Chatbot using PyTorch, NLP, and Neural Networks

🤖 This is a chatbot project built using PyTorch, leveraging natural language processing and neural networks to provide smart and contextual responses to user inputs.

Features

• NLP-Powered: Understands user queries through advanced NLP techniques.
• Neural Networks: Utilizes a neural network model for accurate responses.
• PyTorch Framework: Built with PyTorch, ensuring efficient and flexible model training.

How It Works

1. Data Tokenization: Tokenize the JSON data to break down sentences into individual words.
2. Stemming and Lowercasing: Apply stemming to reduce words to their root forms and convert all text to lowercase for consistency.
3. Bag-of-Words: Use the bag-of-words approach to create a numerical representation of text data suitable for model training.

Packages Used

• nltk for natural language processing tasks.
• numpy for numerical operations.
• torch for building and training neural network models.
• torch.nn for constructing neural networks.
• torch.utils.data for managing data loading.
• Custom modules nltk_utils and model.

Getting Started

Prerequisites

• Python 3.x

Installation

1. Clone this repository:

  git clone https://github.com/codeTun/chatbot.git

2. Run the following command to install the packages:

  pip install -r requirements.txt