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Set up a Jupyter notebook server using Azure ML Studio

Overview

In order to run through this lab, you'll need to set up a notebook server using Azure ML Studio

Setup

Create an Azure ML Workspace

  1. Create an Azure Open AI Workspace
  • Go to the Azure Open AI console from the Azure Portal
  • Select "Create"

01

  1. Choose the resource group you created earlier or create a new one and fill in the required fields
  • Take the defaults for the fields in the rest of the screens and click "Create"

02.png

  1. Go to the resources
  • Once it's done deploying click on "Go To Resource"

03.png

  1. Go to Azure ML Studio
  • Click on the "Studio Web URL" link on the upper right hand side.

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  1. Go to Notebooks
  • Click on the "Notebooks" link on the left side panel.

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  1. Create a Compute Instance for the Notebook server
  • Click on the blue "Create Compute" link on the lower right of the screen.

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  1. Configure and Create Instance
  • Give the instance a name and click "Create".

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  1. Start a Terminal session
  • Click on the blue "Terminal" button on the lower right.

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  1. Clone this Github repository onto the notebook instance
  • Once the compute instance has finished deploying, you will see a terminal prompt.

Clone this repo with the command:

git clone https://github.com/neo4j-partners/neo4j-generative-ai-azure.git

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  1. Enter API and Neo4j authentication details into config.env file

  • Once the cloning is complete navigate into the repository and rename the file 'ingestion/config.env.example' to 'config.env'. Then open the file and fill in the fields with the OpenAI API details and the Neo4j database access and authentication details.

  • Note: for OPEN_API_VERSION, use "2023-03-15-preview"

10.png)

Now you're ready to begin using the notebook.