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IDP-Machine-learning / SETUP_INSTRUCTIONS.md
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IDP System - Manual Setup Instructions (CMD Shell)

Quick Start Commands

Since you're using CMD shell, here are the exact commands to run:

Step 1: Install Frontend Dependencies

Open Command Prompt (cmd) and run:

cd C:\Users\Harsh-Stu\IDP[ML]\frontend
npm install

If you still get permission errors, try:

npm install --legacy-peer-deps

Step 2: Start Backend Server

Open a new Command Prompt window and run:

cd C:\Users\Harsh-Stu\IDP[ML]
python api_server.py

You should see:

  • ✓ Pipeline initialized successfully!
  • ⚠ Using demo mode (rule-based) classifier (this is expected - no trained classifier yet)
  • ✓ Loaded trained NER model
  • Server running on http://0.0.0.0:7860

Step 3: Start Frontend Dev Server

Open a third Command Prompt window and run:

cd C:\Users\Harsh-Stu\IDP[ML]\frontend
npm run dev

Frontend will be available at: http://localhost:3000

Testing the System

  1. Open browser: Navigate to http://localhost:3000
  2. Upload a document: Drag and drop or click to select an invoice/receipt image or PDF
  3. Process: Click "Process Document"
  4. View results: See extracted document type and entities

Current System Status

✅ Backend Ready

  • FastAPI server configured
  • Demo mode classifier (rule-based)
  • Trained NER model (F1: 0.6247)
  • OCR engine (PaddleOCR)

✅ Frontend Ready

  • Next.js application
  • API integration configured
  • File upload with validation
  • Results display

⚠️ Note: Currently using demo mode for document classification. For better accuracy, you can train the classifier later by running:

cd C:\Users\Harsh-Stu\IDP[ML]
python train_classifier.py

Troubleshooting

Backend won't start

  • Check if port 7860 is already in use
  • Verify Python dependencies: pip list | findstr "fastapi torch paddleocr"

Frontend won't start

  • Delete node_modules and package-lock.json, then reinstall
  • Try: npm install --force
  • Check if port 3000 is already in use

CORS errors

  • Backend is configured to allow all origins for development
  • Make sure backend is running before starting frontend