# Databricks (https://www.librechat.ai/docs/configuration/librechat_yaml/ai_endpoints/databricks)

Databricks serves foundation models and your own fine-tuned models through Mosaic AI Model Serving, which exposes an OpenAI-compatible serving endpoint.

## Get an API key

[Sign up for Databricks](https://www.databricks.com/try-databricks#account) and generate a personal access token from your workspace. Add it to your `.env` file:

```bash filename=".env"
DATABRICKS_API_KEY=your-api-key
```

## Configuration

Add the endpoint under `endpoints.custom` in your `librechat.yaml`:

```yaml filename="librechat.yaml"
    - name: 'Databricks'
      apiKey: '${DATABRICKS_API_KEY}'
      baseURL: 'https://your_databricks_serving_endpoint_url_here_ending_with/invocations'
      models:
        default: [
          "databricks-meta-llama-3-70b-instruct",
        ]
        fetch: false
      titleConvo: true
      titleModel: 'current_model'
      directEndpoint: true # required
      titleMessageRole: 'user' # required
```

## Notes

- Databricks exposes a full completions endpoint ending in `invocations` for `serving-endpoints`, so [directEndpoint](/docs/configuration/librechat_yaml/object_structure/custom_endpoint#directendpoint) is required.
- Set [titleMessageRole](/docs/configuration/librechat_yaml/object_structure/custom_endpoint#titlemessagerole) to `user` for title generation. A standalone `system` message is not supported.