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BerriAI-litellm
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About BerriAI-litellm
BerriAI-litellm revolutionizes the interaction with large language models (LLMs) by providing a Python SDK and Proxy Server, designed to seamlessly integrate with over 100 LLM APIs in the OpenAI format. This innovative tool is tailored for developers and enterprises seeking to streamline the process of calling diverse LLM APIs such as Bedrock, Azure, OpenAI, VertexAI, and more. By simplifying the integration and management of multiple LLMs, BerriAI-litellm addresses the complexities associated with managing and translating calls between different AI platforms. Key Features: Comprehensive LLM Integration: Supports over 100 LLM APIs, allowing users to access a wide range of models from providers like HuggingFace, Cohere, and Anthropic. Consistent Output Format: Ensures uniform output by adhering to the OpenAI format, simplifying the integration process across different models. Retry and Fallback Logic: Provides robust mechanisms for retrying and fallback across multiple deployments, enhancing reliability and performance. Budget and Rate Limiting: Allows users to set budgets and rate limits per project, API key, or model, offering precise control over resource usage.
GitHub, Inc.
San Francisco, California, US · Founded 2008
- Founders
- Tom Preston-Werner, Chris Wanstrath, PJ Hyett, Scott Chacon
- Founded
- 2008
- Headquarters
- San Francisco, California, US
- Legal status
- Subsidiary of Microsoft (NASDAQ: MSFT)
Key features
- Comprehensive LLM Integration
- Consistent Output Format
- Retry and Fallback Logic
- Budget and Rate Limiting
- User-Friendly Setup
- Scalable Solution
Use cases
- Software Developers: Leveraging the tool for seamless integration with multiple LLM APIs.
- AI Researchers: Utilizing the tool to experiment with various models across different platforms.
- Tech Enterprises: Implementing the solution for scalable and efficient AI model management.
Pros
- Unified interface to call 100+ LLM providers using OpenAI format, eliminating provider-specific SDK juggling
- Available as both a Python SDK for direct integration and a self-hosted proxy server for centralized access
- Supports advanced features like cost tracking, guardrails, load balancing, and logging
- Rust core with Python SDK for performance and reliability
- Enterprise-ready with features like retry logic, fallback mechanisms, and rate limiting
Cons
- Requires technical expertise for self-hosting and configuration
- May introduce latency due to proxy server routing
- Complexity in managing multiple LLM providers and their unique configurations
Frequently asked questions about BerriAI-litellm
What is BerriAI-litellm?
BerriAI-litellm is an open-source AI Gateway that provides a unified interface to call over 100 LLM providers using the OpenAI format. It can be used as a Python SDK for direct integration or deployed as a proxy server for centralized access.
Who should use BerriAI-litellm?
Developers and enterprises seeking to simplify interactions with multiple LLM APIs will benefit from BerriAI-litellm. It is particularly useful for teams managing diverse AI models across providers like OpenAI, Anthropic, Bedrock, and Azure.
How does BerriAI-litellm work?
The tool standardizes API calls to over 100 LLM providers into a single OpenAI-compatible format. It supports direct SDK integration or deployment as a proxy server, with features like cost tracking, guardrails, load balancing, and logging.
Does BerriAI-litellm support self-hosting?
Yes, BerriAI-litellm is designed for self-hosting and offers an enterprise-ready proxy server deployment option. It can also be used as a Python SDK for direct library integration.
What providers are supported by BerriAI-litellm?
The tool supports over 100 LLM providers, including OpenAI, Anthropic, Gemini, Bedrock, Azure, Cohere, HuggingFace, VertexAI, vLLM, and Nvidia NIM, among others.
Can BerriAI-litellm handle rate limiting and budgeting?
Yes, BerriAI-litellm allows users to set budgets and rate limits per project, API key, or model, providing precise control over resource usage and costs.
