LiteLLM is an open-source Python SDK and proxy server platform designed to simplify the interaction with over 100 large language models (LLMs) by providing a unified API in the OpenAI Chat Completions format. It allows developers and platform teams to call multiple LLM providers like OpenAI, Anthropic, Azure OpenAI, Vertex AI, NVIDIA, HuggingFace, and many others with consistent input/output formats, along with advanced features such as load balancing, retry/fallback logic, cost tracking, and rate limiting. LiteLLM can be used either as a proxy server (LLM Gateway) for centralized access or as a Python SDK for direct use in code.
Key Features:
Unified API Format: Uses OpenAI-style Chat Completion endpoints to standardize calls across multiple LLM providers.
Multi-LLM Support: Seamlessly integrates with over 100 large language models across popular platforms, including OpenAI, Anthropic, Vertex AI, NVIDIA, and HuggingFace.
Advanced Management: Built-in retry and fallback mechanisms, load balancing, budgeting, rate limiting, and detailed logging/observability.
Flexible Deployment: Offers both a Proxy Server for platform-wide LLM management and a Python SDK for direct integration with applications.
Use Cases:
Developing AI-powered chatbots or applications that require flexibility to switch between or combine multiple LLM providers.
Platform teams managing LLM resource allocation, cost tracking, and guardrails centrally for multiple projects and users.
Research and development workflows that benefit from access to diverse models with consistent APIs and failover support.
Technical Specifications:
Platforms & Languages: Python SDK supported; Proxy Server deployable on cloud or local infrastructure.
API Compatibility: Fully compatible with OpenAI API input/output format, supporting streaming responses, embeddings, image generation calls.
Observability & Control: Supports logging integrations with tools like Langfuse, monitoring via Prometheus metrics, customizable guardrails, and spend tracking per API key or project.