Update README.md

README.md

@@ -17,4 +17,173 @@ sdk_version: 1.52.2
 Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
 
 If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+forums](https://discuss.streamlit.io).
+
+
+---
+title: Review Intelligence System
+emoji: 🎯
+colorFrom: blue
+colorTo: purple
+sdk: streamlit
+sdk_version: 1.28.0
+app_file: app.py
+pinned: false
+---
+
+# 🎯 Review Intelligence System
+
+**Multi-Agent AI-Powered Review Analysis Platform**
+
+Analyze customer reviews from App Store and Play Store with 7 specialized AI models working in parallel.
+
+## 🚀 What This Does
+
+This application provides **intelligent, multi-stage analysis** of customer reviews using a sophisticated AI pipeline:
+
+- 📱 Scrapes reviews from **App Store** and **Play Store**
+- 🤖 Classifies reviews by **type**, **department**, and **priority**
+- 😊 Analyzes **sentiment** with dual BERT models
+- 👥 Identifies **user types** and **emotional states**
+- 📊 Generates **actionable insights** and **batch analytics**
+- 🎯 Routes issues to appropriate teams
+
+Perfect for **product managers**, **UX teams**, **support teams**, and **business analysts**.
+
+## ✨ Key Features
+
+### 4-Stage AI Pipeline
+
+| Stage | What It Does | Models Used |
+|-------|-------------|-------------|
+| **Stage 0** | Web Scraping | App Store RSS & Play Store API |
+| **Stage 1** | Classification | Qwen 72B + Llama 3B + Llama 70B |
+| **Stage 2** | Sentiment | Twitter-RoBERTa + BERTweet |
+| **Stage 3** | Synthesis | Llama 70B |
+| **Stage 4** | Analytics | Statistical aggregation |
+
+### What You Get
+
+- ✅ **Review Type**: praise, complaint, suggestion, question, bug_report
+- ✅ **Department**: engineering, ux, support, business
+- ✅ **Priority**: critical, high, medium, low
+- ✅ **Sentiment**: POSITIVE, NEUTRAL, NEGATIVE (with confidence)
+- ✅ **Emotion**: joy, satisfaction, frustration, anger, disappointment
+- ✅ **User Type**: new_user, regular_user, power_user, churning_user
+- ✅ **Actions**: Specific recommendations for each review
+- ✅ **Analytics**: Churn risk, critical issues, quick wins
+
+## 🎬 How to Use
+
+### Step 1: Get HuggingFace API Key
+
+1. Visit [HuggingFace Settings](https://huggingface.co/settings/tokens)
+2. Create new token with **Read** access
+3. Copy token (starts with `hf_`)
+
+### Step 2: Enter App URLs
+
+**App Store:**
+- Format: Just the app ID number
+- Example: `1022164656`
+- Find in URL: `apps.apple.com/app/id1022164656`
+
+**Play Store:**
+- Format: Package name
+- Example: `com.disney.wdpro.dlr`
+- Find in URL: `play.google.com/store/apps/details?id=com.disney.wdpro.dlr`
+
+### Step 3: Run Analysis
+
+1. Paste HuggingFace API key
+2. Enter URLs (one per line)
+3. Choose reviews per app (5-100)
+4. Click **"🚀 Start Analysis"**
+5. Wait ~7 seconds per review
+6. View results!
+
+### Step 4: Manage Database
+
+- **Reset Database**: Click when analyzing different apps
+- **Keep Database**: Don't reset to track trends over time
+
+## 💡 Use Cases
+
+**Product Management**
+- Identify critical issues
+- Prioritize feature requests
+- Track sentiment trends
+
+**UX/Design Teams**
+- Find usability issues
+- Discover improvement ideas
+- Understand user emotions
+
+**Support Teams**
+- Route issues automatically
+- Categorize requests
+- Identify quick wins
+
+**Business Analytics**
+- Measure satisfaction
+- Calculate churn risk
+- Track competitive position
+
+## 🏗️ Technical Details
+
+**AI Models:**
+1. Qwen/Qwen2.5-72B-Instruct - Classification
+2. meta-llama/Llama-3.2-3B-Instruct - User analysis
+3. meta-llama/Llama-3.3-70B-Instruct - Synthesis
+4. cardiffnlp/twitter-roberta-base-sentiment-latest - Sentiment
+5. finiteautomata/bertweet-base-sentiment-analysis - Validation
+6. meta-llama/Llama-3.1-70B-Instruct - Final reasoning
+
+**Technology Stack:**
+- Frontend: Streamlit
+- AI: LangGraph + HuggingFace Inference API
+- Database: SQLite (49 columns)
+- Visualization: Plotly
+
+**Performance:**
+- ⚡ ~7 seconds per review
+- 🔄 Parallel processing
+- 🎯 100% model agreement
+
+## 📊 Sample Output
+
+```
+Dashboard Metrics:
+📊 Total Reviews: 20
+😊 Positive: 15 (75%)
+😞 Negative: 4 (20%)
+🚨 Critical: 0
+📉 Churn Risk: 7.5%
+
+Department Routing:
+🏢 Engineering: 4
+🎨 UX: 9
+💼 Business: 6
+```
+
+## 🔐 Privacy & Data
+
+- ✅ All processing on HuggingFace servers
+- ✅ No permanent data storage
+- ✅ Public reviews only
+- ✅ Reset database anytime
+- ✅ Export your data
+
+## 🙋 Support
+
+For issues:
+1. Check HuggingFace API key is valid
+2. Verify URL format is correct
+3. Try resetting database
+4. Check internet connection
+
+---
+
+**Made with ❤️ for Product Teams**
+
+⭐ Star this space if you find it useful!