Simple-Intent-Based-Chatbot

Simple AI Chatbot: Python, NLP, Tensor Flow, Flask. Understands, responds, learns. Explore, create, chat! 🤖💬

Simple AI Chatbot with Neural Network Intelligence

Welcome to my GitHub repository! Here, you'll find the source code and resources for my Simple AI Chatbot project, designed to engage in meaningful conversations with users.

Project Overview

My chatbot is powered by natural language processing (NLP) techniques, TensorFlow, and Python, making it an excellent example of an AI-driven conversation agent. It understands and responds to text inputs, adapts to various questions, and provides context-aware answers.

Key Features

• Language Understanding: My chatbot processes and comprehends text inputs using NLP, enabling it to understand user queries effectively.

• Pattern Recognition: It recognizes patterns in questions and statements, enhancing its ability to generate relevant responses. This is achieved through a carefully crafted JSON file that defines question types, patterns, and responses.

• Machine Learning Backbone: I've used TensorFlow to create a neural network model. This model is trained using the "bag of words" concept, which helps the chatbot grasp the context of conversations.

• Model Persistence: My trained neural network model is stored in a pickle file, ensuring quick and efficient access to the chatbot's intelligence.

• User Interaction: I've developed a user-friendly Flask web application that serves as the chatbot's interface. Users can input questions and receive real-time responses through an intuitive HTML front-end.

Getting Started

• Explore the source code to understand the inner workings of my chatbot.
• Use the training script ("training.py") to create and train your chatbot models.
• Check out the chatbot script ("chatbot.py") for loading and utilizing trained models.
• Experiment with the Flask app to interact with the chatbot and see its responses in action.

Why This Matters

My project demonstrates the potential of AI in enhancing user experiences. Whether you're interested in improving customer support, building intelligent virtual assistants, or simply exploring the world of AI-driven conversation, this repository provides valuable insights and resources.

Technologies Used

• Python
• NLTK (Natural Language Toolkit)
• TensorFlow
• Flask
• HTML/CSS