Files
commander-ai-lab/routes/coach.py
T

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25 KiB
Python

"""
routes/coach.py
===============
LLM-powered deck coaching endpoints:
GET /api/coach/status
GET /api/coach/decks
GET /api/coach/decks/{deck_id}/report
POST /api/coach/decks/{deck_id}
GET /api/coach/sessions
GET /api/coach/sessions/{session_id}
POST /api/coach/embeddings/download
GET /api/coach/embeddings/search
POST /api/coach/chat
POST /api/coach/apply
GET /api/coach/cards-like
POST /api/coach/reports/generate
Globals:
_coach_service, _coach_embeddings, _coach_llm
_deck_gen_v3, _deck_gen_v3_error
init_coach_service(), _build_deck_report_from_db()
"""
from __future__ import annotations
import json
import os
import time
import traceback
from pathlib import Path
from typing import Optional
from fastapi import APIRouter, HTTPException
from fastapi.responses import StreamingResponse
from models.requests import CoachRequestBody, CoachChatMessage, CoachChatRequest, CoachApplyRequest, CoachGoalsRequest
from routes.shared import (
CFG,
log_coach, log_deckgen,
_get_db_conn,
_compute_deck_analysis,
)
router = APIRouter(tags=["coach"])
# ══════════════════════════════════════════════════════════════
# Coach Service (LLM-powered deck coaching)
# ══════════════════════════════════════════════════════════════
# Global coach instances (initialized at startup)
_coach_service = None
_coach_embeddings = None
_coach_llm = None
_deck_gen_v3 = None # V3 Deck Generator (Perplexity structured output)
_deck_gen_v3_error = None # Error message if V3 init failed
def init_coach_service():
"""Initialize the coach service with LLM client and embeddings."""
global _coach_service, _coach_embeddings, _coach_llm, _deck_gen_v3, _deck_gen_v3_error
try:
from coach.llm_client import LLMClient
from coach.embeddings import MTGEmbeddingIndex
from coach.coach_service import CoachService
from coach.config import ensure_dirs
ensure_dirs()
_coach_llm = LLMClient()
_coach_embeddings = MTGEmbeddingIndex()
# Try to load embeddings (non-blocking — download happens on first use)
try:
from coach.config import EMBEDDINGS_NPZ
if EMBEDDINGS_NPZ.exists():
_coach_embeddings.load()
log_coach.info(f" Coach: Embeddings loaded ({_coach_embeddings.card_count} cards)")
else:
log_coach.warning(" Coach: Embeddings not yet downloaded (will download on first use)")
except Exception as e:
log_coach.error(f" Coach: Embeddings load failed: {e}")
_coach_service = CoachService(_coach_llm, _coach_embeddings)
# Check LLM connection
llm_status = _coach_llm.check_connection()
if llm_status.get("connected"):
log_coach.info(f" Coach LLM: Connected ({llm_status.get('active_model', 'unknown')})")
else:
log_coach.warning(f" Coach LLM: Not connected (start Ollama on 192.168.0.240:11434)")
# Initialize V3 Deck Generator (Ollama-based)
_deck_gen_v3_error = None
try:
from src.commander_ai_lab.deck_builder.adapter import DeckBuilderAdapter
_deck_gen_v3 = DeckBuilderAdapter(
db_conn_factory=_get_db_conn,
model="gpt-oss:20b",
)
log_deckgen.info(" Deck Gen V3: Initialized (Ollama DeckBuilderAdapter)")
except ImportError as e:
_deck_gen_v3_error = f"Missing dependency: {e}"
log_deckgen.error(f" Deck Gen V3: {_deck_gen_v3_error}")
_deck_gen_v3 = None
except Exception as e:
_deck_gen_v3_error = str(e)
log_deckgen.error(f" Deck Gen V3: Failed to initialize: {e}")
_deck_gen_v3 = None
except Exception as e:
log_coach.error(f" Coach: Failed to initialize: {e}\n{traceback.format_exc()}")
_coach_service = None
@router.get("/api/coach/status")
async def coach_status():
"""Check coach subsystem health."""
if _coach_service is None:
return {"llmConnected": False, "embeddingsLoaded": False,
"embeddingCards": 0, "deckReportsAvailable": 0,
"error": "Coach service not initialized"}
status = _coach_service.get_status()
return status.model_dump()
@router.get("/api/coach/decks")
async def coach_list_decks():
"""List all decks available for coaching (from deck builder DB)."""
conn = _get_db_conn()
rows = conn.execute(
"""SELECT d.id as deck_id, d.name as deck_name, d.commander_name,
COUNT(dc.id) as card_count
FROM decks d
LEFT JOIN deck_cards dc ON dc.deck_id = d.id
GROUP BY d.id
ORDER BY d.name"""
).fetchall()
# Also get report availability from coach service
report_ids = set()
if _coach_service:
report_ids = set(_coach_service.list_deck_reports())
decks = []
for r in rows:
deck_name = r["deck_name"]
# Check if a report exists (by deck name slug match)
has_report = any(
deck_name.lower().replace(" ", "-") == rid.lower() or
deck_name.lower() == rid.lower()
for rid in report_ids
)
decks.append({
"deck_id": r["deck_id"],
"deck_name": r["deck_name"],
"commander": r["commander_name"] or "",
"card_count": r["card_count"],
"has_report": has_report,
"report_count": 1 if has_report else 0,
"last_report_date": None,
})
return decks
@router.get("/api/coach/decks/{deck_id}/report")
async def coach_get_report(deck_id: str):
"""Get the latest DeckReport for a deck."""
if _coach_service is None:
raise HTTPException(500, "Coach service not initialized")
report = _coach_service.load_deck_report(deck_id)
if report is None:
raise HTTPException(404, f"Deck report not found: {deck_id}")
return report.model_dump()
@router.post("/api/coach/decks/{deck_id}")
async def coach_run_session(deck_id: str, body: CoachRequestBody = None):
"""Trigger a coaching session for a deck."""
if _coach_service is None:
raise HTTPException(500, "Coach service not initialized")
# Load embeddings on first use if not loaded
if _coach_embeddings and not _coach_embeddings.loaded:
try:
_coach_embeddings.load(force_download=True)
except Exception as e:
log_coach.error(f" Coach: Embeddings download failed: {e}")
goals = None
if body and body.goals:
from coach.models import CoachGoals
try:
goals = CoachGoals(**body.goals)
except Exception:
goals = None
# Build a fallback DeckReport from the DB if no simulation report exists
fallback_report = None
try:
fallback_report = _build_deck_report_from_db(deck_id)
except Exception as e:
log_coach.error(f" Coach: Fallback report build failed for '{deck_id}': {e}")
try:
session = await _coach_service.run_coaching_session(deck_id, goals, fallback_report=fallback_report)
return session.model_dump()
except ValueError as e:
raise HTTPException(404, str(e))
except ConnectionError as e:
raise HTTPException(503, f"LLM connection failed: {e}")
except Exception as e:
raise HTTPException(500, f"Coach session failed: {e}")
def _build_deck_report_from_db(deck_slug: str):
"""
Build a lightweight DeckReport from the deck builder DB when no
simulation report exists. Allows the coach to analyze deck composition
even without simulation data.
"""
from coach.models import DeckReport, CardPerformance, DeckStructure
conn = _get_db_conn()
# --- Input validation ---
import re
if not deck_slug or len(deck_slug) > 200:
return None
deck_slug = re.sub(r'[^a-zA-Z0-9 _-]', '', deck_slug)
if not deck_slug:
return None
# Find the deck by parameterized query instead of full-table scan
slug_lower = deck_slug.lower()
slug_hyphenated = slug_lower.replace(' ', '-')
clean_slug = re.sub(r'[^a-z0-9]+', '-', slug_lower).strip('-')
if slug_lower.isdigit():
# Numeric slug -- match by ID directly
matched_deck = conn.execute(
"SELECT id, name, commander_name, color_identity FROM decks WHERE id = ?",
(int(slug_lower),)
).fetchone()
else:
# Try exact name match, hyphenated match, or clean-slug match
matched_deck = conn.execute(
"""SELECT id, name, commander_name, color_identity FROM decks
WHERE LOWER(name) = ?
OR LOWER(REPLACE(name, ' ', '-')) = ?
OR LOWER(REPLACE(name, ' ', '-')) = ?
LIMIT 1""",
(slug_lower, slug_hyphenated, clean_slug)
).fetchone()
if matched_deck is None:
return None
deck_id = matched_deck["id"]
deck_name = matched_deck["name"]
commander = matched_deck["commander_name"] or ""
# Parse color identity
ci_raw = matched_deck["color_identity"] or "[]"
try:
color_identity = json.loads(ci_raw) if isinstance(ci_raw, str) else ci_raw
except Exception:
color_identity = []
# Load all cards in this deck
card_rows = conn.execute(
"""SELECT dc.card_name, dc.quantity, dc.is_commander, dc.role_tag,
ce.type_line, ce.cmc, ce.oracle_text
FROM deck_cards dc
LEFT JOIN collection_entries ce ON LOWER(dc.card_name) = LOWER(ce.name)
WHERE dc.deck_id = ?""",
(deck_id,)
).fetchall()
cards = []
type_counts = {}
cmc_buckets = [0] * 8
land_count = 0
for cr in card_rows:
card_name = cr["card_name"] or ""
type_line = cr["type_line"] or ""
cmc = cr["cmc"] or 0
qty = cr["quantity"] or 1
role_tag = cr["role_tag"] or ""
# Build tags from type_line and role_tag
tags = []
if role_tag:
tags.append(role_tag)
if "Land" in type_line:
tags.append("land")
land_count += qty
elif "Creature" in type_line:
tags.append("creature")
elif "Instant" in type_line:
tags.append("instant")
elif "Sorcery" in type_line:
tags.append("sorcery")
elif "Artifact" in type_line:
tags.append("artifact")
elif "Enchantment" in type_line:
tags.append("enchantment")
elif "Planeswalker" in type_line:
tags.append("planeswalker")
# Type count
for t in ["Creature", "Instant", "Sorcery", "Artifact", "Enchantment", "Planeswalker", "Land"]:
if t in type_line:
type_counts[t] = type_counts.get(t, 0) + qty
# CMC bucket
bucket = min(int(cmc), 7)
cmc_buckets[bucket] += qty
# CardPerformance with zeroed-out sim stats
cards.append(CardPerformance(
name=card_name,
drawnRate=0.0,
castRate=0.0,
impactScore=0.0,
tags=tags,
))
slug = deck_slug
return DeckReport(
deckId=slug,
commander=commander,
colorIdentity=color_identity,
cards=cards,
structure=DeckStructure(
landCount=land_count,
curveBuckets=cmc_buckets,
cardTypeCounts=type_counts,
),
)
@router.get("/api/coach/sessions")
async def coach_list_sessions(deck_id: str = None):
"""List all coaching sessions, optionally filtered by deck."""
if _coach_service is None:
raise HTTPException(500, "Coach service not initialized")
return {"sessions": _coach_service.list_sessions(deck_id)}
@router.get("/api/coach/sessions/{session_id}")
async def coach_get_session(session_id: str):
"""Get a specific coaching session."""
if _coach_service is None:
raise HTTPException(500, "Coach service not initialized")
session = _coach_service.load_session(session_id)
if session is None:
raise HTTPException(404, f"Session not found: {session_id}")
return session.model_dump()
@router.post("/api/coach/embeddings/download")
async def coach_download_embeddings():
"""Download and convert MTG card embeddings from HuggingFace."""
if _coach_embeddings is None:
raise HTTPException(500, "Coach service not initialized")
try:
_coach_embeddings.load(force_download=True)
return {
"success": True,
"cards": _coach_embeddings.card_count,
"message": f"Loaded {_coach_embeddings.card_count} card embeddings"
}
except Exception as e:
raise HTTPException(500, f"Failed to download embeddings: {e}")
@router.get("/api/coach/embeddings/search")
async def coach_search_similar(card: str, colors: str = None, top_n: int = 10):
"""Search for similar cards by name."""
if _coach_embeddings is None or not _coach_embeddings.loaded:
raise HTTPException(503, "Embeddings not loaded")
color_filter = list(colors.upper()) if colors else None
matches = _coach_embeddings.search_similar(
query_card=card, color_filter=color_filter, top_n=top_n
)
return {"query": card, "matches": [m.to_dict() for m in matches]}
@router.post("/api/coach/chat")
async def coach_chat(body: CoachChatRequest):
"""Multi-turn coaching chat. Sends conversation history to LLM and returns response."""
if _coach_service is None:
raise HTTPException(500, "Coach service not initialized")
# Load deck report for context
report = _coach_service.load_deck_report(body.deck_id)
# Build system prompt with report context
from coach.prompt_template import build_system_prompt
from coach.models import CoachGoals
goals = None
if body.goals:
try:
goals = CoachGoals(**body.goals)
except Exception:
goals = None
system_prompt = ""
if report:
system_prompt = build_system_prompt(report, goals)
else:
system_prompt = (
"You are an expert Magic: The Gathering Commander deck coach. "
"Answer questions about deck building, strategy, card choices, and game theory. "
"Be specific and actionable in your advice."
)
# Build messages array for LLM
messages = [{"role": "system", "content": system_prompt}]
for msg in body.messages:
messages.append({"role": msg.get("role", "user"), "content": msg.get("content", "")})
# Call LLM with multi-turn messages
try:
import json
from urllib.request import urlopen, Request as UrlRequest
from coach.config import LLM_URL, LLM_TIMEOUT
model_name = _coach_llm._resolve_model()
llm_body = {
"model": model_name,
"messages": messages,
"temperature": 0.7,
"max_tokens": 4096,
}
if body.stream:
# SSE streaming response
llm_body["stream"] = True
async def generate():
import asyncio
def _stream():
req = UrlRequest(
f"{_coach_llm.base_url}/chat/completions",
data=json.dumps(llm_body).encode("utf-8"),
headers={"Content-Type": "application/json"},
method="POST",
)
import http.client
import urllib.parse
parsed = urllib.parse.urlparse(f"{_coach_llm.base_url}/chat/completions")
conn = http.client.HTTPConnection(parsed.hostname, parsed.port, timeout=LLM_TIMEOUT)
conn.request("POST", parsed.path, body=json.dumps(llm_body).encode("utf-8"),
headers={"Content-Type": "application/json"})
resp = conn.getresponse()
chunks = []
while True:
line = resp.readline()
if not line:
break
line = line.decode("utf-8").strip()
if line.startswith("data: "):
data = line[6:]
if data == "[DONE]":
chunks.append("[DONE]")
break
chunks.append(data)
conn.close()
return chunks
loop = asyncio.get_event_loop()
chunks = await loop.run_in_executor(None, _stream)
for chunk_str in chunks:
if chunk_str == "[DONE]":
yield f"data: [DONE]\n\n"
break
try:
chunk = json.loads(chunk_str)
delta = chunk.get("choices", [{}])[0].get("delta", {})
content = delta.get("content", "")
if content:
# Strip think tags from streaming chunks
yield f"data: {json.dumps({'content': content})}\n\n"
except json.JSONDecodeError:
continue
return StreamingResponse(generate(), media_type="text/event-stream")
else:
# Non-streaming: regular call
req = UrlRequest(
f"{_coach_llm.base_url}/chat/completions",
data=json.dumps(llm_body).encode("utf-8"),
headers={"Content-Type": "application/json"},
method="POST",
)
import asyncio
loop = asyncio.get_event_loop()
def _call():
with urlopen(req, timeout=LLM_TIMEOUT) as resp:
return json.loads(resp.read().decode("utf-8"))
raw = await loop.run_in_executor(None, _call)
content = raw.get("choices", [{}])[0].get("message", {}).get("content", "")
# Strip think tags
content = _coach_llm._strip_think_tags(content)
usage = raw.get("usage", {})
return {
"content": content,
"model": raw.get("model", ""),
"prompt_tokens": usage.get("prompt_tokens", 0),
"completion_tokens": usage.get("completion_tokens", 0),
}
except Exception as e:
raise HTTPException(500, f"Chat failed: {e}")
@router.post("/api/coach/apply")
async def coach_apply_suggestions(body: CoachApplyRequest):
"""Apply accepted coaching suggestions to a deck — remove cuts, add adds."""
conn = _get_db_conn()
# Verify deck exists
deck = conn.execute("SELECT * FROM decks WHERE id = ?", (body.deck_id,)).fetchone()
if not deck:
raise HTTPException(404, f"Deck {body.deck_id} not found")
results = {"cuts": [], "adds": [], "errors": []}
# Process cuts: remove cards by name
for card_name in body.accepted_cuts:
row = conn.execute(
"SELECT id FROM deck_cards WHERE deck_id = ? AND card_name = ? LIMIT 1",
(body.deck_id, card_name)
).fetchone()
if row:
conn.execute("DELETE FROM deck_cards WHERE id = ?", (row["id"],))
results["cuts"].append({"name": card_name, "status": "removed"})
else:
# Try case-insensitive
row = conn.execute(
"SELECT id, card_name FROM deck_cards WHERE deck_id = ? AND LOWER(card_name) = LOWER(?) LIMIT 1",
(body.deck_id, card_name)
).fetchone()
if row:
conn.execute("DELETE FROM deck_cards WHERE id = ?", (row["id"],))
results["cuts"].append({"name": row["card_name"], "status": "removed"})
else:
results["errors"].append({"name": card_name, "error": "Card not found in deck"})
# Process adds: look up in collection first, then Scryfall
for card_name in body.accepted_adds:
# Try to find in collection
ce = conn.execute(
"SELECT scryfall_id, name FROM collection_entries WHERE LOWER(name) = LOWER(?) LIMIT 1",
(card_name,)
).fetchone()
scryfall_id = None
resolved_name = card_name
if ce:
scryfall_id = ce["scryfall_id"]
resolved_name = ce["name"]
else:
# Try Scryfall API lookup
try:
import urllib.parse
from urllib.request import urlopen, Request as UrlRequest
encoded = urllib.parse.quote(card_name)
scry_req = UrlRequest(
f"https://api.scryfall.com/cards/named?fuzzy={encoded}",
headers={"User-Agent": "commander-ai-lab/1.0"}
)
with urlopen(scry_req, timeout=10) as resp:
card_data = json.loads(resp.read().decode("utf-8"))
scryfall_id = card_data.get("id")
resolved_name = card_data.get("name", card_name)
except Exception:
pass
if scryfall_id:
# Check if already in deck
existing = conn.execute(
"SELECT id FROM deck_cards WHERE deck_id = ? AND scryfall_id = ?",
(body.deck_id, scryfall_id)
).fetchone()
if not existing:
conn.execute(
"INSERT INTO deck_cards (deck_id, scryfall_id, card_name, quantity) VALUES (?, ?, ?, 1)",
(body.deck_id, scryfall_id, resolved_name)
)
results["adds"].append({"name": resolved_name, "scryfall_id": scryfall_id, "status": "added"})
else:
results["adds"].append({"name": resolved_name, "status": "already_in_deck"})
else:
results["errors"].append({"name": card_name, "error": "Could not resolve card"})
conn.execute("UPDATE decks SET updated_at = datetime('now') WHERE id = ?", (body.deck_id,))
conn.commit()
results["total_cuts"] = len(results["cuts"])
results["total_adds"] = len([a for a in results["adds"] if a["status"] == "added"])
return results
@router.get("/api/coach/cards-like")
async def coach_cards_like(card: str, colors: str = None, top_n: int = 10):
"""Find cards similar to a given card using embeddings. UI-friendly version."""
if _coach_embeddings is None or not _coach_embeddings.loaded:
raise HTTPException(503, "Embeddings not loaded")
color_filter = list(colors.upper()) if colors else None
matches = _coach_embeddings.search_similar(
query_card=card, color_filter=color_filter, top_n=top_n
)
conn = _get_db_conn()
results = []
for m in matches:
# Check if card is in collection
owned = conn.execute(
"SELECT SUM(quantity) as qty FROM collection_entries WHERE LOWER(name) = LOWER(?)",
(m.name,)
).fetchone()
owned_qty = (owned["qty"] or 0) if owned else 0
# Get image URL and price
ce = conn.execute(
"SELECT scryfall_id, tcg_price FROM collection_entries WHERE LOWER(name) = LOWER(?) LIMIT 1",
(m.name,)
).fetchone()
results.append({
"name": m.name,
"similarity": round(m.similarity, 4),
"types": m.types,
"mana_value": m.mana_value,
"mana_cost": m.mana_cost,
"text": m.text[:200] if m.text else "",
"owned_qty": owned_qty,
"image_url": f"https://api.scryfall.com/cards/{ce['scryfall_id']}?format=image&version=normal" if ce and ce["scryfall_id"] else None,
"tcg_price": ce["tcg_price"] if ce else None,
})
return {"query": card, "results": results}
@router.post("/api/coach/reports/generate")
async def coach_generate_reports():
"""Rebuild all deck reports from batch result JSONs in results/."""
try:
from coach.report_generator import generate_deck_reports
lab_root = Path(__file__).parent.parent
results_dir = str(lab_root / CFG.results_dir)
reports_dir = str(lab_root / "deck-reports")
updated = generate_deck_reports(results_dir, reports_dir)
return {
"status": "ok",
"decksUpdated": updated,
"count": len(updated),
"message": f"Generated reports for {len(updated)} decks" if updated else "No batch results found",
}
except Exception as e:
raise HTTPException(500, f"Report generation failed: {e}")