ai-workspace-services/litellm

Fork 0

Kowyo 858f557bce docs: use docker compose instead of docker-compose

2025-09-29 11:59:53 +00:00

13 KiB

Raw Blame History

import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';

E2E Tutorial

End-to-End tutorial for LiteLLM Proxy to:

Add an Azure OpenAI model
Make a successful /chat/completion call
Generate a virtual key
Set RPM limit on virtual key

Pre-Requisites

Install LiteLLM Docker Image OR LiteLLM CLI (pip package)

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

See all docker images

$ pip install 'litellm[proxy]'

Use this docker compose to spin up the proxy with a postgres database running locally.

# Get the docker compose file
curl -O https://raw.githubusercontent.com/BerriAI/litellm/main/docker-compose.yml

# Add the master key - you can change this after setup
echo 'LITELLM_MASTER_KEY="sk-1234"' > .env

# Add the litellm salt key - you cannot change this after adding a model
# It is used to encrypt / decrypt your LLM API Key credentials
# We recommend - https://1password.com/password-generator/ 
# password generator to get a random hash for litellm salt key
echo 'LITELLM_SALT_KEY="sk-1234"' >> .env

source .env

# Start
docker compose up

1. Add a model

Control LiteLLM Proxy with a config.yaml file.

Setup your config.yaml with your azure model.

Note: When using the proxy with a database, you can also just add models via UI (UI is available on /ui route).

model_list:
  - model_name: gpt-4o
    litellm_params:
      model: azure/my_azure_deployment
      api_base: os.environ/AZURE_API_BASE
      api_key: "os.environ/AZURE_API_KEY"
      api_version: "2025-01-01-preview" # [OPTIONAL] litellm uses the latest azure api_version by default

Model List Specification

model_name (str) - This field should contain the name of the model as received.
litellm_params (dict) See All LiteLLM Params
- model (str) - Specifies the model name to be sent to litellm.acompletion / litellm.aembedding, etc. This is the identifier used by LiteLLM to route to the correct model + provider logic on the backend.
- api_key (str) - The API key required for authentication. It can be retrieved from an environment variable using os.environ/.
- api_base (str) - The API base for your azure deployment.
- api_version (str) - The API Version to use when calling Azure's OpenAI API. Get the latest Inference API version here.

Useful Links

2. Make a successful /chat/completion call

LiteLLM Proxy is 100% OpenAI-compatible. Test your azure model via the /chat/completions route.

2.1 Start Proxy

Save your config.yaml from step 1. as litellm_config.yaml.

docker run \
    -v $(pwd)/litellm_config.yaml:/app/config.yaml \
    -e AZURE_API_KEY=d6*********** \
    -e AZURE_API_BASE=https://openai-***********/ \
    -p 4000:4000 \
    ghcr.io/berriai/litellm:main-latest \
    --config /app/config.yaml --detailed_debug

# RUNNING on http://0.0.0.0:4000

$ litellm --config /app/config.yaml --detailed_debug

Confirm your config.yaml got mounted correctly

Loaded config YAML (api_key and environment_variables are not shown):
{
"model_list": [
{
"model_name ...

2.2 Make Call

curl -X POST 'http://0.0.0.0:4000/chat/completions' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer sk-1234' \
-d '{
    "model": "gpt-4o",
    "messages": [
      {
        "role": "system",
        "content": "You are an LLM named gpt-4o"
      },
      {
        "role": "user",
        "content": "what is your name?"
      }
    ]
}'

Expected Response

{
  "id": "chatcmpl-BcO8tRQmQV6Dfw6onqMufxPkLLkA8",
  "created": 1748488967,
  "model": "gpt-4o-2024-11-20",
  "object": "chat.completion",
  "system_fingerprint": "fp_ee1d74bde0",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "My name is **gpt-4o**! How can I assist you today?",
        "role": "assistant",
        "tool_calls": null,
        "function_call": null,
        "annotations": []
      }
    }
  ],
  "usage": {
    "completion_tokens": 19,
    "prompt_tokens": 28,
    "total_tokens": 47,
    "completion_tokens_details": {
      "accepted_prediction_tokens": 0,
      "audio_tokens": 0,
      "reasoning_tokens": 0,
      "rejected_prediction_tokens": 0
    },
    "prompt_tokens_details": {
      "audio_tokens": 0,
      "cached_tokens": 0
    }
  },
  "service_tier": null,
  "prompt_filter_results": [
    {
      "prompt_index": 0,
      "content_filter_results": {
        "hate": {
          "filtered": false,
          "severity": "safe"
        },
        "self_harm": {
          "filtered": false,
          "severity": "safe"
        },
        "sexual": {
          "filtered": false,
          "severity": "safe"
        },
        "violence": {
          "filtered": false,
          "severity": "safe"
        }
      }
    }
  ]
}

Useful Links

3. Generate a virtual key

Track Spend, and control model access via virtual keys for the proxy

3.1 Set up a Database

Requirements

Need a postgres database (e.g. Supabase, Neon, etc)

model_list:
  - model_name: gpt-4o
    litellm_params:
      model: azure/my_azure_deployment
      api_base: os.environ/AZURE_API_BASE
      api_key: "os.environ/AZURE_API_KEY"
      api_version: "2025-01-01-preview" # [OPTIONAL] litellm uses the latest azure api_version by default

general_settings: 
  master_key: sk-1234 
  database_url: "postgresql://<user>:<password>@<host>:<port>/<dbname>" # 👈 KEY CHANGE

Save config.yaml as litellm_config.yaml (used in 3.2).

What is general_settings?

These are settings for the LiteLLM Proxy Server.

See All General Settings here.

master_key (str)
- Description:
  - Set a master key, this is your Proxy Admin key - you can use this to create other keys (🚨 must start with sk-).
- Usage:
  - Set on config.yaml set your master key under general_settings:master_key, example - master_key: sk-1234
  - Set env variable set LITELLM_MASTER_KEY
database_url (str)
- Description:
  - Set a database_url, this is the connection to your Postgres DB, which is used by litellm for generating keys, users, teams.
- Usage:
  - Set on config.yaml set your database_url under general_settings:database_url, example - database_url: "postgresql://..."
  - Set DATABASE_URL=postgresql://<user>:<password>@<host>:<port>/<dbname> in your env

3.2 Start Proxy

docker run \
    -v $(pwd)/litellm_config.yaml:/app/config.yaml \
    -e AZURE_API_KEY=d6*********** \
    -e AZURE_API_BASE=https://openai-***********/ \
    -p 4000:4000 \
    ghcr.io/berriai/litellm:main-latest \
    --config /app/config.yaml --detailed_debug

3.3 Create Key w/ RPM Limit

Create a key with rpm_limit: 1. This will only allow 1 request per minute for calls to proxy with this key.

curl -L -X POST 'http://0.0.0.0:4000/key/generate' \
-H 'Authorization: Bearer sk-1234' \
-H 'Content-Type: application/json' \
-d '{
    "rpm_limit": 1
}'

See full API Spec

Expected Response

{
    "key": "sk-12..."
}

3.4 Test it!

Use your virtual key from step 3.3

1st call - Expect to work!

curl -X POST 'http://0.0.0.0:4000/chat/completions' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer sk-12...' \
-d '{
    "model": "gpt-4o",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful math tutor. Guide the user through the solution step by step."
      },
      {
        "role": "user",
        "content": "how can I solve 8x + 7 = -23"
      }
    ]
}'

Expected Response

{
    "id": "chatcmpl-2076f062-3095-4052-a520-7c321c115c68",
    "choices": [
        ...
}

2nd call - Expect to fail!

Why did this call fail?

We set the virtual key's requests per minute (RPM) limit to 1. This has now been crossed.

curl -X POST 'http://0.0.0.0:4000/chat/completions' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer sk-12...' \
-d '{
    "model": "gpt-4o",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful math tutor. Guide the user through the solution step by step."
      },
      {
        "role": "user",
        "content": "how can I solve 8x + 7 = -23"
      }
    ]
}'

Expected Response

{
  "error": {
    "message": "LiteLLM Rate Limit Handler for rate limit type = key. Crossed TPM / RPM / Max Parallel Request Limit. current rpm: 1, rpm limit: 1, current tpm: 348, tpm limit: 9223372036854775807, current max_parallel_requests: 0, max_parallel_requests: 9223372036854775807",
    "type": "None",
    "param": "None",
    "code": "429"
  }
}

Useful Links

Troubleshooting

Non-root docker image?

If you need to run the docker image as a non-root user, use this.

SSL Verification Issue / Connection Error.

If you see

ssl.SSLCertVerificationError: [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: self-signed certificate in certificate chain (_ssl.c:1006)

Connection Error.

You can disable ssl verification with:

model_list:
  - model_name: gpt-4o
    litellm_params:
      model: azure/my_azure_deployment
      api_base: os.environ/AZURE_API_BASE
      api_key: "os.environ/AZURE_API_KEY"
      api_version: "2025-01-01-preview"

litellm_settings:
    ssl_verify: false # 👈 KEY CHANGE

(DB) All connection attempts failed

If you see:

httpx.ConnectError: All connection attempts failed                                                                        
                                                                                                                         
ERROR:    Application startup failed. Exiting.                                                                            
3:21:43 - LiteLLM Proxy:ERROR: utils.py:2207 - Error getting LiteLLM_SpendLogs row count: All connection attempts failed

This might be a DB permission issue.

Validate db user permission issue

Try creating a new database.

STATEMENT: CREATE DATABASE "litellm"

If you get:

ERROR: permission denied to create

This indicates you have a permission issue.

Grant permissions to your DB user

It should look something like this:

psql -U postgres

CREATE DATABASE litellm;

On CloudSQL, this is:

GRANT ALL PRIVILEGES ON DATABASE litellm TO your_username;

What is litellm_settings?

LiteLLM Proxy uses the LiteLLM Python SDK for handling LLM API calls.

litellm_settings are module-level params for the LiteLLM Python SDK (equivalent to doing litellm.<some_param> on the SDK). You can see all params here

Support & Talk with founders

Schedule Demo 👋
Community Discord 💭
Community Slack 💭
Our emails ✉️ ishaan@berri.ai / krrish@berri.ai

13 KiB Raw Blame History

E2E Tutorial

Pre-Requisites

1. Add a model

Model List Specification

Useful Links

2. Make a successful /chat/completion call

2.1 Start Proxy

2.2 Make Call

Useful Links

3. Generate a virtual key

3.1 Set up a Database

3.2 Start Proxy

3.3 Create Key w/ RPM Limit

3.4 Test it!

Useful Links

Troubleshooting

Non-root docker image?

SSL Verification Issue / Connection Error.

(DB) All connection attempts failed

Support & Talk with founders

13 KiB

Raw Blame History