This project presents a contextual chatbot implemented in PyTorch, utilizing a feed-forward neural network (NN) architecture within a natural language processing (NLP) pipeline. The chatbot's architecture comprises input and output layers, with one or more hidden layers facilitating feature extraction and abstraction. The NLP pipeline includes tokenization, embedding, and encoding layers, allowing the model to process and understand natural language input. During inference, the chatbot leverages its trained parameters to generate responses based on the context of the conversation, ensuring relevant and coherent interactions with users. This repository provides the codebase and documentation necessary to train, evaluate, and deploy the contextual chatbot for various applications. I have learned this code from this youtube video and implemented in my company project by doing some changes in hyperparameters.