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https://github.com/jplane/azdo-llm
https://github.com/jplane/azdo-llm
Last synced: 20 days ago
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- Host: GitHub
- URL: https://github.com/jplane/azdo-llm
- Owner: jplane
- Created: 2023-12-07T04:04:54.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-01-03T20:47:38.000Z (10 months ago)
- Last Synced: 2024-04-29T02:39:01.480Z (6 months ago)
- Language: Python
- Size: 8.79 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Querying Azure Devops with OpenAI
This repo demonstrates how to query AzDO content using [Langchain integration with Azure OpenAI](https://python.langchain.com/docs/integrations/chat/azure_chat_openai).
Specifically, it defines custom [document loaders](https://python.langchain.com/docs/modules/data_connection/document_loaders/) for [user stories](./AzdoBacklogLoader.py) and [pull requests](./AzdoPullRequestLoader.py) to facilitate Q&A like:
```
What is the title and owner of the most recently completed user story?
```
```
Summarize Alice's comments on Bob's PR for work item 234.
```
_Note the techniques demonstrated in this repo are generalized and should be refined for specific use cases._
## Requirements
- Access to an AzDO project and [personal access token](https://learn.microsoft.com/en-us/azure/devops/organizations/accounts/use-personal-access-tokens-to-authenticate)
- An [Azure OpenAI Service](https://learn.microsoft.com/en-us/azure/ai-services/openai/overview) instance
- A deployed [embeddings model](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models#embeddings)
- A deployed [GPT model](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models#gpt-4-and-gpt-4-turbo-preview) (3.5 or 4)
- [Visual Studio Code](https://code.visualstudio.com/) and [Docker Desktop](https://www.docker.com/products/docker-desktop/) for devcontainer support
## Getting Started
- Clone this repo and open VS Code in the repo root folder. When prompted, re-open as a devcontainer
- In [main.ipynb](./main.ipynb) add your Azure OpenAI endpoint and key, as well as the names of your embeddings and GPT model deployments
- Also in [main.ipynb](./main.ipynb) add your AzDO URI, PAT, and project name
- In the last notebook cell, update the query as warranted for your use case
- Run all cells and observe the results
- Iterate on the query to coax relevant and accurate responses out of Azure OpenAI