Skip to main content Link Menu Expand (external link) Document Search Copy Copied
Azure OpenAI API Hands-on LevelUp Labs

Module 1: Lab - Transaction Classification Application

In this lab, you will create a transaction classification application that uses the Azure OpenAI API and other Azure services to classify a public dataset of transactions into a number of categories that we have predefined. These approaches should be replicable to any multiclass classificaiton use case where we are trying to fit transactional data into predefined categories, and by the end of running through this you should have an approach for dealing with unlabelled datasets.

Installation

This module requires creation of following Azure resources

  1. An Azure Storage Account and two containers: 1. “classification” - for the transaction file 2. “output” - for the results
  2. An Azure Function App Resource
  3. An Event Grid Subscription to the Azure Function App Resource from the Azure Storage Account for “Blob Created” events
  • The first two listed resources are created by running the Github Actions workflow file module1-infra-worflow.yaml which executes module2-infra.bicep Bicep template. To trigger this workflow manually:
    1. click on the Actions tab.
    2. Select .github/workflows/module2-infra-worflow.yaml.
    3. Click on the Run workflow button
  • Deploy the Azure Function App code using Github Actions workflow file module2-code-workflow.yaml as follows:
    1. In Azure portal, navigate to the Function App that was deployed in the last step.
    2. Click Get publish profile and download .PublishSettings file.
    3. Open the .PublishSettings file and copy the XML content.
    4. Paste the XML content to your GitHub Repository > Settings > Secrets > Add a new secret > AZURE_FUNCTIONAPP_PUBLISH_PROFILE
    5. Trigger this workflow manually:
      • click on the Actions tab.
      • Select .github/workflows/module2-code-worflow.yaml.
      • Click on the Run workflow button
  • Configure following Application Settings for the Azure Function by going to your function app > Configuration > Application Settings:
    1. OPENAI_API_BASE - Azure OpenAI API Endpoint URL (e.g. https://openai-demo-ahmedbham.openai.azure.com/)
    2. OPENAI_API_KEY - Azure OpenAI API Key
    3. OPENAI_API_MODEL - “text-davinci-003” (set it equal to the model name you provided when deploying the text-davinci-003 model in Azure OpenAI Studio)
  • Create an Event Grid Subscription to the Azure Function App Resource from the Azure Storage Account for “Blob Created” events in Azure portal:
    1. Navigate to your storage account > Events > + Event Subscription
    2. Set Event Schema to Event Grid Schema`
    3. Set System Topic Name to classification
    4. Select only Blob Created event type
    5. SelectFunction App as the Endpoint Type
    6. Set Endpointvalue by selecting the correct Subscription, Resource Group, Function App, Slot, and Function from the dropdowns
    7. Click Create to create the subscription

Event Grid Subscription Page

  • Open the sample transaction file 25000_spend_dataset_current_25.csv and notice that the classification column is empty. This is the column that will be populated by the Azure Function by calling Azure OpenAI API.
  • Upload this file to the classification blob container: portal > storage account > containers > classification > upload
  • After few seconds, download the updated file from the output blob container portal > storage account > containers > output > download
  • Open the file and notice the classification column is populated with the predicted category for each transaction.