Model Router Client Credentials

Overview

This example shows a backend service using OAuth client credentials to call the OpenAI-compatible Model Router.

Use this pattern for services, automation jobs, bots, and server-side applications that should authenticate as an app. The app receives a short-lived OAuth access token with the llm:proxy scope, then uses that token as the Model Router bearer token.

The full example is available at github.com/archestra-ai/examples/tree/main/model-router-client-credentials.

What the App Does

1. Uses an OAuth client created on the LLM Proxy page
2. Exchanges client_id and client_secret for an access token
3. Sends the access token to /v1/model-router/chat/completions

OAuth client credentials do not use a browser consent screen and do not inherit a user's Model Provider keys. Provider access comes from the OAuth client's provider key mappings.

Run the Example

Go to LLM Proxy, open the OAuth Clients tab, and create an OAuth client. Map the provider keys it can use, and copy the generated secret.

Then run:

git clone https://github.com/archestra-ai/examples
cd examples/model-router-client-credentials
cp .env.example .env

Set these values in .env:

OAUTH_CLIENT_ID=<client id>
OAUTH_CLIENT_SECRET=<client secret>
MODEL=openai:gpt-4o-mini

Install dependencies and run:

npm install
npm start

OAuth Routes Used

The example uses these Archestra OAuth routes:

The token exchange includes:

grant_type=client_credentials
client_id=<client id>
client_secret=<client secret>
scope=llm:proxy

Model Router Call

After token exchange, the app calls the OpenAI-compatible Model Router:

curl -X POST "http://localhost:9000/v1/model-router/chat/completions" \
  -H "Authorization: Bearer $ACCESS_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai:gpt-4o-mini",
    "messages": [{"role": "user", "content": "Hello"}]
  }'

The requested model prefix determines which provider mapping is needed on the OAuth client.