67 lines
3.8 KiB
Python
67 lines
3.8 KiB
Python
"""
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Commander AI Lab — Coach Configuration
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═══════════════════════════════════════
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Central config for Ollama, embeddings, and coach service paths.
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All paths are relative to the commander-ai-lab root directory.
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"""
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import os
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from pathlib import Path
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# ── Base Paths ──────────────────────────────────────────────
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# Resolve relative to wherever the lab is installed
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LAB_ROOT = Path(os.environ.get("COMMANDER_LAB_ROOT", Path(__file__).parent.parent))
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# ── Ollama (OpenAI-compatible API) ──────────────────────
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LLM_URL = os.environ.get("LLM_URL", "http://192.168.0.240:11434/v1")
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LLM_MODEL = os.environ.get("LLM_MODEL", "gpt-oss:20b")
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LLM_TIMEOUT = int(os.environ.get("LLM_TIMEOUT", "360")) # seconds
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LLM_MAX_RETRIES = 3
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# ── Embeddings ─────────────────────────────────────────────
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EMBEDDINGS_DIR = LAB_ROOT / "data"
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EMBEDDINGS_NPZ = EMBEDDINGS_DIR / "mtg-embeddings.npz"
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EMBEDDINGS_PARQUET = EMBEDDINGS_DIR / "mtg-embeddings.parquet"
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# ── Deck Reports ───────────────────────────────────────────
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DECK_REPORTS_DIR = LAB_ROOT / "deck-reports"
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COACH_SESSIONS_DIR = LAB_ROOT / "coach-sessions"
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# ── Prompt Limits ──────────────────────────────────────────
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MAX_PROMPT_TOKENS = 2048
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MAX_CANDIDATES_PER_UNDERPERFORMER = 5
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MAX_UNDERPERFORMERS = 4
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UNDERPERFORMER_IMPACT_THRESHOLD = -0.05 # impactScore below this = underperformer
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# ── LLM Generation Settings (Coach — Ollama) ──────────────
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DEFAULT_TEMPERATURE = 0.7
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# DeepSeek-R1 uses <think> reasoning tokens before the JSON output,
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# so we need a generous limit to avoid truncation
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DEFAULT_MAX_TOKENS = 8192
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# ── Perplexity Deck Generation Settings ───────────────────────
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# Provider for deck generation: "perplexity" (V3) or "local" (V2 collection-based)
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DECK_GEN_PROVIDER = os.environ.get("DECK_GEN_PROVIDER", "local")
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# Model for deck generation (sonar = fast/$0.004, sonar-pro = deep/$0.04)
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DECK_GEN_MODEL = os.environ.get("DECK_GEN_MODEL", "gpt-oss:20b")
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DECK_GEN_BASE_URL = os.environ.get("DECK_GEN_BASE_URL", "http://192.168.0.240:11434/v1")
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DECK_GEN_TEMPERATURE = float(os.environ.get("DECK_GEN_TEMPERATURE", "0.2"))
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DECK_GEN_MAX_TOKENS = int(os.environ.get("DECK_GEN_MAX_TOKENS", "16384"))
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# ── Smart Substitution Settings ───────────────────────────────
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# Minimum embedding similarity to accept a substitute without Perplexity fallback
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SUBSTITUTION_MIN_SIMILARITY = float(os.environ.get("SUBSTITUTION_MIN_SIMILARITY", "0.75"))
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# Maximum number of alternatives to suggest per missing card
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SUBSTITUTION_MAX_ALTERNATIVES = int(os.environ.get("SUBSTITUTION_MAX_ALTERNATIVES", "5"))
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# Model for substitution fallback (sonar is fine — small focused queries)
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SUBSTITUTION_MODEL = os.environ.get("SUBSTITUTION_MODEL", "gpt-oss:20b")
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# Enable Perplexity fallback for low-confidence embedding matches
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SUBSTITUTION_USE_PPLX_FALLBACK = os.environ.get("SUBSTITUTION_USE_PPLX_FALLBACK", "true").lower() == "true"
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# ── Ensure directories exist ───────────────────────────────
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def ensure_dirs():
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"""Create required directories if they don't exist."""
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EMBEDDINGS_DIR.mkdir(parents=True, exist_ok=True)
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DECK_REPORTS_DIR.mkdir(parents=True, exist_ok=True)
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COACH_SESSIONS_DIR.mkdir(parents=True, exist_ok=True)
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