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Automating Confluence & Jira workflows using LLMs

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ZhenFlow

Hey, you, out there... thanks for checking here!

This is a space to experiment and have fun while automating Jira and Confluence workflows and making sense of unstructured data — all powered by LLMs. Use the code at your dscretion and beware, most of it is LLM generated.

Supported Workflows

Confluence-to-Jira integration

  1. Given Confluence page URL as a prompt, create Epic and Stories (in this Epic) from the Requirements section in the page.
  2. Work with my Jira tickets from Confluence. Update the Confluence page with the created Epic by embedding it in expand macro.

Ask Jira Product Discovery Project a question
Prompt a model with questions related to the Jira tickets in a JPD project of your choice.

Intallation

Prerequisites

  • OpenAI API Token
  • Atlasian API Token

Ensure you have the following installed on your system:

  • Node.js (v12 or higher)
  • npm (Node Package Manager)
  • A GitHub account to clone the repository

Clone the Repository

To get started, clone the repository from GitHub using the following command:

git clone https://github.com/your-username/your-repository-name.git

Replace your-username and your-repository-name with the actual GitHub username and repository name.

Navigate to the Project Directory

cd your-repository-name

Install Dependencies

npm install

Set Up Environment Variables

In the root directory of your project, create a new file named .env and specify the below environment variables.

JIRA_EMAIL=your-jira-email JIRA_API_TOKEN=your-jira-api-token JIRA_URL=https://your-domain.atlassian.net OPENAI_TOKEN=your-openai-api-key PORT=3000

Make sure your .env file is included in .gitignore to prevent it from being tracked by version control and shared publicly. In the root directory of your project, create a new file named .gitignore and list .env in it.

Run the Project

npm start

The application will be available at http://localhost:3000

Access the Web Interface

Open your web browser and navigate to: http://localhost:3000

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