"""Diagnostics routes — /api/db/stats, /api/rag/stats, /api/test/youtube, /api/test-research.""" import logging from typing import Dict, Any from fastapi import APIRouter, HTTPException, Form, Request from services.youtube.youtube_handler import extract_youtube_id, extract_transcript_async from core.constants import DEFAULT_HOST from core.middleware import require_admin logger = logging.getLogger(__name__) def setup_diagnostics_routes( rag_manager, rag_available: bool, research_handler, ) -> APIRouter: router = APIRouter(tags=["diagnostics"]) @router.get("/api/db/stats") async def get_database_stats(request: Request) -> Dict[str, Any]: require_admin(request) try: from core.database import get_detailed_stats return get_detailed_stats() except Exception as e: logger.error(f"DB stats error: {e}") raise HTTPException(500, "Failed to retrieve database statistics") @router.get("/api/rag/stats") async def get_rag_stats(request: Request) -> Dict[str, Any]: require_admin(request) if rag_available and rag_manager: return rag_manager.get_stats() return {"error": "RAG system not available"} @router.get("/api/test/youtube") async def test_youtube(request: Request, url: str) -> Dict[str, Any]: require_admin(request) try: video_id = extract_youtube_id(url) if not video_id: return {"error": "Invalid YouTube URL"} data = await extract_transcript_async(url, video_id) return { "video_id": video_id, "transcript_success": data.get("success", False), "transcript_length": len(data.get("transcript", "")) if data.get("success") else 0, "transcript_preview": (data.get("transcript", "")[:500] + "...") if data.get("success") and len(data.get("transcript", "")) > 500 else data.get("transcript", ""), "error": data.get("error") if not data.get("success") else None, } except Exception as e: return {"error": str(e)} @router.post("/api/test-research") async def test_research(request: Request, query: str = Form("What is machine learning?")) -> Dict[str, Any]: require_admin(request) try: endpoint = f"http://{DEFAULT_HOST}:8000/v1/chat/completions" model = "gpt-oss-120b" result = await research_handler.call_research_service(query, endpoint, model) return { "status": "success", "query": query, "result_preview": result[:200] + "..." if len(result) > 200 else result, "result_length": len(result), } except Exception as e: return {"status": "error", "error": str(e), "query": query} return router