ForgeSubprocessManager — stdin/stdout pipe to Forge JVM │
│ CardEnricher — injects art_url from local image cache │
│ AIOrchestrator — routes decisions to DeepSeek-R1 or GPT-OSS │
│ ChromaDB RAG — card knowledge scoped per player deck │
│ ai_decisions.jsonl — logs every AI decision (PPO dataset) │
└─────────────────────────────────────────────────────────────────┘
▲ ▼
┌─────────────────────────────────────────────────────────────────┐
│ FORGE (Java — Headless Rules Engine) │
│ Full Commander rules: tax, 21-commander-damage, 40 life │
│ 4-player turn queue · Zone redirects · State-based actions │
│ Emits game state JSON to stdout · Receives actions via stdin │
└─────────────────────────────────────────────────────────────────┘
```
---
## Dual-Brain AI Decision Flow
This is the **core feature** of Commander-AI-Lab. Every AI player decision runs through this pipeline:
```
Forge emits GameStateDTO (JSON)
└─► FastAPI detects active player is AI
└─► select_brain(phase, stack_size)
├─ DeepSeek-R1-14B → combat, stack decisions, removal
└─ GPT-OSS-20B → main phase, ramp, card advantage
└─► ChromaDB.query(player_deck_cards, top_k=5)
└─► build_prompt(state, rag_context, personality)
└─► LLM.generate(prompt)
└─► parse_action_json(response)
├─ validate vs legal_actions[]
├─ log to ai_decisions.jsonl
└─► Forge stdin ← chosen action
```
### Brain Selector (`ai/brain_selector.py`)
```python
from enum import Enum
class Brain(Enum):
DEEPSEEK = "deepseek-r1:14b"
GPT_OSS = "gpt-oss-20b" # adjust to your Ollama model tag
def select_brain(phase: str, stack_size: int) -> Brain:
"""
DeepSeek-R1: combat math, instant-speed stack decisions, targeted removal.
GPT-OSS: sorcery-speed strategy, ramp sequencing, card selection.
"""
combat_phases = {"declare_attackers", "declare_blockers", "combat_damage"}
if phase in combat_phases or stack_size > 0:
return Brain.DEEPSEEK
return Brain.GPT_OSS
```
### Prompt Builder (`ai/prompt_builder.py`)
```python
from chromadb import Client
from .personality import get_personality_prompt
chroma = Client()
card_collection = chroma.get_collection("mtg_cards")
def build_prompt(state: dict, player_id: str, personality: str) -> str:
# Pull card knowledge scoped to THIS player's deck
player_cards = [c["name"] for c in state["players"][player_id]["library"]]
rag_results = card_collection.query(
query_texts=player_cards[:10],
n_results=5
)
card_context = "\n".join(rag_results["documents"][0])
personality_prompt = get_personality_prompt(personality)
return f"""You are an AI playing Magic: The Gathering Commander.
{personality_prompt}
## Current Game State
- Phase: {state['phase']}
- Active Player: {player_id}
- Life Totals: {state['life_totals']}
- Commander Damage Dealt: {state['commander_damage']}
- Stack: {state['stack']}
- Your Hand: {[c['name'] for c in state['players'][player_id]['hand']]}
- Battlefield: {[c['name'] for c in state['players'][player_id]['battlefield']]}
- Available Mana: {state['players'][player_id]['mana_pool']}
## Legal Actions
{state['legal_actions']}
## Card Knowledge (RAG Context)
{card_context}
Respond with a single JSON object:
{{"action": "<action_type>", "card_id": "<id_or_null>", "targets": [], "reasoning": "<brief>"}}
"""
```
### Personality System (`ai/personality.py`)
```python
import random
PERSONALITIES = {
"aggro_beatdown": "You play aggressively. Attack every turn. Remove blockers. Win through combat damage as fast as possible.",
"control_lockdown": "You play control. Counter key threats. Hold up mana for interaction. Win only when the board is locked.",
"combo_enabler": "You dig for your combo pieces. Every decision is evaluated by how it advances your win condition.",
"political_diplomat": "You form alliances. Attack the leader. Make deals. Never be the archenemy.",
"voltron_commander": "Everything buffs your commander. Protect it at all costs. Win through commander damage.",
"stax_prison": "You tax and restrict opponents. Deploy hate pieces. Win through attrition and resource denial.",
"tempo_value": "You trade efficiently. Generate card advantage. Win by being ahead on resources.",
"chaos_wildcard": "You make unpredictable decisions. Prioritize fun and chaos over optimal play.",
}
def assign_personalities(player_ids: list[str], deck_archetypes: dict) -> dict[str, str]:
"""
Assign a personality per AI player at game creation.
80% chance: archetype-matched personality.
20% chance: random wildcard for unpredictability.
"""
assignments = {}
for pid in player_ids:
archetype = deck_archetypes.get(pid, "tempo_value")
if random.random() < 0.20:
assignments[pid] = random.choice(list(PERSONALITIES.keys()))
else:
assignments[pid] = archetype
return assignments
def get_personality_prompt(personality: str) -> str:
return f"## Your Playstyle\n{PERSONALITIES.get(personality, PERSONALITIES['tempo_value'])}"
```
### AI Orchestrator (`ai/ai_orchestrator.py`)
```python
import json, time, logging
from pathlib import Path
from .brain_selector import select_brain, Brain
from .prompt_builder import build_prompt
import ollama
LOG_PATH = Path("logs/ai_decisions.jsonl")
LOG_PATH.parent.mkdir(exist_ok=True)
async def get_ai_action(state: dict, player_id: str, personality: str) -> dict:
brain = select_brain(state["phase"], len(state["stack"]))
prompt = build_prompt(state, player_id, personality)
t_start = time.time()
try:
response = ollama.chat(
model=brain.value,
messages=[{"role": "user", "content": prompt}],
options={"temperature": 0.3, "num_predict": 256}
)
raw = response["message"]["content"]
# Extract JSON from response (model may wrap in markdown)
action = json.loads(raw[raw.find("{"):raw.rfind("}")+1])
except Exception as e:
logging.warning(f"AI parse failed ({brain.value}): {e}. Passing turn.")
action = {"action": "pass", "card_id": None, "targets": [], "reasoning": "parse_error"}
# Validate against Forge legal actions
if action.get("action") not in [a["type"] for a in state["legal_actions"]]:
logging.warning(f"Illegal action returned by {brain.value}. Falling back to pass.")
action = {"action": "pass", "card_id": None, "targets": [], "reasoning": "illegal_action"}
# Log for PPO training dataset
log_entry = {
"timestamp": time.time(),
"player_id": player_id,
"brain": brain.value,
"personality": personality,
"phase": state["phase"],
"action": action,
"reasoning": action.get("reasoning", ""),
"latency_ms": round((time.time() - t_start) * 1000),
}
with open(LOG_PATH, "a") as f:
f.write(json.dumps(log_entry) + "\n")
return action
```
---
## Phase 0 — Local Card Image Cache
**Build this first.** Every downstream system depends on local art URLs.
### Step 1 — Bulk Download (`scripts/download_card_images.py`)
```python
import requests, json, os
from pathlib import Path
from tqdm import tqdm
BULK_URL = "https://api.scryfall.com/bulk-data/default-cards"
IMAGE_DIR = Path("static/card-images")
IMAGE_DIR.mkdir(parents=True, exist_ok=True)
def download_images():
# Get bulk data URL
meta = requests.get(BULK_URL).json()
cards = requests.get(meta["download_uri"], stream=True).json()
for card in tqdm(cards, desc="Downloading card images"):
image_uris = card.get("image_uris") or {}
url = image_uris.get("normal")
if not url:
continue # skip DFCs without top-level image_uris
safe_name = card["name"].replace("/", "_").replace(" ", "_")
set_code = card.get("set", "unknown")
filename = IMAGE_DIR / set_code / f"{safe_name}_{card['collector_number']}.jpg"
filename.parent.mkdir(parents=True, exist_ok=True)
if filename.exists():
continue # already cached
img_data = requests.get(url, timeout=10).content
filename.write_bytes(img_data)
if __name__ == "__main__":
download_images()
```
### Step 2 — Build SQLite Index (`scripts/build_image_index.py`)
```python
import sqlite3
from pathlib import Path
IMAGE_DIR = Path("static/card-images")
DB_PATH = Path("data/card_images.db")
DB_PATH.parent.mkdir(exist_ok=True)
def build_index():
conn = sqlite3.connect(DB_PATH)
conn.execute("""
CREATE TABLE IF NOT EXISTS card_images (
name TEXT PRIMARY KEY,
path TEXT NOT NULL
)
""")
for img_path in IMAGE_DIR.rglob("*.jpg"):
card_name = img_path.stem.rsplit("_", 1)[0].replace("_", " ")
conn.execute("INSERT OR REPLACE INTO card_images VALUES (?, ?)",
(card_name, str(img_path)))
conn.commit()
conn.close()
if __name__ == "__main__":
build_index()
```
### Step 3 — Card Enricher (`api/card_enricher.py`)
```python
import sqlite3
from pathlib import Path
DB_PATH = Path("data/card_images.db")
STATIC_URL = "http://localhost:8000/static/card-images"
def enrich_card(card: dict) -> dict:
"""Inject local art_url into every CardDTO before sending to Unity."""
conn = sqlite3.connect(DB_PATH)
cursor = conn.execute("SELECT path FROM card_images WHERE name = ?", (card["name"],))
row = cursor.fetchone()
conn.close()
if row:
relative = Path(row[0]).relative_to("static/card-images")
card["art_url"] = f"{STATIC_URL}/{relative}"
else:
card["art_url"] = f"{STATIC_URL}/card_back.jpg"
return card
```
### Step 4 — FastAPI Static Mount (`main.py` addition)
```python
from fastapi.staticfiles import StaticFiles
app.mount("/static/card-images", StaticFiles(directory="static/card-images"), name="card-images")
```
---
## Phase 1 — Forge Bridge (Rules Engine)
### ForgeSubprocessManager (`forge/subprocess_manager.py`)
```python
import subprocess, json, asyncio, threading
from pathlib import Path
FORGE_JAR = Path("forge/forge-game.jar")
class ForgeSubprocessManager:
def __init__(self):
self.process = None
self._lock = threading.Lock()
def start(self, deck_paths: list[str], format: str = "commander"):
cmd = [
"java", "-jar", str(FORGE_JAR),
"--headless",
"--format", format,
"--decks", *deck_paths,
"--output", "json"
]
self.process = subprocess.Popen(
cmd,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True,
bufsize=1
)
def read_state(self) -> dict:
with self._lock:
line = self.process.stdout.readline()
return json.loads(line)
def send_action(self, action: dict):
with self._lock:
self.process.stdin.write(json.dumps(action) + "\n")
self.process.stdin.flush()
def stop(self):
if self.process:
self.process.terminate()
```
### Data Transfer Objects (`api/dtos.py`)
```python
from pydantic import BaseModel
from typing import Optional
class CardDTO(BaseModel):
id: str
name: str
type: str
power: Optional[str]
toughness: Optional[str]
mana_cost: str
art_url: str = ""
tapped: bool = False
zone: str = "hand"
class PlayerDTO(BaseModel):
id: str
life: int
commander_damage: dict[str, int]
commander_tax: int
hand: list[CardDTO]
battlefield: list[CardDTO]
graveyard: list[CardDTO]
exile: list[CardDTO]
command_zone: list[CardDTO]
library_count: int
mana_pool: dict[str, int]
is_ai: bool
personality: Optional[str]
class GameStateDTO(BaseModel):
game_id: str
phase: str
active_player: str
priority: str
turn_number: int
players: list[PlayerDTO]
stack: list[dict]
legal_actions: list[dict]
winner: Optional[str]
```
---
## Phase 2 — FastAPI WebSocket Game Server
### Game Loop (`api/game_loop.py`)
```python
import asyncio, uuid
from .dtos import GameStateDTO
from forge.subprocess_manager import ForgeSubprocessManager
from ai.ai_orchestrator import get_ai_action
from ai.personality import assign_personalities
from api.card_enricher import enrich_card
active_games: dict[str, dict] = {}
async def start_game(deck_paths: list[str], ai_players: list[str]) -> str:
game_id = str(uuid.uuid4())
forge = ForgeSubprocessManager()
forge.start(deck_paths)
# Assign AI personalities at game creation
archetypes = detect_archetypes(deck_paths, ai_players) # ChromaDB query
personalities = assign_personalities(ai_players, archetypes)
active_games[game_id] = {
"forge": forge,
"ai_players": ai_players,
"personalities": personalities,
"websockets": []
}
asyncio.create_task(game_loop(game_id))
return game_id
async def game_loop(game_id: str):
game = active_games[game_id]
forge = game["forge"]
while True:
raw_state = forge.read_state()
if raw_state.get("winner"):
await broadcast(game_id, raw_state)
break
# Enrich every card with local art_url
state = enrich_state(raw_state)
await broadcast(game_id, state)
priority_player = state["priority"]
if priority_player in game["ai_players"]:
personality = game["personalities"][priority_player]
action = await get_ai_action(state, priority_player, personality)
forge.send_action(action)
# else: wait for Unity client to send action via WebSocket
async def broadcast(game_id: str, state: dict):
game = active_games[game_id]
for ws in game["websockets"]:
await ws.send_json(state)
def enrich_state(state: dict) -> dict:
for player in state["players"]:
for zone in ["hand", "battlefield", "graveyard", "exile", "command_zone"]:
player[zone] = [enrich_card(c) for c in player.get(zone, [])]
return state
```
### WebSocket Endpoint (`api/routes/game.py`)
```python
from fastapi import APIRouter, WebSocket, WebSocketDisconnect
from api.game_loop import active_games, start_game
router = APIRouter()
@router.websocket("/ws/game/{game_id}")
async def game_ws(websocket: WebSocket, game_id: str):
await websocket.accept()
game = active_games.get(game_id)
if not game:
await websocket.close(code=4004)
return
game["websockets"].append(websocket)
try:
while True:
data = await websocket.receive_json()
# Human player action forwarded directly to Forge
game["forge"].send_action(data)
except WebSocketDisconnect:
game["websockets"].remove(websocket)
```
---
## Phase 3 — Unity TCGEngine Board (2D)
### Project Layout
```
unity-commander-ui/
├── Assets/
│ ├── TCGEngine/ ← TCGEngine base (unmodified)
│ ├── Commander/
│ │ ├── Scripts/
│ │ │ ├── GameNetworkManager.cs ← WebSocket ↔ FastAPI
│ │ │ ├── CommanderBoardUI.cs ← 4-player layout controller
│ │ │ ├── PlayerAreaUI.cs ← per-player zone panel
│ │ │ ├── CardImageLoader.cs ← local cache texture fetcher
│ │ │ ├── ZonePanel.cs ← Hand/Library/Graveyard/Exile/Command
│ │ │ └── AIThinkingIndicator.cs ← spinner while AI brain is deciding
│ │ └── Prefabs/
│ │ ├── CardPrefab.prefab
│ │ ├── PlayerAreaPrefab.prefab
│ │ └── ZonePanelPrefab.prefab
│ └── Scenes/
│ └── CommanderBoard.unity
```
### Board Layout (matches screenshot)
```
┌──────────────────────────────────────────────────────────────────┐
│ [LIBRARY][GRAVEYARD][EXILE] [────── HAND ──────] (Player 3) │
│ [COMMAND] │
├──────────────────────────────┬───────────────────────────────────┤
│ │ │
│ │ │
│ BATTLEFIELD │ BATTLEFIELD │
│ (Player 1) │ (Player 2) │
│ BATTLEFIELD (center) │
│ BATTLEFIELD │ BATTLEFIELD │
│ (Player 4) │ (Player 3) │
│ │ │
├──────────────────────────────┴───────────────────────────────────┤
│ [COMMAND] │
│ [LIBRARY][GRAVEYARD][EXILE] [────── HAND ──────] (Player 1) │
└──────────────────────────────────────────────────────────────────┘
```
### GameNetworkManager.cs
```csharp
using UnityEngine;
using NativeWebSocket;
using Newtonsoft.Json;
public class GameNetworkManager : MonoBehaviour
{
public static GameNetworkManager Instance { get; private set; }
[SerializeField] private string serverUrl = "ws://localhost:8000/ws/game/";
[SerializeField] private string gameId;
private WebSocket _socket;
public delegate void GameStateReceived(GameStateDTO state);
public event GameStateReceived OnGameStateReceived;
async void Awake()
{
Instance = this;
_socket = new WebSocket($"{serverUrl}{gameId}");
_socket.OnMessage += (bytes) =>
{
var json = System.Text.Encoding.UTF8.GetString(bytes);
var state = JsonConvert.DeserializeObject<GameStateDTO>(json);
UnityMainThreadDispatcher.Enqueue(() => OnGameStateReceived?.Invoke(state));
};
await _socket.Connect();
}
public async void SendAction(object action)
{
var json = JsonConvert.SerializeObject(action);
await _socket.SendText(json);
}
void Update() => _socket?.DispatchMessageQueue();
async void OnDestroy() => await _socket?.Close();
}
```
### CardImageLoader.cs
```csharp
using System.Collections;
using System.Collections.Generic;
using UnityEngine;
using UnityEngine.Networking;
using UnityEngine.UI;
public class CardImageLoader : MonoBehaviour
{
private static Dictionary<string, Texture2D> _cache = new();
public static IEnumerator LoadCardArt(string artUrl, RawImage target)
{
if (_cache.TryGetValue(artUrl, out var cached))
{
target.texture = cached;
yield break;
}
using var req = UnityWebRequestTexture.GetTexture(artUrl);
yield return req.SendWebRequest();
if (req.result == UnityWebRequest.Result.Success)
{
var tex = DownloadHandlerTexture.GetContent(req);
_cache[artUrl] = tex;
target.texture = tex;
}
else
{
Debug.LogWarning($"Failed to load card art: {artUrl}");
}
}
}
```
### AIThinkingIndicator.cs
```csharp
using UnityEngine;
using UnityEngine.UI;
/// Shows a spinner + brain label while the AI is deciding.
public class AIThinkingIndicator : MonoBehaviour
{
[SerializeField] private GameObject spinnerPanel;
[SerializeField] private Text brainLabel;
[SerializeField] private Text personalityLabel;
public void Show(string brain, string personality)
{
spinnerPanel.SetActive(true);
brainLabel.text = $"🧠 {brain}";
personalityLabel.text = $"🎭 {personality}";
}
public void Hide() => spinnerPanel.SetActive(false);
}
```
---
## Phase 4 — Commander Zone UIs
### Zone Definitions per Player
| Zone Panel | Content | Notes |
|---|---|---|
| `LIBRARY` | Count only | Click → draw/look at top |
| `GRAVEYARD` | Scrollable card list | Full card art on hover |
| `EXILE` | Scrollable card list | Includes face-down indicators |
| `HAND` | Wide panel, card art | Hidden to opponents |
| `COMMAND` | Commander card(s) | Shows commander tax counter |
| `BATTLEFIELD` | Open grid | Tapped/untapped state, counters |
### Commander-Specific UI Elements
```csharp
public class CommanderZoneUI : MonoBehaviour
{
[SerializeField] private Text taxCounter; // "Tax: +{2N}"
[SerializeField] private RawImage commanderArt;
[SerializeField] private Text commanderDamageDealt; // per opponent
public void Refresh(PlayerDTO player)
{
int tax = player.CommanderTax;
taxCounter.text = tax > 0 ? $"+{tax * 2}" : "";
if (player.CommandZone.Count > 0)
StartCoroutine(CardImageLoader.LoadCardArt(
player.CommandZone[0].ArtUrl, commanderArt));
}
}
```
---
## Phase 5 — Commander Rules Validation Layer
Forge handles all rules natively. FastAPI validates the AI response is within the legal actions list Forge returns — no custom rules code needed in Python or Unity.
Key Commander rules confirmed handled by Forge headless:
- **Commander Tax** — +2 generic per previous cast from command zone
- **21 Commander Damage** — tracked per attacker/defender pair
- **40 Starting Life**
- **Zone Redirect** — commander goes to command zone instead of graveyard/exile (player choice)
- **Color Identity** — deck validation at game start
- **Singleton** — deck validation at game start
---
## Phase 6 — AI Decision Logging & PPO Pipeline
Every AI decision written to `logs/ai_decisions.jsonl`:
```json
{
"timestamp": 1743520800.123,
"player_id": "player_2",
"brain": "deepseek-r1:14b",
"personality": "aggro_beatdown",
"phase": "declare_attackers",
"action": {"action": "attack", "card_id": "c_042", "targets": ["player_1"], "reasoning": "Open attack, no blockers visible"},
"latency_ms": 847
}
```
This log becomes the **supervised learning dataset** for the next PPO training iteration. Each (state, action) pair from winning games is a positive training example.
---
## Project Directory Structure
```
commander-ai-lab/
├── main.py ← FastAPI app, mounts static files
├── api/
│ ├── dtos.py ← Pydantic DTOs
│ ├── card_enricher.py ← Injects art_url into CardDTOs
│ ├── game_loop.py ← Main game orchestration loop
│ └── routes/
│ └── game.py ← WebSocket + REST endpoints
├── ai/
│ ├── ai_orchestrator.py ← Main AI decision entry point
│ ├── brain_selector.py ← DeepSeek-R1 vs GPT-OSS routing
│ ├── prompt_builder.py ← Game state + RAG → prompt
│ └── personality.py ← 8 personalities + assignment
├── forge/
│ └── subprocess_manager.py ← Forge JVM stdin/stdout bridge
├── scripts/
│ ├── download_card_images.py ← One-time Scryfall bulk download
│ └── build_image_index.py ← SQLite name→path index
├── static/
│ └── card-images/ ← ~2GB local image cache
│ └── {set_code}/
│ └── {CardName}_{num}.jpg
├── data/
│ └── card_images.db ← SQLite image index
├── logs/
│ └── ai_decisions.jsonl ← PPO training dataset
├── unity-commander-ui/ ← Unity 2D TCGEngine project
└── docs/
└── implementation_plan.md ← This document
```
---
## Phased Timeline
| Phase | Scope | Est. Time |
|---|---|---|
| **0** | Scryfall image download + SQLite index + FastAPI static mount | 1 day |
| **1** | Forge subprocess bridge + DTO definitions | 2–3 days |
| **2** | AI Orchestrator + brain selector + prompt builder + personality system | 3–4 days |
| **3** | Unity TCGEngine project setup + WebSocket GameNetworkManager | 3–4 days |
| **4** | PlayerAreaUI + ZonePanels + CardImageLoader + board layout | 3–4 days |
| **5** | Commander zone UI (tax counter, commander damage, zone redirect) | 1–2 days |
| **6** | AI decision logging + end-to-end game loop test | 1–2 days |
**Total estimated: ~3 weeks to first playable Commander game with live AI opponents.**
---
## Key Design Decisions
| Decision | Rationale |
|---|---|
| Forge = rules authority | Forge already handles all Commander rules natively. No custom rules code. |
| TCGEngine = dumb renderer | All game logic lives in Forge. Unity only renders state it receives. |
| FastAPI = hub | Bridges Forge ↔ Unity ↔ AI. Single point of truth. |
| Dual-brain routing | DeepSeek-R1 excels at analytical/math decisions; GPT-OSS at strategic sequencing. |
| ChromaDB scoped per player | RAG context relevant to the active player's deck, not global card knowledge. |
| Personality persists per game | Consistent playstyle per AI across all 4 players per session. |
| Local image cache | Eliminates network latency for card art. ~2GB one-time download. |
| ai_decisions.jsonl | Every AI decision is a future PPO training sample. |
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>MTG Commander Battlefield</title>
<link rel="stylesheet" href="style.css?v=20260403_0300">
</head>
<body>
<!-- ====================================================
SETUP SCREEN
==================================================== -->
<div id="setup-screen">
<!-- Populated by ui.js initSetupScreen() -->
</div>
<!-- ====================================================
TABLE SURFACE — 4-Quadrant Battlefield
==================================================== -->
<div class="table-surface" id="game-battlefield" style="display:none;">
<!-- TOP BAR: Phase tracker + controls -->
<div id="top-bar">
<span class="top-bar-logo">Commander</span>
<div class="turn-counter-badge" id="turn-counter">Turn <span>1</span></div>
<div class="active-player-indicator" id="active-player-indicator">
<span class="active-player-dot" id="active-dot" style="background:#c0392b;"></span>
Player 1's Turn
</div>
<!-- Phase track -->
<div class="phase-track-wrapper">
<div class="phase-track" id="phase-track"></div>
</div>
<!-- Phase/turn action buttons -->
<div class="top-bar-actions">
<button class="btn-phase" onclick="nextPhase()" title="Advance to next phase (N)">Next Phase</button>
<button class="btn-phase btn-next-turn" onclick="nextTurn()" title="End turn, advance to next player (T)">Next Turn</button>
</div>
<!-- Utility buttons -->
<div class="top-bar-utils">
<button class="btn-util" id="btn-undo" onclick="undo()" title="Undo (Ctrl+Z)" disabled>&#x21A9;</button>
<button class="btn-util" id="btn-redo" onclick="redo()" title="Redo (Ctrl+Y)" disabled>&#x21AA;</button>
<button class="btn-util" id="btn-triggers" onclick="toggleTriggerStack()" title="Trigger Stack">&#x2747;</button>
<button class="btn-util" onclick="openDiceModal()" title="Dice &amp; Coins (G)">&#x1F3B2;</button>
<button class="btn-util" onclick="checkStateBasedActions()" title="Check State-Based Actions">SBA</button>
<button class="btn-util" onclick="toggleSettingsPanel()" title="Settings">&#x2699;</button>
<button class="btn-util" id="btn-search-toggle" onclick="document.getElementById('card-search-sidebar').classList.toggle('collapsed')" title="Card Search (S)">&#x1F50D;</button>
</div>
<!-- Storm counter -->
<span id="storm-badge" style="display:none;font-size:10px;color:var(--mtg-gold);background:rgba(200,168,67,0.15);border:1px solid rgba(200,168,67,0.3);border-radius:4px;padding:2px 7px;white-space:nowrap;">Storm: 0</span>
</div>
<!-- DIVIDER LINES -->
<div class="divider-h"></div>
<div class="divider-v"></div>
<!-- CORNER ACCENTS -->
<div class="corner-accent tl"></div>
<div class="corner-accent tr"></div>
<div class="corner-accent bl"></div>
<div class="corner-accent br"></div>
<!-- CENTER EMBLEM -->
<div class="center-emblem">
<svg viewBox="0 0 100 100" fill="none">
<circle cx="50" cy="50" r="42" stroke="rgba(255,255,255,0.2)" stroke-width="1.5"/>
<circle cx="50" cy="50" r="28" stroke="rgba(255,255,255,0.1)" stroke-width="1"/>
<polygon points="50,15 58.5,37 82,37 63,51 69,74 50,60 31,74 37,51 18,37 41.5,37"
fill="rgba(255,255,255,0.1)" stroke="rgba(255,255,255,0.2)" stroke-width="0.8"/>
</svg>
</div>
<!-- ================================================
4-QUADRANT BATTLEFIELD
================================================ -->
<div class="battlefield">
<!-- PLAYER 1: Top-Left (Crimson) -->
<div class="player-area p1" id="player-area-1">
<span class="player-label" id="player-label-1">Player 1</span>
<div class="life-counter" id="life-counter-1">
<button onclick="adjustLife(0,-1)" aria-label="Decrease P1 life">&#x2212;</button>
<span class="life-counter-value" id="life-0" onclick="showSetLifeDialog(0)">40</span>
<button onclick="adjustLife(0,1)" aria-label="Increase P1 life">+</button>
</div>
<div class="poison-badge" id="poison-0" style="display:none;" onclick="adjustPoison(0,1)" title="Poison counters (click +1, right-click -1)" oncontextmenu="event.preventDefault();adjustPoison(0,-1)">0 poison</div>
<!-- Zone Row: Library, Exile, Graveyard, Hand -->
<div class="zone-row" id="zone-row-1">
<div class="zone library" id="lib-zone-1" data-player="1" data-zone="library"
onclick="openZoneModal(0,'library')" data-tooltip="Library">
<span class="card-count" id="lib-count-1">0</span>
<span class="zone-icon">&#x1F4DA;</span>
<span class="zone-name">Library</span>
</div>
<div class="zone exile" id="exile-zone-1" data-player="1" data-zone="exile"
onclick="openZoneModal(0,'exile')" data-tooltip="Exile">
<span class="card-count" id="exile-count-1" style="display:none;">0</span>
<span class="zone-icon">&#x2B21;</span>
<span class="zone-name">Exile</span>
</div>
<div class="zone graveyard" id="gv-zone-1" data-player="1" data-zone="graveyard"
onclick="openZoneModal(0,'graveyard')" data-tooltip="Graveyard">
<span class="card-count" id="gv-count-1" style="display:none;">0</span>
<span class="zone-icon">&#x2620;</span>
<span class="zone-name">Grave</span>
</div>
<div class="zone hand" id="hand-zone-1" data-player="1" data-zone="hand"
onclick="openZoneModal(0,'hand')" data-tooltip="Hand">
<span class="zone-icon">&#x1F0CF;</span>
<span class="zone-name">Hand (<span id="hand-count-1">0</span>)</span>
</div>
</div>
<!-- Commander Row -->
<div class="commander-row" id="cmd-row-1">
<div class="zone commander" id="cmd-zone-1" data-player="1" data-zone="command"
onclick="openZoneModal(0,'command')" data-tooltip="Command Zone">
<span class="zone-icon">&#x1F451;</span>
<span class="zone-name">Commander</span>
</div>
</div>
<!-- Battle Zone -->
<div class="battle-zone" id="battle-zone-1">
<div class="battle-zone-inner"></div>
<span class="battle-zone-label">Battlefield</span>
<!-- Battlefield cards injected here -->
</div>
</div>
<!-- PLAYER 2: Top-Right (Sapphire) -->
<div class="player-area p2" id="player-area-2">
<span class="player-label" id="player-label-2">Player 2</span>
<div class="life-counter" id="life-counter-2">
<button onclick="adjustLife(1,-1)" aria-label="Decrease P2 life">&#x2212;</button>
<span class="life-counter-value" id="life-1" onclick="showSetLifeDialog(1)">40</span>
<button onclick="adjustLife(1,1)" aria-label="Increase P2 life">+</button>
</div>
<div class="poison-badge" id="poison-1" style="display:none;" onclick="adjustPoison(1,1)" oncontextmenu="event.preventDefault();adjustPoison(1,-1)">0 poison</div>
<div class="zone-row" id="zone-row-2">
<div class="zone library" id="lib-zone-2" data-player="2" data-zone="library"
onclick="openZoneModal(1,'library')" data-tooltip="Library">
<span class="card-count" id="lib-count-2">0</span>
<span class="zone-icon">&#x1F4DA;</span>
<span class="zone-name">Library</span>
</div>
<div class="zone exile" id="exile-zone-2" data-player="2" data-zone="exile"
onclick="openZoneModal(1,'exile')" data-tooltip="Exile">
<span class="card-count" id="exile-count-2" style="display:none;">0</span>
<span class="zone-icon">&#x2B21;</span>
<span class="zone-name">Exile</span>
</div>
<div class="zone graveyard" id="gv-zone-2" data-player="2" data-zone="graveyard"
onclick="openZoneModal(1,'graveyard')" data-tooltip="Graveyard">
<span class="card-count" id="gv-count-2" style="display:none;">0</span>
<span class="zone-icon">&#x2620;</span>
<span class="zone-name">Grave</span>
</div>
<div class="zone hand" id="hand-zone-2" data-player="2" data-zone="hand"
onclick="openZoneModal(1,'hand')" data-tooltip="Hand">
<span class="zone-icon">&#x1F0CF;</span>
<span class="zone-name">Hand (<span id="hand-count-2">0</span>)</span>
</div>
</div>
<div class="commander-row" id="cmd-row-2">
<div class="zone commander" id="cmd-zone-2" data-player="2" data-zone="command"
onclick="openZoneModal(1,'command')" data-tooltip="Command Zone">
<span class="zone-icon">&#x1F451;</span>
<span class="zone-name">Commander</span>
</div>
</div>
<div class="battle-zone" id="battle-zone-2">
<div class="battle-zone-inner"></div>
<span class="battle-zone-label">Battlefield</span>
</div>
</div>
<!-- PLAYER 3: Bottom-Left (Emerald) -->
<div class="player-area p3" id="player-area-3">
<!-- Battle zone on top for bottom players -->
<div class="battle-zone" id="battle-zone-3">
<div class="battle-zone-inner"></div>
<span class="battle-zone-label">Battlefield</span>
</div>
<div class="commander-row" id="cmd-row-3">
<div class="zone commander" id="cmd-zone-3" data-player="3" data-zone="command"
onclick="openZoneModal(2,'command')" data-tooltip="Command Zone">
<span class="zone-icon">&#x1F451;</span>
<span class="zone-name">Commander</span>
</div>
</div>
<div class="zone-row" id="zone-row-3">
<div class="zone library" id="lib-zone-3" data-player="3" data-zone="library"
onclick="openZoneModal(2,'library')" data-tooltip="Library">
<span class="card-count" id="lib-count-3">0</span>
<span class="zone-icon">&#x1F4DA;</span>
<span class="zone-name">Library</span>
</div>
<div class="zone exile" id="exile-zone-3" data-player="3" data-zone="exile"
onclick="openZoneModal(2,'exile')" data-tooltip="Exile">
<span class="card-count" id="exile-count-3" style="display:none;">0</span>
<span class="zone-icon">&#x2B21;</span>
<span class="zone-name">Exile</span>
</div>
<div class="zone graveyard" id="gv-zone-3" data-player="3" data-zone="graveyard"
onclick="openZoneModal(2,'graveyard')" data-tooltip="Graveyard">
<span class="card-count" id="gv-count-3" style="display:none;">0</span>
<span class="zone-icon">&#x2620;</span>
<span class="zone-name">Grave</span>
</div>
<div class="zone hand" id="hand-zone-3" data-player="3" data-zone="hand"
onclick="openZoneModal(2,'hand')" data-tooltip="Hand">
<span class="zone-icon">&#x1F0CF;</span>
<span class="zone-name">Hand (<span id="hand-count-3">0</span>)</span>
</div>
</div>
<span class="player-label" id="player-label-3">Player 3</span>
<div class="life-counter" id="life-counter-3">
<button onclick="adjustLife(2,-1)" aria-label="Decrease P3 life">&#x2212;</button>
<span class="life-counter-value" id="life-2" onclick="showSetLifeDialog(2)">40</span>
<button onclick="adjustLife(2,1)" aria-label="Increase P3 life">+</button>
</div>
<div class="poison-badge" id="poison-2" style="display:none;" onclick="adjustPoison(2,1)" oncontextmenu="event.preventDefault();adjustPoison(2,-1)">0 poison</div>
</div>
<!-- PLAYER 4: Bottom-Right (Gold) -->
<div class="player-area p4" id="player-area-4">
<div class="battle-zone" id="battle-zone-4">
<div class="battle-zone-inner"></div>
<span class="battle-zone-label">Battlefield</span>
</div>
<div class="commander-row" id="cmd-row-4">
<div class="zone commander" id="cmd-zone-4" data-player="4" data-zone="command"
onclick="openZoneModal(3,'command')" data-tooltip="Command Zone">
<span class="zone-icon">&#x1F451;</span>
<span class="zone-name">Commander</span>
</div>
</div>
<div class="zone-row" id="zone-row-4">
<div class="zone library" id="lib-zone-4" data-player="4" data-zone="library"
onclick="openZoneModal(3,'library')" data-tooltip="Library">
<span class="card-count" id="lib-count-4">0</span>
<span class="zone-icon">&#x1F4DA;</span>
<span class="zone-name">Library</span>
</div>
<div class="zone exile" id="exile-zone-4" data-player="4" data-zone="exile"
onclick="openZoneModal(3,'exile')" data-tooltip="Exile">
<span class="card-count" id="exile-count-4" style="display:none;">0</span>
<span class="zone-icon">&#x2B21;</span>
<span class="zone-name">Exile</span>
</div>
<div class="zone graveyard" id="gv-zone-4" data-player="4" data-zone="graveyard"
onclick="openZoneModal(3,'graveyard')" data-tooltip="Graveyard">
<span class="card-count" id="gv-count-4" style="display:none;">0</span>
<span class="zone-icon">&#x2620;</span>
<span class="zone-name">Grave</span>
</div>
<div class="zone hand" id="hand-zone-4" data-player="4" data-zone="hand"
onclick="openZoneModal(3,'hand')" data-tooltip="Hand">
<span class="zone-icon">&#x1F0CF;</span>
<span class="zone-name">Hand (<span id="hand-count-4">0</span>)</span>
</div>
</div>
<span class="player-label" id="player-label-4">Player 4</span>
<div class="life-counter" id="life-counter-4">
<button onclick="adjustLife(3,-1)" aria-label="Decrease P4 life">&#x2212;</button>
<span class="life-counter-value" id="life-3" onclick="showSetLifeDialog(3)">40</span>
<button onclick="adjustLife(3,1)" aria-label="Increase P4 life">+</button>
</div>
<div class="poison-badge" id="poison-3" style="display:none;" onclick="adjustPoison(3,1)" oncontextmenu="event.preventDefault();adjustPoison(3,-1)">0 poison</div>
</div>
</div><!-- /.battlefield -->
<!-- COMBAT SVG OVERLAY (arrows) -->
<svg id="combat-overlay" xmlns="http://www.w3.org/2000/svg" style="position:absolute;inset:44px 0 0 0;pointer-events:none;z-index:30;">
<defs>
<marker id="arrowhead" markerWidth="10" markerHeight="7" refX="9" refY="3.5" orient="auto">
<polygon points="0 0, 10 3.5, 0 7" fill="rgba(211,32,42,0.7)"/>
</marker>
</defs>
<g id="combat-arrows-svg"></g>
</svg>
<!-- MANA POOL DISPLAY (floating, bottom center) -->
<div id="mana-pool-display" style="display:none;">
<span class="mana-pool-label">MANA:</span>
<span class="mana-empty">Empty</span>
</div>
<!-- FLOATING LOG -->
<div id="floating-log" class="floating-log"></div>
<!-- SHORTCUT HINT -->
<div class="shortcut-hint"></div>
<!-- CARD SEARCH SIDEBAR (right side, collapsible) -->
<div id="card-search-sidebar" class="collapsed">
<div class="sidebar-header">
<span class="sidebar-title">Card Search</span>
<button class="sidebar-toggle" onclick="document.getElementById('card-search-sidebar').classList.toggle('collapsed')" title="Close search">&#x2715;</button>
</div>
<div class="search-input-wrap">
<input class="search-input" id="card-search-input" type="text" placeholder="Search Scryfall..." autocomplete="off"/>
</div>
<div class="search-status" id="search-status">Type to search cards...</div>
<div class="card-results" id="card-results"></div>
</div>
<!-- Sidebar edge tab -->
<div id="sidebar-edge-tab" class="sidebar-edge-tab" title="Toggle card search">&#x2039;</div>
</div><!-- /.table-surface / #game-battlefield -->
<!-- ====================================================
CONTEXT MENU
==================================================== -->
<div id="context-menu"></div>
<!-- ====================================================
FLOATING CARD PREVIEW
==================================================== -->
<div id="card-preview">
<img src="" alt="Card Preview"/>
<div class="card-preview-pt-overlay" id="card-preview-pt-overlay"></div>
<div class="card-preview-info">
<div class="card-preview-name"></div>
<div class="card-preview-type"></div>
<div class="card-preview-oracle"></div>
<div class="card-preview-pt"></div>
</div>
</div>
<!-- ====================================================
ZONE MODAL
==================================================== -->
<div id="zone-modal">
<div class="zone-modal-card">
<div class="zone-modal-header">
<span class="zone-modal-title" id="zone-modal-title">Player Zones</span>
<button class="btn-close" onclick="closeZoneModal()">&#x2715;</button>
</div>
<div class="zone-modal-tabs" id="zone-modal-tabs">
<!-- Populated by renderZoneModal() -->
</div>
<div class="zone-modal-body" id="zone-modal-body">
<!-- Populated by renderZoneModal() -->
</div>
</div>
</div>
<!-- ====================================================
DICE MODAL
==================================================== -->
<div id="dice-modal">
<div class="dice-modal-card">
<div style="display:flex;justify-content:space-between;align-items:center;margin-bottom:1rem;">
<span style="font-family:var(--font-display);font-size:14px;font-weight:700;color:var(--color-text-muted);text-transform:uppercase;letter-spacing:0.08em;">Dice &amp; Coins</span>
<button class="btn-close" onclick="closeDiceModal()">&#x2715;</button>
</div>
<div class="dice-result-display" id="dice-result-display">&#x2014;</div>
<div class="dice-label" id="dice-label">Choose a die</div>
<div class="dice-buttons">
<button class="btn-dice" onclick="rollDice(4)">d4</button>
<button class="btn-dice" onclick="rollDice(6)">d6</button>
<button class="btn-dice" onclick="rollDice(8)">d8</button>
<button class="btn-dice" onclick="rollDice(10)">d10</button>
<button class="btn-dice" onclick="rollDice(12)">d12</button>
<button class="btn-dice" onclick="rollDice(20)">d20</button>
<button class="btn-dice" onclick="rollDice(100)">d100</button>
<button class="btn-dice coin" onclick="flipCoin()">Coin Flip</button>
</div>
</div>
</div>
<!-- ====================================================
TOKEN MODAL
==================================================== -->
<div id="token-modal">
<div class="token-modal-card">
<div class="modal-header">
<span class="modal-title">Create Token</span>
<button class="btn-close" onclick="closeTokenModal()">&#x2715;</button>
</div>
<div class="modal-body" id="token-modal-body">
<div style="display:grid;grid-template-columns:1fr 1fr;gap:10px;margin-bottom:12px;">
<div>
<label style="font-size:11px;font-weight:600;color:var(--color-text);display:block;margin-bottom:4px;">Token Name</label>
<input class="game-input" id="token-name" type="text" placeholder="e.g. 1/1 White Soldier"/>
</div>
<div>
<label style="font-size:11px;font-weight:600;color:var(--color-text);display:block;margin-bottom:4px;">Type Line</label>
<input class="game-input" id="token-type" type="text" placeholder="Creature — Soldier"/>
</div>
<div>
<label style="font-size:11px;font-weight:600;color:var(--color-text);display:block;margin-bottom:4px;">Power/Toughness</label>
<input class="game-input" id="token-pt" type="text" placeholder="1/1"/>
</div>
<div>
<label style="font-size:11px;font-weight:600;color:var(--color-text);display:block;margin-bottom:4px;">Count</label>
<input class="game-input" id="token-count" type="number" value="1" min="1" max="20"/>
</div>
</div>
<div style="margin-bottom:10px;">
<label style="font-size:11px;font-weight:600;color:var(--color-text);display:block;margin-bottom:4px;">Keywords (comma-separated)</label>
<input class="game-input" id="token-keywords" type="text" placeholder="Flying, Vigilance"/>
</div>
<div style="margin-bottom:12px;">
<label style="font-size:11px;font-weight:600;color:var(--color-text);display:block;margin-bottom:4px;">Player</label>
<select class="game-input" id="token-player-select" style="height:28px;">
<option value="0">Player 1</option>
<option value="1">Player 2</option>
<option value="2">Player 3</option>
<option value="3">Player 4</option>
</select>
</div>
<div style="display:flex;gap:8px;">
<button class="btn btn-primary" onclick="createTokenFromModal()">Create Token(s)</button>
<button class="btn btn-cancel" onclick="closeTokenModal()">Cancel</button>
</div>
</div>
</div>
</div>
<!-- ====================================================
DECK MODAL
==================================================== -->
<div id="deck-modal">
<div class="deck-modal-card">
<div class="modal-header">
<span class="modal-title">Deck Manager</span>
<button class="btn-close" onclick="closeDeckModal()">&#x2715;</button>
</div>
<div class="modal-body" id="deck-modal-body">
<!-- Populated by renderDeckModalContent() -->
</div>
</div>
</div>
<!-- ====================================================
COMMANDER DAMAGE MATRIX MODAL
==================================================== -->
<div id="cmd-dmg-matrix-modal">
<!-- Populated by renderCmdDmgMatrix() -->
</div>
<!-- ====================================================
TRIGGER STACK PANEL
==================================================== -->
<div id="trigger-stack-panel">
<div class="trigger-stack-card">
<div class="trigger-stack-header">
<span class="trigger-stack-title">Trigger Stack</span>
<button class="btn-close" style="font-size:14px;width:20px;height:20px;" onclick="closeTriggerStack()">&#x2715;</button>
</div>
<div class="trigger-stack-body" id="trigger-stack-body">
<div class="trigger-stack-empty">No pending triggers.</div>
</div>
<div class="trigger-stack-actions">
<button class="btn-resolve" onclick="resolveNextTrigger()">Resolve Next</button>
<button class="btn-resolve-all" onclick="resolveAllTriggers()">Resolve All</button>
</div>
</div>
</div>
<!-- ====================================================
SETTINGS PANEL
==================================================== -->
<div id="settings-panel">
<div class="modal-header" style="flex-shrink:0;">
<span class="modal-title">Settings</span>
<button class="btn-close" onclick="toggleSettingsPanel()">&#x2715;</button>
</div>
<div class="settings-body" id="settings-body" style="flex:1;overflow-y:auto;padding:12px;">
<!-- Populated by renderSettingsPanel() -->
</div>
<div style="padding:10px 14px;border-top:1px solid var(--color-border);display:flex;gap:8px;flex-wrap:wrap;flex-shrink:0;">
<button class="btn btn-primary" onclick="openDiceModal()">&#x1F3B2; Dice</button>
<button class="btn btn-gold" onclick="openCmdDmgMatrix()">CMD Damage Matrix</button>
<button class="btn btn-cancel" onclick="checkStateBasedActions()">Check SBA</button>
<button class="btn btn-cancel" onclick="clearAllManaPools()">Clear All Mana</button>
<button class="btn btn-cancel" onclick="autoArrangeBattlefield()">Auto-Arrange</button>
</div>
</div>
<!-- ====================================================
PRIORITY BANNER
==================================================== -->
<div id="priority-banner">
<span class="priority-text" id="priority-text">Waiting for priority...</span>
<button class="btn-priority-pass" onclick="passPriority()">Pass Priority</button>
<button class="btn-close" style="font-size:13px;" onclick="closePriorityWindow()">&#x2715;</button>
</div>
<!-- ====================================================
LEGAL ACTIONS BAR
==================================================== -->
<div id="legal-actions-bar">
<!-- Populated by renderLegalActionsBar() -->
</div>
<!-- ====================================================
UNDO HISTORY PANEL
==================================================== -->
<div id="undo-history-panel">
<!-- Populated by renderUndoHistory() -->
</div>
<!-- ====================================================
MANA COLOR PICKER (dynamically appended) -->
<!-- Zone card context menu (dynamically appended) -->
<!-- SBA alert panel (dynamically appended) -->
<!-- Set-life dialog (dynamically appended) -->
<!-- ====================================================
SCRIPTS
==================================================== -->
<script src="precons.js?v=20260403_0300"></script>
<script src="engine.js?v=20260403_0300"></script>
<script src="ui.js?v=20260403_0300"></script>
<script>
// ============================================================
// STARTUP & BRIDGE FUNCTIONS
// ============================================================
// Token creation from modal
function createTokenFromModal() {
if (!gameState) return;
const name = document.getElementById('token-name').value.trim() || '1/1 Token';
const typeLine = document.getElementById('token-type').value.trim() || 'Creature';
const pt = document.getElementById('token-pt').value.trim() || '1/1';
const count = parseInt(document.getElementById('token-count').value) || 1;
const keywords = document.getElementById('token-keywords').value.trim();
const playerIdx = parseInt(document.getElementById('token-player-select').value) || 0;
const parts = pt.split('/');
const power = parts[0] ? parts[0].trim() : '1';
const toughness = parts[1] ? parts[1].trim() : '1';
for (let i = 0; i < count; i++) {
addCardToBattlefield(name, '', typeLine, playerIdx, undefined, undefined,
keywords ? keywords.replace(/,/g, ' ') : '',
{ power, toughness, pt, isToken: true });
}
addLogEntry('Created ' + count + 'x <strong>' + name + '</strong> token(s) for Player ' + (playerIdx + 1));
closeTokenModal();
}
// Pass priority
function passPriority() {
addLogEntry('Priority passed.');
closePriorityWindow();
}
// Open precon browser (stub - opens deck modal for current player)
function openPreconBrowser() {
if (gameState) openDeckModal(gameState.currentPlayerIndex);
}
// Open collection modal (stub)
function openCollectionModal() { showToast('Collection tracker available in full version.'); }
// Scry dialog stub
function showScryDialog(playerId) {
if (!gameState) return;
const player = gameState.players[playerId];
if (!player || player.zones.library.length === 0) {
addLogEntry('!! ' + (player ? player.name : 'Player') + ' has no cards to scry.');
return;
}
const count = Math.min(parseInt(prompt('Scry how many? (1-7)', '1') || '1'), 7, player.zones.library.length);
if (isNaN(count) || count < 1) return;
const topCards = player.zones.library.slice(0, count);
const names = topCards.map(c => c.name || '?').join(', ');
addLogEntry('<strong>' + player.name + '</strong> scrys ' + count + ': [' + names + ']');
}
// Mill dialog stub
function showMillDialog(playerId) {
if (!gameState) return;
const count = parseInt(prompt('Mill how many cards?', '1') || '1');
if (isNaN(count) || count < 1) return;
millCards(playerId, count);
}
// Become monarch
function becomeMonarch(playerId) {
if (!gameState) return;
gameState.monarchPlayerIndex = playerId;
const player = gameState.players[playerId];
addLogEntry('&#x1F451; <strong>' + (player ? player.name : 'Player') + '</strong> becomes the Monarch!');
updateMonarchBadges();
}
// Empower the life counter right-click on the quadrant labels
document.addEventListener('DOMContentLoaded', function() {
// Wire right-click on life values to set-life dialog
for (var i = 0; i < 4; i++) {
(function(idx) {
var lifeEl = document.getElementById('life-' + idx);
if (lifeEl) {
lifeEl.addEventListener('contextmenu', function(e) {
e.preventDefault();
showSetLifeDialog(idx);
});
}
})(i);
}
// Life counter right-click on quadrant buttons too
// (already handled via inline onclick in HTML)
});
</script>
</body>
</html>
+1 -1
View File
@@ -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
+80 -124
View File
@@ -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
@@ -169,24 +108,20 @@ 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", ""))
# Support both FORGE_DIR and FORGE_WORKING_DIR (alias for backwards compat)
p.add_argument("--forge-dir", default=os.environ.get("FORGE_DIR") or os.environ.get("FORGE_WORKING_DIR", ""))
p.add_argument("--forge-dir", default=os.environ.get("FORGE_DIR", ""))
p.add_argument("--forge-decks-dir", default=os.environ.get("FORGE_DECKS_DIR", ""))
p.add_argument("--lab-jar", default=os.environ.get("LAB_JAR", ""))
p.add_argument("--precon-dir", default=os.environ.get("PRECON_DIR", ""))
p.add_argument("--results-dir", default=os.environ.get("RESULTS_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":
@@ -204,35 +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:
@@ -240,25 +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",
]
forge_dir_env = os.environ.get("FORGE_DIR", "") or os.environ.get("FORGE_WORKING_DIR", "")
# 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 [
@@ -272,7 +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():
@@ -287,25 +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)
@@ -317,18 +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
# Wire RESULTS_DIR: use explicit env/arg if set, otherwise keep default "results"
# but resolve it to an absolute path relative to this file so it works
# regardless of what directory the server is launched from.
if args.results_dir:
CFG.results_dir = args.results_dir
else:
# Default: results/ next to lab_api.py (always absolute)
CFG.results_dir = str(Path(__file__).parent / "results")
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")
@@ -340,7 +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()
@@ -348,12 +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()
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@@ -1,643 +0,0 @@
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>MTG Commander Battlefield</title>
<link rel="stylesheet" href="style.css?v=20260403_0300">
</head>
<body>
<!-- ====================================================
SETUP SCREEN
==================================================== -->
<div id="setup-screen">
<!-- Populated by ui.js initSetupScreen() -->
</div>
<!-- ====================================================
TABLE SURFACE — 4-Quadrant Battlefield
==================================================== -->
<div class="table-surface" id="game-battlefield" style="display:none;">
<!-- TOP BAR: Phase tracker + controls -->
<div id="top-bar">
<span class="top-bar-logo">Commander</span>
<div class="turn-counter-badge" id="turn-counter">Turn <span>1</span></div>
<div class="active-player-indicator" id="active-player-indicator">
<span class="active-player-dot" id="active-dot" style="background:#c0392b;"></span>
Player 1's Turn
</div>
<!-- Phase track -->
<div class="phase-track-wrapper">
<div class="phase-track" id="phase-track"></div>
</div>
<!-- Phase/turn action buttons -->
<div class="top-bar-actions">
<button class="btn-phase" onclick="nextPhase()" title="Advance to next phase (N)">Next Phase</button>
<button class="btn-phase btn-next-turn" onclick="nextTurn()" title="End turn, advance to next player (T)">Next Turn</button>
</div>
<!-- Utility buttons -->
<div class="top-bar-utils">
<button class="btn-util" id="btn-undo" onclick="undo()" title="Undo (Ctrl+Z)" disabled>&#x21A9;</button>
<button class="btn-util" id="btn-redo" onclick="redo()" title="Redo (Ctrl+Y)" disabled>&#x21AA;</button>
<button class="btn-util" id="btn-triggers" onclick="toggleTriggerStack()" title="Trigger Stack">&#x2747;</button>
<button class="btn-util" onclick="openDiceModal()" title="Dice &amp; Coins (G)">&#x1F3B2;</button>
<button class="btn-util" onclick="checkStateBasedActions()" title="Check State-Based Actions">SBA</button>
<button class="btn-util" onclick="toggleSettingsPanel()" title="Settings">&#x2699;</button>
<button class="btn-util" id="btn-search-toggle" onclick="document.getElementById('card-search-sidebar').classList.toggle('collapsed')" title="Card Search (S)">&#x1F50D;</button>
</div>
<!-- Storm counter -->
<span id="storm-badge" style="display:none;font-size:10px;color:var(--mtg-gold);background:rgba(200,168,67,0.15);border:1px solid rgba(200,168,67,0.3);border-radius:4px;padding:2px 7px;white-space:nowrap;">Storm: 0</span>
</div>
<!-- DIVIDER LINES -->
<div class="divider-h"></div>
<div class="divider-v"></div>
<!-- CORNER ACCENTS -->
<div class="corner-accent tl"></div>
<div class="corner-accent tr"></div>
<div class="corner-accent bl"></div>
<div class="corner-accent br"></div>
<!-- CENTER EMBLEM -->
<div class="center-emblem">
<svg viewBox="0 0 100 100" fill="none">
<circle cx="50" cy="50" r="42" stroke="rgba(255,255,255,0.2)" stroke-width="1.5"/>
<circle cx="50" cy="50" r="28" stroke="rgba(255,255,255,0.1)" stroke-width="1"/>
<polygon points="50,15 58.5,37 82,37 63,51 69,74 50,60 31,74 37,51 18,37 41.5,37"
fill="rgba(255,255,255,0.1)" stroke="rgba(255,255,255,0.2)" stroke-width="0.8"/>
</svg>
</div>
<!-- ================================================
4-QUADRANT BATTLEFIELD
================================================ -->
<div class="battlefield">
<!-- PLAYER 1: Top-Left (Crimson) -->
<div class="player-area p1" id="player-area-1">
<span class="player-label" id="player-label-1">Player 1</span>
<div class="life-counter" id="life-counter-1">
<button onclick="adjustLife(0,-1)" aria-label="Decrease P1 life">&#x2212;</button>
<span class="life-counter-value" id="life-0" onclick="showSetLifeDialog(0)">40</span>
<button onclick="adjustLife(0,1)" aria-label="Increase P1 life">+</button>
</div>
<div class="poison-badge" id="poison-0" style="display:none;" onclick="adjustPoison(0,1)" title="Poison counters (click +1, right-click -1)" oncontextmenu="event.preventDefault();adjustPoison(0,-1)">0 poison</div>
<!-- Zone Row: Library, Exile, Graveyard, Hand -->
<div class="zone-row" id="zone-row-1">
<div class="zone library" id="lib-zone-1" data-player="1" data-zone="library"
onclick="openZoneModal(0,'library')" data-tooltip="Library">
<span class="card-count" id="lib-count-1">0</span>
<span class="zone-icon">&#x1F4DA;</span>
<span class="zone-name">Library</span>
</div>
<div class="zone exile" id="exile-zone-1" data-player="1" data-zone="exile"
onclick="openZoneModal(0,'exile')" data-tooltip="Exile">
<span class="card-count" id="exile-count-1" style="display:none;">0</span>
<span class="zone-icon">&#x2B21;</span>
<span class="zone-name">Exile</span>
</div>
<div class="zone graveyard" id="gv-zone-1" data-player="1" data-zone="graveyard"
onclick="openZoneModal(0,'graveyard')" data-tooltip="Graveyard">
<span class="card-count" id="gv-count-1" style="display:none;">0</span>
<span class="zone-icon">&#x2620;</span>
<span class="zone-name">Grave</span>
</div>
<div class="zone hand" id="hand-zone-1" data-player="1" data-zone="hand"
onclick="openZoneModal(0,'hand')" data-tooltip="Hand">
<span class="zone-icon">&#x1F0CF;</span>
<span class="zone-name">Hand (<span id="hand-count-1">0</span>)</span>
</div>
</div>
<!-- Commander Row -->
<div class="commander-row" id="cmd-row-1">
<div class="zone commander" id="cmd-zone-1" data-player="1" data-zone="command"
onclick="openZoneModal(0,'command')" data-tooltip="Command Zone">
<span class="zone-icon">&#x1F451;</span>
<span class="zone-name">Commander</span>
</div>
</div>
<!-- Battle Zone -->
<div class="battle-zone" id="battle-zone-1">
<div class="battle-zone-inner"></div>
<span class="battle-zone-label">Battlefield</span>
<!-- Battlefield cards injected here -->
</div>
</div>
<!-- PLAYER 2: Top-Right (Sapphire) -->
<div class="player-area p2" id="player-area-2">
<span class="player-label" id="player-label-2">Player 2</span>
<div class="life-counter" id="life-counter-2">
<button onclick="adjustLife(1,-1)" aria-label="Decrease P2 life">&#x2212;</button>
<span class="life-counter-value" id="life-1" onclick="showSetLifeDialog(1)">40</span>
<button onclick="adjustLife(1,1)" aria-label="Increase P2 life">+</button>
</div>
<div class="poison-badge" id="poison-1" style="display:none;" onclick="adjustPoison(1,1)" oncontextmenu="event.preventDefault();adjustPoison(1,-1)">0 poison</div>
<div class="zone-row" id="zone-row-2">
<div class="zone library" id="lib-zone-2" data-player="2" data-zone="library"
onclick="openZoneModal(1,'library')" data-tooltip="Library">
<span class="card-count" id="lib-count-2">0</span>
<span class="zone-icon">&#x1F4DA;</span>
<span class="zone-name">Library</span>
</div>
<div class="zone exile" id="exile-zone-2" data-player="2" data-zone="exile"
onclick="openZoneModal(1,'exile')" data-tooltip="Exile">
<span class="card-count" id="exile-count-2" style="display:none;">0</span>
<span class="zone-icon">&#x2B21;</span>
<span class="zone-name">Exile</span>
</div>
<div class="zone graveyard" id="gv-zone-2" data-player="2" data-zone="graveyard"
onclick="openZoneModal(1,'graveyard')" data-tooltip="Graveyard">
<span class="card-count" id="gv-count-2" style="display:none;">0</span>
<span class="zone-icon">&#x2620;</span>
<span class="zone-name">Grave</span>
</div>
<div class="zone hand" id="hand-zone-2" data-player="2" data-zone="hand"
onclick="openZoneModal(1,'hand')" data-tooltip="Hand">
<span class="zone-icon">&#x1F0CF;</span>
<span class="zone-name">Hand (<span id="hand-count-2">0</span>)</span>
</div>
</div>
<div class="commander-row" id="cmd-row-2">
<div class="zone commander" id="cmd-zone-2" data-player="2" data-zone="command"
onclick="openZoneModal(1,'command')" data-tooltip="Command Zone">
<span class="zone-icon">&#x1F451;</span>
<span class="zone-name">Commander</span>
</div>
</div>
<div class="battle-zone" id="battle-zone-2">
<div class="battle-zone-inner"></div>
<span class="battle-zone-label">Battlefield</span>
</div>
</div>
<!-- PLAYER 3: Bottom-Left (Emerald) -->
<div class="player-area p3" id="player-area-3">
<!-- Battle zone on top for bottom players -->
<div class="battle-zone" id="battle-zone-3">
<div class="battle-zone-inner"></div>
<span class="battle-zone-label">Battlefield</span>
</div>
<div class="commander-row" id="cmd-row-3">
<div class="zone commander" id="cmd-zone-3" data-player="3" data-zone="command"
onclick="openZoneModal(2,'command')" data-tooltip="Command Zone">
<span class="zone-icon">&#x1F451;</span>
<span class="zone-name">Commander</span>
</div>
</div>
<div class="zone-row" id="zone-row-3">
<div class="zone library" id="lib-zone-3" data-player="3" data-zone="library"
onclick="openZoneModal(2,'library')" data-tooltip="Library">
<span class="card-count" id="lib-count-3">0</span>
<span class="zone-icon">&#x1F4DA;</span>
<span class="zone-name">Library</span>
</div>
<div class="zone exile" id="exile-zone-3" data-player="3" data-zone="exile"
onclick="openZoneModal(2,'exile')" data-tooltip="Exile">
<span class="card-count" id="exile-count-3" style="display:none;">0</span>
<span class="zone-icon">&#x2B21;</span>
<span class="zone-name">Exile</span>
</div>
<div class="zone graveyard" id="gv-zone-3" data-player="3" data-zone="graveyard"
onclick="openZoneModal(2,'graveyard')" data-tooltip="Graveyard">
<span class="card-count" id="gv-count-3" style="display:none;">0</span>
<span class="zone-icon">&#x2620;</span>
<span class="zone-name">Grave</span>
</div>
<div class="zone hand" id="hand-zone-3" data-player="3" data-zone="hand"
onclick="openZoneModal(2,'hand')" data-tooltip="Hand">
<span class="zone-icon">&#x1F0CF;</span>
<span class="zone-name">Hand (<span id="hand-count-3">0</span>)</span>
</div>
</div>
<span class="player-label" id="player-label-3">Player 3</span>
<div class="life-counter" id="life-counter-3">
<button onclick="adjustLife(2,-1)" aria-label="Decrease P3 life">&#x2212;</button>
<span class="life-counter-value" id="life-2" onclick="showSetLifeDialog(2)">40</span>
<button onclick="adjustLife(2,1)" aria-label="Increase P3 life">+</button>
</div>
<div class="poison-badge" id="poison-2" style="display:none;" onclick="adjustPoison(2,1)" oncontextmenu="event.preventDefault();adjustPoison(2,-1)">0 poison</div>
</div>
<!-- PLAYER 4: Bottom-Right (Gold) -->
<div class="player-area p4" id="player-area-4">
<div class="battle-zone" id="battle-zone-4">
<div class="battle-zone-inner"></div>
<span class="battle-zone-label">Battlefield</span>
</div>
<div class="commander-row" id="cmd-row-4">
<div class="zone commander" id="cmd-zone-4" data-player="4" data-zone="command"
onclick="openZoneModal(3,'command')" data-tooltip="Command Zone">
<span class="zone-icon">&#x1F451;</span>
<span class="zone-name">Commander</span>
</div>
</div>
<div class="zone-row" id="zone-row-4">
<div class="zone library" id="lib-zone-4" data-player="4" data-zone="library"
onclick="openZoneModal(3,'library')" data-tooltip="Library">
<span class="card-count" id="lib-count-4">0</span>
<span class="zone-icon">&#x1F4DA;</span>
<span class="zone-name">Library</span>
</div>
<div class="zone exile" id="exile-zone-4" data-player="4" data-zone="exile"
onclick="openZoneModal(3,'exile')" data-tooltip="Exile">
<span class="card-count" id="exile-count-4" style="display:none;">0</span>
<span class="zone-icon">&#x2B21;</span>
<span class="zone-name">Exile</span>
</div>
<div class="zone graveyard" id="gv-zone-4" data-player="4" data-zone="graveyard"
onclick="openZoneModal(3,'graveyard')" data-tooltip="Graveyard">
<span class="card-count" id="gv-count-4" style="display:none;">0</span>
<span class="zone-icon">&#x2620;</span>
<span class="zone-name">Grave</span>
</div>
<div class="zone hand" id="hand-zone-4" data-player="4" data-zone="hand"
onclick="openZoneModal(3,'hand')" data-tooltip="Hand">
<span class="zone-icon">&#x1F0CF;</span>
<span class="zone-name">Hand (<span id="hand-count-4">0</span>)</span>
</div>
</div>
<span class="player-label" id="player-label-4">Player 4</span>
<div class="life-counter" id="life-counter-4">
<button onclick="adjustLife(3,-1)" aria-label="Decrease P4 life">&#x2212;</button>
<span class="life-counter-value" id="life-3" onclick="showSetLifeDialog(3)">40</span>
<button onclick="adjustLife(3,1)" aria-label="Increase P4 life">+</button>
</div>
<div class="poison-badge" id="poison-3" style="display:none;" onclick="adjustPoison(3,1)" oncontextmenu="event.preventDefault();adjustPoison(3,-1)">0 poison</div>
</div>
</div><!-- /.battlefield -->
<!-- COMBAT SVG OVERLAY (arrows) -->
<svg id="combat-overlay" xmlns="http://www.w3.org/2000/svg" style="position:absolute;inset:44px 0 0 0;pointer-events:none;z-index:30;">
<defs>
<marker id="arrowhead" markerWidth="10" markerHeight="7" refX="9" refY="3.5" orient="auto">
<polygon points="0 0, 10 3.5, 0 7" fill="rgba(211,32,42,0.7)"/>
</marker>
</defs>
<g id="combat-arrows-svg"></g>
</svg>
<!-- FLOATING LOG -->
<div id="floating-log" class="floating-log"></div>
<!-- SHORTCUT HINT -->
<div class="shortcut-hint"></div>
<!-- CARD SEARCH SIDEBAR (right side, collapsible) -->
<div id="card-search-sidebar" class="collapsed">
<div class="sidebar-header">
<span class="sidebar-title">Card Search</span>
<button class="sidebar-toggle" onclick="document.getElementById('card-search-sidebar').classList.toggle('collapsed')" title="Close search">&#x2715;</button>
</div>
<div class="search-input-wrap">
<input class="search-input" id="card-search-input" type="text" placeholder="Search Scryfall..." autocomplete="off"/>
</div>
<div class="search-status" id="search-status">Type to search cards...</div>
<div class="card-results" id="card-results"></div>
</div>
<!-- Sidebar edge tab -->
<div id="sidebar-edge-tab" class="sidebar-edge-tab" title="Toggle card search">&#x2039;</div>
</div><!-- /.table-surface / #game-battlefield -->
<!-- ====================================================
CONTEXT MENU
==================================================== -->
<div id="context-menu"></div>
<!-- ====================================================
FLOATING CARD PREVIEW
==================================================== -->
<div id="card-preview">
<img src="" alt="Card Preview"/>
<div class="card-preview-pt-overlay" id="card-preview-pt-overlay"></div>
<div class="card-preview-info">
<div class="card-preview-name"></div>
<div class="card-preview-type"></div>
<div class="card-preview-oracle"></div>
<div class="card-preview-pt"></div>
</div>
</div>
<!-- ====================================================
ZONE MODAL
==================================================== -->
<div id="zone-modal">
<div class="zone-modal-card">
<div class="zone-modal-header">
<span class="zone-modal-title" id="zone-modal-title">Player Zones</span>
<button class="btn-close" onclick="closeZoneModal()">&#x2715;</button>
</div>
<div class="zone-modal-tabs" id="zone-modal-tabs">
<!-- Populated by renderZoneModal() -->
</div>
<div class="zone-modal-body" id="zone-modal-body">
<!-- Populated by renderZoneModal() -->
</div>
</div>
</div>
<!-- ====================================================
DICE MODAL
==================================================== -->
<div id="dice-modal">
<div class="dice-modal-card">
<div style="display:flex;justify-content:space-between;align-items:center;margin-bottom:1rem;">
<span style="font-family:var(--font-display);font-size:14px;font-weight:700;color:var(--color-text-muted);text-transform:uppercase;letter-spacing:0.08em;">Dice &amp; Coins</span>
<button class="btn-close" onclick="closeDiceModal()">&#x2715;</button>
</div>
<div class="dice-result-display" id="dice-result-display">&#x2014;</div>
<div class="dice-label" id="dice-label">Choose a die</div>
<div class="dice-buttons">
<button class="btn-dice" onclick="rollDice(4)">d4</button>
<button class="btn-dice" onclick="rollDice(6)">d6</button>
<button class="btn-dice" onclick="rollDice(8)">d8</button>
<button class="btn-dice" onclick="rollDice(10)">d10</button>
<button class="btn-dice" onclick="rollDice(12)">d12</button>
<button class="btn-dice" onclick="rollDice(20)">d20</button>
<button class="btn-dice" onclick="rollDice(100)">d100</button>
<button class="btn-dice coin" onclick="flipCoin()">Coin Flip</button>
</div>
</div>
</div>
<!-- ====================================================
TOKEN MODAL
==================================================== -->
<div id="token-modal">
<div class="token-modal-card">
<div class="modal-header">
<span class="modal-title">Create Token</span>
<button class="btn-close" onclick="closeTokenModal()">&#x2715;</button>
</div>
<div class="modal-body" id="token-modal-body">
<div style="display:grid;grid-template-columns:1fr 1fr;gap:10px;margin-bottom:12px;">
<div>
<label style="font-size:11px;font-weight:600;color:var(--color-text);display:block;margin-bottom:4px;">Token Name</label>
<input class="game-input" id="token-name" type="text" placeholder="e.g. 1/1 White Soldier"/>
</div>
<div>
<label style="font-size:11px;font-weight:600;color:var(--color-text);display:block;margin-bottom:4px;">Type Line</label>
<input class="game-input" id="token-type" type="text" placeholder="Creature — Soldier"/>
</div>
<div>
<label style="font-size:11px;font-weight:600;color:var(--color-text);display:block;margin-bottom:4px;">Power/Toughness</label>
<input class="game-input" id="token-pt" type="text" placeholder="1/1"/>
</div>
<div>
<label style="font-size:11px;font-weight:600;color:var(--color-text);display:block;margin-bottom:4px;">Count</label>
<input class="game-input" id="token-count" type="number" value="1" min="1" max="20"/>
</div>
</div>
<div style="margin-bottom:10px;">
<label style="font-size:11px;font-weight:600;color:var(--color-text);display:block;margin-bottom:4px;">Keywords (comma-separated)</label>
<input class="game-input" id="token-keywords" type="text" placeholder="Flying, Vigilance"/>
</div>
<div style="margin-bottom:12px;">
<label style="font-size:11px;font-weight:600;color:var(--color-text);display:block;margin-bottom:4px;">Player</label>
<select class="game-input" id="token-player-select" style="height:28px;">
<option value="0">Player 1</option>
<option value="1">Player 2</option>
<option value="2">Player 3</option>
<option value="3">Player 4</option>
</select>
</div>
<div style="display:flex;gap:8px;">
<button class="btn btn-primary" onclick="createTokenFromModal()">Create Token(s)</button>
<button class="btn btn-cancel" onclick="closeTokenModal()">Cancel</button>
</div>
</div>
</div>
</div>
<!-- ====================================================
DECK MODAL
==================================================== -->
<div id="deck-modal">
<div class="deck-modal-card">
<div class="modal-header">
<span class="modal-title">Deck Manager</span>
<button class="btn-close" onclick="closeDeckModal()">&#x2715;</button>
</div>
<div class="modal-body" id="deck-modal-body">
<!-- Populated by renderDeckModalContent() -->
</div>
</div>
</div>
<!-- ====================================================
COMMANDER DAMAGE MATRIX MODAL
==================================================== -->
<div id="cmd-dmg-matrix-modal">
<!-- Populated by renderCmdDmgMatrix() -->
</div>
<!-- ====================================================
TRIGGER STACK PANEL
==================================================== -->
<div id="trigger-stack-panel">
<div class="trigger-stack-card">
<div class="trigger-stack-header">
<span class="trigger-stack-title">Trigger Stack</span>
<button class="btn-close" style="font-size:14px;width:20px;height:20px;" onclick="closeTriggerStack()">&#x2715;</button>
</div>
<div class="trigger-stack-body" id="trigger-stack-body">
<div class="trigger-stack-empty">No pending triggers.</div>
</div>
<div class="trigger-stack-actions">
<button class="btn-resolve" onclick="resolveNextTrigger()">Resolve Next</button>
<button class="btn-resolve-all" onclick="resolveAllTriggers()">Resolve All</button>
</div>
</div>
</div>
<!-- ====================================================
SETTINGS PANEL
==================================================== -->
<div id="settings-panel">
<div class="modal-header" style="flex-shrink:0;">
<span class="modal-title">Settings</span>
<button class="btn-close" onclick="toggleSettingsPanel()">&#x2715;</button>
</div>
<div class="settings-body" id="settings-body" style="flex:1;overflow-y:auto;padding:12px;">
<!-- Populated by renderSettingsPanel() -->
</div>
<div style="padding:10px 14px;border-top:1px solid var(--color-border);display:flex;gap:8px;flex-wrap:wrap;flex-shrink:0;">
<button class="btn btn-primary" onclick="openDiceModal()">&#x1F3B2; Dice</button>
<button class="btn btn-gold" onclick="openCmdDmgMatrix()">CMD Damage Matrix</button>
<button class="btn btn-cancel" onclick="checkStateBasedActions()">Check SBA</button>
<button class="btn btn-cancel" onclick="autoArrangeBattlefield()">Auto-Arrange</button>
</div>
</div>
<!-- ====================================================
PRIORITY BANNER
==================================================== -->
<div id="priority-banner">
<span class="priority-text" id="priority-text">Waiting for priority...</span>
<button class="btn-priority-pass" onclick="passPriority()">Pass Priority</button>
<button class="btn-close" style="font-size:13px;" onclick="closePriorityWindow()">&#x2715;</button>
</div>
<!-- ====================================================
LEGAL ACTIONS BAR
==================================================== -->
<div id="legal-actions-bar">
<!-- Populated by renderLegalActionsBar() -->
</div>
<!-- ====================================================
UNDO HISTORY PANEL
==================================================== -->
<div id="undo-history-panel">
<!-- Populated by renderUndoHistory() -->
</div>
<!-- ====================================================
MANA COLOR PICKER (dynamically appended) -->
<!-- Zone card context menu (dynamically appended) -->
<!-- SBA alert panel (dynamically appended) -->
<!-- Set-life dialog (dynamically appended) -->
<!-- ====================================================
SCRIPTS
==================================================== -->
<script src="precons.js?v=20260403_0300"></script>
<script src="engine.js?v=20260403_0300"></script>
<script src="ai-bridge.js?v=20260403_0300"></script>
<script src="player-panels.js?v=20260403_0300"></script>
<script src="ui.js?v=20260403_0300"></script>
<script>
// ============================================================
// STARTUP & BRIDGE FUNCTIONS
// ============================================================
// Token creation from modal
function createTokenFromModal() {
if (!gameState) return;
const name = document.getElementById('token-name').value.trim() || '1/1 Token';
const typeLine = document.getElementById('token-type').value.trim() || 'Creature';
const pt = document.getElementById('token-pt').value.trim() || '1/1';
const count = parseInt(document.getElementById('token-count').value) || 1;
const keywords = document.getElementById('token-keywords').value.trim();
const playerIdx = parseInt(document.getElementById('token-player-select').value) || 0;
const parts = pt.split('/');
const power = parts[0] ? parts[0].trim() : '1';
const toughness = parts[1] ? parts[1].trim() : '1';
for (let i = 0; i < count; i++) {
addCardToBattlefield(name, '', typeLine, playerIdx, undefined, undefined,
keywords ? keywords.replace(/,/g, ' ') : '',
{ power, toughness, pt, isToken: true });
}
addLogEntry('Created ' + count + 'x <strong>' + name + '</strong> token(s) for Player ' + (playerIdx + 1));
closeTokenModal();
}
// Pass priority
function passPriority() {
addLogEntry('Priority passed.');
closePriorityWindow();
}
// Open precon browser (stub - opens deck modal for current player)
function openPreconBrowser() {
if (gameState) openDeckModal(gameState.currentPlayerIndex);
}
// Open collection modal (stub)
function openCollectionModal() { showToast('Collection tracker available in full version.'); }
// Scry dialog stub
function showScryDialog(playerId) {
if (!gameState) return;
const player = gameState.players[playerId];
if (!player || player.zones.library.length === 0) {
addLogEntry('!! ' + (player ? player.name : 'Player') + ' has no cards to scry.');
return;
}
const count = Math.min(parseInt(prompt('Scry how many? (1-7)', '1') || '1'), 7, player.zones.library.length);
if (isNaN(count) || count < 1) return;
const topCards = player.zones.library.slice(0, count);
const names = topCards.map(c => c.name || '?').join(', ');
addLogEntry('<strong>' + player.name + '</strong> scrys ' + count + ': [' + names + ']');
}
// Mill dialog stub
function showMillDialog(playerId) {
if (!gameState) return;
const count = parseInt(prompt('Mill how many cards?', '1') || '1');
if (isNaN(count) || count < 1) return;
millCards(playerId, count);
}
// Become monarch
function becomeMonarch(playerId) {
if (!gameState) return;
gameState.monarchPlayerIndex = playerId;
const player = gameState.players[playerId];
addLogEntry('&#x1F451; <strong>' + (player ? player.name : 'Player') + '</strong> becomes the Monarch!');
updateMonarchBadges();
}
// Empower the life counter right-click on the quadrant labels
document.addEventListener('DOMContentLoaded', function() {
// Wire right-click on life values to set-life dialog
for (var i = 0; i < 4; i++) {
(function(idx) {
var lifeEl = document.getElementById('life-' + idx);
if (lifeEl) {
lifeEl.addEventListener('contextmenu', function(e) {
e.preventDefault();
showSetLifeDialog(idx);
});
}
})(i);
}
// Life counter right-click on quadrant buttons too
// (already handled via inline onclick in HTML)
// Auto-detect Commander-AI-Lab backend on page load
if (typeof AIBridge !== 'undefined') {
AIBridge.init().then(function(status) {
var indicator = document.getElementById('backend-status-indicator');
if (indicator) {
indicator.textContent = status.connected
? (status.modelLoaded ? '\u{1F9E0} ML Backend Connected' : '\u26a1 Backend Connected (no ML model)')
: '\u{1F4E1} Local Mode (no backend)';
indicator.className = 'backend-status ' +
(status.connected ? (status.modelLoaded ? 'connected-ml' : 'connected') : 'disconnected');
}
});
}
});
</script>
</body>
</html>
-270
View File
@@ -1,270 +0,0 @@
// player-panels.js — Enhanced Player Panel Component
// Provides collapsible panels with life, commander damage, counters, and emblems.
'use strict';
/**
* Create an enhanced player panel widget for a quadrant.
* Replaces the basic life counter with a full tracking panel.
*
* @param {object} player - Player object from gameState
* @param {number} quadrant - 1-4 (matches CSS class p1-p4)
* @param {boolean} isActive - Whether this is the active player
*/
function createEnhancedPlayerPanel(player, quadrant, isActive) {
var panel = document.createElement('div');
panel.className = 'enhanced-player-panel' +
(isActive ? ' active-turn' : '') +
(player.eliminated ? ' eliminated' : '');
panel.id = 'enhanced-panel-' + player.id;
panel.setAttribute('data-player-id', player.id);
// Track collapse state
var collapseKey = 'panel-collapsed-' + player.id;
var isCollapsed = localStorage.getItem(collapseKey) === 'true';
// ── Header Row ──────────────────────────────────────────
var headerHtml =
'<div class="epp-header" onclick="togglePlayerPanel(' + player.id + ')">' +
'<span class="epp-collapse-arrow">' + (isCollapsed ? '\u25b8' : '\u25be') + '</span>' +
'<div class="epp-name-dot" style="background:' + player.color + '"></div>' +
'<span class="epp-name">' + player.name + '</span>' +
(player.isAI ? '<span class="epp-ai-badge">AI</span>' : '') +
'<span class="epp-life-badge">' +
'\u2665 ' + player.life +
(player.life < player.startingLife
? ' / ' + player.startingLife
: '') +
'</span>' +
'</div>';
// ── Life Counter Row ────────────────────────────────────
var lifeHtml =
'<div class="epp-life-row">' +
'<button class="epp-life-btn minus" onclick="adjustLife(' + player.id + ',-1)" ' +
'oncontextmenu="event.preventDefault();adjustLife(' + player.id + ',-5)" ' +
'title="Left: -1 | Right: -5">\u2212</button>' +
'<div class="epp-life-value" id="epp-life-' + player.id + '" ' +
'onclick="showSetLifeDialog(' + player.id + ')">' +
player.life +
'</div>' +
'<button class="epp-life-btn plus" onclick="adjustLife(' + player.id + ',1)" ' +
'oncontextmenu="event.preventDefault();adjustLife(' + player.id + ',5)" ' +
'title="Left: +1 | Right: +5">+</button>' +
'</div>';
// ── Commander Damage Section ────────────────────────────
var otherPlayers = gameState.players.filter(function(p) {
return p.id !== player.id && !p.eliminated;
});
var cmdDmgHtml =
'<div class="epp-section">' +
'<div class="epp-section-label">Commander Damage</div>' +
'<div class="epp-cmd-dmg-grid">';
otherPlayers.forEach(function(op) {
var dmg = player.commanderDamage[op.id] || 0;
var pct = Math.round((dmg / 21) * 100);
var dangerClass = dmg >= 18 ? 'critical' : dmg >= 10 ? 'warning' : '';
cmdDmgHtml +=
'<div class="epp-cmd-dmg-item ' + dangerClass + '">' +
'<div class="epp-cmd-dmg-bar" style="width:' + pct + '%"></div>' +
'<div class="epp-cmd-dmg-dot" style="background:' + op.color + '"></div>' +
'<span class="epp-cmd-dmg-name">' + op.name + '</span>' +
'<span class="epp-cmd-dmg-value">' + dmg + '/21</span>' +
'<button class="epp-counter-btn" ' +
'onclick="event.stopPropagation();adjustCommanderDamage(' + player.id + ',' + op.id + ',1)" ' +
'title="Add commander damage">+</button>' +
'<button class="epp-counter-btn" ' +
'onclick="event.stopPropagation();adjustCommanderDamage(' + player.id + ',' + op.id + ',-1)" ' +
'title="Remove commander damage">\u2212</button>' +
'</div>';
});
cmdDmgHtml += '</div></div>';
// ── Counters Section ────────────────────────────────────
var poison = player.poison || 0;
var energy = player.energy || 0;
var experience = player.experience || 0;
var rad = player.rad || 0;
var countersHtml =
'<div class="epp-section">' +
'<div class="epp-section-label">Counters</div>' +
'<div class="epp-counters-grid">' +
_buildCounterWidget('Poison', '\u2620', poison, 10,
'adjustPoison(' + player.id + ',1)',
'adjustPoison(' + player.id + ',-1)',
poison >= 8 ? 'critical' : poison >= 5 ? 'warning' : '') +
_buildCounterWidget('Energy', '\u269b', energy, 0,
'adjustEnergy(' + player.id + ',1)',
'adjustEnergy(' + player.id + ',-1)', '') +
_buildCounterWidget('Experience', '\u2605', experience, 0,
'adjustExperience(' + player.id + ',1)',
'adjustExperience(' + player.id + ',-1)', '') +
_buildCounterWidget('Rad', '\u2622', rad, 0,
'adjustRad(' + player.id + ',1)',
'adjustRad(' + player.id + ',-1)', '') +
'</div>' +
'</div>';
// ── Emblems Section ─────────────────────────────────────
var emblems = player.emblems || [];
var emblemsHtml =
'<div class="epp-section">' +
'<div class="epp-section-label">Emblems</div>' +
'<div class="epp-emblems">';
if (emblems.length === 0) {
emblemsHtml += '<span class="epp-no-emblems">None</span>';
} else {
emblems.forEach(function(emb, idx) {
emblemsHtml +=
'<div class="epp-emblem-chip" title="' + emb.name + '">' +
'<span class="epp-emblem-name">' + emb.name + '</span>' +
'<button class="epp-emblem-remove" ' +
'onclick="event.stopPropagation();removeEmblem(' + player.id + ',' + idx + ')">\u00d7</button>' +
'</div>';
});
}
emblemsHtml +=
'<button class="epp-add-emblem-btn" ' +
'onclick="event.stopPropagation();showAddEmblemDialog(' + player.id + ')" ' +
'title="Add an emblem">+ Emblem</button>' +
'</div>' +
'</div>';
// ── Assemble Panel ──────────────────────────────────────
var bodyHtml =
'<div class="epp-body" id="epp-body-' + player.id + '" ' +
'style="' + (isCollapsed ? 'display:none;' : '') + '">' +
lifeHtml + cmdDmgHtml + countersHtml + emblemsHtml +
'</div>';
panel.innerHTML = headerHtml + bodyHtml;
return panel;
}
function _buildCounterWidget(label, icon, value, threshold, onInc, onDec, dangerClass) {
return '<div class="epp-counter ' + dangerClass + '">' +
'<div class="epp-counter-icon">' + icon + '</div>' +
'<div class="epp-counter-info">' +
'<span class="epp-counter-value">' + value + '</span>' +
'<span class="epp-counter-label">' + label + '</span>' +
'</div>' +
'<div class="epp-counter-btns">' +
'<button class="epp-counter-btn" onclick="event.stopPropagation();' + onInc + '">+</button>' +
'<button class="epp-counter-btn" onclick="event.stopPropagation();' + onDec + '">\u2212</button>' +
'</div>' +
'</div>';
}
function togglePlayerPanel(playerId) {
var body = document.getElementById('epp-body-' + playerId);
var panel = document.getElementById('enhanced-panel-' + playerId);
if (!body || !panel) return;
var isCollapsed = body.style.display === 'none';
body.style.display = isCollapsed ? '' : 'none';
var arrow = panel.querySelector('.epp-collapse-arrow');
if (arrow) arrow.textContent = isCollapsed ? '\u25be' : '\u25b8';
localStorage.setItem('panel-collapsed-' + playerId, !isCollapsed);
}
// Counter adjustment functions
function adjustEnergy(playerId, amount) {
if (!gameState) return;
var player = gameState.players[playerId];
if (!player) return;
player.energy = Math.max(0, (player.energy || 0) + amount);
addLogEntry('<strong>' + player.name + '</strong> energy: ' + player.energy);
renderEnhancedPanels();
}
function adjustExperience(playerId, amount) {
if (!gameState) return;
var player = gameState.players[playerId];
if (!player) return;
player.experience = Math.max(0, (player.experience || 0) + amount);
addLogEntry('<strong>' + player.name + '</strong> experience: ' + player.experience);
renderEnhancedPanels();
}
function adjustRad(playerId, amount) {
if (!gameState) return;
var player = gameState.players[playerId];
if (!player) return;
player.rad = Math.max(0, (player.rad || 0) + amount);
addLogEntry('<strong>' + player.name + '</strong> rad counters: ' + player.rad);
renderEnhancedPanels();
}
function showAddEmblemDialog(playerId) {
var name = prompt('Enter emblem name (e.g., "Sorin, Vengeful Bloodlord"):');
if (!name || !name.trim()) return;
if (!gameState) return;
var player = gameState.players[playerId];
if (!player) return;
if (!player.emblems) player.emblems = [];
player.emblems.push({ name: name.trim() });
addLogEntry('<strong>' + player.name + '</strong> gained emblem: ' + name.trim());
renderEnhancedPanels();
}
function removeEmblem(playerId, idx) {
if (!gameState) return;
var player = gameState.players[playerId];
if (!player || !player.emblems) return;
var removed = player.emblems.splice(idx, 1);
if (removed.length > 0) {
addLogEntry('<strong>' + player.name + '</strong> lost emblem: ' + removed[0].name);
}
renderEnhancedPanels();
}
/**
* Re-render all enhanced player panels in their quadrant positions.
*/
function renderEnhancedPanels() {
if (!gameState) return;
for (var i = 0; i < gameState.players.length; i++) {
var player = gameState.players[i];
var quadrant = i + 1;
var areaEl = document.getElementById('player-area-' + quadrant);
if (!areaEl) continue;
// Find or create the enhanced panel container
var container = areaEl.querySelector('.epp-container');
if (!container) {
container = document.createElement('div');
container.className = 'epp-container';
// Insert before the zone row
var zoneRow = areaEl.querySelector('.zone-row');
if (zoneRow) {
areaEl.insertBefore(container, zoneRow);
} else {
areaEl.appendChild(container);
}
}
var isActive = gameState.currentPlayerIndex === i;
var panel = createEnhancedPlayerPanel(player, quadrant, isActive);
container.innerHTML = '';
container.appendChild(panel);
// Hide the old life counter (we have our own now)
var oldLifeCounter = areaEl.querySelector('.life-counter');
if (oldLifeCounter) oldLifeCounter.style.display = 'none';
// Hide old poison badge (we have counters section)
var oldPoison = areaEl.querySelector('.poison-badge');
if (oldPoison) oldPoison.style.display = 'none';
}
}
-167
View File
@@ -1,167 +0,0 @@
// Auto-generated from precon-decks/precon-index.json
// Run: node scripts/generate-precons-js.js to regenerate
var PRECON_DATA = [
{"id":"Counterpunch","name":"Counterpunch","commander":"Ghave, Guru of Spores","set":"Commander 2011","fileName":"Counterpunch.dck","colors":[],"year":2011},
{"id":"Devour_for_Power_CMD","name":"Devour for Power","commander":"The Mimeoplasm","set":"Commander 2011","fileName":"Devour_for_Power_CMD.dck","colors":[],"year":2011},
{"id":"Heavenly_Inferno_CMD","name":"Heavenly Inferno","commander":"Kaalia of the Vast","set":"Commander 2011","fileName":"Heavenly_Inferno_CMD.dck","colors":[],"year":2011},
{"id":"Mirror_Mastery","name":"Mirror Mastery","commander":"Riku of Two Reflections","set":"Commander 2011","fileName":"Mirror_Mastery.dck","colors":[],"year":2011},
{"id":"Political_Puppets","name":"Political Puppets","commander":"Zedruu the Greathearted","set":"Commander 2011","fileName":"Political_Puppets.dck","colors":[],"year":2011},
{"id":"Eternal_Bargain","name":"Eternal Bargain","commander":"Oloro, Ageless Ascetic","set":"Commander 2013","fileName":"Eternal_Bargain.dck","colors":[],"year":2013},
{"id":"Evasive_Maneuvers_C13","name":"Evasive Maneuvers","commander":"Derevi, Empyrial Tactician","set":"Commander 2013","fileName":"Evasive_Maneuvers_C13.dck","colors":[],"year":2013},
{"id":"Mind_Seize","name":"Mind Seize","commander":"Jeleva, Nephalia's Scourge","set":"Commander 2013","fileName":"Mind_Seize.dck","colors":[],"year":2013},
{"id":"Nature_of_the_Beast","name":"Nature of the Beast","commander":"Marath, Will of the Wild","set":"Commander 2013","fileName":"Nature_of_the_Beast.dck","colors":[],"year":2013},
{"id":"Power_Hungry","name":"Power Hungry","commander":"Prossh, Skyraider of Kher","set":"Commander 2013","fileName":"Power_Hungry.dck","colors":[],"year":2013},
{"id":"Built_From_Scratch_C14","name":"Built From Scratch","commander":"Daretti, Scrap Savant","set":"Commander 2014","fileName":"Built_From_Scratch_C14.dck","colors":[],"year":2014},
{"id":"Forged_In_Stone","name":"Forged In Stone","commander":"Nahiri, the Lithomancer","set":"Commander 2014","fileName":"Forged_In_Stone.dck","colors":[],"year":2014},
{"id":"Guided_By_Nature","name":"Guided By Nature","commander":"Freyalise, Llanowar's Fury","set":"Commander 2014","fileName":"Guided_By_Nature.dck","colors":[],"year":2014},
{"id":"Peer_Through_Time","name":"Peer Through Time","commander":"Teferi, Temporal Archmage","set":"Commander 2014","fileName":"Peer_Through_Time.dck","colors":[],"year":2014},
{"id":"Sworn_To_Darkness","name":"Sworn To Darkness","commander":"Ob Nixilis of the Black Oath","set":"Commander 2014","fileName":"Sworn_To_Darkness.dck","colors":[],"year":2014},
{"id":"Call_the_Spirits","name":"Call the Spirits","commander":"Daxos the Returned","set":"Commander 2015","fileName":"Call_the_Spirits.dck","colors":[],"year":2015},
{"id":"Plunder_the_Graves_C15","name":"Plunder the Graves","commander":"Meren of Clan Nel Toth","set":"Commander 2015","fileName":"Plunder_the_Graves_C15.dck","colors":[],"year":2015},
{"id":"Seize_Control","name":"Seize Control","commander":"Mizzix of the Izmagnus","set":"Commander 2015","fileName":"Seize_Control.dck","colors":[],"year":2015},
{"id":"Swell_the_Host","name":"Swell the Host","commander":"Ezuri, Claw of Progress","set":"Commander 2015","fileName":"Swell_the_Host.dck","colors":[],"year":2015},
{"id":"Wade_into_Battle_C15","name":"Wade into Battle","commander":"Kalemne, Disciple of Iroas","set":"Commander 2015","fileName":"Wade_into_Battle_C15.dck","colors":[],"year":2015},
{"id":"Breed_Lethality_C16","name":"Breed Lethality","commander":"Atraxa, Praetors' Voice","set":"Commander 2016","fileName":"Breed_Lethality_C16.dck","colors":[],"year":2016},
{"id":"Entropic_Uprising","name":"Entropic Uprising","commander":"Yidris, Maelstrom Wielder","set":"Commander 2016","fileName":"Entropic_Uprising.dck","colors":[],"year":2016},
{"id":"Invent_Superiority","name":"Invent Superiority","commander":"Breya, Etherium Shaper","set":"Commander 2016","fileName":"Invent_Superiority.dck","colors":[],"year":2016},
{"id":"Open_Hostility","name":"Open Hostility","commander":"Saskia the Unyielding","set":"Commander 2016","fileName":"Open_Hostility.dck","colors":[],"year":2016},
{"id":"Stalwart_Unity","name":"Stalwart Unity","commander":"Kynaios and Tiro of Meletis","set":"Commander 2016","fileName":"Stalwart_Unity.dck","colors":[],"year":2016},
{"id":"Evasive_Maneuvers_CMA","name":"Evasive Maneuvers","commander":"Derevi, Empyrial Tactician","set":"Commander Anthology","fileName":"Evasive_Maneuvers_CMA.dck","colors":[],"year":2017},
{"id":"Guided_by_Nature","name":"Guided by Nature","commander":"Freyalise, Llanowar's Fury","set":"Commander Anthology","fileName":"Guided_by_Nature.dck","colors":[],"year":2017},
{"id":"Heavenly_Inferno_CMA","name":"Heavenly Inferno","commander":"Kaalia of the Vast","set":"Commander Anthology","fileName":"Heavenly_Inferno_CMA.dck","colors":[],"year":2017},
{"id":"Plunder_the_Graves_CMA","name":"Plunder the Graves","commander":"Meren of Clan Nel Toth","set":"Commander Anthology","fileName":"Plunder_the_Graves_CMA.dck","colors":[],"year":2017},
{"id":"Arcane_Wizardry","name":"Arcane Wizardry","commander":"Inalla, Archmage Ritualist","set":"Commander 2017","fileName":"Arcane_Wizardry.dck","colors":[],"year":2017},
{"id":"Draconic_Domination","name":"Draconic Domination","commander":"The Ur-Dragon","set":"Commander 2017","fileName":"Draconic_Domination.dck","colors":[],"year":2017},
{"id":"Feline_Ferocity","name":"Feline Ferocity","commander":"Arahbo, Roar of the World","set":"Commander 2017","fileName":"Feline_Ferocity.dck","colors":[],"year":2017},
{"id":"Vampiric_Bloodlust","name":"Vampiric Bloodlust","commander":"Edgar Markov","set":"Commander 2017","fileName":"Vampiric_Bloodlust.dck","colors":[],"year":2017},
{"id":"Breed_Lethality_CM2","name":"Breed Lethality","commander":"Atraxa, Praetors' Voice","set":"Commander Anthology Volume II","fileName":"Breed_Lethality_CM2.dck","colors":[],"year":2018},
{"id":"Built_From_Scratch_CM2","name":"Built From Scratch","commander":"Daretti, Scrap Savant","set":"Commander Anthology Volume II","fileName":"Built_From_Scratch_CM2.dck","colors":[],"year":2018},
{"id":"Devour_for_Power_CM2","name":"Devour for Power","commander":"The Mimeoplasm","set":"Commander Anthology Volume II","fileName":"Devour_for_Power_CM2.dck","colors":[],"year":2018},
{"id":"Wade_into_Battle_CM2","name":"Wade into Battle","commander":"Kalemne, Disciple of Iroas","set":"Commander Anthology Volume II","fileName":"Wade_into_Battle_CM2.dck","colors":[],"year":2018},
{"id":"Adaptive_Enchantment","name":"Adaptive Enchantment","commander":"Estrid, the Masked","set":"Commander 2018","fileName":"Adaptive_Enchantment.dck","colors":[],"year":2018},
{"id":"Exquisite_Invention","name":"Exquisite Invention","commander":"Saheeli, the Gifted","set":"Commander 2018","fileName":"Exquisite_Invention.dck","colors":[],"year":2018},
{"id":"Natures_Vengeance","name":"Nature's Vengeance","commander":"Lord Windgrace","set":"Commander 2018","fileName":"Natures_Vengeance.dck","colors":[],"year":2018},
{"id":"Subjective_Reality","name":"Subjective Reality","commander":"Aminatou, the Fateshifter","set":"Commander 2018","fileName":"Subjective_Reality.dck","colors":[],"year":2018},
{"id":"Faceless_Menace","name":"Faceless Menace","commander":"Kadena, Slinking Sorcerer","set":"Commander 2019","fileName":"Faceless_Menace.dck","colors":[],"year":2019},
{"id":"Merciless_Rage","name":"Merciless Rage","commander":"Anje Falkenrath","set":"Commander 2019","fileName":"Merciless_Rage.dck","colors":[],"year":2019},
{"id":"Mystic_Intellect","name":"Mystic Intellect","commander":"Sevinne, the Chronoclasm","set":"Commander 2019","fileName":"Mystic_Intellect.dck","colors":[],"year":2019},
{"id":"Primal_Genesis","name":"Primal Genesis","commander":"Ghired, Conclave Exile","set":"Commander 2019","fileName":"Primal_Genesis.dck","colors":[],"year":2019},
{"id":"Arcane_Maelstrom","name":"Arcane Maelstrom","commander":"Kalamax, the Stormsire","set":"Commander 2020","fileName":"Arcane_Maelstrom.dck","colors":[],"year":2020},
{"id":"Enhanced_Evolution","name":"Enhanced Evolution","commander":"Otrimi, the Ever-Playful","set":"Commander 2020","fileName":"Enhanced_Evolution.dck","colors":[],"year":2020},
{"id":"Ruthless_Regiment","name":"Ruthless Regiment","commander":"Jirina Kudro","set":"Commander 2020","fileName":"Ruthless_Regiment.dck","colors":[],"year":2020},
{"id":"Symbiotic_Swarm","name":"Symbiotic Swarm","commander":"Kathril, Aspect Warper","set":"Commander 2020","fileName":"Symbiotic_Swarm.dck","colors":[],"year":2020},
{"id":"Timeless_Wisdom","name":"Timeless Wisdom","commander":"Gavi, Nest Warden","set":"Commander 2020","fileName":"Timeless_Wisdom.dck","colors":[],"year":2020},
{"id":"Lands_Wrath","name":"Land's Wrath","commander":"Obuun, Mul Daya Ancestor","set":"Zendikar Rising Commander","fileName":"Lands_Wrath.dck","colors":[],"year":2020},
{"id":"Sneak_Attack","name":"Sneak Attack","commander":"Anowon, the Ruin Thief","set":"Zendikar Rising Commander","fileName":"Sneak_Attack.dck","colors":[],"year":2020},
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@@ -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])
+6 -6
View File
@@ -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,
+30 -72
View File
@@ -178,23 +178,6 @@ class StateEncoder:
[0:29] - Global features (life, mana, turn, phase, etc.)
[29:6173] - Zone embeddings (4 zones × 2 players × 768)
[6173:6177] - Playstyle one-hot (4 dims)
Global feature layout per player block (14 features × 2 players + 1 turn = 29):
idx 0 life (normalised /40)
idx 1 cmdr_dmg (normalised /21)
idx 2 mana (normalised /20, clamped)
idx 3 cmdr_tax (normalised /10, clamped)
idx 4 hand_size (normalised /15, clamped)
idx 5 graveyard_size (normalised /100, clamped)
idx 6 creatures (normalised /30, clamped)
idx 7 total_power (normalised /100, clamped)
└─ real Forge value when present;
falls back to creatures*3 heuristic
idx 8 is_active (binary 0/1)
idx 9-12 phase one-hot (4 dims: main_1/combat/main_2/end)
idx 13 lands (normalised /15, clamped)
--- repeat for player 1 at idx 14-27 ---
idx 28 turn (normalised /max_turns)
"""
def __init__(self, card_index: CardEmbeddingIndex):
@@ -214,6 +197,7 @@ class StateEncoder:
"""
players = decision.get("players", [])
if len(players) < 2:
# Pad to 2 players for 1v1
while len(players) < 2:
players.append(self._empty_player(len(players)))
@@ -234,71 +218,55 @@ class StateEncoder:
return state.astype(np.float32)
def _encode_global(self, decision: dict, players: list) -> np.ndarray:
"""Encode global scalar features. Shape: (29,)
Per-player block (14 features each, 2 players = 28) + 1 turn feature.
Index 7 priority for total_power:
1. p['total_power'] — real Forge value from Step 4 / _build_encoder_snapshot()
2. p['creatures'] * 3 — legacy heuristic for old JSONL snapshots
"""
"""Encode global scalar features. Shape: (29,)"""
features = []
for p in players[:2]:
# idx 0: life
for p in players[:2]: # Exactly 2 players for 1v1
# Per-player scalars (10 each)
life = p.get("life", 40)
features.append(life / 40.0)
features.append(life / 40.0) # Normalized life
# idx 1: commander damage taken
cmdr_dmg = p.get("cmdr_dmg", 0)
features.append(cmdr_dmg / 21.0)
features.append(cmdr_dmg / 21.0) # Normalized commander damage
# idx 2: mana available
mana = p.get("mana", 0)
features.append(min(mana / 20.0, 1.0))
features.append(min(mana / 20.0, 1.0)) # Normalized mana
# idx 3: commander tax
cmdr_tax = p.get("cmdr_tax", 0)
features.append(min(cmdr_tax / 10.0, 1.0))
features.append(min(cmdr_tax / 10.0, 1.0)) # Normalized tax
# idx 4: cards in hand
hand_size = len(p.get("hand", []))
features.append(min(hand_size / 15.0, 1.0))
# idx 5: graveyard size
grave_size = len(p.get("graveyard", []))
features.append(min(grave_size / 100.0, 1.0))
# idx 6: creatures on battlefield
creatures = p.get("creatures", 0)
features.append(min(creatures / 30.0, 1.0))
# idx 7: total power on board
# Use real Forge value when available (Step 4); fall back to heuristic
# for legacy JSONL snapshots that predate Step 4.
raw_power = p.get("total_power", 0)
total_power = raw_power if raw_power > 0 else creatures * 3
# Total power on board (not yet tracked accurately; use creatures as proxy)
total_power = creatures * 3 # rough heuristic: avg 3 power
features.append(min(total_power / 100.0, 1.0))
# idx 8: is active player
# Is active player
is_active = 1.0 if p.get("seat") == decision.get("active_seat") else 0.0
features.append(is_active)
# idx 9-12: phase one-hot (4 dims)
# Land count (extra feature — helps distinguish ramp strategies)
lands = p.get("lands", 0)
features.append(min(lands / 15.0, 1.0))
# Phase one-hot (4 dims per player)
phase_str = decision.get("phase", "main_1")
phase_oh = [0.0] * 4
try:
phase_enum = GamePhase(phase_str)
phase_oh[PHASE_TO_IDX[phase_enum]] = 1.0
except (ValueError, KeyError):
phase_oh[0] = 1.0 # default to main_1
phase_oh[0] = 1.0 # Default to main_1
features.extend(phase_oh)
# idx 13: land count
lands = p.get("lands", 0)
features.append(min(lands / 15.0, 1.0))
# idx 28: turn number (shared, 1 feature)
# Turn number (1 feature, shared)
turn = decision.get("turn", 1)
features.append(min(turn / GAME_SCOPE.max_turns, 1.0))
@@ -308,13 +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 = []
@@ -334,27 +295,24 @@ class StateEncoder:
style = Playstyle(playstyle_str.lower())
vec[PLAYSTYLE_TO_IDX[style]] = 1.0
except (ValueError, KeyError):
# Default: midrange
vec[PLAYSTYLE_TO_IDX[Playstyle.MIDRANGE]] = 1.0
return vec
def _empty_player(self, seat: int) -> dict:
"""Create an empty player dict for padding."""
return {
"seat": seat,
"life": 40,
"cmdr_dmg": 0,
"mana": 0,
"cmdr_tax": 0,
"creatures": 0,
"total_power": 0,
"total_toughness": 0,
"artifacts": 0,
"enchantments": 0,
"lands": 0,
"hand": [],
"battlefield": [],
"graveyard": [],
"command_zone": [],
"seat": seat,
"life": 40,
"cmdr_dmg": 0,
"mana": 0,
"cmdr_tax": 0,
"creatures": 0,
"lands": 0,
"hand": [],
"battlefield": [],
"graveyard": [],
"command_zone": [],
}
+1 -25
View File
@@ -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
-548
View File
@@ -1,548 +0,0 @@
"""
Commander AI Lab — Forge Evaluator (Issue #153)
═════════════════════════════════════════════════
Reusable eval harness that:
1. Starts the policy inference server pointing at a given checkpoint
2. Launches Forge games via MultiThreadBatchRunner with the policy
server wired in as the AI decision-maker
3. Collects per-game metrics and writes a JSON results file
Metrics collected per game:
- won : bool
- turns : int
- life_final : int (winning seat final life)
- life_delta : int (winner life - loser life at game end)
- cmd_damage : int (commander damage dealt by policy seat)
- illegal_acts : int (actions rejected by Forge — should be 0)
- entropy_mean : float (mean policy entropy across decision steps)
- inference_ms : float (mean per-step inference latency)
Usage:
from ml.eval.forge_evaluator import ForgeEvaluator, EvalConfig
cfg = EvalConfig(
checkpoint_path="ml/models/checkpoints/forge-trained/final.pt",
forge_jar="forge/forge-gui-desktop-2.0.12-SNAPSHOT-jar-with-dependencies.jar",
deck_files=["decks/cedh_test_a.dck", "decks/cedh_test_b.dck"],
num_games=200,
num_threads=4,
run_id="forge-trained",
results_dir="results",
)
evaluator = ForgeEvaluator(cfg)
summary = evaluator.run()
print(summary)
"""
import json
import logging
import os
import sys
import time
import uuid
import subprocess
from dataclasses import dataclass, field, asdict
from pathlib import Path
from typing import Dict, List, Optional
import numpy as np
project_root = str(Path(__file__).parent.parent.parent)
if project_root not in sys.path:
sys.path.insert(0, project_root)
logger = logging.getLogger("ml.eval.forge_evaluator")
# ─────────────────────────────────────────────
# Configuration
# ─────────────────────────────────────────────
@dataclass
class EvalConfig:
"""All parameters needed for a single evaluation run."""
# Model
checkpoint_path: str = "ml/models/checkpoints/best_policy.pt"
embeddings_dir: str = "embeddings"
device: str = None # None = auto-detect
# Forge
forge_jar: str = "forge/forge-gui-desktop-2.0.12-SNAPSHOT-jar-with-dependencies.jar"
forge_work_dir: str = "forge"
java_path: str = "java"
deck_files: List[str] = field(default_factory=list)
deck_names: List[str] = field(default_factory=list)
policy_server_url: str = "http://localhost:8091"
clock_seconds: int = 120
# Run
num_games: int = 200
num_threads: int = 4
seed: Optional[int] = None
run_id: str = ""
results_dir: str = "results"
# Inference
greedy: bool = True
temperature: float = 1.0
def __post_init__(self):
if not self.run_id:
self.run_id = str(uuid.uuid4())[:8]
# ─────────────────────────────────────────────
# Per-game result
# ─────────────────────────────────────────────
@dataclass
class GameRecord:
game_index: int
won: bool
turns: int
life_final_policy: int # life total of policy seat at game end
life_final_opponent: int
life_delta: int # policy life - opponent life
commander_damage_dealt: int
illegal_actions: int
entropy_mean: float # mean per-step policy entropy
inference_ms_mean: float # mean per-step inference latency
decision_steps: int # number of decision points in this game
error: str = ""
# ─────────────────────────────────────────────
# Eval summary
# ─────────────────────────────────────────────
@dataclass
class EvalSummary:
run_id: str
checkpoint_path: str
num_games: int
wins: int
losses: int
win_rate: float
win_rate_ci95_low: float
win_rate_ci95_high: float
avg_turns: float
avg_life_delta: float
avg_commander_damage: float
avg_illegal_actions: float
avg_entropy: float
avg_inference_ms: float
total_decision_steps: int
elapsed_wall_s: float
games_per_sec: float
error_count: int
result_file: str
def __str__(self) -> str:
return (
f"EvalSummary run={self.run_id}\n"
f" checkpoint : {self.checkpoint_path}\n"
f" games : {self.num_games} ({self.wins}W / {self.losses}L)\n"
f" win rate : {self.win_rate:.1%} "
f"[{self.win_rate_ci95_low:.1%}, {self.win_rate_ci95_high:.1%}] 95% CI\n"
f" avg turns : {self.avg_turns:.1f}\n"
f" avg life Δ : {self.avg_life_delta:+.1f}\n"
f" avg cmd dmg: {self.avg_commander_damage:.1f}\n"
f" illegal : {self.avg_illegal_actions:.2f}/game\n"
f" entropy : {self.avg_entropy:.4f}\n"
f" latency : {self.avg_inference_ms:.1f} ms/step\n"
f" throughput : {self.games_per_sec:.2f} games/sec\n"
f" result file: {self.result_file}\n"
)
# ─────────────────────────────────────────────
# Main evaluator
# ─────────────────────────────────────────────
class ForgeEvaluator:
"""
Orchestrates a full eval run:
1. Spin up PolicyInferenceService on cfg.policy_server_url port
2. Run cfg.num_games Forge games via MultiThreadBatchRunner
3. Parse Forge JSONL output for per-game metrics
4. Write results to {results_dir}/eval-{run_id}.json
"""
def __init__(self, cfg: EvalConfig):
self.cfg = cfg
self._records: List[GameRecord] = []
self._result_path = os.path.join(
cfg.results_dir, f"eval-{cfg.run_id}.json"
)
# ── Public entry point ───────────────────
def run(self) -> EvalSummary:
"""Run the full evaluation. Returns an EvalSummary."""
t0 = time.time()
os.makedirs(self.cfg.results_dir, exist_ok=True)
logger.info("[Eval %s] Starting %d-game eval run", self.cfg.run_id, self.cfg.num_games)
logger.info("[Eval %s] Checkpoint: %s", self.cfg.run_id, self.cfg.checkpoint_path)
# Load policy service
service = self._load_policy_service()
# Run games — either via real Forge or synthetic fallback
forge_available = (
self.cfg.forge_jar
and Path(self.cfg.forge_jar).exists()
and len(self.cfg.deck_files) >= 3
)
if forge_available:
self._records = self._run_forge_games(service)
else:
logger.warning(
"[Eval %s] Forge JAR or decks not found — running synthetic eval.",
self.cfg.run_id
)
self._records = self._run_synthetic_eval(service)
elapsed = time.time() - t0
summary = self._build_summary(elapsed)
self._write_results(summary)
logger.info("[Eval %s] Done. %s", self.cfg.run_id, summary)
return summary
# ── Policy service setup ─────────────────
def _load_policy_service(self):
try:
from ml.serving.policy_server import PolicyInferenceService
svc = PolicyInferenceService(
checkpoint_dir=str(Path(self.cfg.checkpoint_path).parent),
embeddings_dir=self.cfg.embeddings_dir,
device=self.cfg.device,
)
svc.load()
ok = svc.reload(self.cfg.checkpoint_path)
if not ok:
logger.warning("[Eval] Policy service load failed — entropy/latency metrics unavailable")
return svc
except Exception as e:
logger.error("[Eval] Could not load PolicyInferenceService: %s", e)
return None
# ── Real Forge game runner ───────────────
def _run_forge_games(self, service) -> List[GameRecord]:
"""Launch LabCli Java subprocess with --ml-log, then parse JSONL output."""
logger.info("[Eval %s] Launching Forge CLI subprocess for %d games", self.cfg.run_id, self.cfg.num_games)
deck_args = []
for i, df in enumerate(self.cfg.deck_files[:4]):
deck_args.extend([f"--deck{i+1}", Path(df).stem])
# Resolve Java 17
java_exe = self.cfg.java_path
for c in [r"C:\Program Files\Eclipse Adoptium\jdk-17.0.18.8-hotspot\bin\java.exe",
r"C:\Program Files\Java\jdk-17\bin\java.exe"]:
if Path(c).exists():
java_exe = c
break
lab_jar = os.path.join(project_root, "target", "commander-ai-lab-1.0.0-SNAPSHOT.jar")
if not Path(lab_jar).exists():
logger.error("[Eval] Lab JAR not found at %s -- run mvn package -DskipTests first", lab_jar)
return self._run_synthetic_eval(service)
cmd = [
java_exe, "-jar", lab_jar,
"--forge-jar", self.cfg.forge_jar,
"--forge-dir", self.cfg.forge_work_dir,
*deck_args,
"--games", str(self.cfg.num_games),
"--threads", str(self.cfg.num_threads),
"--clock", str(self.cfg.clock_seconds),
"--ml-log",
"--output", os.path.join(self.cfg.results_dir, f"eval-{self.cfg.run_id}-batch.json"),
]
if self.cfg.seed is not None:
cmd.extend(["--seed", str(self.cfg.seed)])
logger.info("[Eval %s] CMD: %s", self.cfg.run_id, " ".join(cmd))
try:
result = subprocess.run(cmd, capture_output=True, text=True,
timeout=self.cfg.clock_seconds * self.cfg.num_games + 300)
if result.returncode != 0:
logger.warning("[Eval %s] Forge CLI exit %d: %s", self.cfg.run_id, result.returncode, result.stderr[:500])
except (subprocess.TimeoutExpired, FileNotFoundError) as e:
logger.error("[Eval %s] Forge CLI failed: %s -- falling back to synthetic", self.cfg.run_id, e)
return self._run_synthetic_eval(service)
return self._parse_batch_json(service)
def _parse_batch_json(self, service) -> List[GameRecord]:
"""Parse the batch JSON output from LabCli Java subprocess."""
batch_path = os.path.join(
self.cfg.results_dir, f"eval-{self.cfg.run_id}-batch.json"
)
if not Path(batch_path).exists():
logger.warning("[Eval] Batch JSON not found at %s — falling back to synthetic", batch_path)
return self._run_synthetic_eval(service)
with open(batch_path) as f:
batch = json.load(f)
games_list = batch.get("games", [])
if not games_list:
logger.warning("[Eval] No games in batch JSON — falling back to synthetic")
return self._run_synthetic_eval(service)
records = []
for idx, g in enumerate(games_list):
won = g.get("winningSeat", -1) == 0
turns = g.get("totalTurns", 0)
pr = g.get("playerResults", [])
lp = pr[0].get("finalLife", 40) if len(pr) > 0 else 40
lo = pr[1].get("finalLife", 40) if len(pr) > 1 else 40
records.append(GameRecord(
game_index=idx,
won=won,
turns=turns,
life_final_policy=lp,
life_final_opponent=lo,
life_delta=lp - lo,
commander_damage_dealt=0,
illegal_actions=0,
entropy_mean=0.0,
inference_ms_mean=0.0,
decision_steps=turns,
))
if len(records) >= self.cfg.num_games:
break
logger.info("[Eval %s] Parsed %d games from batch JSON", self.cfg.run_id, len(records))
return records
def _run_forge_via_subprocess(self, service) -> List[GameRecord]:
"""Parse JSONL files produced by a separately-launched Forge batch."""
records = []
results_path = Path(self.cfg.results_dir)
pattern = f"ml-decisions-forge-eval-{self.cfg.run_id}*.jsonl"
all_files = sorted(results_path.glob(pattern))
if not all_files:
logger.warning("[Eval] No JSONL files found matching %s — falling back to synthetic", pattern)
return self._run_synthetic_eval(service)
from ml.training.forge_episode_generator import parse_forge_jsonl, snapshots_to_episode
games_seen: Dict[str, list] = {}
for f in all_files:
for snap in parse_forge_jsonl(f):
gid = snap.get("game_id", "g0")
games_seen.setdefault(gid, []).append(snap)
for idx, (gid, snaps) in enumerate(games_seen.items()):
records.append(self._snaps_to_record(idx, gid, snaps, service))
if len(records) >= self.cfg.num_games:
break
return records
def _java_results_to_records(self, java_results, service) -> List[GameRecord]:
"""Convert Java GameResult objects to GameRecord."""
records = []
for jr in java_results:
try:
won = getattr(jr, "winningSeat", 0) == 0 # seat 0 = policy
records.append(GameRecord(
game_index=getattr(jr, "gameIndex", len(records)),
won=won,
turns=getattr(jr, "turns", 0),
life_final_policy=getattr(jr, "lifeAtEnd", [40])[0] if hasattr(jr, "lifeAtEnd") else 40,
life_final_opponent=getattr(jr, "lifeAtEnd", [40, 40])[1] if hasattr(jr, "lifeAtEnd") else 40,
life_delta=0,
commander_damage_dealt=0,
illegal_actions=getattr(jr, "illegalActions", 0),
entropy_mean=0.0,
inference_ms_mean=0.0,
decision_steps=0,
))
except Exception as e:
logger.warning("[Eval] Skipping malformed GameResult: %s", e)
return records
# ── Synthetic fallback ───────────────────
def _run_synthetic_eval(self, service) -> List[GameRecord]:
"""Run synthetic games using self_play engine (no Forge required).
Used when Forge JAR is missing or deck files aren't configured.
Metrics like illegal_actions and commander_damage are 0 in this mode.
"""
import warnings
warnings.filterwarnings("ignore", category=DeprecationWarning)
records = []
try:
from ml.training.self_play import (
create_random_initial_state, apply_action, advance_turn,
encode_state_simple, HeuristicPolicy
)
from ml.config.scope import NUM_ACTIONS, IDX_TO_ACTION
import torch
import torch.nn.functional as F
except ImportError as e:
logger.error("[Eval] Cannot import self_play: %s", e)
return []
opponent = HeuristicPolicy()
agent_has_model = service is not None and service._loaded
for game_idx in range(self.cfg.num_games):
state = create_random_initial_state()
entropies, latencies = [], []
steps = 0
while not state.game_over and steps < 60:
sv = encode_state_simple(state, 0, "midrange")
t0 = time.time()
if agent_has_model:
snap = state.to_snapshot()
result = service.predict(
snap, playstyle="midrange",
greedy=self.cfg.greedy,
temperature=self.cfg.temperature,
)
action_idx = result.get("action_index", 7)
probs_map = result.get("probabilities", {})
probs = np.array(list(probs_map.values())) if probs_map else np.ones(NUM_ACTIONS) / NUM_ACTIONS
else:
action_idx = np.random.randint(NUM_ACTIONS)
probs = np.ones(NUM_ACTIONS) / NUM_ACTIONS
latencies.append((time.time() - t0) * 1000)
p = np.clip(probs, 1e-9, 1.0)
p /= p.sum()
entropies.append(float(-np.sum(p * np.log(p))))
state = apply_action(state, action_idx, 0)
if not state.game_over:
opp_sv = encode_state_simple(state, 1, "midrange")
opp_a, _ = opponent.select_action(opp_sv)
state = apply_action(state, opp_a, 1)
if not state.game_over:
state = advance_turn(state)
steps += 1
won = state.winner == 0
lp = state.players[0].life_total
lo = state.players[1].life_total
records.append(GameRecord(
game_index=game_idx,
won=won,
turns=state.turn,
life_final_policy=lp,
life_final_opponent=lo,
life_delta=lp - lo,
commander_damage_dealt=0,
illegal_actions=0,
entropy_mean=float(np.mean(entropies)) if entropies else 0.0,
inference_ms_mean=float(np.mean(latencies)) if latencies else 0.0,
decision_steps=steps,
))
return records
# ── JSONL snapshot → GameRecord ──────────
def _snaps_to_record(self, idx: int, gid: str, snaps: list, service) -> GameRecord:
entropies, latencies = [], []
won = False
turns = len(snaps)
cmd_dmg = 0
illegal = 0
lp, lo = 40, 40
for snap in snaps:
if "outcome" in snap and snap == snaps[-1]:
won = snap["outcome"].get("winner_seat", -1) == 0
lp = snap["outcome"].get("life_remaining", 40)
lo = snap["outcome"].get("opp_life_remaining", 0)
cmd_dmg = snap["outcome"].get("commander_damage_dealt", 0)
if service and service._loaded and "state_vector" in snap:
t0 = time.time()
result = service.predict(snap, playstyle="midrange", greedy=self.cfg.greedy)
latencies.append((time.time() - t0) * 1000)
probs_map = result.get("probabilities", {})
if probs_map:
p = np.clip(list(probs_map.values()), 1e-9, 1.0)
p /= p.sum()
entropies.append(float(-np.sum(p * np.log(p))))
return GameRecord(
game_index=idx,
won=won,
turns=turns,
life_final_policy=lp,
life_final_opponent=lo,
life_delta=lp - lo,
commander_damage_dealt=cmd_dmg,
illegal_actions=illegal,
entropy_mean=float(np.mean(entropies)) if entropies else 0.0,
inference_ms_mean=float(np.mean(latencies)) if latencies else 0.0,
decision_steps=len(snaps),
)
# ── Summary builder ──────────────────────
def _build_summary(self, elapsed: float) -> EvalSummary:
n = len(self._records)
if n == 0:
return EvalSummary(
run_id=self.cfg.run_id,
checkpoint_path=self.cfg.checkpoint_path,
num_games=0, wins=0, losses=0,
win_rate=0.0, win_rate_ci95_low=0.0, win_rate_ci95_high=0.0,
avg_turns=0.0, avg_life_delta=0.0, avg_commander_damage=0.0,
avg_illegal_actions=0.0, avg_entropy=0.0, avg_inference_ms=0.0,
total_decision_steps=0, elapsed_wall_s=elapsed, games_per_sec=0.0,
error_count=0, result_file=self._result_path,
)
wins = sum(1 for r in self._records if r.won)
losses = n - wins
wr = wins / n
# Wilson score 95% CI
z = 1.96
denom = 1 + z**2 / n
centre = (wr + z**2 / (2 * n)) / denom
margin = (z * (wr * (1 - wr) / n + z**2 / (4 * n**2)) ** 0.5) / denom
ci_lo = max(0.0, centre - margin)
ci_hi = min(1.0, centre + margin)
errors = sum(1 for r in self._records if r.error)
return EvalSummary(
run_id=self.cfg.run_id,
checkpoint_path=self.cfg.checkpoint_path,
num_games=n,
wins=wins,
losses=losses,
win_rate=wr,
win_rate_ci95_low=ci_lo,
win_rate_ci95_high=ci_hi,
avg_turns=float(np.mean([r.turns for r in self._records])),
avg_life_delta=float(np.mean([r.life_delta for r in self._records])),
avg_commander_damage=float(np.mean([r.commander_damage_dealt for r in self._records])),
avg_illegal_actions=float(np.mean([r.illegal_actions for r in self._records])),
avg_entropy=float(np.mean([r.entropy_mean for r in self._records])),
avg_inference_ms=float(np.mean([r.inference_ms_mean for r in self._records])),
total_decision_steps=sum(r.decision_steps for r in self._records),
elapsed_wall_s=elapsed,
games_per_sec=n / max(elapsed, 0.001),
error_count=errors,
result_file=self._result_path,
)
# ── Result writer ────────────────────────
def _write_results(self, summary: EvalSummary) -> None:
payload = {
"summary": asdict(summary),
"games": [asdict(r) for r in self._records],
}
os.makedirs(self.cfg.results_dir, exist_ok=True)
with open(self._result_path, "w") as f:
json.dump(payload, f, indent=2)
logger.info("[Eval %s] Results written to %s", self.cfg.run_id, self._result_path)
-210
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@@ -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]
-40
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@@ -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",
]
+3 -3
View File
@@ -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
-352
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@@ -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
+1 -2
View File
@@ -223,8 +223,7 @@ def load_checkpoint(path: str, device: str = "cpu"):
num_layers=config.get("num_layers", TRAINING_CONFIG.num_layers),
dropout=config.get("dropout", TRAINING_CONFIG.dropout),
)
state = {k: v for k, v in checkpoint["model_state_dict"].items() if not k.startswith("value_head")}
model.load_state_dict(state, strict=False)
model.load_state_dict(checkpoint["model_state_dict"])
model.to(device)
return model, checkpoint
+132 -339
View File
@@ -9,27 +9,22 @@ Proximal Policy Optimization (Clip) with:
- Self-play episode collection between updates
- Periodic checkpointing and evaluation
- Win-rate tracking against opponent policies
- Forge-based episode source via --data-source forge|mixed
Reference: Schulman et al., "Proximal Policy Optimization Algorithms", 2017
Usage:
python -m ml.training.ppo_trainer --iterations 100 --episodes-per-iter 64
python -m ml.training.ppo_trainer --load-supervised ml/models/checkpoints/best_policy.pt
python -m ml.training.ppo_trainer --data-source forge --forge-results-dir results --iterations 50
python -m ml.training.ppo_trainer --data-source mixed --forge-weight 0.7 --iterations 100
"""
import argparse
import asyncio
import json
import logging
import os
import sys
import threading
import time
from pathlib import Path
from typing import Dict, List, Optional
from typing import Dict, Optional
import numpy as np
@@ -56,114 +51,6 @@ from ml.training.self_play import (
logger = logging.getLogger("ml.ppo")
# ══════════════════════════════════════════════════════════
# Forge data-source integration
# ══════════════════════════════════════════════════════════
def episodes_to_buffer(episodes, buffer: RolloutBuffer) -> int:
"""Drain a list of ForgeEpisodes into an existing RolloutBuffer.
Returns the number of transitions added.
"""
added = 0
for ep in episodes:
for t in ep.transitions:
if buffer.size >= buffer.buffer_size:
break
buffer.add(
state=t.state,
action=t.action,
reward=t.reward,
log_prob=t.log_prob,
value=t.value,
done=t.done,
)
added += 1
return added
class ForgeDataSource:
"""Runs the Forge producer pipeline in a background thread and
exposes a synchronous drain() method for the PPO training loop.
Usage::
source = ForgeDataSource(results_dir="results", batch_id="run1", num_games=64)
source.start()
# ... in training loop ...
episodes = source.drain()
source.stop()
"""
def __init__(
self,
results_dir: str = "results",
batch_id: str = "forge-batch",
num_games: int = 256,
reward_config: Optional[RewardConfig] = None,
queue_size: int = 256,
):
self.results_dir = results_dir
self.batch_id = batch_id
self.num_games = num_games
self.reward_config = reward_config or RewardConfig()
self.queue_size = queue_size
self._episodes: List = []
self._lock = threading.Lock()
self._thread: Optional[threading.Thread] = None
self._stop_event = threading.Event()
def start(self):
"""Launch the background producer thread."""
self._thread = threading.Thread(target=self._run, daemon=True)
self._thread.start()
logger.info("[ForgeDataSource] Producer started (results_dir=%s, batch_id=%s, num_games=%d)",
self.results_dir, self.batch_id, self.num_games)
def _run(self):
from ml.training.forge_episode_generator import ForgeEpisodeQueue, forge_producer
async def _produce():
queue = ForgeEpisodeQueue(max_size=self.queue_size)
produced = await forge_producer(
queue=queue,
results_dir=self.results_dir,
batch_id=self.batch_id,
num_games=self.num_games,
reward_config=self.reward_config,
)
queue.close()
# Drain remaining items
while not queue.is_closed:
ep = await queue.get(timeout=1.0)
if ep is not None:
with self._lock:
self._episodes.append(ep)
logger.info("[ForgeDataSource] Producer finished: %d episodes", produced)
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
try:
loop.run_until_complete(_produce())
finally:
loop.close()
def drain(self) -> List:
"""Return and clear all buffered episodes (thread-safe)."""
with self._lock:
eps = list(self._episodes)
self._episodes.clear()
return eps
def stop(self):
self._stop_event.set()
if self._thread:
self._thread.join(timeout=5.0)
# ══════════════════════════════════════════════════════════
# PPO Config
# ══════════════════════════════════════════════════════════
class PPOConfig:
"""PPO hyperparameters."""
@@ -204,13 +91,6 @@ class PPOConfig:
# Supervised preload
load_supervised: Optional[str] = None,
# Data source
data_source: str = "synthetic", # synthetic | forge | mixed
forge_results_dir: str = "results",
forge_batch_id: str = "forge-batch",
forge_num_games: int = 256,
forge_weight: float = 0.7, # fraction of buffer from Forge when mixed
):
self.iterations = iterations
self.episodes_per_iter = episodes_per_iter
@@ -234,19 +114,10 @@ class PPOConfig:
self.eval_every = eval_every
self.eval_episodes = eval_episodes
self.load_supervised = load_supervised
self.data_source = data_source
self.forge_results_dir = forge_results_dir
self.forge_batch_id = forge_batch_id
self.forge_num_games = forge_num_games
self.forge_weight = max(0.0, min(1.0, forge_weight))
# ══════════════════════════════════════════════════════════
# PPO Trainer
# ══════════════════════════════════════════════════════════
class PPOTrainer:
"""Proximal Policy Optimization trainer with self-play and optional Forge data source."""
"""Proximal Policy Optimization trainer with self-play."""
def __init__(self, config: PPOConfig):
if not TORCH_AVAILABLE:
@@ -255,24 +126,28 @@ class PPOTrainer:
self.config = config
self.device = self._detect_device()
# Create actor-critic model
from ml.training.policy_network import PolicyValueNetwork
self.model = PolicyValueNetwork(
input_dim=STATE_DIMS.total_state_dim,
hidden_dim=TRAINING_CONFIG.hidden_dim,
num_actions=NUM_ACTIONS,
num_layers=TRAINING_CONFIG.num_layers,
dropout=0.0,
dropout=0.0, # No dropout during RL
).to(self.device)
# Optionally load from supervised checkpoint
if config.load_supervised and os.path.exists(config.load_supervised):
self._load_supervised_weights(config.load_supervised)
# Optimizer
self.optimizer = torch.optim.Adam(
self.model.parameters(),
lr=config.learning_rate,
eps=1e-5,
)
# Learning rate scheduler
self.scheduler = None
if config.lr_schedule == "linear":
self.scheduler = torch.optim.lr_scheduler.LinearLR(
@@ -288,6 +163,7 @@ class PPOTrainer:
eta_min=config.min_lr,
)
# Rollout buffer
self.buffer = RolloutBuffer(
buffer_size=config.buffer_size,
state_dim=STATE_DIMS.total_state_dim,
@@ -295,23 +171,16 @@ class PPOTrainer:
gae_lambda=config.gae_lambda,
)
# Reward config
self.reward_config = RewardConfig(
gamma=config.gamma,
gae_lambda=config.gae_lambda,
)
# Opponent policy
self.opponent = self._create_opponent(config.opponent)
# Forge data source (started lazily in train())
self._forge_source: Optional[ForgeDataSource] = None
if config.data_source in ("forge", "mixed"):
self._forge_source = ForgeDataSource(
results_dir=config.forge_results_dir,
batch_id=config.forge_batch_id,
num_games=config.forge_num_games,
reward_config=self.reward_config,
)
# Tracking
self.iteration = 0
self.total_steps = 0
self.best_win_rate = 0.0
@@ -327,9 +196,13 @@ class PPOTrainer:
return "cpu"
def _load_supervised_weights(self, path: str):
"""Load weights from a supervised PolicyNetwork checkpoint into the
PolicyValueNetwork (ignoring the value head, which is new)."""
logger.info("Loading supervised weights from %s", path)
checkpoint = torch.load(path, map_location=self.device, weights_only=False)
state_dict = checkpoint.get("model_state_dict", checkpoint)
# Filter out keys that don't match (e.g., value_head)
model_dict = self.model.state_dict()
compatible = {k: v for k, v in state_dict.items() if k in model_dict and v.shape == model_dict[k].shape}
model_dict.update(compatible)
@@ -343,10 +216,14 @@ class PPOTrainer:
elif opponent_type == "heuristic":
return HeuristicPolicy()
elif opponent_type == "self":
# Self-play: opponent uses a snapshot of the current policy
return self._create_self_play_opponent()
return HeuristicPolicy()
else:
return HeuristicPolicy()
def _create_self_play_opponent(self):
"""Create an opponent that uses a frozen copy of the current policy."""
class SelfPlayPolicy:
def __init__(self, model, device):
self.model = model
@@ -364,99 +241,11 @@ class PPOTrainer:
return SelfPlayPolicy(self.model, self.device)
def _collect_forge_rollouts(self) -> Dict:
"""Drain buffered Forge episodes into the RolloutBuffer.
Returns stats dict compatible with collect_rollouts() output.
"""
episodes = self._forge_source.drain()
if not episodes:
logger.warning("[Forge] No episodes available yet — waiting for JSONL output in %s",
self.config.forge_results_dir)
return {"steps": 0, "win_rate": 0.0, "avg_reward_per_ep": 0.0,
"wins": 0, "losses": 0, "draws": 0, "source": "forge"}
added = episodes_to_buffer(episodes, self.buffer)
wins = sum(1 for ep in episodes if ep.winner == 0)
win_rate = wins / max(len(episodes), 1)
avg_reward = sum(ep.total_reward for ep in episodes) / max(len(episodes), 1)
logger.info("[Forge] Drained %d episodes (%d transitions) into buffer — WR=%.0f%% AvgR=%.3f",
len(episodes), added, win_rate * 100, avg_reward)
return {
"steps": added,
"win_rate": win_rate,
"avg_reward_per_ep": avg_reward,
"wins": wins,
"losses": len(episodes) - wins,
"draws": 0,
"source": "forge",
}
def _collect_rollouts_for_iter(self) -> Dict:
"""Collect rollouts according to configured data_source.
- synthetic: pure self_play.collect_rollouts (original behaviour)
- forge: pure Forge episode drain
- mixed: Forge fills forge_weight fraction of buffer, synthetic fills remainder
"""
cfg = self.config
self.buffer.reset()
self.model.eval()
if cfg.data_source == "forge":
stats = self._collect_forge_rollouts()
elif cfg.data_source == "mixed":
forge_cap = int(cfg.buffer_size * cfg.forge_weight)
synth_cap = cfg.buffer_size - forge_cap
# Temporarily shrink buffer for Forge slice
original_size = self.buffer.buffer_size
self.buffer.buffer_size = forge_cap
forge_stats = self._collect_forge_rollouts()
self.buffer.buffer_size = original_size
synth_eps = max(1, int(cfg.episodes_per_iter * (1.0 - cfg.forge_weight)))
synth_stats = collect_rollouts(
agent_model=self.model,
opponent_policy=self.opponent,
buffer=self.buffer,
num_episodes=synth_eps,
playstyle=cfg.playstyle,
reward_config=self.reward_config,
)
stats = {
"steps": forge_stats["steps"] + synth_stats["steps"],
"win_rate": (
forge_stats["win_rate"] * cfg.forge_weight
+ synth_stats["win_rate"] * (1.0 - cfg.forge_weight)
),
"avg_reward_per_ep": (
forge_stats["avg_reward_per_ep"] * cfg.forge_weight
+ synth_stats["avg_reward_per_ep"] * (1.0 - cfg.forge_weight)
),
"wins": forge_stats["wins"] + synth_stats["wins"],
"losses": forge_stats["losses"] + synth_stats["losses"],
"draws": synth_stats.get("draws", 0),
"source": "mixed",
}
else: # synthetic (default — unchanged behaviour)
stats = collect_rollouts(
agent_model=self.model,
opponent_policy=self.opponent,
buffer=self.buffer,
num_episodes=cfg.episodes_per_iter,
playstyle=cfg.playstyle,
reward_config=self.reward_config,
)
stats["source"] = "synthetic"
self.model.train()
return stats
def ppo_update(self) -> Dict:
"""Run PPO update epochs on the collected rollout buffer."""
"""Run PPO update epochs on the collected rollout buffer.
Returns dict of loss metrics.
"""
cfg = self.config
total_policy_loss = 0.0
total_value_loss = 0.0
@@ -469,42 +258,56 @@ class PPOTrainer:
for batch in self.buffer.get_batches(cfg.batch_size):
states, actions, old_log_probs, advantages, returns = batch
# To tensors
states_t = torch.from_numpy(states).to(self.device)
actions_t = torch.from_numpy(actions).to(self.device)
old_log_probs_t = torch.from_numpy(old_log_probs).to(self.device)
advantages_t = torch.from_numpy(advantages).to(self.device)
returns_t = torch.from_numpy(returns).to(self.device)
# Forward pass
logits, values = self.model.forward_with_value(states_t)
values = values.squeeze(-1)
# Action distribution
probs = F.softmax(logits, dim=-1)
dist = torch.distributions.Categorical(probs)
new_log_probs = dist.log_prob(actions_t)
entropy = dist.entropy().mean()
# --- Policy Loss (clipped surrogate) ---
ratio = torch.exp(new_log_probs - old_log_probs_t)
surr1 = ratio * advantages_t
surr2 = torch.clamp(ratio, 1.0 - cfg.clip_epsilon, 1.0 + cfg.clip_epsilon) * advantages_t
policy_loss = -torch.min(surr1, surr2).mean()
# --- Value Loss (clipped) ---
if cfg.value_clip > 0:
# Get old values from buffer for clipping
old_values_t = torch.from_numpy(
self.buffer.values[:self.buffer.size]
).to(self.device)
# Reindex to match batch
# Since we use shuffled indices in get_batches, we clip against returns
value_loss_unclipped = (values - returns_t) ** 2
value_loss = 0.5 * value_loss_unclipped.mean()
else:
value_loss = 0.5 * ((values - returns_t) ** 2).mean()
# --- Total Loss ---
loss = (
policy_loss
+ cfg.value_loss_coeff * value_loss
- cfg.entropy_coeff * entropy
)
# Optimize
self.optimizer.zero_grad()
loss.backward()
nn.utils.clip_grad_norm_(self.model.parameters(), cfg.max_grad_norm)
self.optimizer.step()
# Track metrics
with torch.no_grad():
approx_kl = ((ratio - 1) - torch.log(ratio)).mean().item()
clip_frac = ((ratio - 1.0).abs() > cfg.clip_epsilon).float().mean().item()
@@ -527,8 +330,12 @@ class PPOTrainer:
}
def evaluate(self, num_episodes: int = 50) -> Dict:
"""Evaluate the current policy against heuristic and random opponents."""
"""Evaluate the current policy against opponents.
Returns win rates and metrics.
"""
self.model.eval()
results = {}
for opp_name, opp_policy in [
("heuristic", HeuristicPolicy()),
@@ -556,15 +363,18 @@ class PPOTrainer:
"avg_reward": stats["avg_reward_per_ep"],
"avg_steps": stats["avg_steps_per_ep"],
}
self.model.train()
return results
def save_checkpoint(self, path: str = None, metrics: dict = None):
"""Save PPO checkpoint."""
if path is None:
path = os.path.join(
self.config.checkpoint_dir,
f"ppo_iter_{self.iteration:04d}.pt",
)
os.makedirs(os.path.dirname(path), exist_ok=True)
torch.save({
"iteration": self.iteration,
@@ -578,7 +388,6 @@ class PPOTrainer:
"learning_rate": self.config.learning_rate,
"opponent": self.config.opponent,
"playstyle": self.config.playstyle,
"data_source": self.config.data_source,
},
"best_win_rate": self.best_win_rate,
"model_config": {
@@ -592,7 +401,14 @@ class PPOTrainer:
logger.info("Checkpoint saved: %s", path)
def train(self, progress_callback=None) -> Dict:
"""Run the full PPO training loop."""
"""Run the full PPO training loop.
Args:
progress_callback: Optional callable(iteration, metrics) for progress reporting
Returns:
Training summary dict
"""
cfg = self.config
logger.info("=" * 60)
logger.info("PPO Training — Commander AI Lab")
@@ -607,94 +423,98 @@ class PPOTrainer:
logger.info(" Opponent: %s", cfg.opponent)
logger.info(" Device: %s", self.device)
logger.info(" Supervised: %s", cfg.load_supervised or "None")
logger.info(" Data source: %s", cfg.data_source)
if cfg.data_source in ("forge", "mixed"):
logger.info(" Forge results: %s / %s", cfg.forge_results_dir, cfg.forge_batch_id)
logger.info(" Forge weight: %.0f%%", cfg.forge_weight * 100)
logger.info("")
# Start Forge producer background thread if needed
if self._forge_source:
self._forge_source.start()
t_start = time.time()
try:
for iteration in range(1, cfg.iterations + 1):
self.iteration = iteration
t_iter = time.time()
for iteration in range(1, cfg.iterations + 1):
self.iteration = iteration
t_iter = time.time()
rollout_stats = self._collect_rollouts_for_iter()
self.total_steps += rollout_stats["steps"]
# --- Collect rollouts ---
self.model.eval()
rollout_stats = collect_rollouts(
agent_model=self.model,
opponent_policy=self.opponent,
buffer=self.buffer,
num_episodes=cfg.episodes_per_iter,
playstyle=cfg.playstyle,
reward_config=self.reward_config,
)
self.total_steps += rollout_stats["steps"]
self.model.train()
update_metrics = self.ppo_update()
# --- PPO Update ---
update_metrics = self.ppo_update()
current_lr = self.optimizer.param_groups[0]["lr"]
if self.scheduler:
self.scheduler.step()
# --- LR Schedule ---
current_lr = self.optimizer.param_groups[0]["lr"]
if self.scheduler:
self.scheduler.step()
eval_results = None
if iteration % cfg.eval_every == 0 or iteration == 1:
eval_results = self.evaluate(cfg.eval_episodes)
heuristic_wr = eval_results.get("heuristic", {}).get("win_rate", 0)
if heuristic_wr > self.best_win_rate:
self.best_win_rate = heuristic_wr
best_path = os.path.join(cfg.checkpoint_dir, "best_ppo.pt")
self.save_checkpoint(best_path, {"eval": eval_results})
logger.info(" ★ New best win rate: %.1f%%", heuristic_wr * 100)
# --- Evaluate ---
eval_results = None
if iteration % cfg.eval_every == 0 or iteration == 1:
eval_results = self.evaluate(cfg.eval_episodes)
heuristic_wr = eval_results.get("heuristic", {}).get("win_rate", 0)
if iteration % cfg.save_every == 0:
self.save_checkpoint()
if heuristic_wr > self.best_win_rate:
self.best_win_rate = heuristic_wr
best_path = os.path.join(cfg.checkpoint_dir, "best_ppo.pt")
self.save_checkpoint(best_path, {"eval": eval_results})
logger.info(" ★ New best win rate: %.1f%%", heuristic_wr * 100)
iter_time = time.time() - t_iter
metrics = {
"iteration": iteration,
"steps": rollout_stats["steps"],
"total_steps": self.total_steps,
"win_rate": rollout_stats["win_rate"],
"avg_reward": rollout_stats["avg_reward_per_ep"],
"policy_loss": update_metrics["policy_loss"],
"value_loss": update_metrics["value_loss"],
"entropy": update_metrics["entropy"],
"approx_kl": update_metrics["approx_kl"],
"clip_fraction": update_metrics["clip_fraction"],
"lr": current_lr,
"iter_time_s": round(iter_time, 1),
"data_source": rollout_stats.get("source", cfg.data_source),
"eval": eval_results,
}
self.history.append(metrics)
# --- Save periodic checkpoint ---
if iteration % cfg.save_every == 0:
self.save_checkpoint()
eval_str = ""
if eval_results:
h_wr = eval_results.get("heuristic", {}).get("win_rate", 0)
r_wr = eval_results.get("random", {}).get("win_rate", 0)
eval_str = f" | eval: h={h_wr:.0%} r={r_wr:.0%}"
# --- Log ---
iter_time = time.time() - t_iter
metrics = {
"iteration": iteration,
"steps": rollout_stats["steps"],
"total_steps": self.total_steps,
"win_rate": rollout_stats["win_rate"],
"avg_reward": rollout_stats["avg_reward_per_ep"],
"policy_loss": update_metrics["policy_loss"],
"value_loss": update_metrics["value_loss"],
"entropy": update_metrics["entropy"],
"approx_kl": update_metrics["approx_kl"],
"clip_fraction": update_metrics["clip_fraction"],
"lr": current_lr,
"iter_time_s": round(iter_time, 1),
"eval": eval_results,
}
self.history.append(metrics)
src_tag = f"[{rollout_stats.get('source', '?')[:3]}]"
logger.info(
" [%3d/%d]%s wr=%.0f%% rew=%.3f ploss=%.4f vloss=%.4f ent=%.3f kl=%.4f%s (%.1fs)",
iteration, cfg.iterations, src_tag,
rollout_stats["win_rate"] * 100,
rollout_stats["avg_reward_per_ep"],
update_metrics["policy_loss"],
update_metrics["value_loss"],
update_metrics["entropy"],
update_metrics["approx_kl"],
eval_str,
iter_time,
)
# Pretty log
eval_str = ""
if eval_results:
h_wr = eval_results.get("heuristic", {}).get("win_rate", 0)
r_wr = eval_results.get("random", {}).get("win_rate", 0)
eval_str = f" | eval: h={h_wr:.0%} r={r_wr:.0%}"
if progress_callback:
progress_callback(iteration, metrics)
logger.info(
" [%3d/%d] wr=%.0f%% rew=%.3f ploss=%.4f vloss=%.4f ent=%.3f kl=%.4f%s (%.1fs)",
iteration, cfg.iterations,
rollout_stats["win_rate"] * 100,
rollout_stats["avg_reward_per_ep"],
update_metrics["policy_loss"],
update_metrics["value_loss"],
update_metrics["entropy"],
update_metrics["approx_kl"],
eval_str,
iter_time,
)
finally:
if self._forge_source:
self._forge_source.stop()
if progress_callback:
progress_callback(iteration, metrics)
# --- Final Save ---
total_time = time.time() - t_start
self.save_checkpoint()
# Save training history
history_path = os.path.join(cfg.checkpoint_dir, "ppo_history.json")
with open(history_path, "w") as f:
json.dump(self.history, f, indent=2, default=str)
@@ -706,7 +526,6 @@ class PPOTrainer:
"final_win_rate": self.history[-1]["win_rate"] if self.history else 0,
"total_time_s": round(total_time, 1),
"device": self.device,
"data_source": cfg.data_source,
"checkpoint_dir": cfg.checkpoint_dir,
"history_path": history_path,
}
@@ -717,7 +536,6 @@ class PPOTrainer:
logger.info(" Total time: %.1f s", total_time)
logger.info(" Total steps: %d", self.total_steps)
logger.info(" Best win rate: %.1f%%", self.best_win_rate * 100)
logger.info(" Data source: %s", cfg.data_source)
logger.info(" History: %s", history_path)
logger.info("=" * 60)
@@ -760,32 +578,12 @@ def main():
parser.add_argument("--load-supervised", default=None,
help="Path to supervised checkpoint to initialize from")
# Data source
parser.add_argument(
"--data-source", default="synthetic",
choices=["synthetic", "forge", "mixed"],
help="Episode source: synthetic (self-play), forge (Forge JSONL), mixed (blend)",
)
parser.add_argument(
"--forge-results-dir", default="results",
help="Directory where Forge writes ml-decisions-forge-*.jsonl files",
)
parser.add_argument(
"--forge-batch-id", default="forge-batch",
help="Batch ID prefix for Forge JSONL files (matches BatchRunner --batchId)",
)
parser.add_argument(
"--forge-num-games", type=int, default=256,
help="Total Forge games to consume before stopping the producer",
)
parser.add_argument(
"--forge-weight", type=float, default=0.7,
help="Fraction of RolloutBuffer filled from Forge when --data-source mixed (0.0–1.0)",
)
args = parser.parse_args()
logging.basicConfig(level=logging.INFO, format="%(message)s")
logging.basicConfig(
level=logging.INFO,
format="%(message)s",
)
config = PPOConfig(
iterations=args.iterations,
@@ -807,11 +605,6 @@ def main():
eval_every=args.eval_every,
eval_episodes=args.eval_episodes,
load_supervised=args.load_supervised,
data_source=args.data_source,
forge_results_dir=args.forge_results_dir,
forge_batch_id=args.forge_batch_id,
forge_num_games=args.forge_num_games,
forge_weight=args.forge_weight,
)
trainer = PPOTrainer(config)
-13
View File
@@ -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
+1 -2
View File
@@ -9,7 +9,7 @@ class StartRequest(BaseModel):
numGames: int = 100
threads: int = 4
seed: Optional[int] = None
clock: int = 5000
clock: int = 300
deckSources: Optional[list[Optional[dict]]] = None
useLearnedPolicy: bool = False
policyStyle: str = "midrange"
@@ -170,7 +170,6 @@ class CoachGoalsRequest(BaseModel):
meta_focus: Optional[str] = None # aggro, control, combo, midrange, stax
budget: Optional[str] = None # budget, medium, no-limit
focus_areas: list[str] = [] # e.g., ["ramp", "card draw"]
class DeckGenV3SubstituteRequest(BaseModel):
card_name: str
substitute_name: str
+102 -154
View File
@@ -1,154 +1,102 @@
"""Runtime configuration, state classes, and static data for Commander AI Lab."""
from __future__ import annotations
import json
import logging
import os
import subprocess
from datetime import datetime
from pathlib import Path
from typing import Optional
# ── .env bootstrap ────────────────────────────────────────────
# Load .env automatically so plain `python script.py` and bare uvicorn
# both pick up FORGE_DIR, PRECON_DIR, etc. without a manual load_dotenv
# call at every entry point. override=False means real env vars always win.
try:
from dotenv import load_dotenv as _load_dotenv
_here = Path(__file__).resolve().parent
for _candidate in [_here, _here.parent, _here.parent.parent]:
_env_file = _candidate / ".env"
if _env_file.is_file():
_load_dotenv(dotenv_path=_env_file, override=False)
break
except ImportError:
pass # python-dotenv not installed; rely on real environment variables
# ─────────────────────────────────────────────────────────────
log = logging.getLogger("commander_ai_lab.api")
# ══════════════════════════════════════════════════════════════
# Configuration
# ══════════════════════════════════════════════════════════════
class Config:
"""Runtime configuration -- set via CLI args or env vars."""
forge_jar: str = ""
forge_dir: str = ""
forge_decks_dir: str = ""
lab_jar: str = ""
precon_dir: str = ""
results_dir: str = "results"
port: int = 8080
ximilar_api_key: str = ""
pplx_api_key: str = ""
anthropic_api_key: str = ""
CFG = Config()
# Pre-populate from environment so uvicorn/ASGI mode works without CLI args.
# CLI args (lab_api.py main()) will override these if provided.
CFG.anthropic_api_key = os.environ.get("ANTHROPIC_API_KEY", "")
CFG.ximilar_api_key = os.environ.get("XIMILAR_API_KEY", "")
CFG.pplx_api_key = os.environ.get("PPLX_API_KEY", "")
CFG.forge_jar = os.environ.get("FORGE_JAR", "")
CFG.forge_dir = os.environ.get("FORGE_DIR", "")
CFG.lab_jar = os.environ.get("LAB_JAR", "")
# PRECON_DIR / PRECON_DECKS_DIR are aliases -- prefer PRECON_DIR
CFG.precon_dir = os.environ.get("PRECON_DIR") or os.environ.get("PRECON_DECKS_DIR", "")
CFG.forge_decks_dir = os.environ.get("FORGE_DECKS_DIR", "")
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)
# ══════════════════════════════════════════════════════════════
# In-Memory State
# ══════════════════════════════════════════════════════════════
class BatchState:
def __init__(self, batch_id: str, total_games: int, threads: int):
self.batch_id = batch_id
self.total_games = total_games
self.threads = threads
self.completed_games = 0
self.running = True
self.start_time = datetime.now()
self.elapsed_ms = 0
self.result_path: Optional[str] = None
self.error: Optional[str] = None
self.process: Optional[subprocess.Popen] = None
self.log_lines: list = []
self.sims_per_sec: float = 0.0
import asyncio as _asyncio
active_batches: dict[str, BatchState] = {}
active_batches_lock = _asyncio.Lock()
COMMANDER_META: dict = {}
BUILTIN_COMMANDERS: dict = {
"Edgar Markov": [{"source": "edhrec", "archetype": "aggro", "colorIdentity": ["W","B","R"]}],
"Atraxa, Praetors' Voice": [{"source": "edhrec", "archetype": "midrange", "colorIdentity": ["W","U","B","G"]}],
"Korvold, Fae-Cursed King": [{"source": "edhrec", "archetype": "combo", "colorIdentity": ["B","R","G"]}],
"Muldrotha, the Gravetide": [{"source": "edhrec", "archetype": "midrange", "colorIdentity": ["U","B","G"]}],
"The Ur-Dragon": [{"source": "edhrec", "archetype": "midrange", "colorIdentity": ["W","U","B","R","G"]}],
"Yuriko, the Tiger's Shadow": [{"source": "edhrec", "archetype": "aggro", "colorIdentity": ["U","B"]}],
"Krenko, Mob Boss": [{"source": "edhrec", "archetype": "aggro", "colorIdentity": ["R"]}],
"Meren of Clan Nel Toth": [{"source": "edhrec", "archetype": "midrange", "colorIdentity": ["B","G"]}],
"Prossh, Skyraider of Kher": [{"source": "edhrec", "archetype": "combo", "colorIdentity": ["B","R","G"]}],
"Kaalia of the Vast": [{"source": "edhrec", "archetype": "aggro", "colorIdentity": ["W","B","R"]}],
"Talrand, Sky Summoner": [{"source": "edhrec", "archetype": "control", "colorIdentity": ["U"]}],
"Omnath, Locus of Creation": [{"source": "edhrec", "archetype": "combo", "colorIdentity": ["W","U","R","G"]}],
"Teysa Karlov": [{"source": "edhrec", "archetype": "combo", "colorIdentity": ["W","B"]}],
"Lathril, Blade of the Elves": [{"source": "edhrec", "archetype": "aggro", "colorIdentity": ["B","G"]}],
"Breya, Etherium Shaper": [{"source": "edhrec", "archetype": "combo", "colorIdentity": ["W","U","B","R"]}],
}
def load_commander_meta() -> None:
"""Load commander meta mapping from file or fall back to builtins."""
meta_path = Path(__file__).parent.parent / "commander-meta.json"
if meta_path.exists():
try:
with open(meta_path, "r", encoding="utf-8") as f:
COMMANDER_META.clear()
COMMANDER_META.update(json.load(f))
log.info(f" Meta: Loaded {len(COMMANDER_META)} commanders from {meta_path}")
return
except Exception as e:
log.warning(f" WARNING: Failed to load commander-meta.json: {e}")
COMMANDER_META.clear()
COMMANDER_META.update(BUILTIN_COMMANDERS)
log.info(f" Meta: {len(COMMANDER_META)} built-in commanders")
# ══════════════════════════════════════════════════════════════
# AI Profiles
# ══════════════════════════════════════════════════════════════
AI_PROFILES = {
"default": {"name": "default", "description": "Balanced — Forge's default AI behavior", "aggression": 0.5, "cardAdvantage": 0.5, "removalPriority": 0.5, "boardPresence": 0.5, "comboPriority": 0.3, "patience": 0.5},
"aggro": {"name": "aggro", "description": "Aggressive — attacks early, prioritizes damage", "aggression": 0.9, "cardAdvantage": 0.3, "removalPriority": 0.3, "boardPresence": 0.8, "comboPriority": 0.1, "patience": 0.1},
"control": {"name": "control", "description": "Control — defensive, removal-heavy, card advantage", "aggression": 0.2, "cardAdvantage": 0.9, "removalPriority": 0.9, "boardPresence": 0.3, "comboPriority": 0.4, "patience": 0.9},
"combo": {"name": "combo", "description": "Combo — ramps, digs for pieces, assembles combos", "aggression": 0.2, "cardAdvantage": 0.8, "removalPriority": 0.4, "boardPresence": 0.3, "comboPriority": 0.95, "patience": 0.7},
"midrange": {"name": "midrange", "description": "Midrange — flexible, strong board presence, value-oriented", "aggression": 0.5, "cardAdvantage": 0.6, "removalPriority": 0.6, "boardPresence": 0.7, "comboPriority": 0.3, "patience": 0.5},
}
"""Runtime configuration, state classes, and static data for Commander AI Lab."""
from __future__ import annotations
import json
import logging
import subprocess
from datetime import datetime
from pathlib import Path
from typing import Optional
log = logging.getLogger("commander_ai_lab.api")
# ══════════════════════════════════════════════════════════════
# Configuration
# ══════════════════════════════════════════════════════════════
class Config:
"""Runtime configuration -- set via CLI args or env vars."""
forge_jar: str = ""
forge_dir: str = ""
forge_decks_dir: str = ""
lab_jar: str = ""
precon_dir: str = ""
results_dir: str = "results"
port: int = 8080
ximilar_api_key: str = ""
pplx_api_key: str = ""
CFG = Config()
# ══════════════════════════════════════════════════════════════
# In-Memory State
# ══════════════════════════════════════════════════════════════
class BatchState:
def __init__(self, batch_id: str, total_games: int, threads: int):
self.batch_id = batch_id
self.total_games = total_games
self.threads = threads
self.completed_games = 0
self.running = True
self.start_time = datetime.now()
self.elapsed_ms = 0
self.result_path: Optional[str] = None
self.error: Optional[str] = None
self.process: Optional[subprocess.Popen] = None
self.log_lines: list = []
self.sims_per_sec: float = 0.0
active_batches: dict[str, BatchState] = {}
COMMANDER_META: dict = {}
BUILTIN_COMMANDERS: dict = {
"Edgar Markov": [{"source": "edhrec", "archetype": "aggro", "colorIdentity": ["W","B","R"]}],
"Atraxa, Praetors' Voice": [{"source": "edhrec", "archetype": "midrange", "colorIdentity": ["W","U","B","G"]}],
"Korvold, Fae-Cursed King": [{"source": "edhrec", "archetype": "combo", "colorIdentity": ["B","R","G"]}],
"Muldrotha, the Gravetide": [{"source": "edhrec", "archetype": "midrange", "colorIdentity": ["U","B","G"]}],
"The Ur-Dragon": [{"source": "edhrec", "archetype": "midrange", "colorIdentity": ["W","U","B","R","G"]}],
"Yuriko, the Tiger's Shadow": [{"source": "edhrec", "archetype": "aggro", "colorIdentity": ["U","B"]}],
"Krenko, Mob Boss": [{"source": "edhrec", "archetype": "aggro", "colorIdentity": ["R"]}],
"Meren of Clan Nel Toth": [{"source": "edhrec", "archetype": "midrange", "colorIdentity": ["B","G"]}],
"Prossh, Skyraider of Kher": [{"source": "edhrec", "archetype": "combo", "colorIdentity": ["B","R","G"]}],
"Kaalia of the Vast": [{"source": "edhrec", "archetype": "aggro", "colorIdentity": ["W","B","R"]}],
"Talrand, Sky Summoner": [{"source": "edhrec", "archetype": "control", "colorIdentity": ["U"]}],
"Omnath, Locus of Creation": [{"source": "edhrec", "archetype": "combo", "colorIdentity": ["W","U","R","G"]}],
"Teysa Karlov": [{"source": "edhrec", "archetype": "combo", "colorIdentity": ["W","B"]}],
"Lathril, Blade of the Elves": [{"source": "edhrec", "archetype": "aggro", "colorIdentity": ["B","G"]}],
"Breya, Etherium Shaper": [{"source": "edhrec", "archetype": "combo", "colorIdentity": ["W","U","B","R"]}],
}
def load_commander_meta() -> None:
"""Load commander meta mapping from file or fall back to builtins."""
meta_path = Path(__file__).parent.parent / "commander-meta.json"
if meta_path.exists():
try:
with open(meta_path, "r", encoding="utf-8") as f:
COMMANDER_META.clear()
COMMANDER_META.update(json.load(f))
log.info(f" Meta: Loaded {len(COMMANDER_META)} commanders from {meta_path}")
return
except Exception as e:
log.warning(f" WARNING: Failed to load commander-meta.json: {e}")
COMMANDER_META.clear()
COMMANDER_META.update(BUILTIN_COMMANDERS)
log.info(f" Meta: {len(COMMANDER_META)} built-in commanders")
# ══════════════════════════════════════════════════════════════
# AI Profiles
# ══════════════════════════════════════════════════════════════
AI_PROFILES = {
"default": {"name": "default", "description": "Balanced \u2014 Forge's default AI behavior", "aggression": 0.5, "cardAdvantage": 0.5, "removalPriority": 0.5, "boardPresence": 0.5, "comboPriority": 0.3, "patience": 0.5},
"aggro": {"name": "aggro", "description": "Aggressive \u2014 attacks early, prioritizes damage", "aggression": 0.9, "cardAdvantage": 0.3, "removalPriority": 0.3, "boardPresence": 0.8, "comboPriority": 0.1, "patience": 0.1},
"control": {"name": "control", "description": "Control \u2014 defensive, removal-heavy, card advantage", "aggression": 0.2, "cardAdvantage": 0.9, "removalPriority": 0.9, "boardPresence": 0.3, "comboPriority": 0.4, "patience": 0.9},
"combo": {"name": "combo", "description": "Combo \u2014 ramps, digs for pieces, assembles combos", "aggression": 0.2, "cardAdvantage": 0.8, "removalPriority": 0.4, "boardPresence": 0.3, "comboPriority": 0.95, "patience": 0.7},
"midrange": {"name": "midrange", "description": "Midrange \u2014 flexible, strong board presence, value-oriented", "aggression": 0.5, "cardAdvantage": 0.6, "removalPriority": 0.6, "boardPresence": 0.7, "comboPriority": 0.3, "patience": 0.5},
}
-4
View File
@@ -1,4 +0,0 @@
unzip mtg-commander-lan.zip
cd mtg-commander-lan
npm install
node server.js
+4 -75
View File
@@ -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
-6
View File
@@ -1,6 +0,0 @@
{
"name": "MTG Commander (HTML)",
"lockfileVersion": 3,
"requires": true,
"packages": {}
}
-104
View File
@@ -1,104 +0,0 @@
[metadata]
Name=20 Ways to Win
[Commander]
1 Go-Shintai of Life's Origin
[Main]
1 Alseid of Life's Bounty
1 Approach of the Second Sun
1 Arcane Signet
1 Augur of Autumn
1 Auriok Champion
1 Austere Command
1 Azorius Guildgate
1 Baldur's Gate
1 Biovisionary
1 Black Dragon Gate
1 Boros Guildgate
1 Bountiful Promenade
1 Brushland
1 Chromatic Lantern
1 Circuitous Route
1 Citadel Gate
1 Clever Concealment
1 Cliffgate
1 Command Tower
1 Crib Swap
1 Darksteel Citadel
1 Darksteel Mutation
1 Dimir Guildgate
1 Drown in Dreams
1 Dryad of the Ilysian Grove
1 Eerie Ultimatum
1 Exotic Orchard
1 Faeburrow Elder
1 Felidar Sovereign
1 Fertile Ground
1 Forbidden Orchard
1 Forest
1 Forgotten Ancient
1 Gateway Plaza
1 Ghostly Prison
1 Ghoulish Impetus
1 Golgari Guildgate
1 Gond Gate
1 Gruul Guildgate
1 Halo Fountain
1 Hangarback Walker
1 Happily Ever After
1 Heap Gate
1 Heliod's Intervention
1 Heliod, Sun-Crowned
1 Helix Pinnacle
1 Hellkite Tyrant
1 Homeward Path
1 Izzet Guildgate
1 Kynaios and Tiro of Meletis
1 Lightning Greaves
1 Lignify
1 Liliana's Contract
1 Mangara, the Diplomat
1 Manor Gate
1 Maskwood Nexus
1 Mayael's Aria
1 Maze's End
1 Mechanized Production
1 Monologue Tax
1 Morbid Opportunist
1 Mystic Remora
1 Orzhov Guildgate
1 Overgrown Farmland
1 Pariah
1 Path of Ancestry
1 Plains
1 Plaza of Harmony
1 Rakdos Guildgate
1 Razorverge Thicket
1 Reflecting Pool
1 Revel in Riches
1 Rite of Replication
1 Sanctum Weaver
1 Sea Gate
1 Seedborn Muse
1 Selesnya Guildgate
1 Shalai, Voice of Plenty
1 Shiny Impetus
1 Simic Ascendancy
1 Simic Guildgate
1 Sol Ring
1 Soul's Attendant
1 Sphinx's Revelation
1 Sun Titan
1 Sunscorch Regent
1 Supreme Verdict
1 Taurean Mauler
1 Test of Endurance
1 The Eternal Wanderer
1 The World Tree
1 Thornglint Bridge
1 Tireless Tracker
1 Trace of Abundance
1 Tragic Arrogance
1 Triskaidekaphile
1 Twenty-Toed Toad
1 Wooded Bastion
1 Yahenni, Undying Partisan
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[metadata]
Name=Abzan Armor
[Commander]
1 Felothar the Steadfast
[Main]
1 Betor, Ancestor's Voice
1 Protector of the Wastes
1 Reunion of the House
1 Jaws of Defeat
1 Tip the Scales
1 Will of the Abzan
1 Arbor Adherent
1 Canopy Gargantuan
1 Rampart Architect
1 Tree of Redemption
1 Ikra Shidiqi, the Usurper
1 Baldin, Century Herdmaster
1 Expel the Interlopers
1 Indomitable Ancients
1 Rhox Faithmender
1 Shalai, Voice of Plenty
1 Wakestone Gargoyle
1 Wall of Reverence
1 Welcoming Vampire
1 Zetalpa, Primal Dawn
1 Arasta of the Endless Web
1 Assault Formation
1 Hornet Nest
1 Seedborn Muse
1 Sylvan Caryatid
1 Towering Titan
1 Anguished Unmaking
1 Dragonlord Dromoka
1 Faeburrow Elder
1 Shadrix Silverquill
1 Sidar Kondo of Jamuraa
1 Colfenor's Urn
1 Staff of Compleation
1 Weathered Sentinels
1 Canopy Vista
1 Exotic Orchard
1 Fortified Village
1 Isolated Chapel
1 Overgrown Farmland
1 Sungrass Prairie
1 Sunpetal Grove
1 Temple of Malady
1 Temple of Plenty
1 Temple of Silence
1 Twilight Mire
1 Woodland Cemetery
1 Arcane Signet
1 Sol Ring
1 Command Tower
1 Nyx-Fleece Ram
1 Slaughter the Strong
1 Swords to Plowshares
1 Wall of Omens
1 Wingmantle Chaplain
1 Behind the Scenes
1 Blight Pile
1 Feed the Swarm
1 Infernal Grasp
1 Wall of Limbs
1 Arboreal Grazer
1 Axebane Guardian
1 Carven Caryatid
1 Evolving Wilds
1 Jaddi Offshoot
1 Overgrown Battlement
1 Sandsteppe Citadel
1 Tower Defense
1 Wall of Blossoms
1 Wall of Roots
1 Despark
1 Indulging Patrician
1 Crashing Drawbridge
1 Orzhov Signet
1 Selesnya Signet
1 Swiftfoot Boots
1 Walking Bulwark
1 Access Tunnel
1 Bojuka Bog
1 Deceptive Landscape
1 Path of Ancestry
1 Radiant Grove
3 Plains
3 Plains
3 Swamp
2 Swamp
4 Forest
3 Forest
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[metadata]
Name=Adaptive Enchantment
[Commander]
1 Estrid, the Masked
[Main]
1 Bruna, Light of Alabaster
1 Eidolon of Blossoms
1 Hydra Omnivore
1 Ajani's Chosen
1 Celestial Archon
1 Silent Sentinel
1 Boon Satyr
1 Herald of the Pantheon
1 Cold-Eyed Selkie
1 Daxos of Meletis
1 Elderwood Scion
1 Archetype of Imagination
1 Whitewater Naiads
1 Aura Gnarlid
1 Reclamation Sage
1 Yavimaya Enchantress
1 Martial Coup
1 Phyrexian Rebirth
1 Winds of Rath
1 Creeping Renaissance
1 Kruphix's Insight
1 Dismantling Blow
1 Bant Charm
1 Sol Ring
1 Sigil of the Empty Throne
1 Dictate of Kruphix
1 Bear Umbra
1 Enchantress's Presence
1 Epic Proportions
1 Ground Seal
1 Spawning Grounds
1 Finest Hour
1 Righteous Authority
1 Sage's Reverie
1 Soul Snare
1 Unquestioned Authority
1 Eel Umbra
1 Vow of Flight
1 Dawn's Reflection
1 Fertile Ground
1 Overgrowth
1 Snake Umbra
1 Vow of Wildness
1 Wild Growth
1 Unflinching Courage
3 Plains
3 Plains
3 Plains
2 Island
2 Island
2 Island
3 Forest
3 Forest
2 Forest
1 Azorius Chancery
1 Blossoming Sands
1 Command Tower
1 Evolving Wilds
1 Krosan Verge
1 Meandering River
1 Mosswort Bridge
1 Seaside Citadel
1 Selesnya Sanctuary
1 Simic Growth Chamber
1 Terramorphic Expanse
1 Thornwood Falls
1 Tranquil Cove
1 Tranquil Expanse
1 Woodland Stream
1 Kestia, the Cultivator
1 Tuvasa the Sunlit
1 Empyrial Storm
1 Heavenly Blademaster
1 Estrid's Invocation
1 Ever-Watching Threshold
1 Octopus Umbra
1 Genesis Storm
1 Myth Unbound
1 Nylea's Colossus
1 Ravenous Slime
1 Arixmethes, Slumbering Isle
1 Loyal Unicorn
1 Loyal Drake
1 Loyal Guardian
1 Forge of Heroes
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[metadata]
Name=Ahoy Mateys
[Commander]
1 Admiral Brass, Unsinkable
[Main]
1 Don Andres, the Renegade
1 The Indomitable
1 Storm Fleet Negotiator
1 Francisco, Fowl Marauder
1 The Grim Captain's Locker
1 Skeleton Crew
1 Broadside Bombardiers
1 Gemcutter Buccaneer
1 Arm-Mounted Anchor
1 Amphin Mutineer
1 Bident of Thassa
1 Corsair Captain
1 Evacuation
1 Timestream Navigator
1 Warkite Marauder
1 Black Market Connections
1 Blood Money
1 Dire Fleet Ravager
1 Fathom Fleet Captain
1 Lethal Scheme
1 Angrath's Marauders
1 Blasphemous Act
1 Captain Lannery Storm
1 Captivating Crew
1 Chaos Warp
1 Coercive Recruiter
1 Dire Fleet Daredevil
1 Kari Zev, Skyship Raider
1 Port Razer
1 Shared Animosity
1 Admiral Beckett Brass
1 Hostage Taker
1 King Narfi's Betrayal
1 Prismari Command
1 Zara, Renegade Recruiter
1 Icon of Ancestry
1 Vanquisher's Banner
1 Choked Estuary
1 Desolate Lighthouse
1 Exotic Orchard
1 Foreboding Ruins
1 Frostboil Snarl
1 Geier Reach Sanitarium
1 Nephalia Drownyard
1 Smoldering Marsh
1 Sulfur Falls
1 Sunken Hollow
1 Azure Fleet Admiral
1 Enterprising Scallywag
1 Daring Saboteur
1 Departed Deckhand
1 Distant Melody
1 Ghost of Ramirez DePietro
1 Malcolm, Keen-Eyed Navigator
1 Merchant Raiders
1 Siren Stormtamer
1 Spectral Sailor
1 Windfall
1 Feed the Swarm
1 Pitiless Plunderer
1 Breeches, Brazen Plunderer
1 Faithless Looting
1 Rakdos Charm
1 Ramirez DePietro, Pillager
1 Arcane Signet
1 Commander's Sphere
1 Dimir Signet
1 Herald's Horn
1 Izzet Signet
1 Rakdos Signet
1 Sol Ring
1 Wayfarer's Bauble
1 Command Tower
1 Crumbling Necropolis
1 Evolving Wilds
1 Path of Ancestry
1 Port of Karfell
1 Rogue's Passage
1 Secluded Courtyard
1 Terramorphic Expanse
1 Thriving Bluff
1 Thriving Isle
1 Thriving Moor
1 Unclaimed Territory
3 Island
3 Island
2 Swamp
2 Swamp
3 Mountain
2 Mountain
@@ -1,78 +0,0 @@
[metadata]
Name=Angels: They're Just Like Us but Cooler and with Wings
[Commander]
1 Gisela, the Broken Blade
[Main]
1 Bruna, the Fading Light
1 Ajani, Strength of the Pride
1 Angel of Destiny
1 Angel of Finality
1 Angel of Serenity
1 Angel of the Ruins
1 Angel of Vitality
1 Angelic Accord
1 Angelic Field Marshal
1 Arcane Signet
1 Arch of Orazca
1 Archangel of Thune
1 Archangel of Tithes
1 Arden Angel
1 Austere Command
1 Bishop of Wings
1 Bonders' Enclave
1 Breathkeeper Seraph
1 Cleansing Nova
1 Commander's Plate
1 Cosmos Elixir
1 Court of Grace
1 Dawn of Hope
1 Dawnbreak Reclaimer
1 Dismantling Wave
1 Emeria Shepherd
1 Emeria, the Sky Ruin
1 Endless Atlas
1 Entreat the Angels
1 Everflowing Chalice
1 Giada, Font of Hope
1 Griffin Aerie
1 Heirloom Blade
1 Invoke the Divine
1 Karoo
1 Keeper of the Accord
1 Kindred Boon
1 Lightning Greaves
1 Marble Diamond
1 Mazemind Tome
1 Mind Stone
1 Myriad Landscape
1 Nykthos Paragon
1 Nykthos, Shrine to Nyx
1 Oketra's Monument
1 Path of Ancestry
1 Path to Exile
1 Pearl Medallion
8 Plains
8 Plains
7 Plains
7 Plains
1 Righteous Valkyrie
1 Search for Glory
1 Sephara, Sky's Blade
1 Seraph Sanctuary
1 Serra Ascendant
1 Shattered Angel
1 Sol Ring
1 Speaker of the Heavens
1 Starnheim Aspirant
1 Sunblast Angel
1 Swiftfoot Boots
1 Sword of the Animist
1 Swords to Plowshares
1 Thalia's Lancers
1 The Book of Exalted Deeds
1 Tome of Legends
1 Urza's Incubator
1 Valkyrie Harbinger
1 Vanquisher's Banner
1 War Room
1 Well of Lost Dreams
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[metadata]
Name=Animated Army
[Commander]
1 Bello, Bard of the Brambles
[Main]
1 Wildsear, Scouring Maw
1 Domri, Anarch of Bolas
1 Etali, Primal Storm
1 Prosperous Bandit
1 Pyreswipe Hawk
1 Alchemist's Talent
1 Berserkers' Onslaught
1 Outpost Siege
1 Rain of Riches
1 Chaos Warp
1 Sunbird's Invocation
1 Gratuitous Violence
1 Warstorm Surge
1 Starstorm
1 Lotus Cobra
1 Evercoat Ursine
1 Brightcap Badger // Fungus Frolic
1 Trailtracker Scout
1 Thickest in the Thicket
1 Ghalta, Primal Hunger
1 Esika's Chariot
1 Unnatural Growth
1 Greater Good
1 Kodama of the East Tree
1 Grothama, All-Devouring
1 Rampaging Baloths
1 Bootleggers' Stash
1 Primeval Bounty
1 Gilded Lotus
1 Spine of Ish Sah
1 Temple of Abandon
1 Karplusan Forest
1 Exotic Orchard
1 Sheltered Thicket
1 Game Trail
1 Raging Ravine
1 Copperline Gorge
1 Mossfire Valley
1 Cinder Glade
1 Rootbound Crag
1 Mosswort Bridge
1 Blasphemous Act
1 Llanowar Loamspeaker
1 Tendershoot Dryad
1 Goreclaw, Terror of Qal Sisma
1 Path of Discovery
1 Decimate
1 Rolling Hamsphere
1 Teapot Slinger
1 Explore
1 Farseek
1 Cultivate
1 Grumgully, the Generous
1 Wandertale Mentor
1 Thought Vessel
1 Arcane Signet
1 Wooded Ridgeline
1 Big Score
1 Abrade
1 Rampant Growth
1 Sakura-Tribe Elder
1 Beast Within
1 Garruk's Packleader
1 Harmonize
1 Garruk's Uprising
1 Gruul Signet
1 Burnished Hart
1 Hedron Archive
1 Fellwar Stone
1 Thran Dynamo
1 Sol Ring
1 Mind Stone
1 Talisman of Impulse
1 Terramorphic Expanse
1 Path of Ancestry
1 Gruul Turf
1 Evolving Wilds
1 Forgotten Cave
1 Tranquil Thicket
1 Command Tower
1 Reliquary Tower
4 Mountain
4 Mountain
5 Forest
5 Forest
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[metadata]
Name=Arcane Maelstrom
[Commander]
1 Kalamax, the Stormsire
[Main]
1 Jace, Architect of Thought
1 Xyris, the Writhing Storm
1 Haldan, Avid Arcanist
1 Pako, Arcane Retriever
1 Eon Frolicker
1 Nascent Metamorph
1 Glademuse
1 Ravenous Gigantotherium
1 Lunar Mystic
1 Niblis of Frost
1 Talrand, Sky Summoner
1 Charmbreaker Devils
1 Dualcaster Mage
1 Etali, Primal Storm
1 Goblin Dark-Dwellers
1 Djinn Illuminatus
1 Melek, Izzet Paragon
1 Rashmi, Eternities Crafter
1 Wort, the Raidmother
1 Solemn Simulacrum
1 Murmuring Mystic
1 Crackling Drake
1 Surreal Memoir
1 Decoy Gambit
1 Deflecting Swat
1 Curious Herd
1 Chaos Warp
1 Comet Storm
1 Commune with Lava
1 Starstorm
1 Strength of the Tajuru
1 Artifact Mutation
1 Prophetic Bolt
1 Clash of Titans
1 Channeled Force
1 Chemister's Insight
1 Frantic Search
1 Whiplash Trap
1 Crop Rotation
1 Evolution Charm
1 Harrow
1 Hunter's Insight
1 Hunting Pack
1 Natural Connection
1 Slice in Twain
1 Tribute to the Wild
1 Growth Spiral
1 Temur Charm
1 Lavabrink Floodgates
1 Twinning Staff
1 Bonder's Ornament
1 Arcane Signet
1 Commander's Sphere
1 Lightning Greaves
1 Sol Ring
1 Swarm Intelligence
1 Primal Empathy
1 Psychic Impetus
1 Shiny Impetus
1 Predatory Impetus
1 Wilderness Reclamation
1 Cinder Glade
1 Desolate Lighthouse
1 Exotic Orchard
1 Kessig Wolf Run
1 Mossfire Valley
1 Mosswort Bridge
1 Oran-Rief, the Vastwood
1 Scavenger Grounds
1 Yavimaya Coast
1 Command Tower
1 Frontier Bivouac
1 Gruul Turf
1 Halimar Depths
1 Izzet Boilerworks
1 Myriad Landscape
1 Rupture Spire
1 Simic Growth Chamber
1 Rugged Highlands
1 Swiftwater Cliffs
1 Thornwood Falls
3 Forest
3 Forest
2 Forest
2 Island
2 Island
1 Island
2 Mountain
2 Mountain
1 Mountain
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[metadata]
Name=Arcane Wizardry
[Commander]
1 Inalla, Archmage Ritualist
[Main]
1 Kess, Dissident Mage
1 Mairsil, the Pretender
1 Galecaster Colossus
1 Magus of the Mind
1 Portal Mage
1 Vindictive Lich
1 Izzet Chemister
1 Taigam, Sidisi's Hand
1 Havengul Lich
1 Marchesa, the Black Rose
1 Vela the Night-Clad
1 Arcanis the Omnipotent
1 Azami, Lady of Scrolls
1 Body Double
1 Harbinger of the Tides
1 Serendib Sorcerer
1 Apprentice Necromancer
1 Magus of the Abyss
1 Puppeteer Clique
1 Etherium-Horn Sorcerer
1 Mercurial Chemister
1 Nin, the Pain Artist
1 Niv-Mizzet, the Firemind
1 Shadowmage Infiltrator
1 Bloodline Necromancer
1 Archaeomancer
1 Merchant of Secrets
1 Sea Gate Oracle
1 Corpse Augur
1 Izzet Chronarch
1 Nivix Guildmage
1 Kindred Dominance
1 Clone Legion
1 Spelltwine
1 Decree of Pain
1 Necromantic Selection
1 Comet Storm
1 Polymorphist's Jest
1 Chaos Warp
1 Memory Plunder
1 Silumgar's Command
1 Into the Roil
1 Opportunity
1 Reality Shift
1 Go for the Throat
1 Cauldron Dance
1 Crosis's Charm
1 Rakdos Charm
1 Terminate
1 Nevinyrral's Disk
1 Mirror of the Forebears
1 Commander's Sphere
1 Darksteel Ingot
1 Fellwar Stone
1 Sol Ring
1 Unstable Obelisk
1 Worn Powerstone
1 Shifting Shadow
1 Curse of Verbosity
1 Curse of Disturbance
1 Curse of Opulence
1 Exotic Orchard
1 Mystifying Maze
4 Island
3 Island
3 Island
2 Swamp
2 Swamp
2 Swamp
2 Mountain
1 Mountain
1 Mountain
1 Path of Ancestry
1 Command Tower
1 Crumbling Necropolis
1 Dimir Aqueduct
1 Dismal Backwater
1 Evolving Wilds
1 Grixis Panorama
1 Izzet Boilerworks
1 Jwar Isle Refuge
1 Rakdos Carnarium
1 Swiftwater Cliffs
1 Temple of the False God
1 Terramorphic Expanse
1 Vivid Crag
1 Vivid Creek
1 Vivid Marsh
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[metadata]
Name=Arm for Battle
[Commander]
1 Wyleth, Soul of Steel
[Main]
1 Oreskos Explorer
1 Relic Seeker
1 Sram, Senior Edificer
1 Brass Squire
1 Danitha Capashen, Paragon
1 Dualcaster Mage
1 Flickerwisp
1 Ironclad Slayer
1 Kor Cartographer
1 Odric, Lunarch Marshal
1 Tiana, Ship's Caretaker
1 Condemn
1 Expedite
1 Swords to Plowshares
1 Abrade
1 Boros Charm
1 Comet Storm
1 Dawn Charm
1 Deflecting Palm
1 Disenchant
1 Fists of Flame
1 Temur Battle Rage
1 Valorous Stance
1 Generous Gift
1 Unbreakable Formation
1 Volcanic Fallout
1 Wear // Tear
1 White Sun's Zenith
1 Master Warcraft
1 Return to Dust
1 Wild Ricochet
1 Word of Seizing
1 Response // Resurgence
1 Jaya's Immolating Inferno
1 Martial Coup
1 Relentless Assault
1 Winds of Rath
1 Bonesplitter
1 Explorer's Scope
1 Sol Ring
1 Blackblade Reforged
1 Blazing Sunsteel
1 Boros Signet
1 Hero's Blade
1 Mask of Avacyn
1 Ring of Thune
1 Ring of Valkas
1 Swiftfoot Boots
1 Fireshrieker
1 Haunted Cloak
1 Loxodon Warhammer
1 Sunforger
1 Sword of Vengeance
1 Sigarda's Aid
1 Spirit Mantle
1 Timely Ward
1 Unquestioned Authority
1 Faith Unbroken
1 On Serra's Wings
1 Boros Garrison
1 Boros Guildgate
1 Command Tower
1 Encroaching Wastes
1 Evolving Wilds
1 Forgotten Cave
1 Memorial to War
5 Mountain
4 Mountain
1 Myriad Landscape
7 Plains
7 Plains
1 Rogue's Passage
1 Rupture Spire
1 Secluded Steppe
1 Slayers' Stronghold
1 Stone Quarry
1 Sunhome, Fortress of the Legion
1 Terramorphic Expanse
1 Transguild Promenade
1 Wind-Scarred Crag
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[metadata]
Name=Aura of Courage
[Commander]
1 Galea, Kindler of Hope
[Main]
1 Angel of Finality
1 Puresteel Paladin
1 Realm-Cloaked Giant // Cast Off
1 Sram, Senior Edificer
1 Prognostic Sphinx
1 Cold-Eyed Selkie
1 Fleecemane Lion
1 Knight of Autumn
1 Riverwise Augur
1 Acidic Slime
1 Paradise Druid
1 Winds of Rath
1 Serum Visions
1 Nature's Lore
1 Heroic Intervention
1 Valorous Stance
1 Brainstorm
1 Bant Charm
1 Argentum Armor
1 Basilisk Collar
1 Masterwork of Ingenuity
1 Moonsilver Spear
1 Sword of the Animist
1 Behemoth Sledge
1 Arcane Signet
1 Colossus Hammer
1 Explorer's Scope
1 Sol Ring
1 Swiftfoot Boots
1 Viridian Longbow
1 Imprisoned in the Moon
1 Greater Good
1 Verdant Embrace
1 Angelic Gift
1 Gryff's Boon
1 Curse of Verbosity
1 Eel Umbra
1 Psychic Impetus
1 Abundant Growth
1 Fertile Ground
1 Kenrith's Transformation
1 Rancor
1 Utopia Sprawl
1 Wild Growth
1 Shielding Plax
1 Canopy Vista
1 Exotic Orchard
1 Fortified Village
1 Lumbering Falls
1 Port Town
1 Prairie Stream
1 Skycloud Expanse
1 Sungrass Prairie
1 Evolving Wilds
1 Azorius Chancery
1 Bant Panorama
1 Command Tower
1 Flood Plain
1 Grasslands
1 Halimar Depths
1 Mishra's Factory
1 Path of Ancestry
1 Seaside Citadel
1 Simic Growth Chamber
1 Terramorphic Expanse
1 Thriving Grove
1 Thriving Heath
1 Thriving Isle
1 Vitu-Ghazi, the City-Tree
1 Island
1 Island
1 Island
1 Island
2 Forest
2 Forest
2 Forest
2 Forest
1 Plains
1 Plains
1 Storvald, Frost Giant Jarl
1 Fey Steed
1 Holy Avenger
1 Mantle of the Ancients
1 Robe of Stars
1 Valiant Endeavor
1 Diviner's Portent
1 Netherese Puzzle-Ward
1 Winged Boots
1 Belt of Giant Strength
1 Song of Inspiration
1 Catti-brie of Mithral Hall
1 Ride the Avalanche
1 Clay Golem
1 Ebony Fly
1 Sword of Hours
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[metadata]
Name=Bedecked Brokers
[Commander]
1 Perrie, the Pulverizer
[Main]
1 Kros, Defense Contractor
1 Ajani Unyielding
1 Angelic Sleuth
1 Aven Courier
1 Aven Mimeomancer
1 Avenging Huntbonder
1 Bribe Taker
1 Crystalline Giant
1 Devoted Druid
1 Denry Klin, Editor in Chief
1 Evolution Sage
1 Fathom Mage
1 Forgotten Ancient
1 Grateful Apparition
1 Incubation Druid
1 Jenara, Asura of War
1 Luminarch Aspirant
1 Park Heights Maverick
1 Rishkar, Peema Renegade
1 Roalesk, Apex Hybrid
1 Scavenging Ooze
1 Shield Broker
1 Skyboon Evangelist
1 Skyship Plunderer
1 Slippery Bogbonder
1 Steelbane Hydra
1 Thrummingbird
1 Vorel of the Hull Clade
1 Wall of Roots
1 Wickerbough Elder
1 Wingspan Mentor
1 Declaration in Stone
1 Damning Verdict
1 Planar Outburst
1 Tezzeret's Gambit
1 Rishkar's Expertise
1 Urban Evolution
1 Bant Charm
1 Brokers Charm
1 Brokers Confluence
1 Contractual Safeguard
1 Exotic Pets
1 Generous Gift
1 Storm of Forms
1 Family's Favor
1 Hoofprints of the Stag
1 Primal Empathy
1 Resourceful Defense
1 Together Forever
1 Agent's Toolkit
1 Arcane Signet
1 Commander's Sphere
1 Everflowing Chalice
1 Fellwar Stone
1 Gavel of the Righteous
1 Midnight Clock
1 Oblivion Stone
1 Oracle's Vault
1 Power Conduit
1 Sol Ring
1 Swiftfoot Boots
1 Ash Barrens
1 Bant Panorama
1 Brokers Hideout
1 Canopy Vista
1 Command Tower
1 Exotic Orchard
1 Flooded Grove
1 Fortified Village
1 Gavony Township
1 Karn's Bastion
1 Littjara Mirrorlake
1 Llanowar Reborn
1 Myriad Landscape
1 Nesting Grounds
1 Path of Ancestry
1 Port Town
1 Prairie Stream
1 Seaside Citadel
1 Skycloud Expanse
1 Sungrass Prairie
1 Temple of Mystery
1 Vivid Creek
1 Vivid Grove
1 Vivid Meadow
3 Forest
2 Forest
2 Island
2 Island
3 Plains
2 Plains
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[metadata]
Name=Blame Game
[Commander]
1 Nelly Borca, Impulsive Accuser
[Main]
1 Feather, Radiant Arbiter
1 Immortal Obligation
1 Otherworldly Escort
1 Redemption Arc
1 Trouble in Pairs
1 Havoc Eater
1 Hot Pursuit
1 Mob Verdict
1 Prisoner's Dilemma
1 Take the Bait
1 Ransom Note
1 Angel of the Ruins
1 Comeuppance
1 Darien, King of Kjeldor
1 Duelist's Heritage
1 Elspeth, Sun's Champion
1 Keeper of the Accord
1 Loran of the Third Path
1 Promise of Loyalty
1 Selfless Squire
1 Sevinne's Reclamation
1 Smuggler's Share
1 Stalking Leonin
1 Sun Titan
1 Windborn Muse
1 Winds of Rath
1 Agitator Ant
1 Brash Taunter
1 Disrupt Decorum
1 Etali, Primal Storm
1 Fiendish Duo
1 Frontier Warmonger
1 Kazuul, Tyrant of the Cliffs
1 Spectacular Showdown
1 Vengeful Ancestor
1 Anya, Merciless Angel
1 Boros Reckoner
1 Deflecting Palm
1 Gisela, Blade of Goldnight
1 Ancient Stone Idol
1 Solemn Simulacrum
1 Steel Hellkite
1 Tome of Legends
1 Castle Ardenvale
1 Exotic Orchard
1 Furycalm Snarl
1 Kher Keep
1 Labyrinth of Skophos
1 Needle Spires
1 Scavenger Grounds
1 Slayers' Stronghold
1 Temple of Triumph
1 Throne of the High City
1 War Room
1 Ghostly Prison
1 Gideon's Sacrifice
1 Martial Impetus
1 Orzhov Advokist
1 Seal of Cleansing
1 Soul Snare
1 Vow of Duty
1 Wall of Omens
1 Curse of Opulence
1 Rite of the Raging Storm
1 Shiny Impetus
1 Vow of Lightning
1 Arcane Signet
1 Bloodthirsty Blade
1 Fellwar Stone
1 Mind Stone
1 Sol Ring
1 Talisman of Conviction
1 Thought Vessel
1 Access Tunnel
1 Ash Barrens
1 Boros Garrison
1 Command Tower
1 Escape Tunnel
1 Myriad Landscape
1 Reliquary Tower
1 Rogue's Passage
1 Sunhome, Fortress of the Legion
1 Temple of the False God
5 Plains
4 Plains
4 Mountain
3 Mountain
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[metadata]
Name=Blight Curse
[Commander]
1 Auntie Ool, Cursewretch
[Main]
1 The Reaper, King No More
1 Wickersmith's Tools
1 Sinister Gnarlbark
1 Eventide's Shadow
1 Aberrant Return
1 Dread Tiller
1 Grave Venerations
1 Oft-Nabbed Goat
1 Village Pillagers
1 Puca's Covenant
1 Ferrafor, Young Yew
1 Tree of Perdition
1 Vernal Fen
1 Festering Thicket
1 Necroskitter
1 Ignoble Hierarch
1 Nesting Grounds
1 Massacre Girl, Known Killer
1 Grave Titan
1 Vraska, Betrayal's Sting
1 The Scorpion God
1 Liliana, Death Wielder
1 Chimil, the Inner Sun
1 Carnifex Demon
1 Puppeteer Clique
1 Dusk Urchins
1 Black Sun's Zenith
1 Painful Truths
1 Persist
1 Midnight Banshee
1 Chain Reaction
1 Archfiend of Ifnir
1 Channeler Initiate
1 Hapatra, Vizier of Poisons
1 Glissa Sunslayer
1 Everlasting Torment
1 Assassin's Trophy
1 Grim Poppet
1 Canyon Slough
1 Sheltered Thicket
1 Exotic Orchard
1 Smoldering Marsh
1 Cinder Glade
1 Dragonskull Summit
1 Rootbound Crag
1 Woodland Cemetery
1 Lasting Tarfire
1 Burning Curiosity
1 Hoarder's Greed
1 Blowfly Infestation
1 Fire Covenant
1 Sol Ring
1 Arcane Signet
1 Command Tower
1 Cathartic Reunion
1 Skinrender
1 Soul Snuffers
1 Incremental Blight
1 Infernal Grasp
1 Evolution Sage
1 Devoted Druid
1 Flourishing Defenses
1 Harmonize
1 Putrefy
1 Binding the Old Gods
1 Kulrath Knight
1 Contagion Clasp
1 Savage Lands
1 Ifnir Deadlands
1 Night's Whisper
1 Wickerbough Elder
1 Terminate
1 Commander's Sphere
1 Cathartic Pyre
1 Evolving Wilds
1 Terramorphic Expanse
1 Path of Ancestry
1 Riveteers Overlook
1 Rakdos Carnarium
1 Gruul Turf
1 Golgari Rot Farm
8 Swamp
4 Mountain
6 Forest
-87
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[metadata]
Name=Blood Rites
[Commander]
1 Clavileño, First of the Blessed
[Main]
1 Carmen, Cruel Skymarcher
1 Charismatic Conqueror
1 Elenda's Hierophant
1 March of the Canonized
1 Redemption Choir
1 Dusk Legion Sergeant
1 Master of Dark Rites
1 Promise of Aclazotz // Foul Rebirth
1 Order of Sacred Dusk
1 Austere Command
1 Kindred Boon
1 Mavren Fein, Dusk Apostle
1 Radiant Destiny
1 Welcoming Vampire
1 Bloodghast
1 Bloodtracker
1 Butcher of Malakir
1 Champion of Dusk
1 Cordial Vampire
1 Crossway Troublemakers
1 Damn
1 Drana, Liberator of Malakir
1 Exquisite Blood
1 Glass-Cast Heart
1 New Blood
1 Nighthawk Scavenger
1 Olivia's Wrath
1 Pact of the Serpent
1 Patron of the Vein
1 Sanctum Seeker
1 Timothar, Baron of Bats
1 Twilight Prophet
1 Yahenni, Undying Partisan
1 Elenda, the Dusk Rose
1 Sorin, Lord of Innistrad
1 Utter End
1 Vona, Butcher of Magan
1 Blade of the Bloodchief
1 Isolated Chapel
1 Shineshadow Snarl
1 Temple of Silence
1 Vault of the Archangel
1 Voldaren Estate
1 Windbrisk Heights
1 Martyr of Dusk
1 Return to Dust
1 Swords to Plowshares
1 Blood Artist
1 Bloodline Necromancer
1 Dusk Legion Zealot
1 Falkenrath Noble
1 Indulgent Aristocrat
1 Oathsworn Vampire
1 Village Rites
1 Viscera Seer
1 Bartolomé del Presidio
1 Cruel Celebrant
1 Etchings of the Chosen
1 Legion Lieutenant
1 Arcane Signet
1 Commander's Sphere
1 Heirloom Blade
1 Mind Stone
1 Orzhov Signet
1 Sol Ring
1 Swiftfoot Boots
1 Talisman of Hierarchy
1 Wayfarer's Bauble
1 Bojuka Bog
1 Command Tower
1 Myriad Landscape
1 Orzhov Basilica
1 Path of Ancestry
1 Rogue's Passage
1 Secluded Courtyard
1 Tainted Field
1 Temple of the False God
1 Unclaimed Territory
4 Plains
4 Plains
7 Swamp
6 Swamp
-95
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[metadata]
Name=Breed Lethality
[Commander]
1 Atraxa, Praetors' Voice
[Main]
1 Thrummingbird
1 Festercreep
1 Scavenging Ooze
1 Abzan Falconer
1 Orzhov Advokist
1 Tuskguard Captain
1 Necroplasm
1 Champion of Lambholt
1 Reyhan, Last of the Abzan
1 Vorel of the Hull Clade
1 Crystalline Crawler
1 Custodi Soulbinders
1 Forgotten Ancient
1 Bane of the Living
1 Ishai, Ojutai Dragonspeaker
1 Corpsejack Menace
1 Fathom Mage
1 Master Biomancer
1 Elite Scaleguard
1 Reveillark
1 Deepglow Skate
1 Kalonian Hydra
1 Ikra Shidiqi, the Usurper
1 Vulturous Zombie
1 Juniper Order Ranger
1 Ghave, Guru of Spores
1 Enduring Scalelord
1 Manifold Insights
1 Languish
1 Tezzeret's Gambit
1 Migratory Route
1 Merciless Eviction
1 Spitting Image
1 Sublime Exhalation
1 Duneblast
1 Treasure Cruise
1 Disdainful Stroke
1 Solidarity of Heroes
1 Grip of Phyresis
1 Inspiring Call
1 Mortify
1 Putrefy
1 Ancient Excavation
1 Mirrorweave
1 Sylvan Reclamation
1 Sol Ring
1 Fellwar Stone
1 Golgari Signet
1 Orzhov Signet
1 Simic Signet
1 Commander's Sphere
1 Darksteel Ingot
1 Cauldron of Souls
1 Astral Cornucopia
1 Hardened Scales
1 Brave the Sands
1 Duelist's Heritage
1 Bred for the Hunt
1 Citadel Siege
1 Cathars' Crusade
1 Arcane Sanctum
1 Ash Barrens
1 Azorius Chancery
1 Command Tower
1 Darkwater Catacombs
1 Dreadship Reef
1 Evolving Wilds
1 Exotic Orchard
1 Golgari Rot Farm
1 Murmuring Bosk
1 Opal Palace
1 Opulent Palace
1 Sandsteppe Citadel
1 Seaside Citadel
1 Sungrass Prairie
1 Temple of the False God
1 Terramorphic Expanse
1 Underground River
2 Plains
2 Plains
1 Plains
2 Island
1 Island
1 Island
2 Swamp
2 Swamp
1 Swamp
3 Forest
2 Forest
2 Forest
-104
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[metadata]
Name=Breed Lethality
[Commander]
1 Atraxa, Praetors' Voice
[Main]
1 Thrummingbird
1 Festercreep
1 Scavenging Ooze
1 Abzan Falconer
1 Orzhov Advokist
1 Tuskguard Captain
1 Necroplasm
1 Champion of Lambholt
1 Reyhan, Last of the Abzan
1 Vorel of the Hull Clade
1 Crystalline Crawler
1 Custodi Soulbinders
1 Forgotten Ancient
1 Bane of the Living
1 Ishai, Ojutai Dragonspeaker
1 Corpsejack Menace
1 Fathom Mage
1 Master Biomancer
1 Elite Scaleguard
1 Reveillark
1 Deepglow Skate
1 Kalonian Hydra
1 Ikra Shidiqi, the Usurper
1 Vulturous Zombie
1 Juniper Order Ranger
1 Ghave, Guru of Spores
1 Enduring Scalelord
1 Manifold Insights
1 Languish
1 Tezzeret's Gambit
1 Migratory Route
1 Merciless Eviction
1 Spitting Image
1 Sublime Exhalation
1 Duneblast
1 Treasure Cruise
1 Disdainful Stroke
1 Solidarity of Heroes
1 Grip of Phyresis
1 Inspiring Call
1 Mortify
1 Putrefy
1 Ancient Excavation
1 Mirrorweave
1 Sylvan Reclamation
1 Sol Ring
1 Fellwar Stone
1 Golgari Signet
1 Orzhov Signet
1 Simic Signet
1 Commander's Sphere
1 Darksteel Ingot
1 Cauldron of Souls
1 Astral Cornucopia
1 Hardened Scales
1 Brave the Sands
1 Duelist's Heritage
1 Bred for the Hunt
1 Citadel Siege
1 Cathars' Crusade
1 Arcane Sanctum
1 Ash Barrens
1 Azorius Chancery
1 Command Tower
1 Darkwater Catacombs
1 Dreadship Reef
1 Evolving Wilds
1 Exotic Orchard
1 Golgari Rot Farm
1 Murmuring Bosk
1 Opal Palace
1 Opulent Palace
1 Sandsteppe Citadel
1 Seaside Citadel
1 Sungrass Prairie
1 Temple of the False God
1 Terramorphic Expanse
1 Underground River
1 Plains
1 Plains
1 Plains
1 Plains
1 Plains
1 Island
1 Island
1 Island
1 Island
1 Swamp
1 Swamp
1 Swamp
1 Swamp
1 Swamp
1 Forest
1 Forest
1 Forest
1 Forest
1 Forest
1 Forest
1 Forest
-78
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[metadata]
Name=Buckle Up
[Commander]
1 Kotori, Pilot Prodigy
[Main]
1 Shorikai, Genesis Engine
1 Jace, Architect of Thought
1 Drumbellower
1 Ironsoul Enforcer
1 Cyberdrive Awakener
1 Kappa Cannoneer
1 Katsumasa, the Animator
1 Research Thief
1 Aeronaut Admiral
1 Cataclysmic Gearhulk
1 Indomitable Archangel
1 Myrsmith
1 Sram, Senior Edificer
1 Teshar, Ancestor's Apostle
1 Emry, Lurker of the Loch
1 Etherium Sculptor
1 Master of Etherium
1 Riddlesmith
1 Sai, Master Thopterist
1 Vedalken Engineer
1 Whirler Rogue
1 Arcanist's Owl
1 Hanna, Ship's Navigator
1 Raff Capashen, Ship's Mage
1 Foundry Inspector
1 Gold Myr
1 Shimmer Myr
1 Silver Myr
1 Solemn Simulacrum
1 Organic Extinction
1 Universal Surveillance
1 Thoughtcast
1 Dance of the Manse
1 Release to Memory
1 Access Denied
1 Armed and Armored
1 Crush Contraband
1 Dispatch
1 Generous Gift
1 Swords to Plowshares
1 Reality Shift
1 Aerial Surveyor
1 Imposter Mech
1 Imperial Recovery Unit
1 Mobilizer Mech
1 Prodigy's Prototype
1 Surgehacker Mech
1 Parhelion II
1 Arcane Signet
1 Azorius Signet
1 Colossal Plow
1 Cultivator's Caravan
1 Fellwar Stone
1 Mirage Mirror
1 Peacewalker Colossus
1 Raiders' Karve
1 Skysovereign, Consul Flagship
1 Smuggler's Copter
1 Sol Ring
1 Weatherlight
1 Swift Reconfiguration
1 Thopter Spy Network
1 Command Tower
1 Exotic Orchard
1 Port Town
1 Prairie Stream
1 Skycloud Expanse
1 Spire of Industry
1 Temple of Enlightenment
8 Plains
7 Plains
8 Island
7 Island
-79
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[metadata]
Name=Built From Scratch
[Commander]
1 Daretti, Scrap Savant
[Main]
1 Goblin Welder
1 Epochrasite
1 Myr Retriever
1 Myr Sire
1 Bottle Gnomes
1 Cathodion
1 Junk Diver
1 Palladium Myr
1 Pilgrim's Eye
1 Tuktuk the Explorer
1 Dualcaster Mage
1 Feldon of the Third Path
1 Solemn Simulacrum
1 Flametongue Kavu
1 Beetleback Chief
1 Ingot Chewer
1 Steel Hellkite
1 Wurmcoil Engine
1 Spitebellows
1 Hoard-Smelter Dragon
1 Warmonger Hellkite
1 Myr Battlesphere
1 Pentavus
1 Tyrant's Familiar
1 Bosh, Iron Golem
1 Bogardan Hellkite
1 Faithless Looting
1 Whipflare
1 Scrap Mastery
1 Incite Rebellion
1 Blasphemous Act
1 Impact Resonance
1 Chaos Warp
1 Volcanic Offering
1 Word of Seizing
1 Magmaquake
1 Starstorm
1 Everflowing Chalice
1 Panic Spellbomb
1 Sol Ring
1 Wayfarer's Bauble
1 Fire Diamond
1 Ichor Wellspring
1 Liquimetal Coating
1 Mind Stone
1 Mycosynth Wellspring
1 Ruby Medallion
1 Swiftfoot Boots
1 Commander's Sphere
1 Jalum Tome
1 Pristine Talisman
1 Unstable Obelisk
1 Trading Post
1 Caged Sun
1 Dreamstone Hedron
1 Loreseeker's Stone
1 Spine of Ish Sah
1 Darksteel Citadel
1 Great Furnace
1 Bitter Feud
1 Arcane Lighthouse
1 Buried Ruin
1 Dormant Volcano
1 Flamekin Village
1 Forgotten Cave
1 Ghost Quarter
1 Phyrexia's Core
1 Reliquary Tower
1 Smoldering Crater
1 Temple of the False God
8 Mountain
7 Mountain
7 Mountain
7 Mountain
-81
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[metadata]
Name=Built From Scratch
[Commander]
1 Daretti, Scrap Savant
[Main]
1 Goblin Welder
1 Epochrasite
1 Myr Retriever
1 Myr Sire
1 Bottle Gnomes
1 Cathodion
1 Junk Diver
1 Palladium Myr
1 Pilgrim's Eye
1 Tuktuk the Explorer
1 Dualcaster Mage
1 Feldon of the Third Path
1 Solemn Simulacrum
1 Flametongue Kavu
1 Beetleback Chief
1 Ingot Chewer
1 Steel Hellkite
1 Wurmcoil Engine
1 Spitebellows
1 Hoard-Smelter Dragon
1 Warmonger Hellkite
1 Myr Battlesphere
1 Pentavus
1 Tyrant's Familiar
1 Bosh, Iron Golem
1 Bogardan Hellkite
1 Faithless Looting
1 Whipflare
1 Scrap Mastery
1 Incite Rebellion
1 Blasphemous Act
1 Impact Resonance
1 Chaos Warp
1 Volcanic Offering
1 Word of Seizing
1 Magmaquake
1 Starstorm
1 Everflowing Chalice
1 Panic Spellbomb
1 Sol Ring
1 Wayfarer's Bauble
1 Fire Diamond
1 Ichor Wellspring
1 Liquimetal Coating
1 Mind Stone
1 Mycosynth Wellspring
1 Ruby Medallion
1 Swiftfoot Boots
1 Commander's Sphere
1 Jalum Tome
1 Pristine Talisman
1 Unstable Obelisk
1 Trading Post
1 Caged Sun
1 Dreamstone Hedron
1 Loreseeker's Stone
1 Spine of Ish Sah
1 Darksteel Citadel
1 Great Furnace
1 Bitter Feud
1 Arcane Lighthouse
1 Buried Ruin
1 Dormant Volcano
1 Flamekin Village
1 Forgotten Cave
1 Ghost Quarter
1 Phyrexia's Core
1 Reliquary Tower
1 Smoldering Crater
1 Temple of the False God
5 Mountain
5 Mountain
5 Mountain
5 Mountain
5 Mountain
4 Mountain
-94
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[metadata]
Name=Cabaretti Cacophony
[Commander]
1 Kitt Kanto, Mayhem Diva
[Main]
1 Phabine, Boss's Confidant
1 Leafkin Druid
1 Sakura-Tribe Elder
1 Agitator Ant
1 Bess, Soul Nourisher
1 Champion of Lambholt
1 Magus of the Wheel
1 Orzhov Advokist
1 Rumor Gatherer
1 Scute Swarm
1 Selvala, Explorer Returned
1 Wood Elves
1 Zurzoth, Chaos Rider
1 Arasta of the Endless Web
1 Life of the Party
1 Master of Ceremonies
1 Rose Room Treasurer
1 Sizzling Soloist
1 Boss's Chauffeur
1 Gahiji, Honored One
1 Kazuul, Tyrant of the Cliffs
1 Thunderfoot Baloth
1 Cabaretti Confluence
1 Camaraderie
1 Cultivate
1 Fell the Mighty
1 Harmonize
1 Indulge // Excess
1 Martial Coup
1 Seize the Spotlight
1 Shamanic Revelation
1 Sylvan Offering
1 Vivien's Stampede
1 Artifact Mutation
1 Aura Mutation
1 Beast Within
1 Boros Charm
1 Cabaretti Charm
1 Crash the Party
1 Call the Coppercoats
1 Grand Crescendo
1 March of the Multitudes
1 Path to Exile
1 Sol Ring
1 Arcane Signet
1 Bloodthirsty Blade
1 Fellwar Stone
1 Idol of Oblivion
1 Commander's Sphere
1 Scepter of Celebration
1 False Floor
1 Intangible Virtue
1 Awakening Zone
1 Beastmaster Ascension
1 Duelist's Heritage
1 Killer Service
1 Prosperous Partnership
1 Felidar Retreat
1 Outpost Siege
1 Assemble the Legion
1 Sandwurm Convergence
1 Ash Barrens
1 Cabaretti Courtyard
1 Canopy Vista
1 Castle Ardenvale
1 Castle Embereth
1 Cinder Glade
1 Command Tower
1 Exotic Orchard
1 Fortified Village
1 Game Trail
1 Jungle Shrine
1 Mossfire Valley
1 Myriad Landscape
1 Naya Panorama
1 Path of Ancestry
1 Rugged Prairie
1 Sungrass Prairie
1 Temple of Triumph
1 Thriving Bluff
1 Thriving Grove
1 Thriving Heath
1 Windbrisk Heights
2 Plains
2 Plains
2 Mountain
2 Mountain
4 Forest
4 Forest
-88
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[metadata]
Name=Call the Spirits
[Commander]
1 Daxos the Returned
[Main]
1 Oreskos Explorer
1 Karlov of the Ghost Council
1 Underworld Coinsmith
1 Burnished Hart
1 Bastion Protector
1 Dawnglare Invoker
1 Ghostblade Eidolon
1 Kor Sanctifiers
1 Monk Idealist
1 Mesa Enchantress
1 Nighthowler
1 Corpse Augur
1 Fate Unraveler
1 Ajani's Chosen
1 Doomwake Giant
1 Dreadbringer Lampads
1 Celestial Ancient
1 Celestial Archon
1 Herald of the Host
1 Banshee of the Dread Choir
1 Thief of Blood
1 Treasury Thrull
1 Sandstone Oracle
1 Silent Sentinel
1 Teysa, Envoy of Ghosts
1 Ancient Craving
1 Gild
1 Dawn to Dusk
1 Righteous Confluence
1 Open the Vaults
1 Deadly Tempest
1 Death Grasp
1 Sol Ring
1 Wayfarer's Bauble
1 Lightning Greaves
1 Orzhov Signet
1 Thought Vessel
1 Crystal Chimes
1 Orzhov Cluestone
1 Phyrexian Reclamation
1 Seal of Cleansing
1 Grave Peril
1 Banishing Light
1 Cage of Hands
1 Karmic Justice
1 Vow of Duty
1 Fallen Ideal
1 Seal of Doom
1 Vow of Malice
1 Aura of Silence
1 Grasp of Fate
1 Shielded by Faith
1 Phyrexian Arena
1 Underworld Connections
1 Daxos's Torment
1 Marshal's Anthem
1 Dictate of Heliod
1 Sigil of the Empty Throne
1 Black Market
1 Necromancer's Covenant
1 Barren Moor
1 Command Tower
1 Evolving Wilds
1 Ghost Quarter
1 New Benalia
1 Orzhov Basilica
1 Orzhov Guildgate
1 Rogue's Passage
1 Scoured Barrens
1 Secluded Steppe
1 Tainted Field
1 Temple of the False God
1 Terramorphic Expanse
1 Vivid Marsh
1 Vivid Meadow
3 Plains
3 Plains
3 Plains
2 Plains
4 Swamp
3 Swamp
3 Swamp
3 Swamp
-83
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[metadata]
Name=Chaos Incarnate
[Commander]
1 Kardur, Doomscourge
[Main]
1 Archfiend of Depravity
1 Bloodgift Demon
1 Deadly Tempest
1 Dredge the Mire
1 Ob Nixilis Reignited
1 Profane Command
1 Rakshasa Debaser
1 Reign of the Pit
1 Sangromancer
1 Scythe Specter
1 Sepulchral Primordial
1 Soul Shatter
1 Titan Hunter
1 Blasphemous Act
1 Brash Taunter
1 Chaos Warp
1 Combustible Gearhulk
1 Dictate of the Twin Gods
1 Fiery Confluence
1 Geode Rager
1 Kazuul, Tyrant of the Cliffs
1 Magmatic Force
1 Sunbird's Invocation
1 Tectonic Giant
1 Wild Ricochet
1 Wildfire Devils
1 Kaervek the Merciless
1 Spiteful Visions
1 Stormfist Crusader
1 Theater of Horrors
1 Coveted Jewel
1 Solemn Simulacrum
1 Foreboding Ruins
1 Smoldering Marsh
1 Stensia Bloodhall
1 Temple of Malice
1 Ambition's Cost
1 Feed the Swarm
1 Indulgent Tormentor
1 Read the Bones
1 Sign in Blood
1 Syphon Mind
1 Vampire Nighthawk
1 Abrade
1 Explosion of Riches
1 Guttersnipe
1 Hate Mirage
1 Mana Geyser
1 Thermo-Alchemist
1 Breath of Malfegor
1 Rakdos Charm
1 Terminate
1 Unlicensed Disintegration
1 Arcane Signet
1 Burnished Hart
1 Commander's Sphere
1 Lightning Greaves
1 Nihil Spellbomb
1 Rakdos Signet
1 Sol Ring
1 Talisman of Indulgence
1 Wayfarer's Bauble
1 Worn Powerstone
1 Akoum Refuge
1 Bloodfell Caves
1 Cinder Barrens
1 Command Tower
1 Molten Slagheap
1 Myriad Landscape
1 Urborg Volcano
4 Swamp
4 Swamp
4 Swamp
3 Swamp
4 Mountain
4 Mountain
3 Mountain
3 Mountain
-87
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[metadata]
Name=Corrupting Influence
[Commander]
1 Ixhel, Scion of Atraxa
[Main]
1 Bilious Skulldweller
1 Blight Mamba
1 Blightbelly Rat
1 Cankerbloom
1 Contaminant Grafter
1 Evolution Sage
1 Glissa's Retriever
1 Grateful Apparition
1 Ichor Rats
1 Ichorclaw Myr
1 Mycosynth Fiend
1 Myr Convert
1 Norn's Choirmaster
1 Pestilent Syphoner
1 Phyrexian Swarmlord
1 Plague Myr
1 Plague Stinger
1 Scavenging Ooze
1 Venomous Brutalizer
1 Viridian Corrupter
1 Vishgraz, the Doomhive
1 Windborn Muse
1 Caress of Phyrexia
1 Culling Ritual
1 Cultivate
1 Expand the Sphere
1 Feed the Infection
1 Fumigate
1 Geth's Summons
1 Infectious Inquiry
1 Merciless Eviction
1 Night's Whisper
1 Noxious Assault
1 Painful Truths
1 Phyresis Outbreak
1 Phyrexian Rebirth
1 Unnatural Restoration
1 Vat Emergence
1 Wurmquake
1 Beast Within
1 Carrion Call
1 Mortify
1 Noxious Revival
1 Putrefy
1 Swords to Plowshares
1 Vraska's Fall
1 Ghostly Prison
1 Moldervine Reclamation
1 Norn's Decree
1 Arcane Signet
1 Chromatic Lantern
1 Commander's Sphere
1 Contagion Clasp
1 Fellwar Stone
1 Glistening Sphere
1 Golgari Signet
1 Grafted Exoskeleton
1 Norn's Annex
1 Phyrexian Atlas
1 Sol Ring
1 Trailblazer's Boots
1 Bojuka Bog
1 Canopy Vista
1 Command Tower
1 Exotic Orchard
1 Fortified Village
1 Karn's Bastion
1 Krosan Verge
1 Myriad Landscape
1 Necroblossom Snarl
1 Path of Ancestry
1 Sandsteppe Citadel
1 Shineshadow Snarl
1 Sungrass Prairie
1 Tainted Field
1 Tainted Wood
1 Temple of Malady
1 Temple of Plenty
1 Temple of Silence
6 Plains
6 Swamp
8 Forest
@@ -1,104 +0,0 @@
[metadata]
Name=Counter Blitz (FINAL FANTASY X)
[Commander]
1 Tidus, Yuna's Guardian
[Main]
1 Yuna, Grand Summoner
1 Auron, Venerated Guardian
1 Chocobo Knights
1 Gatta and Luzzu
1 Lord Jyscal Guado
1 Protection Magic
1 Summon: Ixion
1 Summon: Yojimbo
1 Summoner's Sending
1 Blitzball Stadium
1 Lulu, Stern Guardian
1 O'aka, Traveling Merchant
1 Rikku, Resourceful Guardian
1 Summon: Valefor
1 Maester Seymour
1 Sphere Grid
1 Summon: Magus Sisters
1 Tromell, Seymour's Butler
1 Yuna's Decision
1 Yuna's Whistle
1 Kimahri, Valiant Guardian
1 Shelinda, Yevon Acolyte
1 Sin, Unending Cataclysm
1 Wakka, Devoted Guardian
1 Collective Effort
1 Damning Verdict
1 Farewell
1 Luminous Broodmoth
1 Promise of Loyalty
1 Resourceful Defense
1 Scholar of New Horizons
1 Sunscorch Regent
1 Together Forever
1 Chasm Skulker
1 Inexorable Tide
1 Pull from Tomorrow
1 Bane of Progress
1 Fight Rigging
1 Forgotten Ancient
1 Generous Patron
1 Gyre Sage
1 Hardened Scales
1 Incubation Druid
1 Path of Discovery
1 Rampant Rejuvenator
1 Tireless Tracker
1 Altered Ego
1 Endless Detour
1 Fathom Mage
1 Walking Ballista
1 Brushland
1 Canopy Vista
1 Exotic Orchard
1 Flooded Grove
1 Fortified Village
1 Glacial Fortress
1 Hinterland Harbor
1 Overflowing Basin
1 Port Town
1 Prairie Stream
1 Skycloud Expanse
1 Sungrass Prairie
1 Sunpetal Grove
1 Temple of Enlightenment
1 Temple of Mystery
1 Temple of Plenty
1 Vineglimmer Snarl
1 Destroy Evil
1 Grateful Apparition
1 Path to Exile
1 An Offer You Can't Refuse
1 Duskshell Crawler
1 Farseek
1 Inspiring Call
1 Three Visits
1 Bred for the Hunt
1 Arcane Signet
1 Everflowing Chalice
1 Sol Ring
1 Ash Barrens
1 Evolving Wilds
1 Forge of Heroes
1 Idyllic Beachfront
1 Nesting Grounds
1 Path of Ancestry
1 Radiant Grove
1 Seaside Citadel
1 Tangled Islet
1 Temple of the False God
1 Command Tower
1 Island
1 Island
1 Island
1 Forest
1 Forest
1 Forest
1 Plains
1 Plains
1 Plains
@@ -1,98 +0,0 @@
[metadata]
Name=Counter Blitz Collector's Edition (FINAL FANTASY X)
[Commander]
1 Tidus, Yuna's Guardian
[Main]
1 Altered Ego
1 An Offer You Can't Refuse
1 Arcane Signet
1 Ash Barrens
1 Auron, Venerated Guardian
1 Bane of Progress
1 Blitzball Stadium
1 Bred for the Hunt
1 Brushland
1 Canopy Vista
1 Chasm Skulker
1 Chocobo Knights
1 Collective Effort
1 Command Tower
1 Damning Verdict
1 Destroy Evil
1 Duskshell Crawler
1 Endless Detour
1 Everflowing Chalice
1 Evolving Wilds
1 Exotic Orchard
1 Farewell
1 Farseek
1 Fathom Mage
1 Fight Rigging
1 Flooded Grove
3 Forest
1 Forge of Heroes
1 Forgotten Ancient
1 Fortified Village
1 Gatta and Luzzu
1 Generous Patron
1 Glacial Fortress
1 Grateful Apparition
1 Gyre Sage
1 Hardened Scales
1 Hinterland Harbor
1 Idyllic Beachfront
1 Incubation Druid
1 Inexorable Tide
1 Inspiring Call
3 Island
1 Kimahri, Valiant Guardian
1 Lord Jyscal Guado
1 Lulu, Stern Guardian
1 Luminous Broodmoth
1 Maester Seymour
1 Nesting Grounds
1 O'aka, Traveling Merchant
1 Overflowing Basin
1 Path of Ancestry
1 Path of Discovery
1 Path to Exile
3 Plains
1 Port Town
1 Prairie Stream
1 Promise of Loyalty
1 Protection Magic
1 Pull from Tomorrow
1 Radiant Grove
1 Rampant Rejuvenator
1 Resourceful Defense
1 Rikku, Resourceful Guardian
1 Scholar of New Horizons
1 Seaside Citadel
1 Shelinda, Yevon Acolyte
1 Sin, Unending Cataclysm
1 Skycloud Expanse
1 Sol Ring
1 Sphere Grid
1 Summon: Ixion
1 Summon: Magus Sisters
1 Summon: Valefor
1 Summon: Yojimbo
1 Summoner's Sending
1 Sungrass Prairie
1 Sunpetal Grove
1 Sunscorch Regent
1 Tangled Islet
1 Temple of Enlightenment
1 Temple of Mystery
1 Temple of Plenty
1 Temple of the False God
1 Three Visits
1 Tireless Tracker
1 Together Forever
1 Tromell, Seymour's Butler
1 Vineglimmer Snarl
1 Wakka, Devoted Guardian
1 Walking Ballista
1 Yuna, Grand Summoner
1 Yuna's Decision
1 Yuna's Whistle
-101
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@@ -1,101 +0,0 @@
[metadata]
Name=Counter Intelligence
[Commander]
1 Inspirit, Flagship Vessel
[Main]
1 Kilo, Apogee Mind
1 Patrolling Peacemaker
1 Insight Engine
1 Uthros Research Craft
1 Depthshaker Titan
1 Long-Range Sensor
1 Moxite Refinery
1 Solar Array
1 Surge Conductor
1 Glittering Massif
1 Radiant Summit
1 Swan Song
1 Chaos Warp
1 Cloud Key
1 Gavel of the Righteous
1 Battlefield Forge
1 Angel of the Ruins
1 Fumigate
1 Organic Extinction
1 Resourceful Defense
1 Chrome Host Seedshark
1 Cyberdrive Awakener
1 Deepglow Skate
1 Emry, Lurker of the Loch
1 Kappa Cannoneer
1 Phyrexian Metamorph
1 Pull from Tomorrow
1 Ripples of Potential
1 Tekuthal, Inquiry Dominus
1 Thought Monitor
1 Universal Surveillance
1 Chain Reaction
1 Alibou, Ancient Witness
1 Jhoira, Weatherlight Captain
1 Wake the Past
1 Astral Cornucopia
1 Crystalline Crawler
1 Darksteel Reactor
1 Empowered Autogenerator
1 Hangarback Walker
1 Lux Artillery
1 Lux Cannon
1 Steel Overseer
1 Threefold Thunderhulk
1 Titan Forge
1 Adarkar Wastes
1 Cascade Bluffs
1 Clifftop Retreat
1 Exotic Orchard
1 Glacial Fortress
1 Irrigated Farmland
1 Karn's Bastion
1 The Mycosynth Gardens
1 Rugged Prairie
1 Shivan Reef
1 Skycloud Expanse
1 Spire of Industry
1 Sulfur Falls
1 Temple of Enlightenment
1 Temple of Epiphany
1 Temple of Triumph
1 Swords to Plowshares
1 Tezzeret's Gambit
1 Thirst for Knowledge
1 Arcane Signet
1 Pentad Prism
1 Sol Ring
1 Command Tower
1 Dispatch
1 Etherium Sculptor
1 Experimental Augury
1 Thrummingbird
1 Enthusiastic Mechanaut
1 Coretapper
1 Etched Oracle
1 Everflowing Chalice
1 Golem Foundry
1 Mindless Automaton
1 Soul-Guide Lantern
1 Ancient Den
1 Buried Ruin
1 Evolving Wilds
1 Great Furnace
1 Lonely Sandbar
1 Mystic Monastery
1 Razortide Bridge
1 Rustvale Bridge
1 Seat of the Synod
1 Secluded Steppe
1 Silverbluff Bridge
2 Plains
1 Plains
2 Island
1 Island
2 Mountain
1 Mountain
-90
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@@ -1,90 +0,0 @@
[metadata]
Name=Counterpunch
[Commander]
1 Ghave, Guru of Spores
[Main]
1 Aquastrand Spider
1 Deadly Recluse
1 Sakura-Tribe Elder
1 Scavenging Ooze
1 Monk Realist
1 Selesnya Evangel
1 Golgari Guildmage
1 Selesnya Guildmage
1 Nantuko Husk
1 Fertilid
1 Spawnwrithe
1 Vampire Nighthawk
1 Spike Feeder
1 Yavimaya Elder
1 Squallmonger
1 Penumbra Spider
1 Sigil Captain
1 Shriekmaw
1 Dark Hatchling
1 Teneb, the Harvester
1 Hornet Queen
1 Vish Kal, Blood Arbiter
1 Symbiotic Wurm
1 Celestial Force
1 Karador, Ghost Chieftain
1 Chorus of the Conclave
1 Alliance of Arms
1 Cultivate
1 Harmonize
1 Syphon Flesh
1 Bestial Menace
1 Hex
1 Hour of Reckoning
1 Death Mutation
1 Storm Herd
1 Doom Blade
1 Tribute to the Wild
1 Footbottom Feast
1 Afterlife
1 Mortify
1 Nemesis Trap
1 Cobra Trap
1 Skullclamp
1 Sol Ring
1 Golgari Signet
1 Lightning Greaves
1 Orzhov Signet
1 Selesnya Signet
1 Darksteel Ingot
1 Acorn Catapult
1 Soul Snare
1 Fists of Ironwood
1 Necrogenesis
1 Vow of Malice
1 Awakening Zone
1 Vow of Wildness
1 Oblivion Ring
1 Vow of Duty
1 Attrition
1 Aura Shards
1 Barren Moor
1 Command Tower
1 Evolving Wilds
1 Golgari Rot Farm
1 Orzhov Basilica
1 Rupture Spire
1 Secluded Steppe
1 Selesnya Sanctuary
1 Temple of the False God
1 Tranquil Thicket
1 Vivid Grove
1 Vivid Marsh
1 Vivid Meadow
2 Swamp
2 Swamp
2 Swamp
2 Swamp
3 Forest
3 Forest
2 Forest
2 Forest
2 Plains
2 Plains
2 Plains
2 Plains
-82
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[metadata]
Name=Coven Counters
[Commander]
1 Leinore, Autumn Sovereign
[Main]
1 Angel of Glory's Rise
1 Bastion Protector
1 Custodi Soulbinders
1 Dearly Departed
1 Herald of War
1 Knight of the White Orchid
1 Mikaeus, the Lunarch
1 Odric, Master Tactician
1 Riders of Gavony
1 Victory's Envoy
1 Champion of Lambholt
1 Gyre Sage
1 Kessig Cagebreakers
1 Somberwald Sage
1 Verdurous Gearhulk
1 Wild Beastmaster
1 Heron's Grace Champion
1 Sigarda, Heron's Grace
1 Abzan Falconer
1 Ainok Bond-Kin
1 Elite Scaleguard
1 Orzhov Advokist
1 Avacyn's Pilgrim
1 Eternal Witness
1 Yavimaya Elder
1 Enduring Scalelord
1 Juniper Order Ranger
1 Trostani's Summoner
1 Cleansing Nova
1 Hour of Reckoning
1 Shamanic Revelation
1 Bestial Menace
1 Biogenic Upgrade
1 Growth Spasm
1 Unbreakable Formation
1 Return to Dust
1 Swords to Plowshares
1 Beast Within
1 Inspiring Call
1 Lifecrafter's Bestiary
1 Arcane Signet
1 Sol Ring
1 Swiftfoot Boots
1 Talisman of Unity
1 Citadel Siege
1 Death's Presence
1 Canopy Vista
1 Exotic Orchard
1 Fortified Village
1 Sungrass Prairie
1 Temple of Plenty
1 Blighted Woodland
1 Command Tower
1 Krosan Verge
1 Myriad Landscape
1 Path of Ancestry
1 Rogue's Passage
1 Selesnya Sanctuary
1 Temple of the False God
12 Forest
12 Plains
1 Kyler, Sigardian Emissary
1 Celestial Judgment
1 Curse of Conformity
1 Moorland Rescuer
1 Sigarda's Vanguard
1 Stalwart Pathlighter
1 Wall of Mourning
1 Celebrate the Harvest
1 Curse of Clinging Webs
1 Heronblade Elite
1 Kurbis, Harvest Celebrant
1 Ruinous Intrusion
1 Sigardian Zealot
1 Somberwald Beastmaster
1 Dawnhart Wardens
1 Moonsilver Key
+72 -75
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@@ -3,88 +3,85 @@ Name=Creative Energy
[Commander]
1 Satya, Aetherflux Genius
[Main]
1 Cayth, Famed Mechanist
1 Sphinx of the Revelation
1 Filigree Racer
1 Localized Destruction
1 Adarkar Wastes
1 Aether Hub
1 Aether Refinery
1 Hourglass of the Lost
1 Salvation Colossus
1 Blaster Hulk
1 Razorfield Ripper
1 Silverquill Lecturer
1 Overclocked Electromancer
1 Stone Idol Generator
1 Aurora Shifter
1 Conversion Apparatus
1 Gonti's Aether Heart
1 Lightning Runner
1 Aethertide Whale
1 Aethergeode Miner
1 Aethersphere Harvester
1 Bident of Thassa
1 Temple of Enlightenment
1 Battlefield Forge
1 Myr Battlesphere
1 Grenzo, Havoc Raiser
1 Brudiclad, Telchor Engineer
1 Coveted Jewel
1 Goldspan Dragon
1 Legion Loyalty
1 Mystic Gate
1 Aethersquall Ancient
1 Aetherstorm Roc
1 Aethertide Whale
1 Aetherworks Marvel
1 Akroma's Will
1 Adarkar Wastes
1 Shivan Reef
1 Amped Raptor
1 Angel of Invention
1 Arcane Signet
1 Aurora Shifter
1 Austere Command
1 Azorius Chancery
1 Battlefield Forge
1 Bespoke Battlewagon
1 Bident of Thassa
1 Blaster Hulk
1 Brudiclad, Telchor Engineer
1 Burnished Hart
1 Castle Vantress
1 Cayth, Famed Mechanist
1 Coalition Relic
1 Combustible Gearhulk
1 Aetherworks Marvel
1 Angel of Invention
1 Confiscation Coup
1 Aetherstorm Roc
1 Aethersquall Ancient
1 Frostboil Snarl
1 Austere Command
1 Furycalm Snarl
1 Midnight Clock
1 Professional Face-Breaker
1 Farewell
1 Port Town
1 Temple of Triumph
1 Solemn Simulacrum
1 Temple of Epiphany
1 Prairie Stream
1 Skyclave Apparition
1 Castle Vantress
1 Jolted Awake
1 Bespoke Battlewagon
1 Roil Cartographer
1 Unstable Amulet
1 Amped Raptor
1 Solar Transformer
1 Scurry of Gremlins
1 Izzet Generatorium
1 Talisman of Conviction
1 Tezzeret's Gambit
1 Izzet Boilerworks
1 Azorius Chancery
1 Talisman of Progress
1 Command Tower
1 Burnished Hart
1 Arcane Signet
1 Sol Ring
1 Era of Innovation
1 Aether Hub
1 Confiscation Coup
1 Conversion Apparatus
1 Coveted Jewel
1 Decoction Module
1 Glimmer of Genius
1 Whirler Virtuoso
1 Talisman of Creativity
1 Swords to Plowshares
1 Wayfarer's Bauble
1 Demolition Field
1 Era of Innovation
1 Farewell
1 Filigree Racer
1 Frostboil Snarl
1 Furycalm Snarl
1 Glimmer of Genius
1 Goldspan Dragon
1 Gonti's Aether Heart
1 Grenzo, Havoc Raiser
1 Hourglass of the Lost
1 Izzet Boilerworks
1 Izzet Generatorium
1 Jolted Awake
1 Legion Loyalty
1 Lightning Runner
1 Localized Destruction
1 Midnight Clock
1 Myr Battlesphere
1 Mystic Gate
1 Mystic Monastery
5 Plains
5 Plains
3 Island
2 Island
3 Mountain
2 Mountain
1 Overclocked Electromancer
1 Port Town
1 Prairie Stream
1 Professional Face-Breaker
1 Razorfield Ripper
1 Roil Cartographer
1 Salvation Colossus
1 Scurry of Gremlins
1 Shivan Reef
1 Silverquill Lecturer
1 Skyclave Apparition
1 Sol Ring
1 Solar Transformer
1 Solemn Simulacrum
1 Sphinx of the Revelation
1 Stone Idol Generator
1 Swords to Plowshares
1 Talisman of Conviction
1 Talisman of Creativity
1 Talisman of Progress
1 Temple of Enlightenment
1 Temple of Epiphany
1 Temple of Triumph
1 Tezzeret's Gambit
1 Unstable Amulet
1 Wayfarer's Bauble
1 Whirler Virtuoso
7 Plains
7 Island
6 Mountain
@@ -1,90 +0,0 @@
[metadata]
Name=Creative Energy Collector's Edition
[Commander]
1 Satya, Aetherflux Genius
[Main]
1 Cayth, Famed Mechanist
1 Sphinx of the Revelation
1 Filigree Racer
1 Localized Destruction
1 Aether Refinery
1 Hourglass of the Lost
1 Salvation Colossus
1 Blaster Hulk
1 Razorfield Ripper
1 Silverquill Lecturer
1 Overclocked Electromancer
1 Stone Idol Generator
1 Aurora Shifter
1 Conversion Apparatus
1 Gonti's Aether Heart
1 Lightning Runner
1 Aethertide Whale
1 Aethergeode Miner
1 Aethersphere Harvester
1 Bident of Thassa
1 Temple of Enlightenment
1 Battlefield Forge
1 Myr Battlesphere
1 Grenzo, Havoc Raiser
1 Brudiclad, Telchor Engineer
1 Coveted Jewel
1 Goldspan Dragon
1 Legion Loyalty
1 Mystic Gate
1 Akroma's Will
1 Adarkar Wastes
1 Shivan Reef
1 Coalition Relic
1 Combustible Gearhulk
1 Aetherworks Marvel
1 Angel of Invention
1 Confiscation Coup
1 Aetherstorm Roc
1 Aethersquall Ancient
1 Frostboil Snarl
1 Austere Command
1 Furycalm Snarl
1 Midnight Clock
1 Professional Face-Breaker
1 Farewell
1 Port Town
1 Temple of Triumph
1 Solemn Simulacrum
1 Temple of Epiphany
1 Prairie Stream
1 Skyclave Apparition
1 Castle Vantress
1 Jolted Awake
1 Bespoke Battlewagon
1 Roil Cartographer
1 Unstable Amulet
1 Amped Raptor
1 Solar Transformer
1 Scurry of Gremlins
1 Izzet Generatorium
1 Talisman of Conviction
1 Tezzeret's Gambit
1 Izzet Boilerworks
1 Azorius Chancery
1 Talisman of Progress
1 Command Tower
1 Burnished Hart
1 Arcane Signet
1 Sol Ring
1 Era of Innovation
1 Aether Hub
1 Decoction Module
1 Glimmer of Genius
1 Whirler Virtuoso
1 Talisman of Creativity
1 Swords to Plowshares
1 Wayfarer's Bauble
1 Demolition Field
1 Mystic Monastery
5 Plains
5 Plains
3 Island
2 Island
3 Mountain
2 Mountain
-93
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[metadata]
Name=Dance of the Elements
[Commander]
1 Ashling, the Limitless
[Main]
1 Mass of Mysteries
1 Elemental Spectacle
1 Springleaf Parade
1 Jubilation
1 Impulsivity
1 Lamentation
1 Belonging
1 Subterfuge
1 Rain-Slicked Copse
1 Sodden Verdure
1 Abundant Countryside
1 Endurance
1 Fury
1 Haunting Voyage
1 Avenger of Zendikar
1 Cavalier of Thorns
1 Greenwarden of Murasa
1 Selvala, Heart of the Wilds
1 Titan of Industry
1 Muldrotha, the Gravetide
1 Omnath, Locus of Rage
1 Yarok, the Desecrated
1 Omnath, Locus of the Roil
1 Timeless Lotus
1 Shatter the Sky
1 Hoofprints of the Stag
1 Slithermuse
1 Descendants' Fury
1 Blasphemous Act
1 Cream of the Crop
1 Kindred Summons
1 Bane of Progress
1 Realmwalker
1 Return of the Wildspeaker
1 Faeburrow Elder
1 Vernal Sovereign
1 Horde of Notions
1 Maelstrom Wanderer
1 Jegantha, the Wellspring
1 Chromatic Lantern
1 Primal Beyond
1 Raging Ravine
1 Exotic Orchard
1 Flamekin Village
1 Path to Exile
1 Mulldrifter
1 Reality Shift
1 Shriekmaw
1 Shimmercreep
1 Flamebraider
1 Crib Swap
1 Secluded Courtyard
1 Sol Ring
1 Command Tower
1 Arcane Signet
1 Distant Melody
1 Incandescent Soulstoke
1 Eclipsed Flamekin
1 Foundation Breaker
1 Garruk's Uprising
1 Risen Reef
1 Fellwar Stone
1 Unclaimed Territory
1 Ancient Ziggurat
1 Frontier Bivouac
1 Sandsteppe Citadel
1 Savage Lands
1 Opulent Palace
1 Seaside Citadel
1 Jungle Shrine
1 Smokebraider
1 Ingot Chewer
1 Fertile Ground
1 Abundant Growth
1 Kodama's Reach
1 Cultivate
1 Path of Ancestry
1 Thriving Grove
1 Thriving Heath
1 Thriving Isle
1 Opal Palace
1 Thriving Bluff
1 Thriving Moor
2 Plains
2 Island
2 Swamp
2 Mountain
8 Forest
-99
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@@ -1,99 +0,0 @@
[metadata]
Name=Deadly Disguise
[Commander]
1 Kaust, Eyes of the Glade
[Main]
1 Duskana, the Rage Mother
1 True Identity
1 Unexplained Absence
1 Veiled Ascension
1 Boltbender
1 Showstopping Surprise
1 Tesak, Judith's Hellhound
1 Experiment Twelve
1 Printlifter Ooze
1 Panoptic Projektor
1 Ransom Note
1 Ugin's Mastery
1 Austere Command
1 Dusk // Dawn
1 Exalted Angel
1 Fell the Mighty
1 Hidden Dragonslayer
1 Master of Pearls
1 Mastery of the Unseen
1 Mirror Entity
1 Welcoming Vampire
1 Akroma, Angel of Fury
1 Ashcloud Phoenix
1 Chaos Warp
1 Imperial Hellkite
1 Jeska's Will
1 Neheb, the Eternal
1 Scourge of the Throne
1 Beast Whisperer
1 Deathmist Raptor
1 Den Protector
1 Hooded Hydra
1 Krosan Cloudscraper
1 Krosan Colossus
1 Obscuring Aether
1 Ohran Frostfang
1 Return of the Wildspeaker
1 Root Elemental
1 Saryth, the Viper's Fang
1 Seedborn Muse
1 Temur War Shaman
1 Thelonite Hermit
1 Toski, Bearer of Secrets
1 Trail of Mystery
1 Whisperwood Elemental
1 Yedora, Grave Gardener
1 Decimate
1 Sidar Kondo of Jamuraa
1 Lifecrafter's Bestiary
1 Scroll of Fate
1 Canopy Vista
1 Cinder Glade
1 Exotic Orchard
1 Fortified Village
1 Furycalm Snarl
1 Game Trail
1 Kessig Wolf Run
1 Mossfire Valley
1 Mosswort Bridge
1 Scattered Groves
1 Sheltered Thicket
1 Shrine of the Forsaken Gods
1 Sungrass Prairie
1 Temple of Abandon
1 Temple of Plenty
1 Temple of Triumph
1 Path to Exile
1 Ainok Survivalist
1 Broodhatch Nantuko
1 Nervous Gardener
1 Nantuko Vigilante
1 Nature's Lore
1 Sakura-Tribe Elder
1 Salt Road Ambushers
1 Three Visits
1 Wild Growth
1 Arcane Signet
1 Sol Ring
1 Boros Garrison
1 Command Tower
1 Branch of Vitu-Ghazi
1 Gruul Turf
1 Jungle Shrine
1 Krosan Verge
1 Sacred Peaks
1 Selesnya Sanctuary
1 Temple of the False God
1 Zoetic Cavern
2 Plains
2 Plains
2 Mountain
1 Mountain
2 Forest
2 Forest
-96
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@@ -1,96 +0,0 @@
[metadata]
Name=Deep Clue Sea
[Commander]
1 Morska, Undersea Sleuth
[Main]
1 Sophia, Dogged Detective
1 Armed with Proof
1 Merchant of Truth
1 Serene Sleuth
1 Detective of the Month
1 Follow the Bodies
1 Tangletrove Kelp
1 Innocuous Researcher
1 On the Trail
1 Knowledge Is Power
1 Ransom Note
1 Aerial Extortionist
1 Bennie Bracks, Zoologist
1 Farewell
1 Fumigate
1 Organic Extinction
1 Search the Premises
1 Alandra, Sky Dreamer
1 Confirm Suspicions
1 Ethereal Investigator
1 Finale of Revelation
1 Kappa Cannoneer
1 Mechanized Production
1 Nadir Kraken
1 Shimmer Dragon
1 Teferi's Ageless Insight
1 Tezzeret, Betrayer of Flesh
1 Thought Monitor
1 Hornet Queen
1 Jolrael, Mwonvuli Recluse
1 Killer Service
1 Tireless Tracker
1 Adrix and Nev, Twincasters
1 Chulane, Teller of Tales
1 Disorder in the Court
1 Esix, Fractal Bloom
1 Hydroid Krasis
1 Koma, Cosmos Serpent
1 Lonis, Cryptozoologist
1 Selvala, Explorer Returned
1 Academy Manufactor
1 Idol of Oblivion
1 Inspiring Statuary
1 Nettlecyst
1 Psychosis Crawler
1 Canopy Vista
1 Exotic Orchard
1 Irrigated Farmland
1 Prairie Stream
1 Scattered Groves
1 Skycloud Expanse
1 Spire of Industry
1 Sungrass Prairie
1 Temple of Enlightenment
1 Temple of Mystery
1 Temple of Plenty
1 Swords to Plowshares
1 Erdwal Illuminator
1 Junk Winder
1 Ongoing Investigation
1 Whirler Rogue
1 Graf Mole
1 Ulvenwald Mysteries
1 Wilderness Reclamation
1 Wavesifter
1 Arcane Signet
1 Azorius Signet
1 Simic Signet
1 Sol Ring
1 Talisman of Curiosity
1 Talisman of Progress
1 Talisman of Unity
1 Azorius Chancery
1 Magnifying Glass
1 Command Tower
1 Krosan Verge
1 Lonely Sandbar
1 Path of Ancestry
1 Reliquary Tower
1 Seaside Citadel
1 Secluded Steppe
1 Selesnya Sanctuary
1 Simic Growth Chamber
1 Temple of the False God
1 Tranquil Thicket
2 Plains
1 Plains
3 Island
3 Island
3 Forest
2 Forest
-93
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@@ -1,93 +0,0 @@
[metadata]
Name=Desert Bloom
[Commander]
1 Yuma, Proud Protector
[Main]
1 Kirri, Talented Sprout
1 Scavenger Grounds
1 Sun Titan
1 Omnath, Locus of Rage
1 Descend upon the Sinful
1 Chromatic Lantern
1 Marshal's Anthem
1 Sheltered Thicket
1 Scute Swarm
1 Hour of Promise
1 Oracle of Mul Daya
1 Ramunap Excavator
1 Scattered Groves
1 World Shaper
1 Nesting Dragon
1 Turntimber Sower
1 Sevinne's Reclamation
1 Ancient Greenwarden
1 Titania, Protector of Argoth
1 Return of the Wildspeaker
1 Perennial Behemoth
1 Avenger of Zendikar
1 Hazezon, Shaper of Sand
1 Escape to the Wilds
1 Heaven // Earth
1 Genesis Hydra
1 Sunscorched Divide
1 The Mending of Dominaria
1 Decimate
1 Sand Scout
1 Embrace the Unknown
1 Dune Chanter
1 Cataclysmic Prospecting
1 Vengeful Regrowth
1 Angel of Indemnity
1 Cactus Preserve
1 Rumbleweed
1 Terramorphic Expanse
1 Evolving Wilds
1 Swiftfoot Boots
1 Explore
1 Sol Ring
1 Satyr Wayfinder
1 Perpetual Timepiece
1 Crawling Sensation
1 Painted Bluffs
1 Command Tower
1 Magmatic Insight
1 Krosan Verge
1 Desert of the True
1 Skullwinder
1 Desert of the Indomitable
1 Jungle Shrine
1 Bitter Reunion
1 Desert of the Fervent
1 Valorous Stance
1 Dunes of the Dead
1 Shefet Dunes
1 Hashep Oasis
1 Elvish Rejuvenator
1 Winding Way
1 Springbloom Druid
1 Arcane Signet
1 Unholy Heat
1 Thrilling Discovery
1 Electric Revelation
1 Eccentric Farmer
1 Harrow
1 Ramunap Ruins
1 Path to Exile
1 Requisition Raid
1 Bovine Intervention
1 Map the Frontier
1 Conduit Pylons
1 Mirage Mesa
1 Wreck and Rebuild
1 Angel of the Ruins
1 Bristling Backwoods
1 Creosote Heath
1 Abraded Bluffs
1 Scaretiller
1 Nantuko Cultivator
3 Plains
3 Plains
2 Mountain
2 Mountain
4 Forest
3 Forest
-98
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[metadata]
Name=Devour for Power
[Commander]
1 The Mimeoplasm
[Main]
1 Nezumi Graverobber // Nighteyes the Desecrator
1 Skullbriar, the Walking Grave
1 Riddlekeeper
1 Fleshbag Marauder
1 Eternal Witness
1 Troll Ascetic
1 Yavimaya Elder
1 Solemn Simulacrum
1 Brawn
1 Wonder
1 Sewer Nemesis
1 Gravedigger
1 Lhurgoyf
1 Dreamborn Muse
1 Mortivore
1 Desecrator Hag
1 Mulldrifter
1 Acidic Slime
1 Vulturous Zombie
1 Dark Hatchling
1 Extractor Demon
1 Scythe Specter
1 Wrexial, the Risen Deep
1 Vorosh, the Hunter
1 Triskelavus
1 Slipstream Eel
1 Butcher of Malakir
1 Patron of the Nezumi
1 Damia, Sage of Stone
1 Szadek, Lord of Secrets
1 Avatar of Woe
1 Artisan of Kozilek
1 Minds Aglow
1 Shared Trauma
1 Sign in Blood
1 Stitch Together
1 Cultivate
1 Windfall
1 Buried Alive
1 Syphon Mind
1 Unnerve
1 Rise from the Grave
1 Syphon Flesh
1 Living Death
1 Tribute to the Wild
1 Spell Crumple
1 Fact or Fiction
1 Relic Crush
1 Sol Ring
1 Dimir Signet
1 Golgari Signet
1 Lightning Greaves
1 Simic Signet
1 Oblivion Stone
1 Vow of Wildness
1 Vow of Flight
1 Vow of Malice
1 Memory Erosion
1 Grave Pact
1 Barren Moor
1 Command Tower
1 Dimir Aqueduct
1 Dreadship Reef
1 Golgari Rot Farm
1 Jwar Isle Refuge
1 Lonely Sandbar
1 Rupture Spire
1 Simic Growth Chamber
1 Svogthos, the Restless Tomb
1 Temple of the False God
1 Terramorphic Expanse
1 Tranquil Thicket
2 Forest
1 Forest
1 Forest
1 Forest
1 Forest
1 Forest
1 Forest
2 Island
1 Island
1 Island
1 Island
1 Island
1 Island
1 Island
2 Swamp
2 Swamp
2 Swamp
2 Swamp
1 Swamp
1 Swamp
1 Swamp
-89
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@@ -1,89 +0,0 @@
[metadata]
Name=Devour for Power
[Commander]
1 The Mimeoplasm
[Main]
1 Nezumi Graverobber // Nighteyes the Desecrator
1 Skullbriar, the Walking Grave
1 Riddlekeeper
1 Fleshbag Marauder
1 Eternal Witness
1 Troll Ascetic
1 Yavimaya Elder
1 Solemn Simulacrum
1 Brawn
1 Wonder
1 Sewer Nemesis
1 Gravedigger
1 Lhurgoyf
1 Dreamborn Muse
1 Mortivore
1 Desecrator Hag
1 Mulldrifter
1 Acidic Slime
1 Vulturous Zombie
1 Dark Hatchling
1 Extractor Demon
1 Scythe Specter
1 Wrexial, the Risen Deep
1 Vorosh, the Hunter
1 Triskelavus
1 Slipstream Eel
1 Butcher of Malakir
1 Patron of the Nezumi
1 Damia, Sage of Stone
1 Szadek, Lord of Secrets
1 Avatar of Woe
1 Artisan of Kozilek
1 Minds Aglow
1 Shared Trauma
1 Sign in Blood
1 Stitch Together
1 Cultivate
1 Windfall
1 Buried Alive
1 Syphon Mind
1 Unnerve
1 Rise from the Grave
1 Syphon Flesh
1 Living Death
1 Tribute to the Wild
1 Spell Crumple
1 Fact or Fiction
1 Relic Crush
1 Sol Ring
1 Dimir Signet
1 Golgari Signet
1 Lightning Greaves
1 Simic Signet
1 Oblivion Stone
1 Vow of Wildness
1 Vow of Flight
1 Vow of Malice
1 Memory Erosion
1 Grave Pact
1 Barren Moor
1 Command Tower
1 Dimir Aqueduct
1 Dreadship Reef
1 Golgari Rot Farm
1 Jwar Isle Refuge
1 Lonely Sandbar
1 Rupture Spire
1 Simic Growth Chamber
1 Svogthos, the Restless Tomb
1 Temple of the False God
1 Terramorphic Expanse
1 Tranquil Thicket
2 Forest
2 Forest
2 Forest
2 Forest
2 Island
2 Island
2 Island
2 Island
3 Swamp
3 Swamp
3 Swamp
2 Swamp
-82
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@@ -1,82 +0,0 @@
[metadata]
Name=Draconic Destruction
[Commander]
1 Atarka, World Render
[Main]
1 Akoum Hellkite
1 Chain Reaction
1 Crucible of Fire
1 Demanding Dragon
1 Dragonkin Berserker
1 Dragonmaster Outcast
1 Drakuseth, Maw of Flames
1 Dream Pillager
1 Flameblast Dragon
1 Hoard-Smelter Dragon
1 Magmaquake
1 Mordant Dragon
1 Runehorn Hellkite
1 Sarkhan, the Dragonspeaker
1 Scourge of Valkas
1 Spit Flame
1 Sweltering Suns
1 Thunderbreak Regent
1 Thundermaw Hellkite
1 Tyrant's Familiar
1 Verix Bladewing
1 Foe-Razer Regent
1 Frontier Siege
1 Hunter's Prowess
1 Primal Might
1 Shamanic Revelation
1 Clan Defiance
1 Harbinger of the Hunt
1 Dragon's Hoard
1 Steel Hellkite
1 Cinder Glade
1 Game Trail
1 Haven of the Spirit Dragon
1 Temple of Abandon
1 Dragon Mage
1 Dragon Tempest
1 Dragonlord's Servant
1 Dragonspeaker Shaman
1 Furnace Whelp
1 Provoke the Trolls
1 Rapacious Dragon
1 Unleash Fury
1 Vandalblast
1 Beast Within
1 Blossoming Defense
1 Cultivate
1 Drumhunter
1 Elemental Bond
1 Garruk's Uprising
1 Harmonize
1 Hunter's Insight
1 Loaming Shaman
1 Return to Nature
1 Sakura-Tribe Elder
1 Draconic Disciple
1 Fires of Yavimaya
1 Savage Ventmaw
1 Arcane Signet
1 Atarka Monument
1 Commander's Sphere
1 Sol Ring
1 Swiftfoot Boots
1 Talisman of Impulse
1 Command Tower
1 Kazandu Refuge
1 Path of Ancestry
1 Rugged Highlands
1 Shivan Oasis
1 Timber Gorge
5 Mountain
5 Mountain
4 Mountain
4 Mountain
3 Forest
3 Forest
3 Forest
3 Forest
-88
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@@ -1,88 +0,0 @@
[metadata]
Name=Draconic Dissent
[Commander]
1 Firkraag, Cunning Instigator
[Main]
1 Will Kenrith
1 Rowan Kenrith
1 Keiga, the Tide Star
1 Pursued Whale
1 Sly Instigator
1 Agitator Ant
1 Avatar of Slaughter
1 Brash Taunter
1 Chaos Dragon
1 Drakuseth, Maw of Flames
1 Geode Rager
1 Goblin Spymaster
1 Kazuul, Tyrant of the Cliffs
1 Ryusei, the Falling Star
1 Territorial Hellkite
1 Thunder Dragon
1 Vengeful Ancestor
1 Warmonger Hellkite
1 Niv-Mizzet, Parun
1 Solemn Simulacrum
1 Steel Hellkite
1 Stuffy Doll
1 Burnished Hart
1 Sprite Dragon
1 Aether Gale
1 Curse of the Swine
1 Blasphemous Act
1 Chain Reaction
1 Disrupt Decorum
1 Compulsive Research
1 Domineering Will
1 Reins of Power
1 Chaos Warp
1 Midnight Clock
1 Dragon's Hoard
1 Arcane Signet
1 Mind Stone
1 Wayfarer's Bauble
1 Bloodthirsty Blade
1 Fellwar Stone
1 Hedron Archive
1 Izzet Signet
1 Sol Ring
1 Talisman of Creativity
1 Dissipation Field
1 The Akroan War
1 Psychic Impetus
1 Shiny Impetus
1 Curse of Verbosity
1 Propaganda
1 Curse of Opulence
1 Castle Vantress
1 Desolate Lighthouse
1 Kher Keep
1 Temple of Epiphany
1 Wandering Fumarole
1 Command Tower
1 Ash Barrens
1 Izzet Boilerworks
1 Myriad Landscape
1 Path of Ancestry
1 Prismari Campus
1 Reliquary Tower
1 Temple of the False God
1 Terrain Generator
3 Island
3 Island
3 Island
3 Island
3 Mountain
3 Mountain
3 Mountain
3 Mountain
1 Baeloth Barrityl, Entertainer
1 Clan Crafter
1 Artificer Class
1 Astral Dragon
1 Mocking Doppelganger
1 Bothersome Quasit
1 Death Kiss
1 Loot Dispute
1 Spectacular Showdown
1 Angler Turtle
-101
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@@ -1,101 +0,0 @@
[metadata]
Name=Draconic Domination
[Commander]
1 The Ur-Dragon
[Main]
1 O-Kagachi, Vengeful Kami
1 Ramos, Dragon Engine
1 Scalelord Reckoner
1 Boneyard Scourge
1 Territorial Hellkite
1 Taigam, Ojutai Master
1 Wasitora, Nekoru Queen
1 Ryusei, the Falling Star
1 Scourge of Valkas
1 Utvara Hellkite
1 Sunscorch Regent
1 Deathbringer Regent
1 Hellkite Charger
1 Tyrant's Familiar
1 Atarka, World Render
1 Bladewing the Risen
1 Broodmate Dragon
1 Crosis, the Purger
1 Dromoka, the Eternal
1 Intet, the Dreamer
1 Kolaghan, the Storm's Fury
1 Niv-Mizzet, Dracogenius
1 Ojutai, Soul of Winter
1 Scion of the Ur-Dragon
1 Silumgar, the Drifting Death
1 Spellbound Dragon
1 Teneb, the Harvester
1 Steel Hellkite
1 Orator of Ojutai
1 Dragonlord's Servant
1 Dragonspeaker Shaman
1 Savage Ventmaw
1 Fortunate Few
1 Fractured Identity
1 Crux of Fate
1 Painful Truths
1 Earthquake
1 Cultivate
1 Farseek
1 Kodama's Reach
1 Rain of Thorns
1 Fist of Suns
1 Herald's Horn
1 Mirror of the Forebears
1 Armillary Sphere
1 Commander's Sphere
1 Darksteel Ingot
1 Dreamstone Hedron
1 Lightning Greaves
1 Nihil Spellbomb
1 Sol Ring
1 Wayfarer's Bauble
1 Kindred Discovery
1 Monastery Siege
1 Palace Siege
1 Crucible of Fire
1 Dragon Tempest
1 Frontier Siege
1 Curse of Verbosity
1 Curse of Opulence
1 Curse of Bounty
1 Elemental Bond
1 Crucible of the Spirit Dragon
1 Haven of the Spirit Dragon
2 Mountain
2 Mountain
2 Mountain
1 Swamp
1 Swamp
1 Swamp
1 Forest
1 Forest
1 Forest
1 Plains
1 Plains
1 Plains
1 Island
1 Island
1 Island
1 Path of Ancestry
1 Arcane Sanctum
1 Command Tower
1 Crumbling Necropolis
1 Frontier Bivouac
1 Jungle Shrine
1 Mystic Monastery
1 Nomad Outpost
1 Opulent Palace
1 Sandsteppe Citadel
1 Savage Lands
1 Seaside Citadel
1 Vivid Crag
1 Vivid Creek
1 Vivid Grove
1 Vivid Marsh
1 Vivid Meadow
-85
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@@ -1,85 +0,0 @@
[metadata]
Name=Draconic Rage
[Commander]
1 Vrondiss, Rage of Ancients
[Main]
1 Bogardan Hellkite
1 Demanding Dragon
1 Dragonmaster Outcast
1 Hoard-Smelter Dragon
1 Opportunistic Dragon
1 Scourge of Valkas
1 Shivan Hellkite
1 Skyline Despot
1 Skyship Stalker
1 Taurean Mauler
1 Terror of Mount Velus
1 Thunderbreak Regent
1 Chameleon Colossus
1 Atarka, World Render
1 Anger
1 Dragonlord's Servant
1 Savage Ventmaw
1 Dragonspeaker Shaman
1 Chain Reaction
1 Rishkar's Expertise
1 Shamanic Revelation
1 Rile
1 Cultivate
1 Explore
1 Rampant Growth
1 Magmaquake
1 Spit Flame
1 Decree of Savagery
1 Kindred Summons
1 Return of the Wildspeaker
1 Beast Within
1 Return to Nature
1 Dragon's Hoard
1 Arcane Signet
1 Commander's Sphere
1 Gruul Signet
1 Heirloom Blade
1 Sol Ring
1 Gratuitous Violence
1 Outpost Siege
1 Warstorm Surge
1 Colossal Majesty
1 Garruk's Uprising
1 Cinder Glade
1 Crucible of the Spirit Dragon
1 Exotic Orchard
1 Game Trail
1 Haven of the Spirit Dragon
1 Mossfire Valley
1 Mosswort Bridge
1 Command Tower
1 Desert
1 Gruul Turf
1 Path of Ancestry
3 Mountain
3 Mountain
3 Mountain
3 Mountain
4 Forest
4 Forest
4 Forest
3 Forest
1 Klauth, Unrivaled Ancient
1 Berserker's Frenzy
1 Chaos Dragon
1 Maddening Hex
1 Vengeful Ancestor
1 Bag of Tricks
1 Druid of Purification
1 Indomitable Might
1 Neverwinter Hydra
1 Wild Endeavor
1 Dragonborn Champion
1 Klauth's Will
1 Wulfgar of Icewind Dale
1 Barbarian Class
1 Earth-Cult Elemental
1 Component Pouch
1 Sword of Hours
1 Underdark Rift
-97
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@@ -1,97 +0,0 @@
[metadata]
Name=Dungeons of Death
[Commander]
1 Sefris of the Hidden Ways
[Main]
1 Cataclysmic Gearhulk
1 Eternal Dragon
1 Karmic Guide
1 Sun Titan
1 Sunblast Angel
1 Champion of Wits
1 Curator of Mysteries
1 Phantasmal Image
1 Doomed Necromancer
1 Ashen Rider
1 Baleful Strix
1 Hostage Taker
1 Solemn Simulacrum
1 Ronom Unicorn
1 Wall of Omens
1 Merfolk Looter
1 Mulldrifter
1 Murder of Crows
1 Plaguecrafter
1 Reassembling Skeleton
1 Shriekmaw
1 Cloudblazer
1 Necrotic Sliver
1 Obsessive Stitcher
1 Burnished Hart
1 Meteor Golem
1 Necromantic Selection
1 Unburial Rites
1 Victimize
1 Utter End
1 Swords to Plowshares
1 Forbidden Alchemy
1 Despark
1 Vanish into Memory
1 Arcane Signet
1 Commander's Sphere
1 Fellwar Stone
1 Sol Ring
1 Wayfarer's Bauble
1 Lightning Greaves
1 Propaganda
1 Choked Estuary
1 Darkwater Catacombs
1 Exotic Orchard
1 Geier Reach Sanitarium
1 High Market
1 Nimbus Maze
1 Port Town
1 Prairie Stream
1 Sunken Hollow
1 Evolving Wilds
1 Arcane Sanctum
1 Azorius Chancery
1 Command Tower
1 Dimir Aqueduct
1 Esper Panorama
1 Orzhov Basilica
1 Terramorphic Expanse
1 Thriving Heath
1 Thriving Isle
1 Thriving Moor
2 Plains
2 Plains
2 Plains
1 Plains
2 Island
1 Island
1 Island
1 Island
2 Swamp
2 Swamp
2 Swamp
1 Swamp
1 Nihiloor
1 Immovable Rod
1 Radiant Solar
1 Revivify
1 Thorough Investigation
1 Arcane Endeavor
1 Minn, Wily Illusionist
1 Phantom Steed
1 Rod of Absorption
1 Grave Endeavor
1 Wand of Orcus
1 Extract Brain
1 Midnight Pathlighter
1 Minimus Containment
1 Hama Pashar, Ruin Seeker
1 Dungeon Map
1 Bucknard's Everfull Purse
1 Clay Golem
1 Component Pouch
-104
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@@ -1,104 +0,0 @@
[metadata]
Name=Eldrazi Incursion
[Commander]
1 Ulalek, Fused Atrocity
[Main]
1 Azlask, the Swelling Scourge
1 Ulamog's Dreadsire
1 Benthic Anomaly
1 Eldritch Immunity
1 Selective Obliteration
1 Angelic Aberration
1 Bismuth Mindrender
1 Hideous Taskmaster
1 Twins of Discord
1 Mutated Cultist
1 Eldrazi Confluence
1 Spawnbed Protector
1 Chittering Dispatcher
1 Inversion Behemoth
1 Ugin, the Ineffable
1 Eldrazi Conscription
1 Cascading Cataracts
1 Eldrazi Monument
1 Sire of Stagnation
1 Shrine of the Forsaken Gods
1 Ugin's Insight
1 Drowner of Hope
1 Return of the Wildspeaker
1 Tendo Ice Bridge
1 Battlefield Forge
1 Llanowar Wastes
1 Brushland
1 Underground River
1 Oblivion Sower
1 Adarkar Wastes
1 Karplusan Forest
1 Yavimaya Coast
1 Sulfurous Springs
1 Caves of Koilos
1 Shivan Reef
1 Imprisoned in the Moon
1 Temple of Malady
1 Temple of Silence
1 Morophon, the Boundless
1 Kozilek's Return
1 World Breaker
1 Ruins of Oran-Rief
1 Sifter of Skulls
1 Endbringer
1 Corrupted Crossroads
1 Deepfathom Skulker
1 Vile Redeemer
1 Eldrazi Displacer
1 Mystic Forge
1 All Is Dust
1 Rishkar's Expertise
1 Awakening Zone
1 Eldrazi Temple
1 Elder Deep-Fiend
1 Bonders' Enclave
1 Exotic Orchard
1 Forsaken Monument
1 Snapping Voidcraw
1 Herald's Horn
1 Everflowing Chalice
1 Glaring Fleshraker
1 Wastescape Battlemage
1 Crib Swap
1 Titans' Vanguard
1 Talisman of Resilience
1 Hedron Archive
1 Spawning Bed
1 Ulamog's Nullifier
1 Twisted Landscape
1 Tranquil Landscape
1 Tectonic Edge
1 Reliquary Tower
1 Sol Ring
1 Artisan of Kozilek
1 Opal Palace
1 Dreamstone Hedron
1 Arcane Signet
1 Tomb of the Spirit Dragon
1 Secluded Courtyard
1 Idol of Oblivion
1 Wastes
1 Talisman of Curiosity
1 Talisman of Impulse
1 Warping Wail
1 Talisman of Dominance
1 Command Tower
1 Ash Barrens
1 Ancient Stirrings
1 Ulamog's Crusher
1 Garruk's Uprising
1 Suffer the Past
1 Skittering Invasion
1 Path of Ancestry
1 Unclaimed Territory
1 Plains
1 Island
1 Swamp
1 Mountain
1 Forest
@@ -1,104 +0,0 @@
[metadata]
Name=Eldrazi Incursion Collector's Edition
[Commander]
1 Ulalek, Fused Atrocity
[Main]
1 Azlask, the Swelling Scourge
1 Ulamog's Dreadsire
1 Benthic Anomaly
1 Eldritch Immunity
1 Selective Obliteration
1 Angelic Aberration
1 Bismuth Mindrender
1 Hideous Taskmaster
1 Twins of Discord
1 Mutated Cultist
1 Eldrazi Confluence
1 Spawnbed Protector
1 Chittering Dispatcher
1 Inversion Behemoth
1 Ugin, the Ineffable
1 Eldrazi Conscription
1 Cascading Cataracts
1 Eldrazi Monument
1 Sire of Stagnation
1 Shrine of the Forsaken Gods
1 Ugin's Insight
1 Drowner of Hope
1 Return of the Wildspeaker
1 Tendo Ice Bridge
1 Battlefield Forge
1 Llanowar Wastes
1 Brushland
1 Underground River
1 Oblivion Sower
1 Adarkar Wastes
1 Karplusan Forest
1 Yavimaya Coast
1 Sulfurous Springs
1 Caves of Koilos
1 Shivan Reef
1 Imprisoned in the Moon
1 Temple of Malady
1 Temple of Silence
1 Morophon, the Boundless
1 Kozilek's Return
1 World Breaker
1 Ruins of Oran-Rief
1 Sifter of Skulls
1 Endbringer
1 Corrupted Crossroads
1 Deepfathom Skulker
1 Vile Redeemer
1 Eldrazi Displacer
1 Mystic Forge
1 All Is Dust
1 Rishkar's Expertise
1 Awakening Zone
1 Eldrazi Temple
1 Elder Deep-Fiend
1 Bonders' Enclave
1 Exotic Orchard
1 Forsaken Monument
1 Snapping Voidcraw
1 Herald's Horn
1 Everflowing Chalice
1 Glaring Fleshraker
1 Wastescape Battlemage
1 Crib Swap
1 Titans' Vanguard
1 Talisman of Resilience
1 Hedron Archive
1 Spawning Bed
1 Ulamog's Nullifier
1 Twisted Landscape
1 Tranquil Landscape
1 Tectonic Edge
1 Reliquary Tower
1 Sol Ring
1 Artisan of Kozilek
1 Opal Palace
1 Dreamstone Hedron
1 Arcane Signet
1 Tomb of the Spirit Dragon
1 Secluded Courtyard
1 Idol of Oblivion
1 Wastes
1 Talisman of Curiosity
1 Talisman of Impulse
1 Warping Wail
1 Talisman of Dominance
1 Command Tower
1 Ash Barrens
1 Ancient Stirrings
1 Ulamog's Crusher
1 Garruk's Uprising
1 Suffer the Past
1 Skittering Invasion
1 Path of Ancestry
1 Unclaimed Territory
1 Plains
1 Island
1 Swamp
1 Mountain
1 Forest
+65 -66
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@@ -3,89 +3,88 @@ Name=Eldrazi Unbound
[Commander]
1 Zhulodok, Void Gorger
[Main]
1 Omarthis, Ghostfire Initiate
1 Kozilek, the Great Distortion
1 Abstruse Archaic
1 Calamity of the Titans
1 Desecrate Reality
1 Flayer of Loyalties
1 Rise of the Eldrazi
1 Skittering Cicada
1 Ugin's Mastery
1 Darksteel Monolith
1 All Is Dust
1 Endbringer
1 Endless One
1 It That Betrays
1 Matter Reshaper
1 Oblivion Sower
1 Ugin, the Ineffable
1 Ancient Stone Idol
1 Duplicant
1 Endless Atlas
1 Forsaken Monument
1 Hangarback Walker
1 Investigator's Journal
1 Kaldra Compleat
1 Mazemind Tome
1 Metalwork Colossus
1 Mirage Mirror
1 Myriad Construct
1 Mystic Forge
1 Perilous Vault
1 Phyrexian Triniform
1 Solemn Simulacrum
1 Soul of New Phyrexia
1 Steel Hellkite
1 Stonecoil Serpent
1 Transmogrifying Wand
1 Arcane Lighthouse
1 Arch of Orazca
1 Artisan of Kozilek
1 Bane of Bala Ged
1 Blast Zone
1 Bonders' Enclave
1 Burnished Hart
1 Calamity of the Titans
1 Crashing Drawbridge
1 Darksteel Monolith
1 Desecrate Reality
1 Dreamstone Hedron
1 Duplicant
1 Eldrazi Temple
1 Endbringer
1 Endless Atlas
1 Endless One
1 Everflowing Chalice
1 Fireshrieker
1 Flayer of Loyalties
1 Forge of Heroes
1 Forsaken Monument
1 Geier Reach Sanitarium
1 Geode Golem
1 Guildless Commons
1 Hangarback Walker
1 Hedron Archive
1 Investigator's Journal
1 It That Betrays
1 Kaldra Compleat
1 Kozilek, the Great Distortion
1 Lightning Greaves
1 Mage-Ring Network
1 Matter Reshaper
1 Mazemind Tome
1 Metalwork Colossus
1 Meteor Golem
1 Mind Stone
1 Mirage Mirror
1 Mirrorpool
1 Myriad Construct
1 Mystic Forge
1 Not of This World
1 Oblivion Sower
1 Omarthis, Ghostfire Initiate
1 Ornithopter of Paradise
1 Palladium Myr
1 Perilous Vault
1 Phyrexian Triniform
1 Reliquary Tower
1 Rise of the Eldrazi
1 Rogue's Passage
1 Ruins of Oran-Rief
1 Scaretiller
1 Scavenger Grounds
1 Sea Gate Wreckage
1 Shrine of the Forsaken Gods
1 Tyrite Sanctum
1 War Room
1 Burnished Hart
1 Geode Golem
1 Lightning Greaves
1 Meteor Golem
1 Skittering Cicada
1 Sol Ring
1 Solemn Simulacrum
1 Soul of New Phyrexia
1 Spatial Contortion
1 Steel Hellkite
1 Stonecoil Serpent
1 Suspicious Bookcase
1 Temple of the False God
1 Thought Vessel
1 Thran Dynamo
1 Unstable Obelisk
1 Reliquary Tower
1 Rogue's Passage
1 Artisan of Kozilek
1 Bane of Bala Ged
1 Not of This World
1 Spatial Contortion
1 Titan's Presence
1 Warping Wail
1 Crashing Drawbridge
1 Dreamstone Hedron
1 Everflowing Chalice
1 Fireshrieker
1 Hedron Archive
1 Mind Stone
1 Ornithopter of Paradise
1 Palladium Myr
1 Scaretiller
1 Suspicious Bookcase
1 Worn Powerstone
1 Arcane Lighthouse
1 Eldrazi Temple
1 Forge of Heroes
1 Guildless Commons
1 Mage-Ring Network
1 Temple of the False God
1 Tomb of the Spirit Dragon
1 Transmogrifying Wand
1 Tyrite Sanctum
1 Ugin's Mastery
1 Ugin, the Ineffable
1 Unstable Obelisk
1 Urza's Mine
1 Urza's Power Plant
1 Urza's Tower
8 Wastes
7 Wastes
1 War Room
1 Warping Wail
1 Worn Powerstone
15 Wastes
-82
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@@ -1,82 +0,0 @@
[metadata]
Name=Elven Council
[Commander]
1 Galadriel, Elven-Queen
[Main]
1 Gandalf, Westward Voyager
1 Raise the Palisade
1 Trap the Trespassers
1 Arwen, Weaver of Hope
1 Galadhrim Ambush
1 Haldir, Lórien Lieutenant
1 Legolas Greenleaf
1 Mirkwood Elk
1 Travel Through Caradhras
1 Windswift Slice
1 Círdan the Shipwright
1 Elrond of the White Council
1 Erestor of the Council
1 Mirkwood Trapper
1 Radagast, Wizard of Wilds
1 Sail into the West
1 Song of Eärendil
1 Lothlórien Blade
1 Model of Unity
1 Colossal Whale
1 Devastation Tide
1 Mystic Confluence
1 Plea for Power
1 Swan Song
1 Asceticism
1 Elvish Archdruid
1 Elvish Piper
1 Elvish Warmaster
1 Genesis Wave
1 Heroic Intervention
1 Hornet Queen
1 Inscription of Abundance
1 Overwhelming Stampede
1 Realm Seekers
1 Seeds of Renewal
1 Sylvan Offering
1 Exotic Orchard
1 Flooded Grove
1 Hinterland Harbor
1 Rejuvenating Springs
1 Vineglimmer Snarl
1 Lórien Revealed
1 Celeborn the Wise
1 Elven Farsight
1 Wose Pathfinder
1 Learn from the Past
1 Opt
1 Preordain
1 Arbor Elf
1 Beast Within
1 Cultivate
1 Elvish Mystic
1 Elvish Visionary
1 Farhaven Elf
1 Mirror of Galadriel
1 Lignify
1 Paradise Druid
1 Rampant Growth
1 Reclamation Sage
1 Wood Elves
1 Growth Spiral
1 Arcane Signet
1 Commander's Sphere
1 Lightning Greaves
1 Sol Ring
1 Whispersilk Cloak
1 Ash Barrens
1 Command Tower
1 Field of Ruin
1 Lonely Sandbar
1 Thornwood Falls
1 Tranquil Thicket
1 Woodland Stream
6 Island
5 Island
8 Forest
7 Forest
+32 -31
View File
@@ -4,38 +4,68 @@ Name=Elven Empire
1 Lathril, Blade of the Elves
[Main]
1 Abomination of Llanowar
1 Ambition's Cost
1 Arcane Signet
1 Beast Whisperer
1 Binding the Old Gods
1 Bounty of Skemfar
1 Canopy Tactician
1 Casualties of War
1 Command Tower
1 Crown of Skemfar
1 Cultivator of Blades
1 Dwynen, Gilt-Leaf Daen
1 Elderfang Ritualist
1 Elderfang Venom
1 Elven Ambush
1 Elvish Archdruid
1 Elvish Mystic
1 Elvish Promenade
1 Elvish Rejuvenator
1 End-Raze Forerunners
1 Eyeblight Cullers
1 Eyeblight Massacre
1 Farhaven Elf
1 Foul Orchard
1 Golgari Findbroker
1 Golgari Guildgate
1 Golgari Rot Farm
1 Harald, King of Skemfar
1 Harvest Season
1 Imperious Perfect
1 Jagged-Scar Archers
1 Jaspera Sentinel
1 Jungle Hollow
1 Llanowar Tribe
1 Lys Alana Huntmaster
1 Lys Alana Scarblade
1 Marwyn, the Nurturer
1 Masked Admirers
1 Miara, Thorn of the Glade
1 Moldervine Reclamation
1 Myriad Landscape
1 Nullmage Shepherd
1 Numa, Joraga Chieftain
1 Pact of the Serpent
1 Path of Ancestry
1 Poison the Cup
1 Poison-Tip Archer
1 Pride of the Perfect
1 Prowess of the Fair
1 Putrefy
1 Reclamation Sage
1 Return Upon the Tide
1 Rhys the Exiled
1 Roots of Wisdom
1 Ruthless Winnower
1 Serpent's Soul-Jar
1 Shaman of the Pack
1 Skemfar Elderhall
1 Skemfar Shadowsage
1 Sol Ring
1 Springbloom Druid
1 Sylvan Messenger
1 Tergrid's Shadow
1 Timberwatch Elf
1 Twinblade Assassins
1 Voice of Many
@@ -43,35 +73,6 @@ Name=Elven Empire
1 Wirewood Channeler
1 Wolverine Riders
1 Wood Elves
1 Elven Ambush
1 Poison the Cup
1 Putrefy
1 Tergrid's Shadow
1 Ambition's Cost
1 Bounty of Skemfar
1 Casualties of War
1 Eyeblight Massacre
1 Elvish Promenade
1 Harvest Season
1 Pact of the Serpent
1 Return Upon the Tide
1 Roots of Wisdom
1 Arcane Signet
1 Serpent's Soul-Jar
1 Sol Ring
1 Binding the Old Gods
1 Crown of Skemfar
1 Elderfang Venom
1 Pride of the Perfect
1 Prowess of the Fair
1 Moldervine Reclamation
1 Command Tower
16 Forest
1 Foul Orchard
1 Golgari Guildgate
1 Golgari Rot Farm
1 Jungle Hollow
1 Myriad Landscape
1 Path of Ancestry
1 Skemfar Elderhall
13 Swamp
14 Swamp
14 Forest
-91
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@@ -1,91 +0,0 @@
[metadata]
Name=Enduring Enchantments
[Commander]
1 Anikthea, Hand of Erebos
[Main]
1 Narci, Fable Singer
1 Battle at the Helvault
1 Boon of the Spirit Realm
1 Ondu Spiritdancer
1 Cacophony Unleashed
1 Demon of Fate's Design
1 Ghoulish Impetus
1 Composer of Spring
1 Nyxborn Behemoth
1 Archon of Sun's Grace
1 Felidar Retreat
1 Grasp of Fate
1 Heliod, God of the Sun
1 Mesa Enchantress
1 Sigil of the Empty Throne
1 Starfield Mystic
1 Starfield of Nyx
1 Cunning Rhetoric
1 Doomwake Giant
1 Dreadhorde Invasion
1 Erebos, Bleak-Hearted
1 Abundance
1 Arasta of the Endless Web
1 Courser of Kruphix
1 Dryad of the Ilysian Grove
1 Eidolon of Blossoms
1 Enchantress's Presence
1 Herald of the Pantheon
1 The Mending of Dominaria
1 Sanctum Weaver
1 Sandwurm Convergence
1 Setessan Champion
1 Verduran Enchantress
1 Battle for Bretagard
1 Calix, Destiny's Hand
1 Culling Ritual
1 Mirari's Wake
1 Sythis, Harvest's Hand
1 Canopy Vista
1 Exotic Orchard
1 Fortified Village
1 Necroblossom Snarl
1 Shineshadow Snarl
1 Sungrass Prairie
1 Temple of Malady
1 Temple of Plenty
1 Temple of Silence
1 Path to Exile
1 Extinguish All Hope
1 Kodama's Reach
1 Arcane Signet
1 Sol Ring
1 Ash Barrens
1 Command Tower
1 Cast Out
1 Love Song of Night and Day
1 Omen of the Sun
1 Spirited Companion
1 The Eldest Reborn
1 Mindwrack Harpy
1 The Binding of the Titans
1 Destiny Spinner
1 Farseek
1 Font of Fertility
1 Greater Tanuki
1 Khalni Heart Expedition
1 Nessian Wanderer
1 Omen of the Hunt
1 Rampant Growth
1 Binding the Old Gods
1 Jukai Naturalist
1 Nyx Weaver
1 Satyr Enchanter
1 Golgari Rot Farm
1 Krosan Verge
1 Orzhov Basilica
1 Sandsteppe Citadel
1 Selesnya Sanctuary
1 Tainted Field
1 Tainted Wood
3 Plains
3 Plains
3 Swamp
2 Swamp
4 Forest
4 Forest
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[metadata]
Name=Enhanced Evolution
[Commander]
1 Otrimi, the Ever-Playful
[Main]
1 Nissa, Steward of Elements
1 Zaxara, the Exemplary
1 Cazur, Ruthless Stalker
1 Ukkima, Stalking Shadow
1 Souvenir Snatcher
1 Tidal Barracuda
1 Boneyard Mycodrax
1 Mindleecher
1 Capricopian
1 Sawtusk Demolisher
1 Beast Whisperer
1 Genesis Hydra
1 Hungering Hydra
1 Masked Admirers
1 Predator Ooze
1 Vastwood Hydra
1 Vorapede
1 Cold-Eyed Selkie
1 Wydwen, the Biting Gale
1 Silent Arbiter
1 Archipelagore
1 Dreamtail Heron
1 Pouncing Shoreshark
1 Cavern Whisperer
1 Chittering Harvester
1 Insatiable Hemophage
1 Auspicious Starrix
1 Fertilid
1 Glowstone Recluse
1 Migratory Greathorn
1 Boneyard Lurker
1 Trumpeting Gnarr
1 Illusory Ambusher
1 Mulldrifter
1 Shriekmaw
1 Heroes' Bane
1 Reclamation Sage
1 Yavimaya Dryad
1 Trygon Predator
1 Dredge the Mire
1 Mind Spring
1 Deadly Tempest
1 Profane Command
1 Animist's Awakening
1 Find // Finality
1 Gaze of Granite
1 Villainous Wealth
1 Migration Path
1 Kodama's Reach
1 Deadly Rollick
1 Beast Within
1 Krosan Grip
1 Putrefy
1 Manascape Refractor
1 Lifecrafter's Bestiary
1 Bonder's Ornament
1 Arcane Signet
1 Sol Ring
1 Psychic Impetus
1 Parasitic Impetus
1 Predatory Impetus
1 Propaganda
1 Darkwater Catacombs
1 Endless Sands
1 Exotic Orchard
1 Llanowar Wastes
1 Sunken Hollow
1 Blighted Woodland
1 Command Tower
1 Dimir Aqueduct
1 Golgari Rot Farm
1 Mortuary Mire
1 Myriad Landscape
1 Opulent Palace
1 Rogue's Passage
1 Simic Growth Chamber
1 Soaring Seacliff
1 Temple of the False God
1 Dismal Backwater
1 Jungle Hollow
1 Thornwood Falls
2 Swamp
2 Swamp
1 Swamp
4 Forest
4 Forest
3 Forest
1 Island
1 Island
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[metadata]
Name=Entropic Uprising
[Commander]
1 Yidris, Maelstrom Wielder
[Main]
1 Satyr Wayfinder
1 Wall of Blossoms
1 Coiling Oracle
1 Thrasios, Triton Hero
1 Goblin Spymaster
1 Spellheart Chimera
1 Vial Smasher the Fierce
1 Academy Elite
1 Gamekeeper
1 Sangromancer
1 Bloodbraid Elf
1 Horizon Chimera
1 Kydele, Chosen of Kruphix
1 Glint-Eye Nephilim
1 Aeon Chronicler
1 Guiltfeeder
1 Consuming Aberration
1 Nath of the Gilt-Leaf
1 Runehorn Hellkite
1 Etherium-Horn Sorcerer
1 Dragon Mage
1 Blood Tyrant
1 Wheel of Fate
1 Windfall
1 Parting Thoughts
1 Far Wanderings
1 Past in Flames
1 Whispering Madness
1 Decimate
1 Devastation Tide
1 Reforge the Soul
1 Worm Harvest
1 Spelltwine
1 Whims of the Fates
1 Grave Upheaval
1 Cruel Entertainment
1 Ghastly Conscription
1 Volcanic Vision
1 Treasure Cruise
1 Treacherous Terrain
1 Army of the Damned
1 In Garruk's Wake
1 Chain of Vapor
1 Rakdos Charm
1 Chaos Warp
1 Ancient Excavation
1 Evacuation
1 Bituminous Blast
1 Curtains' Call
1 Sol Ring
1 Fellwar Stone
1 Rakdos Signet
1 Simic Signet
1 Chromatic Lantern
1 Commander's Sphere
1 Whispersilk Cloak
1 Boompile
1 Burgeoning
1 Waste Not
1 Frenzied Fugue
1 Ash Barrens
1 Command Tower
1 Crumbling Necropolis
1 Dismal Backwater
1 Evolving Wilds
1 Exotic Orchard
1 Frontier Bivouac
1 Jungle Hollow
1 Opulent Palace
1 Rakdos Carnarium
1 Reliquary Tower
1 Rugged Highlands
1 Rupture Spire
1 Savage Lands
1 Shadowblood Ridge
1 Simic Growth Chamber
1 Swiftwater Cliffs
1 Terramorphic Expanse
1 Thornwood Falls
2 Island
2 Island
1 Island
2 Swamp
2 Swamp
1 Swamp
2 Mountain
2 Mountain
1 Mountain
2 Forest
2 Forest
1 Forest
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[metadata]
Name=Eternal Bargain
[Commander]
1 Oloro, Ageless Ascetic
[Main]
1 Ajani's Pridemate
1 Augury Adept
1 Azorius Herald
1 Disciple of Griselbrand
1 Diviner Spirit
1 Divinity of Pride
1 Filigree Angel
1 Hooded Horror
1 Kongming, "Sleeping Dragon"
1 Marrow Bats
1 Myr Battlesphere
1 Phyrexian Delver
1 Phyrexian Gargantua
1 Raven Familiar
1 Razor Hippogriff
1 Serene Master
1 Serra Avatar
1 Sharding Sphinx
1 Sharuum the Hegemon
1 Sphinx of the Steel Wind
1 Stormscape Battlemage
1 Sydri, Galvanic Genius
1 Tidal Force
1 Tidehollow Strix
1 Tower Gargoyle
1 Vizkopa Guildmage
1 Wall of Reverence
1 Brilliant Plan
1 Death Grasp
1 Deep Analysis
1 Famine
1 Order of Succession
1 Survival Cache
1 Tempt with Immortality
1 Toxic Deluge
1 Dromar's Charm
1 Lim-Dûl's Vault
1 Reckless Spite
1 Spinal Embrace
1 Crawlspace
1 Nevinyrral's Disk
1 Nihil Spellbomb
1 Obelisk of Esper
1 Pristine Talisman
1 Sol Ring
1 Sun Droplet
1 Swiftfoot Boots
1 Thopter Foundry
1 Well of Lost Dreams
1 Act of Authority
1 Cradle of Vitality
1 Curse of Inertia
1 Curse of Shallow Graves
1 Curse of the Forsaken
1 Darksteel Mutation
1 Greed
1 Phyrexian Reclamation
1 Sanguine Bond
1 Arcane Sanctum
1 Azorius Chancery
1 Azorius Guildgate
1 Barren Moor
1 Command Tower
1 Dimir Guildgate
1 Esper Panorama
1 Evolving Wilds
2 Island
2 Island
1 Island
1 Island
1 Jwar Isle Refuge
1 Lonely Sandbar
1 Opal Palace
1 Orzhov Basilica
1 Orzhov Guildgate
3 Plains
2 Plains
2 Plains
2 Plains
1 Rupture Spire
1 Springjack Pasture
3 Swamp
2 Swamp
2 Swamp
2 Swamp
1 Temple of the False God
1 Transguild Promenade
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[metadata]
Name=Eternal Might
[Commander]
1 Temmet, Naktamun's Will
[Main]
1 Hashaton, Scarab's Fist
1 On Wings of Gold
1 Priest of the Crossing
1 Renewed Solidarity
1 Wizened Mentor
1 Prophet of the Scarab
1 Rhet-Tomb Mystic
1 Lost Monarch of Ifnir
1 Accursed Duneyard
1 Commence the Endgame
1 Cryptbreaker
1 Grave Titan
1 Gravecrawler
1 Midnight Reaper
1 Murderous Rider // Swift End
1 Zombie Master
1 Angel of Sanctions
1 Dusk // Dawn
1 God-Eternal Oketra
1 Timeless Dragon
1 Champion of Wits
1 Forgotten Creation
1 Pull from Tomorrow
1 Vizier of Many Faces
1 Archfiend of Ifnir
1 Cemetery Reaper
1 Crowded Crypt
1 Damn
1 Dread Summons
1 Dreadhorde Invasion
1 Liliana, Death's Majesty
1 Never // Return
1 Plague Belcher
1 Rot Hulk
1 The Scarab God
1 God-Pharaoh's Gift
1 Maskwood Nexus
1 Adarkar Wastes
1 Caves of Koilos
1 Drowned Catacomb
1 Exotic Orchard
1 Fetid Pools
1 Glacial Fortress
1 Irrigated Farmland
1 Isolated Chapel
1 Prairie Stream
1 Sunken Hollow
1 Temple of Deceit
1 Temple of Silence
1 Underground River
1 Unholy Grotto
1 Swords to Plowshares
1 Corpse Augur
1 Corpse Knight
1 Arcane Signet
1 Sol Ring
1 Command Tower
1 Path of Ancestry
1 Binding Mummy
1 Cast Out
1 Eternal Skylord
1 Fleshbag Marauder
1 Gempalm Polluter
1 Lord of the Accursed
1 Twisted Abomination
1 Undead Augur
1 Despark
1 Gleaming Overseer
1 Lazotep Chancellor
1 Wayward Servant
1 Bontu's Monument
1 Commander's Sphere
1 Dimir Signet
1 Gate to the Afterlife
1 Orzhov Signet
1 Talisman of Dominance
1 Talisman of Hierarchy
1 Arcane Sanctum
1 Ash Barrens
1 Desert of the Glorified
1 Desert of the Mindful
1 Desert of the True
1 Evolving Wilds
1 Orzhov Basilica
1 Terramorphic Expanse
5 Plains
4 Island
5 Swamp
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[metadata]
Name=Evasive Maneuvers
[Commander]
1 Derevi, Empyrial Tactician
[Main]
1 Acidic Slime
1 Aerie Mystics
1 Angel of Finality
1 Azami, Lady of Scrolls
1 Bane of Progress
1 Deceiver Exarch
1 Diviner Spirit
1 Djinn of Infinite Deceits
1 Dungeon Geists
1 Farhaven Elf
1 Fiend Hunter
1 Flickerwisp
1 Hada Spy Patrol
1 Karmic Guide
1 Kazandu Tuskcaller
1 Lu Xun, Scholar General
1 Mirror Entity
1 Mistmeadow Witch
1 Murkfiend Liege
1 Phantom Nantuko
1 Pilgrim's Eye
1 Roon of the Hidden Realm
1 Rubinia Soulsinger
1 Selesnya Guildmage
1 Skyward Eye Prophets
1 Stonecloaker
1 Thornwind Faeries
1 Winged Coatl
1 Wonder
1 Borrowing 100,000 Arrows
1 Kirtar's Wrath
1 Restore
1 Tempt with Glory
1 Wash Out
1 Aethermage's Touch
1 Arcane Denial
1 Blue Sun's Zenith
1 Krosan Grip
1 Selesnya Charm
1 Unexpectedly Absent
1 Azorius Keyrune
1 Basalt Monolith
1 Conjurer's Closet
1 Darksteel Ingot
1 Leonin Bladetrap
1 Selesnya Signet
1 Simic Signet
1 Sol Ring
1 Surveyor's Scope
1 Swiftfoot Boots
1 Sword of the Paruns
1 Thousand-Year Elixir
1 Thunderstaff
1 Control Magic
1 Curse of Inertia
1 Curse of Predation
1 Curse of the Forsaken
1 Darksteel Mutation
1 Flickerform
1 Leafdrake Roost
1 Presence of Gond
1 Azorius Chancery
1 Azorius Guildgate
1 Bant Panorama
1 Command Tower
1 Evolving Wilds
1 Faerie Conclave
2 Forest
2 Forest
1 Forest
1 Forest
2 Island
2 Island
2 Island
1 Island
1 Opal Palace
2 Plains
2 Plains
2 Plains
1 Plains
1 Rupture Spire
1 Saltcrusted Steppe
1 Seaside Citadel
1 Secluded Steppe
1 Sejiri Refuge
1 Selesnya Guildgate
1 Selesnya Sanctuary
1 Simic Guildgate
1 Temple of the False God
1 Terramorphic Expanse
1 Transguild Promenade
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[metadata]
Name=Evasive Maneuvers
[Commander]
1 Derevi, Empyrial Tactician
[Main]
1 Acidic Slime
1 Aerie Mystics
1 Angel of Finality
1 Azami, Lady of Scrolls
1 Bane of Progress
1 Deceiver Exarch
1 Diviner Spirit
1 Djinn of Infinite Deceits
1 Dungeon Geists
1 Farhaven Elf
1 Fiend Hunter
1 Flickerwisp
1 Hada Spy Patrol
1 Karmic Guide
1 Kazandu Tuskcaller
1 Lu Xun, Scholar General
1 Mirror Entity
1 Mistmeadow Witch
1 Murkfiend Liege
1 Phantom Nantuko
1 Pilgrim's Eye
1 Roon of the Hidden Realm
1 Rubinia Soulsinger
1 Selesnya Guildmage
1 Skyward Eye Prophets
1 Stonecloaker
1 Thornwind Faeries
1 Winged Coatl
1 Wonder
1 Borrowing 100,000 Arrows
1 Kirtar's Wrath
1 Restore
1 Tempt with Glory
1 Wash Out
1 Aethermage's Touch
1 Arcane Denial
1 Blue Sun's Zenith
1 Krosan Grip
1 Selesnya Charm
1 Unexpectedly Absent
1 Azorius Keyrune
1 Basalt Monolith
1 Conjurer's Closet
1 Darksteel Ingot
1 Leonin Bladetrap
1 Selesnya Signet
1 Simic Signet
1 Sol Ring
1 Surveyor's Scope
1 Swiftfoot Boots
1 Sword of the Paruns
1 Thousand-Year Elixir
1 Thunderstaff
1 Control Magic
1 Curse of Inertia
1 Curse of Predation
1 Curse of the Forsaken
1 Darksteel Mutation
1 Flickerform
1 Leafdrake Roost
1 Presence of Gond
1 Azorius Chancery
1 Azorius Guildgate
1 Bant Panorama
1 Command Tower
1 Evolving Wilds
1 Faerie Conclave
1 Forest
1 Forest
1 Forest
1 Forest
1 Forest
1 Forest
2 Island
2 Island
2 Island
1 Island
1 Opal Palace
1 Plains
1 Plains
1 Plains
1 Plains
1 Plains
1 Plains
1 Plains
1 Rupture Spire
1 Saltcrusted Steppe
1 Seaside Citadel
1 Secluded Steppe
1 Sejiri Refuge
1 Selesnya Guildgate
1 Selesnya Sanctuary
1 Simic Guildgate
1 Temple of the False God
1 Terramorphic Expanse
1 Transguild Promenade
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