A self-contained document scanning and matching system. It allows users to upload .txt files, scan them against a database of .txt documents, and retrieve matches based on semantic similarity.

• AI-powered document matching with Google Gemini (fallback to Levenshtein distance algorithms)
• User authentication and role-based access control
• Credit system with daily free scans and admin-managed additional credits
• Automated credit reset at 11:59 PM
• Smart analytics dashboard for admins
• User activity summary (No of scans, documents uploaded)
• Document management (upload, view, delete)
• Document privacy (Public or Private)
• Multi-user support
• Export scan results

• Backend: Node.js, Express, TypeScript
• Frontend: HTML, CSS, JavaScript
• Database: SQLite (Local) / SQLite Cloud

DocMatrix/
├── /          # Node.js Express TypeScript backend
└── frontend/  # HTML, CSS, JS frontend

• Node.js (v18 or higher)
• SQLite
• SQLite Cloud

1. Navigate to the project directory: cd /
2. Install dependencies: npm install
3. Set up the environment variables: cp .env.example .env
4. Set GEMINI_API_KEY in .env file. You can get it from Google Gemini.
5. Set up the database connection type and connection string in .env:
   • For local database: DB_TYPE=LOCAL
   • For cloud database: DB_TYPE=CLOUD and set up the SQLITE_CLOUD_URI (Get cloud databse url from here).
6. Start the development server: npm run dev
7. Open http://localhost:4000 in your browser to access the application

• Username: admin
• Password: admin1234

• Username: test
• Password: test1234

1. Download test-data1.txt
2. Download test-data2.txt
3. Go to Upload page and upload both files
4. Go to Scan page, select any file from dropdown and click Scan button
5. You will get the scan results

• API Reference: Postman API Reference

• MIT License