Closed MarBeanInc1111 closed 7 months ago
To solve the bug, we need to implement a proactive rate limiting mechanism that can track and limit the number of requests a user makes within a specified time window. This should be done before the requests reach the API call functions to prevent rate limit errors from occurring. The solution should be integrated into the middleware layer of the application, which will allow for centralized management of rate limiting across all endpoints.
The bug is caused by the absence of a proactive rate limiting system. The current implementation only handles rate limit errors after they have occurred, rather than preventing them. Without a proper rate limiting mechanism in place, users can make an unlimited number of requests in a short period, which can lead to abuse and potential service outages.
To address the missing rate limiting, we can implement a middleware function in pilot/utils/middleware.py
that uses an in-memory store or a more persistent solution like Redis to track request counts. Here's a simplified version of the middleware function:
from flask import request, Response
from functools import wraps
import time
# Define rate limits for users
RATE_LIMITS = {
"user": {"calls": 100, "period": 3600} # 100 calls per hour per user
}
# In-memory storage for tracking requests
request_counters = {}
def rate_limit(route_function):
@wraps(route_function)
def wrapper(*args, **kwargs):
user_id = request.headers.get("X-User-ID")
current_time = time.time()
# Initialize or update the request count and timestamp
if user_id not in request_counters or current_time - request_counters[user_id]['timestamp'] > RATE_LIMITS["user"]["period"]:
request_counters[user_id] = {"count": 1, "timestamp": current_time}
else:
request_counters[user_id]["count"] += 1
# Check if the request count exceeds the rate limit
if request_counters[user_id]["count"] > RATE_LIMITS["user"]["calls"]:
return Response("Too many requests", status=429)
return route_function(*args, **kwargs)
return wrapper
This middleware should be applied to all relevant endpoints in the application to ensure rate limiting is enforced.
Additionally, the User
model in pilot/database/models/user.py
can be extended with request_count
and last_request_time
fields to support rate limiting at the database level, which can be useful for persistent tracking across application restarts or in a distributed system.
To replicate the bug, one would need to make a series of API requests to the application's endpoints in quick succession, exceeding what would be considered a reasonable request rate. Since there is no rate limiting in place, the application will not prevent or flag this behavior, which can be observed by the lack of error responses or warnings related to excessive requests.
To complete the task, the following steps should be taken:
pilot/utils/middleware.py
as outlined in the code snippet above.User
model in pilot/database/models/user.py
to include the request_count
and last_request_time
fields, if persistent tracking is required.429 Too Many Requests
response.pilot/utils/llm_connection.py
file to ensure that any existing rate limit handling logic is compatible with the new middleware and adjust as necessary.Click here to create a Pull Request with the proposed solution
Files used for this task:
Tracking issue for: