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Documentation Index

Fetch the complete documentation index at: https://private-04b27de1.mintlify.app/llms.txt

Use this file to discover all available pages before exploring further.

Before starting this guide, ensure you have completed the Installation Guide and installed all required dependencies.

Run LiteLLM as a Docker Container

To connect LiteLLM with an Azure model, configure your litellm_config.yaml as follows:
model_list:
  - model_name: azure-gpt-4o-mini
    litellm_params:
      model: azure/gpt-4o-mini
      api_base: os.environ/AZURE_API_BASE
      api_key: os.environ/AZURE_API_KEY
      api_version: os.environ/AZURE_API_VERSION
Before starting the container, ensure you have correctly set the following environment variables:
  • AZURE_API_KEY
  • AZURE_API_BASE
  • AZURE_API_VERSION
Run the container using:
docker run -v $(pwd)/litellm_config.yaml:/app/config.yaml  \
-e AZURE_API_KEY="your_api_key" -e AZURE_API_BASE="your_api_base_url" -e AZURE_API_VERSION="your_api_version"\
-p 4000:4000 ghcr.io/berriai/litellm:main-latest --config /app/config.yaml --detailed_debug
Once running, LiteLLM will be accessible at: http://0.0.0.0:4000 To confirm that config.yaml is correctly mounted, check the logs:
...
13:49:43 - LiteLLM Proxy:DEBUG: proxy_server.py:1507 - loaded config={
    "model_list": [
        {
            "model_name": "azure-gpt-4o-mini",
            "litellm_params": {
                "model": "azure/gpt-4o-mini",
                "api_base": "os.environ/AZURE_API_BASE",
                "api_key": "os.environ/AZURE_API_KEY",
                "api_version": "os.environ/AZURE_API_VERSION"
            }
        }
    ]
}
...

Initiate Chat

To communicate with LiteLLM, configure the model in config_list and initiate a chat session.
from autogen import AssistantAgent, UserProxyAgent, LLMConfig

llm_config = LLMConfig(
    model="azure-gpt-4o-mini",
    base_url="http://0.0.0.0:4000",
)

user_proxy = UserProxyAgent(
    name="user_proxy",
    human_input_mode="NEVER",
)
with llm_config:
    assistant = AssistantAgent(name="assistant")

user_proxy.initiate_chat(
    recipient=assistant,
    message="Solve the following equation: 2x + 3 = 7",
    max_turns=3,
)