📌 AI-Assisted Technical Requirement Generator

A quick demonstration of the AI-powered requirement generation process.

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🚀 Overview

The AI-Assisted Technical Requirement Generator is a web application that helps engineers, product managers, and students instantly generate structured, professional technical requirements for projects.
By simply providing project details, users receive categorized requirements (Functional, Performance, Safety, Compliance, etc.) in a clear, exportable format.

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✨ Features

• AI-Powered Requirement Generation – Uses an intelligent backend to create precise, categorized requirements.
• Multiple Output Formats – Export results as PDF, DOCX, or Markdown.
• Customizable Inputs – Define:
  • Project name
  • Project type (Software, Mechanical, Electrical, etc.)
  • Project description
  • Tone (formal/informal)
  • Detail level (brief/detailed)
• Attractive, Responsive UI – Clean layout with modern Bootstrap styling.
• Fast & Seamless – Generates outputs within seconds.

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🛠 Tech Stack

Frontend

• React + TypeScript
• Vite
• Bootstrap / Custom CSS

Backend

• Python (FastAPI)
• Uvicorn
• AI model for requirement generation

Utilities

• file-saver for file downloads
• docx, reportlab, and Markdown libraries for export

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📂 Project Structure

Projects-Requirements-Generator/
│
├── mai-backend/         # FastAPI backend for AI requirement generation
├── mai-frontend/        # React TypeScript frontend
├── .gitattributes
├── .gitignore
└── README.md

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🔧 Installation & Setup

1️⃣ Clone the repository

git clone https://github.com/MuhammadSaqib786/Projects-Requirements-Generator.git
cd Projects-Requirements-Generator

2️⃣ Backend Setup

cd mai-backend
pip install -r requirements.txt
uvicorn main:app --reload --port 8000

3️⃣ Frontend Setup

cd ../mai-frontend
npm install
npm run dev

🐳 Run with Docker

Make sure you have Docker and Docker Compose installed, then run:

docker compose up -d --build

This will:

• Build the backend (FastAPI + Python)
• Build the frontend (React + TypeScript)
• Start both containers
• Map ports so you can access the app in your browser

Once running, open your browser at:

http://127.0.0.1

The frontend will connect to the backend automatically inside Docker.

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Check Backend API Health:

http://127.0.0.1:8000/api/health

If it returns:

{"status": "ok"}

then your API is ready.

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Stop the Containers:

docker compose down

Rebuild & Restart:

docker compose up -d --build

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📄 Usage

1. Enter project details in the form.
2. Click Generate Requirements.
3. View categorized requirements instantly.
4. Export in PDF, DOCX, or Markdown format.

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🎯 Future Improvements

• Integration with OpenAI / local LLM models for more accurate results.
• Save projects for later editing.
• Multi-language support.
• Custom export templates.

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👨‍💻 Author

Muhammad Saqib

• 📧 [email protected]

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⭐ Contribute

Contributions are welcome!
Fork the repo, make changes, and submit a pull request.