🤖 Mini Chatbot Project in Python

A Python-based chatbot that uses Natural Language Processing (NLP) and a neural network to understand and respond to user inputs. This project demonstrates how to design, train, and deploy a simple chatbot using custom intents.

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🚀 Features

• Interactive chatbot for text-based queries.
• Customizable intents in intents.json.
• Uses Bag of Words (BoW) and one-hot encoding for NLP.
• Neural network model built with TensorFlow/Keras.
• Lightweight and easy to extend or adapt.

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📁 File Structure

• intents.json: Predefined patterns, tags, and responses.
• ChatBot.ipynb: Jupyter Notebook with model training and chatbot interface.
• README.md: Project documentation (this file).

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🧰 Requirements

Install dependencies with:

pip install tensorflow numpy nltk

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🛠️ How to Run

1. Open ChatBot.ipynb in Jupyter Notebook or Google Colab.
2. Run all cells step-by-step:
   • Load data from intents.json
   • Preprocess text
   • Train the neural network
   • Start chatting with the bot

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🔧 Customization

• Add or edit patterns/responses in intents.json.
• Retrain the model to reflect changes using the notebook.

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🧠 How It Works

1. Text Preprocessing: User inputs and patterns are tokenized and transformed using Bag of Words.
2. Model Training: A neural network learns to classify the intent of inputs.
3. Response Generation: The predicted tag is used to fetch a matching response from intents.json.

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📌 Note

This is a basic chatbot designed for educational purposes. It can be enhanced further using advanced NLP techniques like word embeddings or transformers.