AI Dev Tool: Multi-Provider LLM Fallback Router with Token Budget Enforcement

1. The Production Bottleneck

We engineered this zero-bloat Python 3.12+ / AsyncIO blueprint to enforce bounded concurrency, deterministic exponential backoff with jitter, strict schema validation at the ingestion boundary, and structured JSON telemetry—ready to drop into production without weeks of plumbing.

2. Request & Execution Architecture

3. Production Benchmarks

"""AI Dev Tool: Multi-Provider LLM Fallback Router with Token Budget Enforcement

This module implements a multi-provider LLM fallback router with token budget enforcement.
It uses a bounded concurrency approach to manage the number of concurrent requests to each provider.
The router is designed to handle requests in a way that ensures fairness and prevents any single provider from being overwhelmed.

The module can be used from the command line by providing the following arguments:
    - providers: a list of provider names
    - token_budget: the maximum number of tokens that can be used per provider
    - concurrency: the maximum number of concurrent requests per provider
    - num_requests: the number of requests to send to each provider

Example usage:
    python llm_fallback_router.py --providers provider1 provider2 --token_budget 100 --concurrency 5 --num_requests 10

The module uses exponential backoff with jitter to handle failed requests and ensures that the token budget is enforced for each provider.
It also uses structured JSON logging to provide detailed information about each request and any errors that occur.
"""

import argparse
import dataclasses
import json
import logging
import random
import sys
import time
from typing import List

5. Choose Your Access Tier

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6. Frequently Asked Engineering Questions

7. Related Production Blueprints