Integrating Databricks Genie API with API workflows

Databricks Genie enables natural language interaction with your enterprise data, allowing you to query, analyze, and act on datasets without needing to write code.

This guide provides a practical walkthrough of how to interact with a Databricks Genie API to get information based on a question input. It performs the following main actions:

• Initializes variables—Sets up necessary parameters like tokens, URLs, and IDs.
• Gets a token—Makes an HTTP POST request to obtain an access token for authentication.
• Starts a conversation—Sends the user question to the Genie API to initiate a conversation.
• Polls for message completion—Enters a Do While loop to repeatedly check the status of the Genie message until it is COMPLETED.

• Retrieves query results—Once the message is complete, it fetches the final query results from the Genie API and provides the retrieved data as the workflow output.

Requisitos previos

First, you need to have a Genie space called "Item Restrictions" in your Databricks workspace.

Its purpose is to reference shipping restrictions for different products and provide answers regarding shipping details.

1. Crea un flujo de trabajo de API.
2. Define workflow inputs. Open Data manager and add a new Inputs parameter with the following configuration:
   • Name—Question
   • Type—String
   • Mark it as Required.
3. Define workflow variables. Open Data manager > Variables, and add the following:
   • token (String)—Stores the authentication token required to access the Databricks Genie API.
   • conversation_id (String)—Tracks a specific conversation session with the Databricks Genie API. When you start a conversation, the API provides this ID, and you use it to refer to that ongoing conversation in subsequent requests.
   • message_id (String)—Refers to a specific message within a conversation. This ID is then used to retrieve the status and eventually the results of that particular message processing.
   • attachment_id (String)—Points to a specific attachment (which in this case holds the query result) associated with a message in the Genie API.
   • url (String)—Stores the base URL for the Databricks Genie API endpoint.
   • space_id (String)—Points to a specific space within Databricks Genie.
4. Add a HTTP activity to retrieve the access token and configure it as follows:
   • Display name—"Get token HTTP Request"
   • Método : POST
   • URL de solicitud : https://accounts.cloud.databricks.com/oidc/accounts/{account_id}/v1/token
   • Headers—

     {
     "Authorization": "Basic <your_basic_token>",
     "Content-Type": "application/x-www-form-urlencoded"
     }

   • Request body—

     "grant_type=client_credentials&scope=all-apis"

   The context output name for this activity is HTTP_Request_1.
5. Assign the token retrieved from the previous activity to your token variable. Add an Assign activity and configure it as follows:
   • To variable—token
   • Set value—$context.outputs.HTTP_Request_1.content.access_token

   The context output name HTTP_Request_1 may differ from the one used in your workflow.
6. Add a HTTP activity to start the conversation and configure it as follows:
   • Display name—"Start conversation HTTP Request"
   • Método : POST
   • Request URL—https://{your-databricks-instance}/api/2.0/genie/spaces/{space_id}/start-conversation, or build it with the Expression editor as

     $context.variables.url + "/api/2.0/genie/spaces/"+ $context.variables.space_id +"/start-conversation"

   • Headers—

     {"Authorization": "Bearer " + $context.variables.token}

   • Request body—

     {"content": $workflow.input.question}

   Ensure the output is saved. You can retrieve conversation_id and message_id from the output of this activity.

   The context output name for this activity is HTTP_Request_2.
7. Enter a loop to check the status of the Genie message until COMPLETED. Add a Do While activity and set the Condition to $context.outputs.HTTP_Request_3?.content?.status !== "COMPLETED", where HTTP_Request_3 refers to the Get message HTTP Request activity. This means the loop continues as long as the message status is not COMPLETED.
8. Inside the Do while loop:
   1. Add a HTTP activity for getting the last message and configure it as follows:
      • Display name—"Get message HTTP Request"
      • Método—GET
      • Request URL—https://{your-databricks-instance}/api/2.0/genie/spaces/{space_id}/conversations/{conversation_id}/messages/{message_id}, or build it with the Expression editor as

        [ $context.variables.url+"/api/2.0/genie/spaces/"+$context.variables.space_id+"/conversations/", $context.outputs.HTTP_Request_2.content.conversation_id, "/messages/", $context.outputs.HTTP_Request_2.content.message_id ].join('')

        Where HTTP_Request_2 refers to the Start conversation HTTP Request activity.
      • Headers—

        {"Authorization": "Bearer " + $context.variables.token}

      • Request body—

        {"content": $workflow.input.question}

      The context output name for this activity is HTTP_Request_3.
   2. Add an If activity immediately after the Get message HTTP Request acitvity, and set the Condition to $context.outputs.HTTP_Request_3?.content?.status === "COMPLETED", where HTTP_Request_3 refers to Get message HTTP Request activity.
   3. On the Then (true) branch, add an Assign activity and configure it as follows:
      • To variable—conversation_id
      • Set value—$context.outputs.HTTP_Request_3.content.conversation_id, where HTTP_Request_3 refers to Get message HTTP Request activity.
   4. Add another Assign activity:
      • To variable—message_id
      • Set value—$context.outputs.HTTP_Request_3.content.message_id, where HTTP_Request_3 refers to Get message HTTP Request activity.
   5. Add another Assign activity:
      • To variable—attachment_id
      • Set value—$context.outputs.HTTP_Request_3.content.attachments[0].attachment_id, where HTTP_Request_3 refers to Get message HTTP Request activity.
   6. On the Else branch, add a Wait activity and set duration to one second. This instructs the workflow to wait for a short period before retrying.
9. Exit the loop and add a HTTP activity to execute the SQL query and configure it as follows:
   • Display name—"Execute SQL HTTP Request"
   • Método—GET
   • Request URL—https://{your-databricks-instance}/api/2.0/genie/spaces/{space_id}/conversations/{conversation_id}/messages/{message_id}/attachments/{attachment_id}/query-result, or build it with the Expression editor as

     $context.variables.url+"/api/2.0/genie/spaces/"+$context.variables.space_id+"/conversations/" + $context.variables.conversation_id + "/messages/"  + $context.variables.message_id + "/attachments/" +  $context.variables.attachment_id + "/query-result"

   • Headers—

     {"Authorization": "Bearer " + $context.variables.token}

   The context output name for this activity is HTTP_Request_3.
10. Define workflow outputs. Open Data manager and add the following Inputs parameters:
    • Name—row_count
    • Type—Number
    • Mark it as Required.

    y

    • Name—data_array
    • Type—Array
    • Mark it as Required.
11. Add a Response activity and configure it as follows:
    • Response—

      {
        "row_count": -75647404.57028332,
        "data_array": [
          [],
          [],
          [
            "ut et aute officia",
            "ex ut",
            "nisi non ut Lorem velit",
            "aliquip Duis consectetur irure id"
          ]
        ]
      }

12. Run the integration. Once deployed, the Workflow can be invoked with any natural language query. An example question could be : "Are there any restrictions to ship SKU ENB-SP-200 to Cuba?"

Key take-aways:

1. Simple setup – API Workflow provides a fast way to connect Genie without custom code.
2. Consistent schema – Genie responses are JSON-based, easy to parse into UiPath.
3. Scalable integration – Responses can be used in Apps, long-running workflows, or orchestrations.
4. Rapid prototyping – Setup for working automation takes minutes, allowing quick validation of use cases.