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AI & LLM integration patterns

Call LLM APIs, structure prompts, parse responses, and ship AI features safely.

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How to Retry LLM Calls on Rate Limit Errors in Python

Implement a retry mechanism with exponential backoff for LLM API calls that raises a custom RateLimitError, using a mock function to demonstrate the pattern.

llm retry rate-limit
Python 
import time
import random


def mock_llm_call():
    """Simulates an LLM API call that may raise a rate limit error."""
    if random.random() < 0.4:  # 40% chance of rate limit
        raise RateLimitError("Rate limit exceeded. Try again later.")
    return {"response": "Hello world from mock LLM"}


class RateLimitE…
15 0 Open

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