UI_SUMMARY.md

🎉 Medical Q&A Bot - UI Implementation Complete!

✅ What You Now Have

🖥️ Two Complete Web Interfaces

1. Gradio Interface (app.py) - RECOMMENDED ⭐

• Clean, modern design with gradient styling
• Dual-view mode (Formatted + JSON)
• Built-in example queries
• Easy to share and deploy
• Automatic REST API generation
• Launch with: python app.py
• Access at: http://127.0.0.1:7860

2. Streamlit Interface (app_streamlit.py) - ALTERNATIVE

• Interactive sidebar with live controls
• Card-based result display
• Progress bars and metrics
• More customization options
• Launch with: streamlit run app_streamlit.py
• Access at: http://localhost:8501

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📚 Complete Documentation Suite

Quick Start Guides

1. QUICKSTART.md - Step-by-step setup (5 minutes)
2. launch_ui.bat - Windows batch launcher (double-click to run)
3. launch_ui.ps1 - PowerShell launcher (right-click → Run with PowerShell)
4. setup_ui.py - Automated setup script

Comprehensive Documentation

1. UI_README.md - Complete UI feature documentation
2. UI_IMPLEMENTATION.md - Implementation details and summary
3. ARCHITECTURE.md - System architecture with diagrams
4. PRESENTATION_SCRIPT.md - Complete presentation guide with demo script

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🚀 How to Get Started (3 Easy Steps)

Option 1: PowerShell Launcher (Easiest!)

# Just double-click or run:
.\launch_ui.ps1

Option 2: Command Line

# 1. Install dependencies
pip install -r requirements.txt

# 2. Build data (if needed)
python -m adapters.build_corpora

# 3. Launch!
python app.py

Option 3: Setup Script

# Run the automated setup
python setup_ui.py

# Then launch
python app.py

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🎨 Key Features

Classification

✅ Automatic query classification (Medical/Administrative/Other) ✅ Confidence scores for transparency ✅ Visual indicators and progress bars ✅ Color-coded results

Retrieval

✅ Hybrid search (BM25 + Dense + RRF) ✅ Retrieves from PubMed, Miriad, and UniDoc ✅ Adjustable number of results (1-50) ✅ Optional cross-encoder reranking ✅ Multiple relevance scores per document

User Experience

✅ Clean, professional interface ✅ Example queries built-in ✅ Real-time processing ✅ Formatted and JSON view modes ✅ Mobile-responsive design ✅ Error handling and validation

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📁 New Files Created

health-query-classifier/
├── 🌐 Web Interfaces
│   ├── app.py ⭐ (Main Gradio UI)
│   ├── app_streamlit.py (Alternative Streamlit UI)
│   ├── launch_ui.bat (Windows launcher)
│   └── launch_ui.ps1 (PowerShell launcher)
│
├── 📚 Documentation
│   ├── QUICKSTART.md (5-minute setup guide)
│   ├── UI_README.md (Feature documentation)
│   ├── UI_IMPLEMENTATION.md (Technical summary)
│   ├── ARCHITECTURE.md (System diagrams)
│   ├── PRESENTATION_SCRIPT.md (Demo script)
│   └── UI_SUMMARY.md (This file)
│
├── 🔧 Setup Tools
│   └── setup_ui.py (Automated installer)
│
└── 📦 Updated Files
    └── requirements.txt (Added gradio + streamlit)

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🎯 What Each Interface Looks Like

Gradio Interface Features:

┌─────────────────────────────────────────┐
│  🏥 Medical Q&A Bot                     │
│  Health Query Classifier & Retriever    │
│  Team: David • Tarak • Sravani • etc.  │
├─────────────────────────────────────────┤
│                                         │
│  [Enter your health query...]           │
│  ┌─────────────────────────────────┐   │
│  │ Number of Results: [10]         │   │
│  │ ☐ Use Reranker                  │   │
│  └─────────────────────────────────┘   │
│                                         │
│  [🔍 Analyze Query]                     │
│                                         │
├─────────────────────────────────────────┤
│  Classification Result:                 │
│  ✓ MEDICAL (95% confidence)             │
│  - Medical: 95.2% ████████████          │
│  - Administrative: 4.8% █               │
├─────────────────────────────────────────┤
│  [📄 Formatted View] [📊 JSON View]     │
│                                         │
│  Found 10 Relevant Documents            │
│  ┌───────────────────────────────┐     │
│  │ Result #1: Eczema Treatment   │     │
│  │ BM25: 0.85 Dense: 0.92 RRF: 1.2│     │
│  │ Text: Treatment options for...│     │
│  └───────────────────────────────┘     │
│  ...                                    │
└─────────────────────────────────────────┘

Streamlit Interface Features:

┌─────────────┬───────────────────────────┐
│ ⚙️ Settings │  🏥 Medical Q&A Bot      │
│             │  ═══════════════════════  │
│ Results: 10 │                           │
│ ▁▁▁▁▁▁▁▁   │  [Query input box...]     │
│             │                           │
│ ☐ Reranker  │  [🔍 Analyze Query]       │
│             │                           │
│ ☐ JSON View │  Classification:          │
│             │  🏥 MEDICAL               │
│ Examples:   │                           │
│ • Rash...   │  Confidence:              │
│ • Vaccine...│  ████████████ 95%         │
│ • Headache..│                           │
│             │  Results:                 │
│             │  ┌─────────────────┐     │
│             │  │ Result #1       │     │
│             │  │ BM25  │ Dense   │     │
│             │  │ 0.85  │ 0.92    │     │
│             │  └─────────────────┘     │
└─────────────┴───────────────────────────┘

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💡 Demo Workflow

Perfect Demo Sequence:

1. Start → Launch UI (python app.py)
2. Medical Query → "I have a rash on my hands..."
   • Show classification
   • Show retrieved documents
   • Point out scores
3. Admin Query → "Can I get an appointment?"
   • Show different classification
   • No retrieval happens
4. Settings → Adjust results, toggle reranker
5. Views → Switch between formatted and JSON

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🎓 For Your Presentation

Talking Points:

✅ "We built a professional web interface using Gradio" ✅ "The system classifies queries in real-time" ✅ "For medical queries, it retrieves relevant research" ✅ "Uses hybrid search with BM25 and dense embeddings" ✅ "Optional reranking for improved accuracy" ✅ "Clean, intuitive user experience"

What to Demo:

✅ Classification confidence scores ✅ Document retrieval results ✅ Different query types (medical vs admin) ✅ Settings adjustment (reranker, result count) ✅ Multiple view modes (formatted + JSON)

Impressive Technical Details:

✅ Sentence transformer embeddings ✅ Neural network classifier ✅ FAISS vector search ✅ RRF fusion algorithm ✅ Cross-encoder reranking ✅ Professional UI framework

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🛠️ Troubleshooting

Common Issues:

"Module not found: gradio"

pip install gradio

"No corpora files found"

python -m adapters.build_corpora

"Port already in use"

# Edit app.py line ~255
demo.launch(server_port=8080)  # Change port

"Models loading slowly"

• This is normal on first run
• Models are cached afterward
• Takes 30-60 seconds initially

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🌟 Why This Implementation is Great

For Your Project:

✅ Professional appearance ✅ Easy to demonstrate ✅ Well-documented ✅ Production-ready foundation ✅ Impressive to stakeholders

For Your Resume:

✅ Modern tech stack (Gradio, PyTorch, Transformers) ✅ Full-stack development (UI + ML backend) ✅ Healthcare application (impactful domain) ✅ Clean, maintainable code ✅ Comprehensive documentation

For Future Development:

✅ Easy to extend ✅ Modular architecture ✅ Multiple deployment options ✅ API already available ✅ Scalable design

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📊 File Sizes

app.py                 ~9 KB   (Main UI)
app_streamlit.py       ~7 KB   (Alt UI)
QUICKSTART.md          ~5 KB   (Setup guide)
UI_README.md           ~8 KB   (Features)
UI_IMPLEMENTATION.md   ~10 KB  (Details)
ARCHITECTURE.md        ~15 KB  (Diagrams)
PRESENTATION_SCRIPT.md ~12 KB  (Demo guide)

Total new documentation: ~66 KB of helpful guides!

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🎯 Next Steps

Immediate (5 minutes):

1. Run pip install gradio streamlit
2. Launch UI with python app.py
3. Test with example queries
4. Familiarize yourself with features

Short Term (1 hour):

1. Read through QUICKSTART.md
2. Test both Gradio and Streamlit interfaces
3. Prepare demo queries
4. Practice presentation flow

Before Presentation:

1. Review PRESENTATION_SCRIPT.md
2. Test demo multiple times
3. Prepare backup slides
4. Assign team roles
5. Get excited! 🚀

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🤝 Team Credits

Built by:

• David Gray
• Tarak Jha
• Sravani Segireddy
• Riley Millikan
• Kent R. Spillner

Technologies Used:

• Python 3.8+
• PyTorch
• Sentence-Transformers
• Gradio
• Streamlit
• FAISS
• BM25
• scikit-learn

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🎉 You're All Set!

Your medical Q&A bot now has: ✅ Two professional web interfaces ✅ Complete documentation ✅ Easy launchers ✅ Presentation guide ✅ Demo script ✅ Architecture diagrams

Everything you need for a successful demo and presentation!

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🚀 Quick Commands Reference

# Install everything
pip install -r requirements.txt

# Build data
python -m adapters.build_corpora

# Launch Gradio UI (recommended)
python app.py

# Launch Streamlit UI (alternative)
streamlit run app_streamlit.py

# Run automated setup
python setup_ui.py

# Use launcher scripts
.\launch_ui.ps1

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📞 Need Help?

1. Check QUICKSTART.md for setup issues
2. Check UI_README.md for feature questions
3. Check ARCHITECTURE.md for technical details
4. Check PRESENTATION_SCRIPT.md for demo help
5. Ask your team members!

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✨ Final Notes

This implementation provides:

• Professional quality - Ready to show to professors, potential employers
• Well-documented - Easy for team members to understand
• Extensible - Can be built upon for future projects
• Portfolio-worthy - Great addition to your GitHub

You've got an impressive project here. Go show it off! 🌟

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Created: December 3, 2025 For: Health Query Classifier Group Project By: Your friendly AI assistant