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README.md

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-title: '123'
+title: 'Multilingual Sentiment Analyzer'
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 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+🌍 Multilingual Sentiment Analyzer
+A comprehensive AI-powered sentiment analysis application with explainable AI features (SHAP & LIME) supporting multiple languages.
+🚀 Features
+
+Multi-language Support: Auto-detect or manually select from English, Chinese, Spanish, French, German, Swedish
+Advanced Analysis: SHAP and LIME explainable AI integration
+Batch Processing: Analyze multiple texts simultaneously with parallel processing
+Interactive Visualizations: Real-time charts and dashboards with Plotly
+History Management: Track and export analysis history
+Multiple Themes: Customizable color themes for visualizations
+File Upload: Support for CSV and TXT file uploads
+Export Functionality: Export results in CSV and JSON formats
+
+📁 Project Structure
+sentiment_analyzer/
+├── config.py              # Configuration settings
+├── models.py               # Model management & sentiment engine
+├── analysis.py             # SHAP/LIME explainable AI
+├── visualization.py        # Plotly visualizations
+├── data_utils.py           # Data processing & history management
+├── app.py                  # Application logic
+├── main.py                 # Gradio interface & startup
+├── requirements.txt        # Python dependencies
+├── Dockerfile             # Docker configuration
+└── README.md              # This file
+🛠 Installation
+Option 1: Local Installation
+bash# Clone the repository
+git clone <repository-url>
+cd sentiment_analyzer
+
+# Install dependencies
+pip install -r requirements.txt
+
+# Download NLTK data
+python -c "import nltk; nltk.download('stopwords'); nltk.download('punkt')"
+
+# Run the application
+python main.py
+Option 2: Docker
+bash# Build the Docker image
+docker build -t sentiment-analyzer .
+
+# Run the container
+docker run -p 7860:7860 sentiment-analyzer
+Option 3: Hugging Face Spaces
+
+Create a new Space on Hugging Face
+Select "Docker" as the SDK
+Upload all project files
+The app will automatically deploy
+
+🎯 Usage
+Single Text Analysis
+
+Navigate to the "Single Analysis" tab
+Enter your text in any supported language
+Select language (or use Auto Detect)
+Choose visualization theme
+Configure preprocessing options
+Click "Analyze"
+
+Advanced Analysis (SHAP/LIME)
+
+Go to "Advanced Analysis" tab
+Enter text for explainable AI analysis
+Adjust number of samples (50-300)
+Click "SHAP Analysis" or "LIME Analysis"
+View feature importance visualizations
+
+Batch Processing
+
+Switch to "Batch Analysis" tab
+Upload a file or enter multiple texts (one per line)
+Configure analysis settings
+Click "Analyze Batch"
+View summary statistics and detailed results
+
+History & Analytics
+
+Open "History & Analytics" tab
+View comprehensive analysis dashboard
+Export data in CSV or JSON format
+Clear history when needed
+
+🔧 Configuration
+Edit config.py to customize:
+
+Model Settings: Change supported models and languages
+Processing Limits: Adjust batch sizes and memory limits
+UI Themes: Modify color schemes
+Cache Settings: Configure caching parameters
+
+📊 Supported Models
+
+English: CardiffNLP Twitter RoBERTa
+Multilingual: CardiffNLP XLM-RoBERTa
+Chinese: UER RoBERTa Chinese
+
+🎨 Themes
+
+Default: Green/Red/Orange
+Ocean: Blue/Orange/Cyan
+Dark: Darker variants
+Rainbow: Purple/Pink/Red
+
+⚡ Performance Features
+
+Model Caching: LRU cache for efficient model management
+Parallel Processing: Multi-threaded batch analysis
+Memory Optimization: Automatic cleanup and GPU management
+Lazy Loading: Models loaded on-demand
+
+🐛 Troubleshooting
+Common Issues
+
+SHAP/LIME Errors: Reduce sample size or text length
+Memory Issues: Lower batch size or enable text cleaning
+Model Loading: Check internet connection for model downloads
+Port Conflicts: Change port in main.py if 7860 is occupied
+
+Performance Tips
+
+Use GPU if available for faster processing
+Enable text cleaning for better preprocessing
+Reduce sample sizes for faster explainable AI analysis
+Clear history periodically to save memory
+
+📄 License
+This project is open source and available under the MIT License.
+🤝 Contributing
+Contributions are welcome! Please feel free to submit pull requests or open issues for bugs and feature requests.
+📞 Support
+For support and questions, please open an issue in the repository.
+
+Built with ❤️ using Gradio, Transformers, SHAP, LIME, and Plotly