Monday.com + GPT App Tutorial: Building a Debug Assistant

Build a Debug Assistant with Monday.com and GPT

Debugging can be a challenging process for any programmer. However, with the integration of modern tools like Monday.com and OpenAI's language models, the debugging process can be streamlined significantly. This article will guide you through building a Next.js application that connects to Monday.com's Incoming Bugs board, analyzes bug descriptions, and provides suggestions for fixing them.

What is Monday.com?

Monday.com is a versatile work management platform designed to boost operational efficiency within teams. It enables organizations to track projects, visualize workflows, and automate processes. Its integration capabilities allow seamless communication with various applications, making it ideal for collaborative work.

Setting Up Your Monday App

1. Create a Monday.com developer account if you haven't done so.
2. Log into your Monday.com dashboard and add a new item by clicking the essential icon on the left panel.
3. Select the Product Development template to create a Bug Queue board.
4. Add a new column titled Suggestions to the Incoming Bugs table.

Creating and Installing Your App

To simplify the development process, use a Next.js template provided by Monday.com, which includes pre-built React components.

git clone https://github.com/mondaycom/monday-ai-prompt-template.git
cd monday-ai-prompt-template
npm install

After configuring your .env file with your OPENAI_API_KEY, set up a tunnel to your local server using ngrok.

ngrok http 3000

Connecting to Monday

1. In your Monday app, create a new feature named Debug Widget.
2. Set the source to Custom URL and use your ngrok URL.
3. Publish your app versions to allow it to be added to your Monday board.

Developing the App

In your code editor, copy the boilerplate file to develop the main functionality of your Debug Assistant.

cp monday-ai-prompt-template/src/examples/livestream-example/boilerplate.tsx monday-ai-prompt-template/src/examples/debug-assistant.tsx

Modify the component to handle board selections and form submissions.

Handling Responses

async function handleSend() {
    const response = await fetch("/api/openai", { method: "POST", body: JSON.stringify(data) });
    const result = await response.json();
    updateSuggestionsColumn(result);
}

Testing Your Application

Open the Debug Widget on your Bug Insights board. By selecting the Incoming Bugs group and the Suggestions column, users can input a specific bug description to request solutions from the AI.

"Write a short technical solution for this bug description: @Bug Description"

This input will populate the Suggestions column with relevant suggestions derived from AI after a short processing time.

Final Thoughts

We've explored how to create a Monday.com app integrated with OpenAI's language models. This template uses GPT-3.5 by default, but you can switch to GPT-4 if desired. By customizing the UI and prompts, users can tailor this tool to meet specific debugging needs. Remember to deploy your app to a production server when ready for broader use!

If you have any questions about this tutorial, feel free to connect with me on LinkedIn or Twitter.

Keywords: Monday.com, debugging, Next.js, OpenAI, app development, bug tracking, integration.