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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
  1. Run the following command to install the packages:
  pip install -r requirements.txt