Rate Limiting Section

# Define timeout timeout = 2 # seconds # Example endpoint @app.post("/api/v1/ingest") async def ingest_data(request: Request): # Simulate data ingestion logic try: # Use asyncio.wait_for to enforce timeout await as…

return "Private Data"; } } ``` ### Summary By combining Spring Cloud Gateway and Resilience4j, you can achieve more granular rate limiting: 1. **Spring Cloud Gateway**: Manages API routes and applies rate limiting at the gate…

Implement rate limiting to prevent abuse and ensure that the endpoint can handle 600 req/sec throughput. ```python from fastapi_limiter import FastAPILimiter from fastapi_limiter.depends import RateLimiter @app.on_event("startup") async d…

dense_results = call_dense_retrieval(query) except HTTPException as e: dense_results = {"results": [], "total_results": 0} return JSONResponse(content={"error_code": e.status_code, "message": e.detail}, status_co…

I've also set up a pipeline to process 3,000 queries/sec with 99.9% uptime for sparse retrieval. How can I ensure that my pipeline is properly optimized for performance? ```python import concurrent.futures def process_query(query): # P…

return jsonify({"error": "Unauthorized access"}), 403 ``` ### 4. Rate Limiting and Throttling Implement rate limiting and throttling to prevent abuse: ```python from flask_limiter import Limiter limiter = Limiter(app, key_func=lambd…

1. **Rate Limiting**: You've already set up rate limiting using `Flask-Limiter`. We'll keep that in place. 2. **Caching**: You can use Redis to cache the results of the synonym expansion to reduce the load on your backend and improve respon…

return [f"{term}_synonym1", f"{term}_synonym2"] else: return [] if __name__ == "__main__": app.run(debug=True) ``` ### Explanation 1. **Rate Limiting**: - The `limiter.limit("350 per second")` decorator ensures…