LiteLLM
LiteLLM is an open-source library and proxy server that provides a unified API for interacting with 100+ large language models from various providers using the OpenAI format.
https://litellm.ai/
Product Information
Updated:Dec 9, 2024
LiteLLM Monthly Traffic Trends
LiteLLM reached 172,140 visits in November, showing a 4.8% increase. Without specific updates or market activities for November 2024, this slight growth is likely due to the platform's ongoing features such as load balancing, fallback mechanisms, and budget management.
What is LiteLLM
LiteLLM is a powerful tool designed to simplify the integration and management of large language models (LLMs) in AI applications. It serves as a universal interface for accessing LLMs from multiple providers like OpenAI, Azure, Anthropic, Cohere, and many others. LiteLLM abstracts away the complexities of dealing with different APIs, allowing developers to interact with diverse models using a consistent OpenAI-compatible format. This open-source solution offers both a Python library for direct integration and a proxy server for managing authentication, load balancing, and spend tracking across multiple LLM services.
Key Features of LiteLLM
LiteLLM is a unified API and proxy server that simplifies integration with over 100 large language models (LLMs) from various providers like OpenAI, Azure, Anthropic, and more. It offers features such as authentication management, load balancing, spend tracking, and error handling, all using a standardized OpenAI-compatible format. LiteLLM enables developers to easily switch between or combine different LLM providers while maintaining consistent code.
Unified API: Provides a single interface to interact with 100+ LLMs from different providers using the OpenAI format
Proxy Server: Manages authentication, load balancing, and spend tracking across multiple LLM providers
Virtual Keys and Budgets: Allows creation of project-specific API keys and setting of usage limits
Error Handling and Retries: Automatically handles errors and retries failed requests, improving robustness
Logging and Observability: Integrates with various logging tools for monitoring LLM usage and performance
Use Cases of LiteLLM
Multi-Provider AI Applications: Develop applications that can seamlessly switch between or combine multiple LLM providers
Cost Optimization: Implement intelligent routing and load balancing to optimize LLM usage costs
Enterprise LLM Management: Centralize LLM access, authentication, and usage tracking for large organizations
AI Research and Experimentation: Easily compare and benchmark different LLMs using a consistent interface
Pros
Simplifies integration with multiple LLM providers
Improves code maintainability with standardized format
Offers robust features for enterprise-level LLM management
Cons
May introduce slight latency due to proxy layer
Requires additional setup and configuration
Limited customization for provider-specific features
How to Use LiteLLM
Install LiteLLM: Install the LiteLLM library using pip: pip install litellm
Import and set up environment variables: Import litellm and set up environment variables for API keys: import litellm, os; os.environ['OPENAI_API_KEY'] = 'your-api-key'
Make an API call: Use the completion() function to make an API call: response = litellm.completion(model='gpt-3.5-turbo', messages=[{'role': 'user', 'content': 'Hello'}])
Handle streaming responses: For streaming responses, set stream=True: response = litellm.completion(model='gpt-3.5-turbo', messages=[{'role': 'user', 'content': 'Hello'}], stream=True)
Set up error handling: Use try-except blocks with OpenAIError to handle exceptions: try: litellm.completion(...) except OpenAIError as e: print(e)
Configure callbacks: Set up callbacks for logging: litellm.success_callback = ['helicone', 'langfuse']
Deploy LiteLLM Proxy: To deploy the LiteLLM proxy server, use Docker: docker run -e LITELLM_MASTER_KEY='sk-1234' ghcr.io/berriai/litellm:main
Configure model routing: Create a config.yaml file to set up model routing and API keys for different providers
Use the proxy server: Make API calls to your deployed LiteLLM proxy using the OpenAI SDK or curl commands
LiteLLM FAQs
LiteLLM is a unified API and proxy server that allows developers to interact with over 100 different LLM providers (like OpenAI, Azure, Anthropic, etc.) using a standardized OpenAI-compatible format. It simplifies LLM integration by providing features like load balancing, spend tracking, and consistent error handling across providers.
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Analytics of LiteLLM Website
LiteLLM Traffic & Rankings
172.1K
Monthly Visits
#261898
Global Rank
#5713
Category Rank
Traffic Trends: May 2024-Nov 2024
LiteLLM User Insights
00:02:41
Avg. Visit Duration
2.47
Pages Per Visit
44.83%
User Bounce Rate
Top Regions of LiteLLM
US: 14.67%
IN: 7.58%
CN: 7.15%
TW: 6.69%
GB: 5.19%
Others: 58.71%
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