AI Issue Suite

Project Overview

This project is an AI Issue Suite built using Next.js. It leverages the power of Gemini models to provide intelligent assistance for managing software issues. The suite currently includes an AI Issue Analyzer for automatically categorizing, extracting information, and generating templates for issue reports, and a Real-time Issue Stream feature which is currently under development.

The project provides a modern React-based framework with server-side rendering and static site generation capabilities, optimized for Firebase hosting and backend services.

AI Issue Analyzer

Stream Real-time Issue (Under Development)

Prerequisites

• Node.js (version 16 or higher recommended)
• npm or yarn package manager

Installation

1. Clone the repository:

   git clone <repository-url>
   cd <repository-directory>

2. Install dependencies:

   npm install
   # or
   yarn install

Running the Development Server

To start the development server, run:

npm run dev
# or
yarn dev

Open http://localhost:3000 in your browser to see the app.

Building for Production

To build the project for production, run:

npm run build
# or
yarn build

To start the production server after building:

npm start
# or
yarn start

Project Structure

• src/app/ - Main application directory containing pages and layouts.
• src/components/ - Reusable React components used throughout the app.
• src/hooks/ - Custom React hooks.
• src/lib/ - Utility functions and libraries.
• public/ - Static assets (not present in this project but common in Next.js).
• README.md - Project documentation.
• package.json - Project metadata and dependencies.
• next.config.ts - Next.js configuration file.
• tailwind.config.ts - Tailwind CSS configuration.

Contributing

Contributions are welcome! Please open issues or submit pull requests for improvements or bug fixes.

License

This project is licensed under the MIT License.

Potential Improvements and Roadmap

We are continuously working on improving the AI Issue Suite. Potential future enhancements and planned features for the roadmap include:

• Improve AI Categorization: Enhance the AI Issue Analyzer's ability to categorize issues more accurately using more advanced models and training data.
• Expand Information Extraction: Increase the types and accuracy of information extracted from issue descriptions, potentially including code snippets, error logs, and system information.
• Implement Real-time Issue Stream: Fully implement the Real-time Issue Stream feature with live issue reporting capabilities. This includes:
  • Transcribing spoken issue descriptions.
  • Analyzing screen recordings or shared screen content for errors.
  • Guiding users through troubleshooting steps in real-time.
  • Automatically capturing system information during the session.
• Version Control Integration: Integrate with popular version control systems like Git (e.g., GitHub, GitLab, Bitbucket) for direct issue creation from the AI Issue Suite.
• User Authentication: Develop a robust user authentication system to manage access control and permissions for different users or teams.
• Dashboard and Analytics: Create a dashboard to visualize issue trends, track resolution times, and provide other relevant analytics.
• Customizable Templates: Add support for customizable templates for issue reports, allowing users to define the structure and required information for their specific needs.
• Integrate with Issue Tracking Systems: Explore integrations with popular issue tracking systems (e.g., Jira, Asana, Trello) to synchronize issues and streamline workflows.
• Natural Language Querying: Implement natural language processing to allow users to query issue data using conversational language.
• Mobile Responsiveness: Ensure the application is fully responsive and provides an optimal user experience across various devices, including mobile phones and tablets.
• Accessibility Enhancements: Improve the accessibility of the application to comply with WCAG guidelines and ensure it is usable by individuals with disabilities.
• Performance Optimization: Continuously optimize the application's performance for faster loading times and smoother interactions.