Claude Code
ea2cac6597
The hardcoded 192.168.0.240 IP was a developer-specific LAN address that breaks out-of-the-box for anyone running Ollama locally or via WSL2 on Windows. Switch every default and docstring reference to localhost so the project works without manual configuration. Files changed: - coach/config.py: LLM_URL and DECK_GEN_BASE_URL defaults - ui/simulator.html: API endpoint input value and placeholder - lab_api.py: remove LAN IP from default CORS origins - routes/coach.py: warning message text - src/commander_ai_lab/sim/deepseek_brain.py: docstrings - src/commander_ai_lab/sim/deepseek_engine.py: docstring example - src/commander_ai_lab/sim/validator_brain.py: docstring example Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
67 lines
3.8 KiB
Python
67 lines
3.8 KiB
Python
"""
|
|
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.
|
|
"""
|
|
|
|
import os
|
|
from pathlib import Path
|
|
|
|
# ── 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")
|
|
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_DIR = LAB_ROOT / "data"
|
|
EMBEDDINGS_NPZ = EMBEDDINGS_DIR / "mtg-embeddings.npz"
|
|
EMBEDDINGS_PARQUET = EMBEDDINGS_DIR / "mtg-embeddings.parquet"
|
|
|
|
# ── Deck Reports ───────────────────────────────────────────
|
|
DECK_REPORTS_DIR = LAB_ROOT / "deck-reports"
|
|
COACH_SESSIONS_DIR = LAB_ROOT / "coach-sessions"
|
|
|
|
# ── Prompt Limits ──────────────────────────────────────────
|
|
MAX_PROMPT_TOKENS = 2048
|
|
MAX_CANDIDATES_PER_UNDERPERFORMER = 5
|
|
MAX_UNDERPERFORMERS = 4
|
|
UNDERPERFORMER_IMPACT_THRESHOLD = -0.05 # impactScore below this = underperformer
|
|
|
|
# ── LLM Generation Settings (Coach — Ollama) ──────────────
|
|
DEFAULT_TEMPERATURE = 0.7
|
|
# DeepSeek-R1 uses <think> reasoning tokens before the JSON output,
|
|
# so we need a generous limit to avoid truncation
|
|
DEFAULT_MAX_TOKENS = 8192
|
|
|
|
# ── 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://localhost: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 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 (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 ───────────────────────────────
|
|
def ensure_dirs():
|
|
"""Create required directories if they don't exist."""
|
|
EMBEDDINGS_DIR.mkdir(parents=True, exist_ok=True)
|
|
DECK_REPORTS_DIR.mkdir(parents=True, exist_ok=True)
|
|
COACH_SESSIONS_DIR.mkdir(parents=True, exist_ok=True)
|