https://github.com/umarilly/chatbot

A simple chatbot project implemented in Python using Flask, Keras, NLTK, and JSON. The chatbot can understand and respond to predefined intents based on user input.
https://github.com/umarilly/chatbot

Last synced: 8 days ago
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A simple chatbot project implemented in Python using Flask, Keras, NLTK, and JSON. The chatbot can understand and respond to predefined intents based on user input.

• Host: GitHub
• URL: https://github.com/umarilly/chatbot
• Owner: umarilly
• Created: 2024-03-26T06:53:57.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-03-26T07:07:05.000Z (9 months ago)
• Last Synced: 2024-03-27T07:49:00.652Z (9 months ago)
• Language: Jupyter Notebook
• Size: 609 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Chatbot Project

This project is a simple chatbot implemented using Python, Flask, Keras, NLTK, and JSON. The chatbot is capable of understanding and responding to predefined intents based on user input.

## Project Structure

- **App.py**: Contains the Flask application setup along with the chatbot logic.

- **data.json**: Contains the intents for the chatbot, including tags, patterns, and responses.

- **labels.pkl and texts.pkl**: Store the preprocessed data (words and classes) using pickle.

- **model.h5**: Stores the trained neural network model using Keras.

- **training.ipynb**: Jupyter Notebook used for data preprocessing, model training, and saving the trained model.

- **static/style.css**: Contains the CSS styles for the chatbot interface.

- **templates/index.html**: Contains the HTML structure for the chatbot interface.

## Technologies Used

- **Python**: Programming language used for the backend logic.

- **Flask**: Web framework used for building the web application.

- **Keras**: Deep learning library used for building and training the neural network model.

- **NLTK**: Natural language processing library used for text preprocessing.

- **JSON**: Data format used for storing intents and responses.

- **HTML/CSS**: Used for the frontend interface of the chatbot.

## Usage

1. Install the required libraries using `pip install -r requirements.txt`.

2. Run the Flask application using `python app.py`.

3. Open your web browser and navigate to `http://localhost:5000` to access the chatbot interface.