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""" |
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FastAPI backend for crossword puzzle generator with vector similarity search. |
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""" |
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import os |
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import logging |
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import time |
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from datetime import datetime |
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from contextlib import asynccontextmanager |
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from pathlib import Path |
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from fastapi import FastAPI, HTTPException |
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from fastapi.middleware.cors import CORSMiddleware |
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from fastapi.staticfiles import StaticFiles |
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from fastapi.responses import FileResponse |
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import uvicorn |
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from dotenv import load_dotenv |
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from src.routes.api import router as api_router |
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from src.services.thematic_word_service import ThematicWordService |
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load_dotenv() |
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logging.basicConfig( |
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level=logging.INFO, |
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format='%(asctime)s - %(name)s - %(filename)s:%(lineno)d - %(levelname)s - %(message)s', |
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datefmt='%H:%M:%S' |
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) |
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logger = logging.getLogger(__name__) |
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thematic_service = None |
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@asynccontextmanager |
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async def lifespan(app: FastAPI): |
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"""Initialize and cleanup application resources.""" |
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global thematic_service |
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startup_time = time.time() |
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logger.info("π Initializing Python backend with thematic word service...") |
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try: |
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service_start = time.time() |
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logger.info("π§ Creating ThematicWordService instance...") |
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thematic_service = ThematicWordService() |
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cache_status = thematic_service.get_cache_status() |
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logger.info(f"π Cache directory: {cache_status['cache_directory']}") |
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logger.info(f"π Cache directory exists: {os.path.exists(cache_status['cache_directory'])}") |
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logger.info(f"βοΈ Cache directory writable: {os.access(cache_status['cache_directory'], os.W_OK)}") |
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cache_complete = cache_status['complete'] |
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logger.info(f"π¦ Existing cache complete: {cache_complete}") |
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if not cache_complete: |
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for cache_type in ['vocabulary_cache', 'frequency_cache', 'embeddings_cache']: |
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cache_info = cache_status[cache_type] |
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logger.info(f" {cache_type}: exists={cache_info['exists']}, path={cache_info['path']}") |
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logger.info("β‘ Starting thematic service initialization (creating cache files)...") |
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await thematic_service.initialize_async() |
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cache_status_after = thematic_service.get_cache_status() |
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logger.info(f"β
Cache status after initialization: complete={cache_status_after['complete']}") |
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for cache_type in ['vocabulary_cache', 'frequency_cache', 'embeddings_cache']: |
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cache_info = cache_status_after[cache_type] |
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if cache_info['exists']: |
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logger.info(f" β
{cache_type}: {cache_info.get('size_mb', 0):.1f}MB") |
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else: |
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logger.warning(f" β {cache_type}: NOT CREATED") |
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init_time = time.time() - service_start |
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logger.info(f"π Thematic service initialized in {init_time:.2f}s") |
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logger.info("π§ Initializing WordNet clue generator...") |
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try: |
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wordnet_start = time.time() |
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from src.services.wordnet_clue_generator import WordNetClueGenerator |
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cache_dir = thematic_service.cache_dir if thematic_service else "./cache" |
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wordnet_generator = WordNetClueGenerator(cache_dir=str(cache_dir)) |
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wordnet_generator.initialize() |
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if thematic_service: |
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thematic_service._wordnet_generator = wordnet_generator |
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wordnet_time = time.time() - wordnet_start |
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logger.info(f"β
WordNet clue generator initialized in {wordnet_time:.2f}s") |
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except Exception as e: |
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logger.warning(f"β οΈ Failed to initialize WordNet clue generator during startup: {e}") |
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logger.info("π WordNet clue generator will be initialized on first use") |
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except ImportError as e: |
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logger.error(f"β Missing dependencies for thematic service: {e}") |
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logger.error("π‘ Install missing packages: pip install wordfreq sentence-transformers torch scikit-learn") |
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raise |
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except PermissionError as e: |
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logger.error(f"β Permission error with cache directory: {e}") |
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logger.error(f"π‘ Check cache directory permissions: {thematic_service.cache_dir if 'thematic_service' in locals() else 'unknown'}") |
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raise |
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except Exception as e: |
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logger.error(f"β Failed to initialize thematic service: {e}") |
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logger.error(f"π Error type: {type(e).__name__}") |
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import traceback |
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logger.error(f"π Full traceback: {traceback.format_exc()}") |
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raise |
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app.state.thematic_service = thematic_service |
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yield |
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logger.info("π Shutting down Python backend...") |
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app = FastAPI( |
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title="Crossword Puzzle Generator API", |
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description="Python backend with AI-powered thematic word generation", |
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version="2.0.0", |
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lifespan=lifespan |
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) |
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cors_origins = [] |
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if os.getenv("NODE_ENV") == "production": |
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cors_origins = ["*"] |
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else: |
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cors_origins = [ |
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"http://localhost:5173", |
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"http://localhost:3000", |
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"http://localhost:7860", |
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] |
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app.add_middleware( |
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CORSMiddleware, |
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allow_origins=cors_origins, |
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allow_credentials=True, |
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allow_methods=["*"], |
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allow_headers=["*"], |
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) |
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app.include_router(api_router, prefix="/api") |
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static_path = Path(__file__).parent / "public" |
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if static_path.exists(): |
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app.mount("/assets", StaticFiles(directory=static_path / "assets"), name="assets") |
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@app.get("/") |
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async def serve_frontend(): |
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"""Serve the React frontend.""" |
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index_path = static_path / "index.html" |
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if index_path.exists(): |
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return FileResponse(index_path) |
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else: |
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raise HTTPException(status_code=404, detail="Frontend not found") |
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@app.get("/{full_path:path}") |
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async def serve_spa_routes(full_path: str): |
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"""Serve React SPA routes.""" |
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if not full_path.startswith("api/"): |
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index_path = static_path / "index.html" |
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if index_path.exists(): |
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return FileResponse(index_path) |
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raise HTTPException(status_code=404, detail="Not found") |
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@app.get("/health") |
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async def health_check(): |
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"""Health check endpoint.""" |
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return { |
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"status": "healthy", |
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"backend": "python", |
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"vector_search": vector_service.is_initialized if vector_service else False |
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} |
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if __name__ == "__main__": |
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port = int(os.getenv("PORT", 7860)) |
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host = "0.0.0.0" if os.getenv("NODE_ENV") == "production" else "127.0.0.1" |
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logger.info(f"π Starting Python backend on {host}:{port}") |
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uvicorn.run( |
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"app:app", |
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host=host, |
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port=port, |
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reload=os.getenv("NODE_ENV") != "production" |
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) |