brandonmartinez / ado-chatgpt

A ChatGPT-like experience to query over work item data within an Azure DevOps project.

ADO ChatGPT

A ChatGPT-like experience to query over work item data within an Azure DevOps organization.

Pre-requisites

To run this sample in its entirety, you need the following:

• a bash-like shell (e.g. Git Bash, WSL, etc.)
• an Azure DevOps organization and team project from which data will be exported
• an Azure DevOps work item query to pull work items from (should return 1000 items or less)
• an Azure subscription, with access to Open AI
• az cli installed and logged in to your Azure subscription

Configuration

Duplicate the .envsample file and rename it to .env. Fill in the values for all of the required environment variables.

The following parameters can be configured:

Name	Description	Required?
AZURE_LOCATION	The name of the Azure region to deploy to; a list can be found by running az account list-locations -o table --query "[].displayName"	Yes
AZURE_WORKLOAD	The workload name to be used when creating Azure resources; keep short and limited to A-z, 0-9, and hyphens	Yes
AZURE_SUBSCRIPTIONID	The Subscription ID (GUID) that this sample will be deployed to	Yes
ADO_ORG	The Azure DevOps organization name work items will be exported from	Yes
ADO_PROJECT	The Azure DevOps project name work items will be exported from	Yes
ADO_QUERIES	A comma-separated list of query IDs that work items will be pulled from	No
AZURE_OPENAI_EMBEDDINGMODELNAME	The name of the Azure OpenAI Model to use for embedding vectors into the Azure AI Search index (recommended to use text-embedding-ada-002 or equivalent)	Yes
AZURE_OPENAI_EMBEDDINGMODELVERSION	The version of the Azure OpenAI Model to use for embedding vectors into the Azure AI Search index (recommended to use 2 or equivalent)	Yes
AZURE_OPENAI_MODELNAME	The name of the Azure OpenAI Model to use for querying the Azure AI Search index (recommended to use gpt-35-turbo-16k or equivalent)	Yes
AZURE_OPENAI_MODELVERSION	The version of the Azure OpenAI Model to use for querying the Azure AI Search index (recommended to use 0613 or equivalent)	No
SKIP_ADO_DOWNLOAD	Set to 1 to skip the ADO Work Item download process	No
SKIP_ADO_UPLOAD	Set to 1 to skip the ADO Work Item upload to Azure Storage process	No
SKIP_INFRASTRUCTURE	Set to 1 to skip the Azure infrastructure deployment process	No
SKIP_OPENAI_MODELSETUP	Set to 1 to skip the Azure Open AI model setup process	No
SKIP_SEARCH_DATASOURCESETUP	Set to 1 to skip the Azure AI Search data source setup process	No
SKIP_SEARCH_INDEXERSETUP	Set to 1 to skip the Azure AI Search indexer setup process	No
SKIP_SEARCH_INDEXSETUP	Set to 1 to skip the Azure AI Search index setup process	No
SKIP_SEARCH_SKILLSETSETUP	Set to 1 to skip the Azure AI Search skill set setup process	No

Optionally, copy the templates/ado-record.jq file to queries/ado-recrord.jq to customize the properties that are indexed by Azure AI Search.

Instead of utilizing the ADO_QUERIES environment variable, copy templates/ado-query-example.wiql to the queries/ folder with a descriptive name. Any queries present in this folder will be executed in alphabetical order. Do not add an ORDER BY clause, as one will be added sorting by Work Item ID (System.Id). This will bypass the 1,000 record limit on queries.

Deploy the Resources

Execute the following commands to deploy the sample:

deploy.sh

Use Azure OpenAI Studio to Chat with Your Data

Configure your chat data source

Once the resources are deployed, you can use the Azure OpenAI Studio to chat with your newly deployed model.

1. Navigate to "Chat" under the Playground
2. Under "Setup", choose "Add your data"
3. Click the "Add data source" button

4. Under "Select data source", choose "Azure AI Search";
5. Choose your Azure subscription
6. Choose your Azure AI Search service
7. For "Azure AI Search index", select ado-vector-index
8. Check "Add vector search to this search resource"
9. Choose the embedding model (e.g., text-embedding-ada-002-2)
10. Check the "I acknowledge that connecting to an Azure AI Search account will incur usage to my account."
11. Click the "Next" button

12. Under the "Search type", ensure "Hybrid + semantic" is selected
13. Under "Select an existing semantic search configuration" choose ado-vector-semantic-configuration.
14. Check "I acknowledge that using semantic search will incur usage to my Azure AI Search account
15. Check "I acknowledge that adding vector embeddings will incur usage to my account"
16. Click the "Next" button

17. Review the details presented and click the "Save and close" button

Chat with your data

Now that your data source is configured, modify the chat playground settings to begin chatting with your data:

1. Choose "Advanced settings" to expand additional options
2. Optionally, adjust the Strictness (hover over the information icon for more details)
3. Optionally, adjust the retrieved documents (hover over the information icon for more details)
4. Choose your Open AI model deployment (e.g., gpt-35-turbo-16k-0613)
5. Optionally, adjust past messages to include (hover over the information icon for more details)
6. Enter your first prompt

Note that citations can be expanded and clicked on to show the data source the response came from. You can continue to query through additional prompts to refine the data that has been retrieved.

Optional: Deploy a Web App

If you would like to deploy a web app to interact with your data, you can use the "Deploy to…" button and choose "A new web app…" to create an interactive web application using your newly deployed models and datasets.

For more information, follow the instructions in Tutorial: Deploy a web app for chat on your data

References and Additional Resources

• This sample is heavily based off this article: Chat with your Azure DevOps data | Microsoft Tech Communities
• Which itself is based off this sample: Preview - Sample Chat App with AOAI | GitHub