Add error logging and LLM debug endpoint for troubleshooting

app/main.py

@@ -1,15 +1,20 @@
 """FastAPI application for AIM Learning Companion."""
 
+import logging
 import re
+import traceback
 from contextlib import asynccontextmanager
 from pathlib import Path
 from typing import List
 
 from fastapi import FastAPI, UploadFile, File
-from fastapi.responses import FileResponse
+from fastapi.responses import FileResponse, JSONResponse
 from fastapi.staticfiles import StaticFiles
 from pydantic import BaseModel
 
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
 from app.rag import load_corpus, retrieve, add_documents, list_documents, delete_document
 from app.llm import build_system_prompt, chat, analyze_session
 
@@ -75,16 +80,20 @@ def _detect_phase(reply: str, current_phase: int) -> int:
 
 @app.post("/api/chat", response_model=ChatResponse)
 async def api_chat(req: ChatRequest):
-    rag_chunks = retrieve(req.message)
-    system_prompt = build_system_prompt(req.mode, req.topic, req.phase, rag_chunks)
+    try:
+        rag_chunks = retrieve(req.message)
+        system_prompt = build_system_prompt(req.mode, req.topic, req.phase, rag_chunks)
 
-    messages = [{"role": m["role"], "content": m["content"]} for m in req.history]
-    messages.append({"role": "user", "content": req.message})
+        messages = [{"role": m["role"], "content": m["content"]} for m in req.history]
+        messages.append({"role": "user", "content": req.message})
 
-    reply = await chat(system_prompt, messages)
-    detected_phase = _detect_phase(reply, req.phase)
+        reply = await chat(system_prompt, messages)
+        detected_phase = _detect_phase(reply, req.phase)
 
-    return ChatResponse(reply=reply, phase=detected_phase)
+        return ChatResponse(reply=reply, phase=detected_phase)
+    except Exception as e:
+        logger.error(f"Chat error: {e}\n{traceback.format_exc()}")
+        return JSONResponse(status_code=500, content={"error": str(e)})
 
 
 @app.post("/api/upload")
@@ -149,4 +158,21 @@ async def api_analyze(req: AnalysisRequest):
 
 @app.get("/api/health")
 async def health():
-    return {"status": "ok"}
+    import os
+    return {
+        "status": "ok",
+        "has_api_key": bool(os.environ.get("OPENROUTER_API_KEY", "")),
+        "base_url": os.environ.get("LLM_BASE_URL", "(not set)"),
+        "model": os.environ.get("LLM_MODEL", "(not set)"),
+    }
+
+
+@app.get("/api/test-llm")
+async def test_llm():
+    """Quick test of the LLM connection."""
+    try:
+        reply = await chat("Tu es un assistant. Reponds en une phrase.", [{"role": "user", "content": "Dis bonjour."}])
+        return {"status": "ok", "reply": reply}
+    except Exception as e:
+        logger.error(f"LLM test error: {e}\n{traceback.format_exc()}")
+        return JSONResponse(status_code=500, content={"error": str(e), "type": type(e).__name__})