AI LLM Router

Intelligent routing of LLM API calls across multiple providers with automatic fallbacks, cost optimization, caching, health monitoring, and retry logic.

Features

• Multi-Provider Support: OpenAI, Anthropic, and extensible for other providers
• Intelligent Routing: Priority-based, cost-optimized, and round-robin strategies
• Automatic Fallbacks: Seamless failover between providers
• Cost Optimization: Track and optimize API usage costs
• Caching: Redis-based response caching for improved performance
• Health Monitoring: Real-time provider health checks
• Retry Logic: Configurable retry mechanisms with exponential backoff
• Async Support: Full async/await support for high-performance applications
• Streaming: Support for streaming responses
• CLI Interface: Command-line tool for easy integration
• Metrics: Prometheus-compatible metrics collection

Installation

pip install ai-llm-router

Quick Start

from llm_router import LLMRouter, RouterConfig
from llm_router.providers import OpenAIProvider, AnthropicProvider

# Configure providers
config = RouterConfig(
    providers=[
        OpenAIProvider(api_key="your-openai-key"),
        AnthropicProvider(api_key="your-anthropic-key")
    ],
    strategy="priority"
)

# Create router
router = LLMRouter(config)

# Make a request
response = await router.chat_completion(
    messages=[{"role": "user", "content": "Hello, world!"}],
    model="gpt-4"
)

CLI Usage

After installation, you can use the CLI:

ai-llm-router chat --provider openai --model gpt-4 --message "Hello, world!"

Documentation

For detailed documentation, examples, and API reference, visit our GitHub repository.

Author

Sherin Joseph - LinkedIn

License

MIT License - see LICENSE file for details.