enhanced rate limiting strategy

- A small random jitter is added to the delay to avoid synchronized retries from multiple clients. - The loop continues until a successful response is received or the maximum number of retries is reached. ### Additional Consideration…

- `request_interval = 60 / rate_limit`: Calculate the time interval between requests to stay within the rate limit. - `time.sleep(request_interval)`: Wait for the calculated interval before making the next request. 2. **Authenticatio…

[Turn 5300] User: hmm, can I still use my existing Flask setup without switching to Redis? [Turn 5301] Assistant: Certainly! You can continue using your existing Flask setup without switching to Redis by leveraging the built-in rate-limiti…

app = Flask(__name__) # Connect to Redis redis_client = Redis(host='localhost', port=6379, db=0) # Configure Flask-Limiter with Redis backend limiter = Limiter( app, key_func=get_remote_address, default_limits=["200 per minute…

@app.route("/api/v1/endpoint", methods=["GET"]) @limiter.limit("10/second;30/minute", per_method=True, override_defaults=False) def handle_request(): # Handle the request response = jsonify({"message": "Request handled successfully"…

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…

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…