| # 🚀 QUICK START GUIDE - MVM² | |
| ## ⚡ Fastest Way to Get Started | |
| ### Step 1: Open Terminal in Project Directory | |
| ```bash | |
| cd c:\Users\Varshith Dharmaj\Downloads\major\math_verification_mvp | |
| ``` | |
| ### Step 2: Run the Startup Script | |
| ```powershell | |
| .\start.ps1 | |
| ``` | |
| Choose option **2** for quick demo (Dashboard Only) | |
| --- | |
| ## 📋 What You'll See | |
| 1. **Dashboard opens at:** http://localhost:8501 | |
| 2. **Two input modes:** | |
| - 📝 **Text Input** - Try the pre-filled example | |
| - 📷 **Image Upload** - Upload a handwritten math problem | |
| 3. **Click "Verify Solution"** to see results | |
| --- | |
| ## 🧪 Testing the System | |
| ### Quick Test (No Services Required) | |
| The dashboard will work in demo mode even without microservices running. | |
| ### Full Test (All Services) | |
| ```powershell | |
| .\start.ps1 | |
| ``` | |
| Choose option **1** - This opens 4 windows: | |
| - OCR Service (Port 8001) | |
| - SymPy Service (Port 8002) | |
| - LLM Service (Port 8003) | |
| - Dashboard (Port 8501) | |
| --- | |
| ## 🎯 Try These Examples | |
| ### Example 1: Valid Solution ✅ | |
| **Problem:** "Janet has 3 apples. She buys 2 more. She gives 1 away." | |
| **Steps:** | |
| ``` | |
| Janet starts with 3 apples | |
| She buys 2 more: 3 + 2 = 5 apples | |
| She gives 1 away: 5 - 1 = 4 apples | |
| ``` | |
| **Expected:** VALID with high confidence | |
| --- | |
| ### Example 2: Error Detection ❌ | |
| **Problem:** "There are 5 boxes with 8 apples each." | |
| **Steps:** | |
| ``` | |
| Number of boxes = 5 | |
| Apples per box = 8 | |
| Total = 5 × 8 = 45 | |
| ``` | |
| **Expected:** ERROR detected (5 × 8 = 40, not 45) | |
| --- | |
| ## 🔧 Prerequisites | |
| ### Required (Basic Demo) | |
| - ✅ Python 3.10+ | |
| - ✅ Virtual environment (./start.ps1 creates this automatically) | |
| ### Optional (Full Features) | |
| - Tesseract OCR (for image processing) | |
| - Gemini API Key (for LLM reasoning) | |
| --- | |
| ## 📦 Installing Additional Components | |
| ### Tesseract OCR (for Image Mode) | |
| 1. Download: https://github.com/tesseract-ocr/tesseract | |
| 2. Install and add to PATH | |
| 3. Restart terminal | |
| ### Gemini API Key (for LLM Features) | |
| 1. Get free key: https://ai.google.dev/ | |
| 2. Copy `.env.template` to `.env` | |
| 3. Add: `GEMINI_API_KEY=your_key_here` | |
| --- | |
| ## 🐛 Troubleshooting | |
| ### "Module not found" | |
| ```powershell | |
| .\venv\Scripts\Activate.ps1 | |
| pip install -r requirements.txt | |
| ``` | |
| ### "Port already in use" | |
| Close any applications using ports 8001-8003, 8501 | |
| ### Services not connecting | |
| - Check if all service windows are still open | |
| - Look for error messages in service windows | |
| - Restart the startup script | |
| --- | |
| ## 📊 What to Expect | |
| ### Performance Metrics | |
| - ⏱️ Processing time: 1-5 seconds per problem | |
| - 🎯 Accuracy: 68%+ on valid test cases | |
| - 🔍 Error detection: 78%+ when errors present | |
| ### Features Working | |
| - ✅ Text input verification | |
| - ✅ Multi-model consensus | |
| - ✅ Error detection and reporting | |
| - ✅ Confidence scoring | |
| - ✅ Agreement analysis | |
| ### Image Input (Requires Tesseract) | |
| - 📷 Handwritten math problems | |
| - 📄 Printed worksheets | |
| - 🖼️ Whiteboard photos | |
| --- | |
| ## 🎓 Research Features Demonstrated | |
| 1. **Multimodal Input** - Accept both text and images | |
| 2. **Weighted Consensus** - Symbolic (40%), LLM (35%), ML (25%) | |
| 3. **OCR-Aware Calibration** - Novel uncertainty propagation | |
| 4. **Real-time Processing** - <5 second response time | |
| --- | |
| ## 📞 Next Steps | |
| 1. ✅ **Test basic functionality** - Run the text examples | |
| 2. ⚡ **Try image upload** - If you have Tesseract installed | |
| 3. 🧪 **Run automated tests** - `python tests/test_system.py` | |
| 4. 📊 **Collect data** - Test with your own math problems | |
| 5. 🎨 **Customize** - Modify weights, add more patterns | |
| --- | |
| ## 🆘 Need Help? | |
| Check the full README.md for: | |
| - Detailed architecture | |
| - API documentation | |
| - Advanced configuration | |
| - Deployment options | |
| --- | |
| **MVM²** - Making Mathematical Verification Multimodal | |
| VNR VJIET Major Project 2025 | |