LiteLLM

Overview

LiteLLM is an open-source Python library designed to simplify and standardize the process of interacting with large language models (LLMs) from various providers, including OpenAI, Anthropic, Google, Cohere, Hugging Face, and many more. It provides a unified API interface, allowing developers to switch between different models and providers with minimal code changes, effectively reducing vendor lock-in.

Beyond a consistent API, LiteLLM offers crucial features for building production-ready LLM applications, such as automatic retries for failed API calls, intelligent fallbacks to alternative models, logging and monitoring integrations for observability, fine-grained key management, rate limiting, and caching. This comprehensive feature set enhances the reliability, performance, and cost-effectiveness of applications utilizing multiple or single LLMs. By abstracting away provider-specific complexities and adding essential infrastructure features, LiteLLM significantly speeds up development and deployment workflows for AI engineers and data scientists.

Key Features

• Unified API for 100+ LLMs (OpenAI, Anthropic, Google, Cohere, Hugging Face, etc.)
• Automatic Fallbacks (failover to another model/provider on error)
• Automatic Retries (handle transient API errors)
• Logging & Monitoring Integrations (Langfuse, Helicone, Weights & Biases, Sentry, etc.)
• Key Management (securely manage API keys for different providers)
• Rate Limiting (control request volume to stay within provider limits)
• Caching (reduce latency and cost for repeated prompts)
• Streaming Support
• Cost Tracking
• Consistent API for completions, embeddings, and more

Supported Platforms

• Python Library
• API Access
• Web Browser (for hosted service UI)

Integrations

• Langfuse
• Helicone
• Weights & Biases
• Sentry
• Segment
• PostHog
• Supabase
• Vercel
• Datadog
• Prometheus
• Any LLM API endpoint

Pricing Tiers