Cloudera Docs

Configuring RAG Studio

After launching RAG Studio, an initial configuration is required, with optional settings available for additional customization. Without this configuration, the Studio will not be able to access any AI models.

  1. In the Cloudera console, click the Cloudera AI tile.

    The Cloudera AI Workbenches page displays.

  2. Click on the name of the workbench.

    The workbenches Home page displays.

  3. Click Projects, and then select the required Project.

    In the left navigation pane, the new AI Studios option is displayed.

  4. Click AI Studios and select RAG Studio.

    The RAG Studio page is displayed.

    The Setting page is displayed when opening up the RAG Studio for the first time. If the Setting page is not displayed, click on Settings in the top-right corner.The following settings are available:

    1. Optional: Enable the Enhanced PDF Processing option for better text extraction, however, note that this feature requires at least one GPU and at least 16GB of RAM and can significantly slow down document parsing.
    2. Choose from the following File Storage options:

      • Project Filesystem: Use the Cloudera AI Project filesystem for file storage.

      • AWS S3: Select an existing Amazon S3 bucket and provide the bucket name and prefix to be used for all S3 paths.
    3. Select one of the following Model Providers:
      • Cloudera AI: No authentication required, but you will need to obtain the domain name of the Cloudera AI Inference service. Note, that the domain must be in the same Cloudera environment as the Cloudera AI Workbench that the studio is running in. For more details, see Preparing to interact with the Cloudera AI Inference service API.
      • AWS Bedrock: Requires authentication:
        • AWS Region: Choose the AWS region to use.
        • AWS Access Key ID: Provide the Access Key ID for authentication.
        • AWS Secret Access Key: Provide the Secret Access Key for authentication.
      • Azure OpenAI: Requires configuration and authentication:
        • Azure OpenAI Endpoint: Find the endpoint of the Azure OpenAI service in the Azure portal.
        • API Version: Find the API Version of the Azure OpenAI service in the Azure portal.
        • Authentication Azure OpenAI Key: Provide the Azure OpenAI Key for authentication.

After the initial configuration, the RAG Studio application will restart in order to access the model providers. This restart must be completed, after which the studio is ready to use.