limiter

const PORT = process.env.PORT || 3000; ``` #### 2. Error Handling Add middleware to handle errors. ```javascript app.use((err, req, res, next) => { console.error(err.stack); res.status(500).json({ error: "Something went wrong." }…

response = requests.get(f"https://example.com/api/{query}") response.raise_for_status() return response.json() except requests.exceptions.HTTPError as e: if e.respo…

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…

# Custom key function to identify user roles def get_user_role(): # Assume user role is stored in the request context return getattr(g, 'user_role', 'basic') # Configure Flask-Limiter with custom key function limiter = Limiter( …

return getattr(g, 'user_role', 'basic') # Configure Flask-Limiter with custom key function limiter = Limiter( app, key_func=get_user_role, default_limits=["20/minute"] ) # Decorator to set user role for the request def set…

- Integrate it with FastAPI using middleware. 3. **Implement Timeouts**: - Use FastAPI's `async` and `await` to handle asynchronous operations. - Use `asyncio.wait_for` to enforce timeouts. ### Example Implementation Here's how …

- **Custom Headers**: You can customize headers to provide more information about rate limits, such as `X-RateLimit-Limit`, `X-RateLimit-Remaining`, and `X-RateLimit-Reset`. - **Storage Backend**: For production environments, consider using…

Here, `-w 4` specifies 4 worker processes, and `-t 3` sets a 3-second timeout. ### Step 3: Hybrid Query Logic Implement the hybrid query logic to handle both sparse and dense queries efficiently. Here's an example: ```python from flask i…

``` Here, `-w 4` specifies 4 worker processes, and `-t 2.5` sets a 2.5-second timeout. ### Step 4: Implement Hybrid Ranking Logic Here's a complete example implementation: ```python from flask import Flask, request, jsonify from flask_l…

consumer = KafkaConsumer('topic-name', bootstrap_servers=['localhost:9092']) for message in consumer: query = message.value.decode('utf-8') result = process_query(query) print(result) ``` ### Conc…

from flask_limiter.util import get_remote_address app = Flask(__name__) limiter = Limiter(app, key_func=get_remote_address) # Define the API endpoint @app.route("/api/v1/sparse-train", methods=["GET"]) @limiter.limit("450/second") def get…

#### Existing Flask App Structure ```python from flask import Flask, jsonify, request from flask_limiter import Limiter from flask_limiter.util import get_remote_address from flask_timeout import FlaskTimeout app = Flask(__name__) # Init…

4. **Logging**: Include logging to track requests and errors. Here's an enhanced version of your API design: ```python from flask import Flask, request, jsonify from flask_limiter import Limiter from flask_limiter.util import get_remote_a…

key_func=get_remote_address, default_limits=["350 per second"] ) # Define the synonym expansion endpoint @app.route("/api/v1/synonym-expand", methods=["POST"]) @limiter.limit("350 per second") async def synonym_expand(): try: …