Chatbot using CNN 🤖

A simple chatbot application built with a Convolutional Neural Network (CNN) that classifies user input into predefined intents and generates relevant responses. This project demonstrates how deep learning can be used for basic conversational AI.

🔍 Features

• 💬 Text-based chatbot that responds based on intent classification
• 🧠 Uses CNN model for intent prediction
• 📚 Predefined intents and responses (in intents.json)
• 🧪 Includes training and inference code for easy experimentation

🛠️ Setup & Usage

1. Clone the repo

   git clone https://github.com/krutipandy/Chatbot-using-CNN.git
   cd Chatbot-using-CNN

2. Install dependencies

   pip install -r requirements.txt

3. Train the model

   python train.py

4. Chat with the bot

   python chat.py

🧠 How It Works

• The chatbot reads user input and preprocesses text using NLTK utilities.
• A CNN model classifies this input into one of the predefined intent categories.
• Based on the predicted intent, a suitable response is selected and shown to the user.

📁 File Overview

File	Purpose
train.py	Train the CNN model
chat.py	Run the chatbot
model.py	Model architecture
nltk_utils.py	Text preprocessing helpers
intents.json	Intent categories & responses
app.py	Optional web interface

🚀 Why This Project Is Useful

This project is perfect for beginners learning:

✅ NLP basics ✅ Deep learning for text classification ✅ Building AI-powered chat systems

Generated from Youtube for understanding purpose:

https://github.com/patrickloeber