LiteLLM

What is LiteLLM?

LiteLLM is a powerful tool designed for load balancing across over 100 large language models (LLMs) in the OpenAI format. It seamlessly integrates with Azure OpenAI, Vertex AI, and Bedrock, providing users with the ability to handle loads, execute failover strategies, and keep track of their usage spend effortlessly.

What are the main features of LiteLLM?

1. Diverse Load Balancing: LiteLLM provides effective load balancing among more than 100 LLMs, ensuring that resources are optimally utilized.

2. Fallback Mechanisms: If one model does not respond as expected, LiteLLM will automatically redirect requests to alternative models for continuous operation.

3. Spend Tracking: Users can track their usage spend across different AI providers and models to manage costs effectively.

4. Open Source Options: LiteLLM offers an open-source version, allowing users to deploy and modify the software to meet their needs.

5. User-Friendly Integration: It supports easy integration with multiple platforms to enhance user experience and model deployment.

How to use LiteLLM?

To get started with LiteLLM, users can try the LiteLLM Cloud Free offering, enabling them to test the service without immediate financial commitment. For those who prefer a more customizable experience, they can deploy the open-source version. Users can create keys for different AI models, load balance requests, and keep track of their usage through the intuitive dashboard.

What is the pricing for LiteLLM?

LiteLLM offers a free cloud option for users to explore its features. Pricing for additional features and services may vary based on usage and specific needs. Interested customers can schedule a demo to better understand the potential costs associated with their unique use cases.

Helpful Tips for Using LiteLLM

• Start on the Free Plan: Begin with the free plan to explore LiteLLM’s capabilities without financial investment.

• Monitor Usage: Regularly track your spend to avoid unexpected charges and optimize your model choices based on performance.

• Utilize Fallbacks: Leverage fallback mechanisms to enhance application reliability and ensure seamless user experiences.

• Engage with the Community: Check LiteLLM's documentation and community forums for best practices and troubleshooting tips.

Frequently Asked Questions

Can I deploy LiteLLM on my own server?

Yes, LiteLLM offers an open-source version that can be deployed on your own server for more control and customization.

How does LiteLLM improve my AI workloads?

LiteLLM enhances AI workloads by managing load effectively, handling fallbacks automatically, and providing insights into spending across multiple AI services and models.

Is there support available for LiteLLM?

Yes, LiteLLM has extensive documentation and an active community support network where users can ask questions and share experiences.

How can I track my spending on LiteLLM?

LiteLLM includes built-in tracking features that allow you to monitor your usage and spending across various models effortlessly.

What should I do if I encounter issues with LiteLLM?

If you experience any difficulties, consult the detailed documentation for troubleshooting advice, or reach out to community forums for assistance.