feat: replace Perplexity config with Anthropic Claude settings (#105)

coach/config.py

@@ -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.
 """
@@ -8,58 +8,60 @@ All paths are relative to the commander-ai-lab root directory.
 import os
 from pathlib import Path
 
-# ── Base Paths ────────────────────────────────────────────
+# ── Base Paths ───────────────────────────────────────────────────────
 LAB_ROOT = Path(os.environ.get("COMMANDER_LAB_ROOT", Path(__file__).parent.parent))
 
-# ── Ollama (OpenAI-compatible API) ──────────────────────
+# ── 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 ───────────────────────────────────────────────────
 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 = 5
 MAX_UNDERPERFORMERS = 4
 UNDERPERFORMER_IMPACT_THRESHOLD = -0.05  # impactScore below this = underperformer
 
-# ── LLM Generation Settings (Coach — Ollama fallback) ────────────
+# ── LLM Generation Settings (Coach — Ollama fallback) ─────────────
 DEFAULT_TEMPERATURE = 0.7
 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", "perplexity")
-# Model used when DECK_GEN_PROVIDER="perplexity" (sonar = fast, sonar-pro = deep)
-DECK_GEN_MODEL = os.environ.get("DECK_GEN_MODEL", "sonar-pro")
-# Perplexity cloud model (sonar / sonar-pro / sonar-deep-research)
-PPLX_MODEL = os.environ.get("PPLX_MODEL", "sonar-pro")
-# Coach chat provider: "perplexity" (Perplexity API) or "local" (Ollama)
-COACH_PROVIDER = os.environ.get("COACH_PROVIDER", "perplexity")
+# ── 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-4-0-20250514")
+# 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-4-0-20250514")
+# 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")
 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
+# ── Smart Substitution Settings ───────────────────────────────────
+# Minimum embedding similarity to accept a substitute without Anthropic 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", "sonar")
-# Enable Perplexity fallback for low-confidence embedding matches
-SUBSTITUTION_USE_PPLX_FALLBACK = os.environ.get("SUBSTITUTION_USE_PPLX_FALLBACK", "true").lower() == "true"
+# 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"
 
-# ── 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)