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🐳 Docker, Deploying LiteLLM Proxy

You can find the Dockerfile to build litellm proxy here

Quick Start

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

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

Run 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

Deploy with Database

We maintain a seperate Dockerfile for reducing build time when running LiteLLM proxy with a connected Postgres Database

docker pull docker pull ghcr.io/berriai/litellm-database:main-latest
docker run --name litellm-proxy \
-e DATABASE_URL=postgresql://<user>:<password>@<host>:<port>/<dbname> \
-p 4000:4000 \
ghcr.io/berriai/litellm-database:main-latest

Your OpenAI proxy server is now running on http://0.0.0.0:4000.

Platform-specific Guide

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
}'

Extras

Run with 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.

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