NLP Rule-Based Chatbot using NLTK

This project demonstrates how to build a simple rule-based chatbot using Python and the Natural Language Toolkit (NLTK).
It uses classical NLP techniques to understand user input and generate intelligent responses from a text corpus.

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Features

• Tokenization & Lemmatization
• Cosine Similarity for response matching
• Rule-based conversational logic
• Easy-to-understand Python implementation
• Interactive chatbot interface in terminal
• Jupyter Notebook for learning and experimentation

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Technologies Used

• Python 3
• NLTK
• NumPy
• Scikit-learn
• Jupyter Notebook

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Project Files

File	Description
chatbot.py	Core chatbot logic
chatbot.txt	Text corpus used for training
Chatbot.ipynb	Notebook explaining NLP steps
README.md	Project documentation

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⚙️ Installation

1. Clone the repository:

git clone https://github.com/your-username/nlp-rule-based-chatbot-nltk.git

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2.Navigate to the project directory:

cd nlp-rule-based-chatbot-nltk

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3.Navigate to the project directory:

pip install nltk numpy scikit-learn

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4.Download NLTK packages:

import nltk

• nltk.download('punkt')
• nltk.download('wordnet')

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5. How to Run

python chatbot.py

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6. To Exit

bye

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Learning Outcomes

• Understanding NLP preprocessing techniques

• Implementing similarity-based text matching

• Building conversational AI without deep learning

• Hands-on experience with NLTK

Future Enhancements

• Add GUI or web interface

• Integrate speech-to-text

• Upgrade to ML/DL-based chatbot

• Expand dataset for better responses