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Amrit74/chaybot-nlu

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App README

🤖 Chatbot NLU Trainer & Evaluator

A comprehensive platform for training, evaluating, and managing NLU (Natural Language Understanding) models for chatbots.

Features

🎯 Core Features

  • —Intent Classification Training - Train models to understand user intentions
  • —Entity Recognition - Extract key information from user messages
  • —Multi-Backend Support - Train with HuggingFace, Rasa, or spaCy
  • —Model Evaluation - Comprehensive metrics and confusion matrices
  • —Active Learning - Improve models with uncertain predictions
  • —Model Versioning - Track and manage different model versions

📊 Analytics & Monitoring

  • —Real-time training progress
  • —Performance metrics visualization
  • —Confidence score analysis
  • —Intent distribution charts

🔧 Built With

  • —Frontend: Gradio for interactive UI
  • —Backend: Python with scikit-learn, transformers
  • —Visualization: Plotly for charts and graphs
  • —Storage: JSON-based data management

How to Use

1. Training Tab

  • —Upload your training data (JSON format)
  • —Select backend (HuggingFace/Rasa/spaCy)
  • —Configure training parameters
  • —Start training and monitor progress

2. Evaluation Tab

  • —Test your trained model
  • —View performance metrics
  • —Analyze confusion matrix
  • —Check per-intent statistics

3. Prediction Tab

  • —Enter text to classify
  • —View predicted intent and confidence
  • —See alternative predictions
  • —Get entity extraction results

4. Active Learning

  • —Review uncertain predictions
  • —Provide correct labels
  • —Retrain model with feedback
  • —Improve model accuracy

Sample Data Format

json
[
  {
    "text": "I want to book a flight to New York",
    "intent": "book_flight",
    "entities": [
      {"entity": "destination", "value": "New York"}
    ]
  },
  {
    "text": "Cancel my reservation",
    "intent": "cancel_booking",
    "entities": []
  }
]

Links

Author

Amarjit Kumar

License

MIT License - See LICENSE file for details

This is a demo version optimized for Hugging Face Spaces. For the full-featured application with MongoDB integration, user management, and advanced features, check out the GitHub repository.