# 🚀 GitHub Setup Instructions

## Steps to Publish Your Repository

1. **Create a new repository on GitHub:**
   - Go to https://github.com/new
   - Repository name: `togmal-prompt-analyzer` (or any name you prefer)
   - Description: "Real-time LLM capability boundary detection using vector similarity"
   - Public repository
   - **Do NOT initialize with README**
   - Click "Create repository"

2. **Push your local repository to GitHub:**
   ```bash
   cd /Users/hetalksinmaths/togmal
   git remote add origin https://github.com/YOUR_USERNAME/YOUR_REPO_NAME.git
   git branch -M main
   git push -u origin main
   ```

3. **Replace YOUR_USERNAME and YOUR_REPO_NAME** with your actual GitHub username and repository name.

## What's Included in This Commit

- **benchmark_vector_db.py**: Core vector database implementation
- **demo_app.py**: Gradio web interface for prompt analysis
- **COMPLETE_DEMO_ANALYSIS.md**: Comprehensive analysis of the system
- **DEMO_README.md**: Documentation with results and instructions
- **requirements.txt**: Python dependencies
- **.gitignore**: Excludes large data files and virtual environment
- **test_vector_db.py**: Test script with real data examples

## Live Demo

Your demo is currently running at:
- Local: http://127.0.0.1:7861
- Public: https://db11ee71660c8a3319.gradio.live

## Key Features

- **14,042 real MMLU questions** with actual success rates
- **Real-time difficulty assessment** (<50ms queries)
- **Production-ready vector database**
- **Explainable results** (shows similar benchmark questions)
- **Actionable recommendations** based on difficulty

## Analysis of Test Questions

The system correctly differentiates between:
- **Hard prompts** (23.9% success rate) like "Statement 1 | Every field is also a ring..."
- **Easy prompts** (100% success rate) like "What is 2 + 2?"

## Next Steps After Pushing

1. Add more benchmark datasets (GPQA Diamond, MATH)
2. Fetch real per-question results from multiple top models
3. Integrate with ToGMAL MCP server for Claude Desktop
4. Deploy to HuggingFace Spaces for permanent hosting