A Python-based chatbot that demonstrates basic artificial intelligence concepts through question handling and thoughtful response patterns. This chatbot can identify different types of questions and provide context-aware responses.
- 🤔 Question type recognition (what, why, how)
- 💭 Topic extraction from questions
- 🎯 Pattern-based response generation
- 😊 Basic sentiment analysis
- 💡 POS (Part of Speech) tagging
- Python 3.6 or higher
- NLTK library
- Clone the repository:
git clone https://github.com/yourusername/smart-chatbot.git
cd smart-chatbot
- Install required packages:
python setup.py
- If you encounter NLTK errors, run Python and download required data:
import nltk
nltk.download('punkt')
nltk.download('vader_lexicon')
nltk.download('stopwords')
nltk.download('averaged_perceptron_tagger')
smart-chatbot/
│
├── chatbot.py # Main chatbot implementation
├── setup.py # Setup script for dependencies
└── README.md # This file
Run the chatbot:
python chatbot.py
Example interactions:
Bot: Hi! I'm a smarter chatbot now. I can handle questions! Type 'bye' to exit.
You: What is machine learning?
Bot: Let me think about machine learning...
You: How does a computer work?
Bot: Here's a way to approach computer operation...
You: Why is the sky blue?
Bot: The reason for sky color might be...
The chatbot identifies different types of questions:
- What questions (definitions and explanations)
- How questions (processes and methods)
- Why questions (reasons and causes)
- Templates based on question type
- Topic extraction from user queries
- Sentiment analysis for emotional context
- Fallback responses for unknown queries
- Tokenization
- POS tagging
- Stop word removal
- Basic sentiment analysis
- If 'python' is not recognized:
- Add Python to PATH or use
py
instead ofpython
- Use full path:
C:\Users\YourName\AppData\Local\Programs\Python\Python3x\python.exe
- Add Python to PATH or use
- Run the NLTK downloads manually in Python console
- Ensure internet connection for downloading NLTK data
- Fork the repository
- Create your feature branch (
git checkout -b feature/YourFeature
) - Commit your changes (
git commit -m 'Add some feature'
) - Push to the branch (
git push origin feature/YourFeature
) - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
- Expanded knowledge base
- More sophisticated question patterns
- Conversation context tracking
- Better natural language understanding
- Custom response templates
For support, please open an issue in the GitHub repository.