Enhance README with detailed feature descriptions, tech stack updates…

…, and improved setup instructions

README.md

@@ -10,29 +10,45 @@ This was also an experiement of writing an entire project where:
 
 ## Features 🌟
 
-- **Interactive Timeline**: Visualize chat activity over time
-- **Word Cloud**: See the most frequently used words in your conversations
-- **Top Contributors**: Identify the most active participants
-- **Emoji Analysis**: Track the most popular emojis
-- **AI-Powered Insights**: Get memorable moments and context-aware holiday greetings using Claude AI
-- **Festive UI**: Enjoy snow effects and holiday-themed animations
-- **Real-time Analysis**: Process and visualize chat data instantly
+- **Interactive Timeline**: Visualize chat activity patterns over time with clickable data points
+- **Floating Word Cloud**: Interactive visualization of most used words with popularity counts
+- **Sentiment Analysis**: Track group mood over time with AI-powered sentiment scoring
+- **Top Contributors**: Identify the most active participants with message counts
+- **Emoji Analysis**: Track and visualize the most popular emojis used
+- **Viral Messages**: Detect and showcase messages that sparked the most engagement
+- **Shared Links**: Track and analyze the most engaging shared links with context
+- **AI-Powered Insights**: 
+  - Memorable moments detection
+  - Context-aware holiday greetings
+  - Custom chat poems based on group dynamics
+  - Popular topics analysis
+- **Festive UI**: Snow effects, confetti animations, and holiday-themed design
+- **Real-time Analysis**: Instant processing and visualization of chat data
 - **Responsive Design**: Works beautifully on both desktop and mobile
+- **Smart Caching**: Efficient caching system for faster repeated analyses
 
 ## Tech Stack 🛠
 
 - **Backend**: FastAPI (Python)
 - **Frontend**: HTML, JavaScript, Tailwind CSS
-- **AI/ML**: Claude AI via AWS Bedrock
-- **Visualization**: Chart.js, D3.js
-- **Container**: Docker support
+- **AI/ML**: 
+  - Claude AI via AWS Bedrock for insights
+  - Parallel sentiment analysis processing
+  - Smart message batching
+- **Visualization**: 
+  - Chart.js for timelines and graphs
+  - Custom interactive word cloud implementation
+- **Performance**: 
+  - Caching system with MD5 hashing
+  - Parallel processing for sentiment analysis
+  - Optimized message parsing
 - **Dependencies**: See requirements.txt for full list
 
 ## Prerequisites 📋
 
 - Python 3.9+
 - AWS Account with Bedrock access
-- AWS credentials (access key and secret key)
+- AWS credentials configured
 - Node.js (optional, for development)
 
 ## Setup 🚀
@@ -56,10 +72,12 @@ source holyvenv/bin/activate  # On Windows: holyvenv\Scripts\activate
 pip install -r requirements.txt
 ```
 
-4. Create a .env file with your AWS credentials:
+4. Create a .env file with your credentials:
 ```env
 AWS_ACCESS_KEY_ID=your_access_key
 AWS_SECRET_ACCESS_KEY=your_secret_key
+SENTIMENT_MODEL=anthropic.claude-3-sonnet-20240229-v1:0
+CHAT_INSIGHTS_MODEL=anthropic.claude-3-sonnet-20240229-v1:0
 ```
 
 5. Run the application:
@@ -78,7 +96,12 @@ docker build -t whatsapp-analyzer .
 
 2. Run the container:
 ```bash
-docker run -p 8000:8000 -e AWS_ACCESS_KEY_ID=your_access_key -e AWS_SECRET_ACCESS_KEY=your_secret_key whatsapp-analyzer
+docker run -p 8000:8000 \
+  -e AWS_ACCESS_KEY_ID=your_access_key \
+  -e AWS_SECRET_ACCESS_KEY=your_secret_key \
+  -e SENTIMENT_MODEL=your_model \
+  -e CHAT_INSIGHTS_MODEL=your_model \
+  whatsapp-analyzer
 ```
 
 ## Usage 📱
@@ -92,43 +115,60 @@ docker run -p 8000:8000 -e AWS_ACCESS_KEY_ID=your_access_key -e AWS_SECRET_ACCES
 2. Upload the exported .txt file to the application
 
 3. View your personalized chat analysis with:
-   - Activity timeline
-   - Word cloud
-   - Top contributors
-   - Emoji statistics
-   - AI-generated memorable moments
+   - Interactive activity timeline with clickable data points
+   - Floating word cloud with popularity counts
+   - Sentiment analysis timeline showing group mood
+   - Top contributors and their message counts
+   - Most used emoji statistics
+   - AI-detected memorable moments
+   - Viral messages with engagement metrics
+   - Popular shared links with context
    - Custom holiday greeting
+   - Group chat poem
 
 ## Project Structure 📁
 
 ```
 holiday-ai-hackerspace/
-├── main.py              # FastAPI application and backend logic
-├── requirements.txt     # Python dependencies
-├── Dockerfile          # Container configuration
-├── .env               # Environment variables (create this)
-├── .gitignore        # Git ignore rules
-├── static/           # Frontend assets
-│   ├── index.html    # Main HTML file
-│   └── app.js        # Frontend JavaScript
-└── cache/           # Cache directory for API responses
+├── main.py                # FastAPI application and backend logic
+├── requirements.txt       # Python dependencies
+├── Dockerfile            # Container configuration
+├── .env                 # Environment variables (create this)
+├── .gitignore          # Git ignore rules
+├── static/             # Static frontend assets
+│   ├── index.html      # Main HTML file
+│   ├── app.js          # Frontend JavaScript
+│   └── word-cloud.js   # Word cloud implementation
+├── gh_static_front/    # GitHub static frontend
+│   ├── index.html      # Static HTML file
+│   ├── app.js          # Frontend logic
+│   ├── word-cloud.js   # Word cloud visualization
+│   └── analyzed_data/  # Pre-analyzed chat data
+└── cache/             # Cache directory for API responses
 ```
 
 ## Development 🔧
 
 ### Backend (main.py)
 - FastAPI application with CORS support
 - Structured logging with color formatting
-- Error handling and input validation
-- Caching for API responses
-- WhatsApp chat parsing with multiple timestamp formats
-- Integration with AWS Bedrock for AI analysis
-
-### Frontend (static/)
+- Efficient chat parsing with multiple timestamp formats
+- Parallel sentiment analysis processing
+- Smart message batching for AI analysis
+- Caching system with MD5 hashing
+- Comprehensive error handling
+- Viral message detection algorithm
+- Shared link analysis
+
+### Frontend (static/ & gh_static_front/)
 - Responsive design with Tailwind CSS
-- Interactive visualizations with Chart.js and D3.js
+- Interactive visualizations:
+  - Activity timeline with clickable points
+  - Floating word cloud with hover effects
+  - Sentiment analysis graph
+  - Engagement metrics displays
 - Real-time data processing
-- Festive animations and effects
+- Festive animations (snow, confetti)
 - Error handling and loading states
 
 ## Contributing 🤝
@@ -149,9 +189,12 @@ holiday-ai-hackerspace/
 
 Future improvements could include:
 
-1. [ ] Support for more chat export formats (Facebook Messanger, Discord, etc.)
+1. [ ] Support for more chat export formats (Facebook Messenger, Discord, etc.)
 2. [ ] Export reports as PDF
 3. [ ] More AI-powered insights and additional visualization types
+4. [ ] Enhanced sentiment analysis with emotion detection
+5. [ ] Topic clustering and trend analysis
+6. [ ] Custom theme support
 
 ## License 📄
 
@@ -160,8 +203,9 @@ This project is licensed under the MIT License - see the LICENSE file for detail
 ## Acknowledgments 💝
 
 - Built with Roo-Cline, ChatGPT and @zoharbabin
-- Visualization libraries: Chart.js and D3.js
+- Chart.js for data visualization
 - Tailwind CSS for styling
+- AWS Bedrock for AI capabilities
 
 ---