This project is a chatbot designed to provide comprehensive information about the Crop Diversification Program (CDP) and other farming-related topics. The chatbot uses Natural Language Processing (NLP) techniques to understand and respond to user queries regarding various agricultural practices, crop diversification strategies, sustainable farming methods, and government initiatives that support these areas.
Natural Language Toolkit (NLTK): Used to preprocess and tokenize user input using the Bag of Words (BoW) model, enabling the chatbot to recognize important terms and phrases from user queries.
Numpy: Performs numerical operations, converting text into numerical representations and handling mathematical computations essential for processing user inputs.
Torch (PyTorch): Powers a neural network that classifies user intents and generates appropriate responses based on their queries.
Intents.json: A structured file containing predefined intents (categories of user queries), patterns (sample inputs), and corresponding responses, acting as the chatbot's knowledge base.
Flask: Used for the frontend, Flask provides an easy-to-use interface where users can interact with the chatbot, while handling backend routing and communication between the user and the chatbot's NLP and neural network components.
