Automate responses to StackOverflow queries using OpenAI and Logic Apps

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I'm excited to introduce a powerful solution for automating responses to unanswered Stack Overflow questions using the new AI Search and OpenAI connectors in Logic Apps (Standard). This setup ensures timely and relevant answers to "Logic App" tagged questions, which you can trigger daily, weekly, or monthly based on your preference. Follow this guide to set up your own automated response system for any hashtag, streamlining community support. You can also adapt this solution for tickets in Outlook, ServiceNow, or other platforms using Logic Apps connectors to securely access and automate responses. Plus, we’ve provided a sample solution on GitHub for you to try out, please fill out the feedback form to help us understand what areas you would like us to invest in next.

The Challenge

Stack Overflow is a crucial resource for developers, but many questions remain unanswered, leaving users without solutions. Similarly, in any ticketing system, manually addressing each query is impractical due to increasing volumes. Our new out-of-the-box AI connectors offer a solution to this challenge.

The Solution

By integrating AI Search and OpenAI connectors, you can create an automated system that efficiently addresses unanswered questions on Stack Overflow. Here’s how you can set it up:

Step 1: Set Up a Knowledge Base

In just a few steps, you can ingest data from any source of your choice

1. Gather Documents: For demonstration purposes, use publicly available Logic Apps documentation in PDF format. If your knowledge base is extensive, consider splitting the documents.
2. Ingest Documents Workflow:
   • Configure a blob trigger to check for new documents daily.
   • Upon receiving a new document, the Logic App calls the Tokenize Azure Function API to chunk and tokenize the PDF. We plan to release new operations for document parsing and chunking in the next few weeks, providing all necessary building blocks for Gen AI applications in Logic Apps.
   • Parse string tokens to JSON and send the token payload to OpenAI to generate vector embeddings.
   • Define index criteria and index the document using AI Search.
3. Upload Documents: Upload documents to a blob store to trigger the Logic App, demonstrating real-time ingestion capabilities. Your documents can be stored in SQL, SharePoint, or any other service connected using out-of-the-box connectors.

Step 2: Automate Responses

Iterating through each of the unanswered questions looks something like: 

1. Create Automation Flow: Use an HTTP request trigger or a recurrence trigger to initiate the workflow based on your needs.
2. Access Stack Overflow API: Use the unanswered/my-tags API from Stack Exchange, ensuring to generate and pass the access token in the HTTP GET action.
3. Add Context for Model: Use the Compose action to pass user-defined instructions in the chat completions API, including desired model behavior and scope.
4. Look Up Questions: Generate embeddings for the prompt, perform vector search operations, and look up indexed documents using the Vector Search operation.
5. Generate Response: Add inline JavaScript logic to create a message and pass it in the chat completions API to generate an answer to the Stack Overflow question.
6. Add Human Approval: Insert an Outlook action for human approval before posting the response on Stack Overflow. This is what it will look like once the AI has generated an answer

Benefits of Automation

• Efficiency: Save time and resources by automating responses.
• Consistency: Ensure high-quality, consistent answers.
• Scalability: Handle a large volume of unanswered questions effortlessly.
• Community Engagement: Increase engagement with timely, accurate responses.

Conclusion

Automating Stack Overflow responses using AI Search and OpenAI connectors is transformative for developers and community managers. By leveraging these tools, you can enhance user experience, provide timely support, and foster a more engaged community. Don’t forget to check out our sample solution on GitHub—give it a try and witness the transformation for yourself!