Litellm
Litellm is an open-source AI Gateway that enables users to call over 100 LLM APIs in OpenAI or native format. It features a Rust core with a Python SDK, providing cost tracking, guardrails, load balancing, and logging capabilities. The tool supports various LLM APIs, including Bedrock, Azure, OpenAI, Anthropic, VertexAI, vLLM, and Nvidia NIM. Litellm is designed to be fast and lightweight, making it an ideal solution for developers and organizations looking to integrate AI capabilities into their applications. With its robust features and extensive support for various LLM APIs, Litellm has gained popularity among developers, with over 63,000 stars on GitHub. The project is actively maintained, with regular updates and contributions from the community. Litellm's documentation and resources are also available, making it easier for users to get started and integrate the tool into their projects. Overall, Litellm is a powerful and flexible AI Gateway that provides a comprehensive solution for developers and organizations looking to leverage the capabilities of LLM APIs. The tool's architecture is designed to be scalable and efficient, allowing it to handle large volumes of requests and provide reliable performance. Additionally, Litellm's support for multiple LLM APIs enables users to choose the best model for their specific use case, ensuring optimal results and performance. With its strong community support and extensive documentation, Litellm is an excellent choice for developers and organizations looking to integrate AI capabilities into their applications.
- Category
- LLM
- Pricing
- Open Source
Problem solved
Developers and organizations face the challenge of integrating AI capabilities into their applications, which can be time-consuming and costly. Litellm solves this problem by providing a fast, lightweight, and scalable AI Gateway that enables users to call over 100 LLM APIs in OpenAI or native format. With its robust features and extensive support for various LLM APIs, Litellm makes it easier for developers and organizations to integrate AI capabilities into their applications, reducing the time and cost associated with developing and maintaining custom AI solutions.
Use cases
- Integrating AI capabilities into applications
- Calling LLM APIs in OpenAI or native format
- Cost tracking and guardrails for AI usage
- Load balancing and logging for AI workloads
- Support for multiple LLM APIs, including Bedrock, Azure, OpenAI, and Anthropic
Audience
- Developers
- ML Engineers
- Data Scientists
Pros
- Fast and lightweight
- Scalable and efficient
- Support for multiple LLM APIs
- Robust features and extensive documentation
Cons
- Limited support for certain LLM APIs
- Requires technical expertise to integrate and use
- May require additional infrastructure and resources to support large-scale AI workloads
Official website: https://github.com/BerriAI/litellm
Canonical LambdaBase page: https://www.lambdabase.com/tools/litellm