> For the complete documentation index, see [llms.txt](https://docs.probe.splx.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.probe.splx.ai/ai-red-teaming/probe/target/index/databricks.md).

# Databricks

## Selecting the Connection Type

Once you have [selected your connection type](/ai-red-teaming/probe/target/add-target/integration-setup.md#selecting-a-connection-type), a configuration tab will appear on the next step, prompting you to input the required connection details.

## Integration Setup

<figure><img src="/files/WqzXfYrqINDTDASPxCnj" alt=""><figcaption><p>Figure 1: Databricks Integration Example</p></figcaption></figure>

* **System Prompt** - Your application’s system prompt. It sets the initial instructions or context for the AI model, defines the behavior, tone, and specific guidelines the AI should follow while interacting. For best practices, refer to the [OpenAI documentation on prompt engineering](https://platform.openai.com/docs/guides/prompt-engineering).
* **Workspace URL** - The base URL of your Databricks workspace. Open your Databricks workspace in the [browser and copy the URL.](https://docs.databricks.com/aws/en/workspace/workspace-details)
* **Authentication** - Supported authentication methods are **Personal Access Token** and **Service Principal using OAuth**
  * **Personal Access Token -** For authentication with PAT, an access token needs to be provided, which can be [generated in the Databricks platform.](https://docs.databricks.com/aws/en/dev-tools/auth/pat)
  * **Service Principal using OAuth -** For authentication with OAuth, a client ID and client secret need to be provided, which can be [generated in the Databricks platform](https://docs.databricks.com/aws/en/dev-tools/auth/oauth-m2m#step-4-use-oauth-m2m-authentication).
* **Model** - The Databricks model endpoint name. Available models can be found on the **Serving** page under the **Machine Learning** section in the Databricks platform sidebar. More information about available models can be found in the [Databricks documentation.](https://docs.databricks.com/aws/en/machine-learning/model-serving/)


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