# Release v2.0.0 - Advanced Sentiment Analysis Bot

## 🎉 Release Date: January 2026

This is the initial release of the Advanced Sentiment Analysis Bot with cutting-edge features and comprehensive improvements.

## ✨ Key Features

### Core Functionality
- **Real-time Sentiment Analysis**: Multi-modal analysis using VADER and TextBlob
- **Emotion Detection**: Identifies joy, anger, sadness, fear, and surprise
- **Response Adaptation**: Context-aware responses based on detected emotions
- **Named Entity Recognition**: Extracts entities using spaCy

### Advanced AI Features
- **Personality Trait Detection**: Analyzes Big Five personality traits
- **Emotional Contagion Analysis**: Detects emotional patterns in conversations
- **User Satisfaction Prediction**: Predicts user satisfaction based on conversation patterns
- **Conversation Similarity Matching**: Finds similar conversations using TF-IDF
- **User Profiling**: Tracks and analyzes user behavior over time

### Technical Features
- **Beautiful Web Interface**: Modern, responsive UI with real-time chat
- **RESTful API**: Clean API endpoints for integration
- **Comprehensive Error Handling**: Robust validation and error handling
- **Production Ready**: Docker support and deployment configurations
- **Testing Suite**: Complete test coverage with pytest

## 🐛 Bug Fixes & Improvements

### Code Quality
- ✅ Removed unused `pickle` import
- ✅ Fixed `setup.py` entry point (changed from `app:main` to `run:main`)
- ✅ Created missing `static` directory structure
- ✅ Added comprehensive `.gitignore` file

### Error Handling
- ✅ Added robust datetime parsing with fallback handling
- ✅ Enhanced API endpoint validation (JSON content type, input length)
- ✅ Improved error messages for better debugging
- ✅ Added safe handling for edge cases and invalid data

### API Improvements
- ✅ Added input validation (max 1000 characters)
- ✅ Enhanced error responses with proper HTTP status codes
- ✅ Improved user_id validation across all endpoints
- ✅ Better handling of empty or malformed requests

## 📦 Installation

```bash
# Clone the repository
git clone https://github.com/rskworld/sentiment-analysis-bot.git
cd sentiment-analysis-bot

# Create virtual environment
python -m venv sentiment_env
source sentiment_env/bin/activate  # On Windows: sentiment_env\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Download spaCy model
python -m spacy download en_core_web_sm

# Run the application
python app.py
# or
python run.py
```

## 🚀 Quick Start

1. Install dependencies: `pip install -r requirements.txt`
2. Download spaCy model: `python -m spacy download en_core_web_sm`
3. Run: `python app.py`
4. Open browser: `http://localhost:5000`

## 📊 API Endpoints

- `POST /api/chat` - Chat with sentiment analysis
- `GET /api/report` - Get sentiment analysis report
- `POST /api/reset` - Reset conversation history
- `GET /api/health` - Health check
- `GET /api/user-profile/<user_id>` - Get user profile
- `POST /api/personality-analysis` - Analyze personality
- `POST /api/emotional-contagion` - Check emotional patterns
- `GET /api/satisfaction-prediction/<user_id>` - Get satisfaction prediction
- `POST /api/conversation-similarity` - Find similar conversations

## 🛠️ Technologies

- Python 3.8+
- Flask 2.3.3
- NLTK 3.8.1
- TextBlob 0.17.1
- spaCy 3.6.1
- scikit-learn 1.3.0
- Bootstrap 5
- Font Awesome 6

## 📝 Documentation

Full documentation is available in the [README.md](README.md) file.

## 👥 Credits

- **Founder**: Molla Samser
- **Designer & Tester**: Rima Khatun
- **Organization**: RSK World
- **Contact**: help@rskworld.in | +91 93305 39277
- **Website**: https://rskworld.in

## 📄 License

This project is part of RSK World's educational resources. Usage is permitted for educational and development purposes.

## 🔗 Links

- Repository: https://github.com/rskworld/sentiment-analysis-bot
- Website: https://rskworld.in
- Contact: help@rskworld.in

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**© 2026 RSK World. All rights reserved.**
