llm-litellm 0.2.0

LLM plugin for LiteLLM proxy server

llm-litellm

LLM plugin for models hosted by LiteLLM proxy server.

LiteLLM is a self-hosted proxy server that provides a unified interface to 100+ LLMs including OpenAI, Anthropic, Cohere, Replicate, PaLM, and more.

Installation

First, install the LLM command-line utility.

Now install this plugin in the same environment as LLM:

llm install llm-litellm

Updating to New Versions

To update the plugin to the latest version:

llm install --upgrade llm-litellm

Or using pip directly:

pip install --upgrade llm-litellm

Installing from Source

For development or to install from source:

pip install -e .

Configuration

1. Set up LiteLLM Server

First, you need to have a LiteLLM server running. You can set it up by:

pip install litellm[proxy]
litellm --model gpt-3.5-turbo
# This starts the server on http://localhost:4000

Or use Docker:

docker run -p 4000:4000 -e OPENAI_API_KEY=your-key ghcr.io/berriai/litellm:main-latest --model gpt-3.5-turbo

2. Set Environment Variable

Set the LITELLM_URL environment variable to point to your LiteLLM server:

export LITELLM_URL=http://localhost:4000

3. Set API Key (Optional)

If your LiteLLM server requires authentication, set the API key:

llm keys set litellm
# Enter your LiteLLM API key when prompted

Usage

Once configured, you can use any model supported by your LiteLLM server.

List Available Models

To see all available models:

llm models list

You should see models prefixed with litellm::

litellm: gpt-3.5-turbo
litellm: gpt-4
litellm: claude-3-sonnet
...

You can also use the plugin-specific command:

llm litellm models

Basic Usage

# Use a specific model
llm -m litellm/gpt-3.5-turbo "Hello, world!"

# Use with different models
llm -m litellm/claude-3-sonnet "Explain quantum computing"
llm -m litellm/gpt-4 "Write a short story"

Advanced Usage

# Set temperature and other parameters
llm -m litellm/gpt-3.5-turbo -o temperature 0.9 -o max_tokens 500 "Be creative!"

# Use with streaming
llm -m litellm/gpt-4 "Write a long explanation" --stream

# Conversation mode
llm -m litellm/claude-3-sonnet -c "Let's discuss Python programming"

Model Aliases

You can set shorter aliases for frequently used models:

llm aliases set gpt4 litellm/gpt-4
llm aliases set claude litellm/claude-3-sonnet

Now you can use:

llm -m gpt4 "Hello!"
llm -m claude "Explain this code" < script.py

Plugin Commands

Check Server Status

llm litellm status

This will check if your LiteLLM server is running and accessible.

List Models

# Human-readable format
llm litellm models

# JSON format
llm litellm models --json

Supported Models

The plugin supports any model that your LiteLLM server is configured to handle. Common models include:

• OpenAI: gpt-4, gpt-3.5-turbo, gpt-4-turbo
• Anthropic: claude-3-opus, claude-3-sonnet, claude-3-haiku
• Google: gemini-pro, gemini-pro-vision
• Cohere: command-r, command-r-plus
• Meta: llama-2-70b, llama-2-13b
• Mistral: mistral-7b, mistral-medium
• And many more...

Check your LiteLLM server configuration for the exact models available.

Configuration Options

The plugin supports all standard LLM options:

• temperature: Controls randomness (0.0-2.0)
• max_tokens: Maximum tokens to generate
• top_p: Top-p sampling parameter
• frequency_penalty: Frequency penalty (-2.0 to 2.0)
• presence_penalty: Presence penalty (-2.0 to 2.0)

Example:

llm -m litellm/gpt-3.5-turbo \
    -o temperature 0.7 \
    -o max_tokens 1000 \
    -o top_p 0.9 \
    "Generate creative content"

Troubleshooting

Common Issues

1. "LITELLM_URL environment variable is required"

   • Make sure you've set the LITELLM_URL environment variable
   • Verify your LiteLLM server is running and accessible

2. No models showing up

   • Check server status: llm litellm status
   • Verify the URL is correct (should include protocol: http:// or https://)
   • Test the server directly: curl http://localhost:4000/health

3. Connection errors

   • Check that your LiteLLM server is running
   • Verify firewall settings allow connections to the server
   • Test with: curl http://localhost:4000/v1/models

4. Authentication errors

   • If your LiteLLM server requires authentication, set the key: llm keys set litellm
   • Check your LiteLLM server configuration for authentication requirements

5. Model not found

   • Verify the model is configured in your LiteLLM server
   • Check available models: llm litellm models
   • Ensure the model name matches exactly

Debug Mode

For debugging, you can check what models are available:

# Check server status
llm litellm status

# List all models
llm litellm models --json

# Test a simple query
llm -m litellm/gpt-3.5-turbo "test" -v

Examples

Setting up with Different Providers

OpenAI Models

export OPENAI_API_KEY=your-key
litellm --model gpt-3.5-turbo --model gpt-4
export LITELLM_URL=http://localhost:4000
llm -m litellm/gpt-3.5-turbo "Hello!"

Anthropic Models

export ANTHROPIC_API_KEY=your-key
litellm --model claude-3-sonnet --model claude-3-haiku
export LITELLM_URL=http://localhost:4000
llm -m litellm/claude-3-sonnet "Hello!"

Multiple Providers

export OPENAI_API_KEY=your-openai-key
export ANTHROPIC_API_KEY=your-anthropic-key
litellm --model gpt-4 --model claude-3-sonnet --model gemini-pro
export LITELLM_URL=http://localhost:4000
llm -m litellm/gpt-4 "Compare yourself to Claude"

Development

To set up this plugin locally, first checkout the code. Then create a new virtual environment:

cd llm-litellm
python3 -m venv venv
source venv/bin/activate

Install the plugin in development mode:

pip install -e '.[test]'

To run the tests:

pytest

License

Apache License 2.0