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🐳 Docker, Deploying LiteLLM Proxy

Dockerfile​

You can find the Dockerfile to build litellm proxy here

Quick Start Docker Image: Github Container Registry​

Pull the litellm ghcr docker image​

See the latest available ghcr docker image here: https://github.com/berriai/litellm/pkgs/container/litellm

docker pull ghcr.io/berriai/litellm:main-latest

Run the Docker Image​

docker run ghcr.io/berriai/litellm:main-latest

Run the Docker Image with LiteLLM CLI args​

See all supported CLI args here:

Here's how you can run the docker image and pass your config to litellm

docker run ghcr.io/berriai/litellm:main-latest --config your_config.yaml

Here's how you can run the docker image and start litellm on port 8002 with num_workers=8

docker run ghcr.io/berriai/litellm:main-latest --port 8002 --num_workers 8

Run the Docker Image using docker compose​

Step 1

Here's an example docker-compose.yml file

version: "3.9"
services:
  litellm:
    build:
      context: .
        args:
          target: runtime
    image: ghcr.io/berriai/litellm:main-latest
    ports:
      - "8000:8000" # Map the container port to the host, change the host port if necessary
    volumes:
      - ./litellm-config.yaml:/app/config.yaml # Mount the local configuration file
    # You can change the port or number of workers as per your requirements or pass any new supported CLI augument. Make sure the port passed here matches with the container port defined above in `ports` value
    command: [ "--config", "/app/config.yaml", "--port", "8000", "--num_workers", "8" ]

# ...rest of your docker-compose config if any

Step 2

Create a litellm-config.yaml file with your LiteLLM config relative to your docker-compose.yml file.

Check the config doc here

Step 3

Run the command docker-compose up or docker compose up as per your docker installation.

Use -d flag to run the container in detached mode (background) e.g. docker compose up -d

Your LiteLLM container should be running now on the defined port e.g. 8000.

Deploy on Render https://render.com/​

Deploy on Google Cloud Run​

Click the button to deploy to Google Cloud Run

Deploy

Testing your deployed proxy​

Assuming the required keys are set as Environment Variables

https://litellm-7yjrj3ha2q-uc.a.run.app is our example proxy, substitute it with your deployed cloud run app

curl https://litellm-7yjrj3ha2q-uc.a.run.app/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
     "model": "gpt-3.5-turbo",
     "messages": [{"role": "user", "content": "Say this is a test!"}],
     "temperature": 0.7
   }'

Deploy on Railway https://railway.app​

Step 1: Click the button to deploy to Railway

Deploy on Railway

Step 2: Set PORT = 4000 on Railway Environment Variables

LiteLLM Proxy Performance​

LiteLLM proxy has been load tested to handle 1500 req/s.

Throughput - 30% Increase​

LiteLLM proxy + Load Balancer gives 30% increase in throughput compared to Raw OpenAI API

Latency Added - 0.00325 seconds​

LiteLLM proxy adds 0.00325 seconds latency as compared to using the Raw OpenAI API