How to Connect SquirroGPT to a Microsoft Azure LLM

Profile: System Administrator

This page describes how system or project administrators, or anyone with access to the Server or Setup spaces of a SquirroGPT project, can connect their SquirroGPT application to a Microsoft Azure LLM.

There are two steps involved in connecting to a Microsoft Azure LLM:

1. Obtain Microsoft Azure LLM information via the Microsoft Developer Portal

2. Configure your Squirro project or server settings to use your preferred Microsoft Azure LLM.

1 - Obtain Microsoft Azure LLM Information

To set up SquirroGPT access to a specific Microsoft Azure LLM, you will need information about your OpenAI resource and model deployment from your Microsoft Developer account.

Note

This guide assumes you have already set up your resource and deployed a model. For information on creating a resource and deploying a model within it, see Microsoft’s official guide to Creating and Deploying an OpenAI Service Resource.

Your deployed model information will be used to authenticate your SquirroGPT application when you attempt to connect it. You will need to take note of the following information from your Microsoft Developer account:

• Deployment name

• OpenAI API base

• OpenAI API key

• OpenAI API version

To access this information, follow the steps below:

1. Log in to the Microsoft Developer Portal with your Microsoft ID at https://portal.azure.com/.

2. Locate and click on your OpenAI resource that contains your deployed model.

3. Click Model Deployments.

4. Click Manage Deployments.

5. Click your deployment name. (In the example below, it’s Swiss_North).

6. Click Edit Deployment.

7. Take note of your Deployment name.

8. Return to https://portal.azure.com/.

9. Click Overview in the left navigation menu.

   

10. Next to Endpoints, click Click here to view endpoints.

11. Take note of your KEY 1 value. This is your OpenAI API key.

    

12. Take note of your endpoint. This is your OpenAI API base.

    

2- Configure Your Squirro Server or Project Settings

You have two options in terms of configuring usage of the Microsoft Azure LLM:

• Configure your Squirro instance at the server level, meaning all existing and future SquirroGPT projects will use the Azure LLM you specify.

• Configure your SquirroGPT application at the project level, meaning only that particular project you are working within will use the Azure LLM you specify.

Tip

Typically, Squirro recommends configuring your Squirro instance at the server level.

Configuring Your Squirro Instance at the Server Level

To configure your Squirro instance at the server level, follow the steps below:

1. Log in to your Squirro instance.

2. Click on Server in the spaces navigation bar.

3. Click on Configuration.

4. Click on the plus icon to create a new configuration. (See note below if you have previously created a configuration.)

5. Enter the following name: genai.sqgpt.settings.

6. Select Dictionary as the data type.

7. Paste the following for the value:

{
    "llm": {
        "deployment_name": "<value from Step 1>",
        "kind": "azure",
        "openai_api_base": "<value from Step 1>",
        "openai_api_key": "<value from Step 1>",
        "openai_api_version": "2023-05-15",
        "request_timeout_s": [
            5,
            60
        ]
    }
}

Note

If you have already created the genai.sqgpt.settings configuration, you can simply edit the existing configuration and paste the above value.

Configuring Your SquirroGPT Application at the Project Level

To configure your SquirroGPT application at the project level, follow the steps below:

1. Log in to your Squirro instance.

2. Click on Setup in the spaces navigation bar.

3. Click on Settings.

4. Click on Project Configuration.

5. Click on the plus icon to create a new configuration. (See note below if you have previously created a configuration.)

6. Enter the following name: genai.sqgpt.settings.

7. Select Dictionary as the data type.

8. Paste the following for the value:

{
    "llm": {
        "deployment_name": "<value from Step 1>",
        "kind": "azure",
        "openai_api_base": "<value from Step 1>",
        "openai_api_key": "<value from Step 1>",
        "openai_api_version": "2023-05-15",
        "request_timeout_s": [
            5,
            60
        ]
    }
}

Note

If you have already created the genai.sqgpt.settings configuration, you can simply edit the existing configuration and paste the above value.