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What is docs.litellm.ai?
LiteLLM is a versatile tool designed to streamline interactions with over 100 large language models (LLMs). It offers a unified interface, allowing users to access various LLMs through a consistent OpenAI-compatible input/output format. This simplifies the development process and reduces the complexity of integrating multiple LLMs into applications.
LiteLLM offers functionalities like consistent output formatting, retry/fallback logic across deployments, and spend tracking. It can be used via a Python SDK for direct integration into code or as a proxy server (LLM Gateway) for centralized management and access control.
Features
- Unified Interface: Access 100+ LLMs using a consistent OpenAI-compatible format.
- Consistent Output: Text responses are always available at ['choices'][0]['message']['content'].
- Retry/Fallback Logic: Built-in mechanisms for handling failures and switching between deployments (e.g., Azure/OpenAI).
- Cost Tracking: Monitor and set budgets for LLM usage per project.
- Proxy Server (LLM Gateway): Centralized service for managing access to multiple LLMs, including logging, and access control.
- Python SDK: Integrate LiteLLM directly into Python code for streamlined development.
- Streaming Support: Enable streaming for real-time interactions with LLMs.
- Exception Handling: Maps exceptions across providers to OpenAI exception types.
- Observability: Pre-defined callbacks for integrating with MLflow, Lunary, Langfuse, Helicone, and more.
Use Cases
- Developing applications requiring access to multiple LLMs.
- Building LLM-powered features with fallback and redundancy.
- Centralized management of LLM access and usage within an organization.
- Integrating various LLMs into existing Python projects.
- Tracking and controlling costs associated with LLM usage.
- Creating a unified LLM gateway for internal teams.
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