AI-ChatBot

This project implements a simple chatbot using Keras with a pre-trained model. The chatbot is trained on a dataset of intents and responses. The model predicts the intent of user input and generates an appropriate response.

Overview

This chatbot script uses a neural network model (chatbot_model.h5), a tokenizer (Tokenizer.p), and a label encoder (LabelEncoder.p) to understand user input and generate responses. The model is trained on a dataset of intents and responses provided in the intents.json file.

Prerequisites

• Python 3.x
• Required Python packages: Keras, pandas, numpy

Installation

1. Clone the repository:

   https://github.com/shukur-alom/AI-ChatBot.git
   

2. Install the required dependencies:

pip install -r requirements.txt

3. Run the chatbot script:

python main.py

4. Enter your messages when prompted, and the chatbot will generate responses based on the trained model.

Model Details

• The model is a neural network loaded from chatbot_model.h5.
• Tokenization is performed using the tokenizer saved in Tokenizer.p.
• Intent labels are encoded and decoded using the label encoder saved in LabelEncoder.p.
• The intents and responses are defined in the intents.json file.