Create app.py

app.py

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+# app.py
+from fastapi import FastAPI, Request, status
+from fastapi.responses import JSONResponse
+from fastapi.middleware.cors import CORSMiddleware # If you need CORS
+from contextlib import asynccontextmanager
+import uvicorn
+import logging
+from slowapi import Limiter, _rate_limit_exceeded_handler
+from slowapi.util import get_remote_address
+from slowapi.errors import RateLimitExceeded
+from slowapi.middleware import SlowAPIMiddleware
+
+import config
+from services import generation
+from routers import ideas, images, videos
+
+# --- Logging Setup ---
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+# --- Rate Limiting Setup ---
+limiter = Limiter(key_func=get_remote_address, default_limits=[config.RATE_LIMIT])
+
+# --- Lifespan Management (Model Loading/Unloading) ---
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    # Startup: Load models
+    logger.info("Application startup: Loading models...")
+    try:
+        generation.load_models()
+        app.state.limiter = limiter # Add limiter to app state for dependency injection
+        logger.info("Models loaded successfully.")
+    except Exception as e:
+        logger.error(f"FATAL: Model loading failed during startup: {e}", exc_info=True)
+        # Optionally, prevent app start or handle gracefully
+        # For now, we let it start but endpoints needing models will fail.
+    yield
+    # Shutdown: Clean up (optional, less critical in stateless services)
+    logger.info("Application shutdown.")
+    generation.model_cache.clear()
+    # Add any other cleanup here
+    logger.info("Resources cleaned up.")
+
+
+# --- FastAPI App Initialization ---
+app = FastAPI(
+    title="AI Content Generation API",
+    description="API for generating content ideas, images, and videos using Hugging Face models.",
+    version="1.0.0",
+    lifespan=lifespan # Use the lifespan context manager
+)
+
+# --- Middleware ---
+# Rate Limiting Middleware
+app.add_middleware(SlowAPIMiddleware)
+
+# CORS Middleware (Uncomment and configure if needed for browser-based clients)
+# origins = [
+#     "http://localhost",
+#     "http://localhost:8080",
+#     "https://your-frontend-domain.com", # Add your frontend domain
+# ]
+# app.add_middleware(
+#     CORSMiddleware,
+#     allow_origins=origins,
+#     allow_credentials=True,
+#     allow_methods=["*"],
+#     allow_headers=["*"],
+# )
+
+# --- Exception Handlers ---
+app.add_exception_handler(RateLimitExceeded, _rate_limit_exceeded_handler)
+
+@app.exception_handler(Exception)
+async def general_exception_handler(request: Request, exc: Exception):
+    logger.error(f"Unhandled exception: {exc}", exc_info=True)
+    return JSONResponse(
+        status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+        content={"detail": "An internal server error occurred."},
+    )
+
+# --- API Routers ---
+app.include_router(ideas.router)
+app.include_router(images.router)
+app.include_router(videos.router)
+
+# --- Root Endpoint ---
+@app.get("/", tags=["Status"])
+async def read_root():
+    """Root endpoint providing basic API information."""
+    return {
+        "message": "Welcome to the AI Content Generation API!",
+        "docs": "/docs",
+        "models": {
+            "text": config.TEXT_MODEL_NAME,
+            "image": config.IMAGE_MODEL_NAME,
+            "video": config.VIDEO_MODEL_NAME
+        },
+         "status": "OK"
+    }
+
+# --- Main Execution (for local testing) ---
+if __name__ == "__main__":
+    # When running locally: uvicorn app:app --reload
+    # The following is mostly for structuring; direct execution isn't typical for deployment
+    print("To run locally, use: uvicorn app:app --reload --host 0.0.0.0 --port 7860")
+    # uvicorn.run(app, host="0.0.0.0", port=7860) # Port 7860 is common for HF Spaces