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Rate Limiting an LLM API
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Rate Limiting an LLM API

HardPython

Problem

Intercom's Fin AI Agent API must limit LLM usage per user to control token costs and maintain service stability. Implement a weighted sliding-window rate limiter that processes requests in chronological order.

Each request has a user identifier, timestamp, and estimated token cost. A request is accepted only when adding its cost would keep that user's accepted token usage within max_tokens during the active time window. Rejected requests do not consume capacity.

Formal Specification

Implement rate_limit(requests, window_seconds, max_tokens).

  • requests is a list of [user_id, timestamp, token_cost] records, ordered by nondecreasing timestamp.
  • user_id is a string.
  • timestamp and token_cost are nonnegative integers.
  • window_seconds and max_tokens are positive integers.
  • Return a list of booleans, one per request, where True means accepted and False means rejected.
  • For a request at time t, usage includes accepted requests with timestamps in (t - window_seconds, t].

Constraints

  • 1 <= requests.length <= 10^5
  • 1 <= window_seconds, max_tokens <= 10^9
  • 1 <= token_cost <= 10^9
  • Each request is [user_id, timestamp, token_cost]
  • Requests are ordered by nondecreasing timestamp
  • The active window is (timestamp - window_seconds, timestamp]

Function Signature

def rate_limit(requests, window_seconds, max_tokens):
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