AI Chatbot Setup

This project contains an AI-powered chatbot that leverages Hugging Face's GPT-2 models for text generation. It features a simple Flask web interface to interact with the chatbot. This guide will walk you through setting up the environment, installing dependencies, and running the chatbot.

Note: You must clone/install and use the folder named "chatbot".

Table of Contents

• Project Overview
• Features
• Technologies Used
• Setup
  • Prerequisites
  • Installation
• Running the Application
• Known Issues
• Contributing
• License
• Contact Me
• Acknowledge

Project Overview

This chatbot utilizes pre-trained GPT-2 models to generate responses based on user input. The chatbot allows you to switch between different GPT-2 model sizes dynamically and provides a web-based interface to communicate with the AI.

Features

• Pre-trained GPT-2 Models: Supports text generation using GPT-2 models.
• Dynamic Model Switching: Change between different GPT-2 models via the web interface.
• Simple Web Interface: Users can interact with the chatbot through a web form.
• Predefined Responses: The chatbot includes predefined responses for common queries.
• Easy Setup: Quick to deploy with all necessary steps automated in a batch script.

Technologies Used

• Python 3.9.13
• Flask: Web framework.
• Hugging Face Transformers: GPT-2 models.
• HTML/CSS/JavaScript: Front-end for the chatbot interface.

Setup

Prerequisites

Before you begin, ensure you have:

• Python 3.9.13 installed on your system. Download here.
• Git (optional, to clone the repository).

Installation

1. Clone the Repository:

bash git clone https://github.com/anandsundaramoorthysa/REP05.ANAND.ChatBot/ cd REP05.ANAND.ChatBot

1. Option 1: Run the setup.bat Script

The setup.bat file automates the setup process, including checking your Python version, creating a virtual environment, installing dependencies, and running the app.

• Double-click setup.bat or run it from the command line:

  bash .\setup.bat

1. Option 2: Install Dependencies Manually

If you prefer to install dependencies manually, run the following command:

bash pip install blinker==1.8.2 certifi==2024.8.30 charset-normalizer==3.3.2 click==8.1.7 colorama==0.4.6 diffusers==0.30.2 filelock==3.16.0 Flask==3.0.3 fsspec==2024.9.0 huggingface-hub==0.24.6 idna==3.8 importlib_metadata==8.5.0 itsdangerous==2.2.0 Jinja2==3.1.4 MarkupSafe==2.1.5 mpmath==1.3.0 networkx==3.2.1 numpy==2.0.2 packaging==24.1 pillow==10.4.0 pip==24.2 psutil==6.0.0 PyYAML==6.0.2 regex==2024.7.24 requests==2.32.3 safetensors==0.4.5 setuptools==58.1.0 sympy==1.13.2 tokenizers==0.19.1 torch==2.4.1 tqdm==4.66.5 transformers==4.44.2 typing_extensions==4.12.2 urllib3==2.2.2 Werkzeug==3.0.4 zipp==3.20.1

1. Option 3: Use a requirements.txt File

Alternatively, you can save the dependencies in a requirements.txt file and install them with:

bash pip install -r requirements.txt

What the script does:

• Python Version Check: The script checks if Python 3.9.13 is installed. If the version is incorrect, it will stop and ask you to install the required version.
• Virtual Environment Setup: If the Python version is correct, the script creates a virtual environment named envir.
• Dependency Installation: Installs the necessary Python packages into the virtual environment.
• Running the App: Finally, the script runs the app.py file to start the chatbot.

Running the Application

After successfully running the setup.bat script, the chatbot will be available on localhost. You can open the URL in your web browser and interact with the chatbot.

To manually run the app after setup: 1. Activate the virtual environment: bash .\envir\Scripts\activate

1. Run the Flask app: bash python app.py

Known Issues

• Python Version Errors: If you get an error about the Python version, make sure you have exactly Python 3.9.13 installed.
• Model Loading Delays: GPT-2 models may take time to download the first time they are used. Be patient while the models are cached.
• Path Issue: If the code does not work even after running the setup.bat file, make sure to replace the path in app.py: bash model_dir = os.getenv('MODEL_DIR', '/models/')
  • Replace /models/ with the correct path where your models are stored.
  • Folder Name: The folder name must be "chatbot".

Contribution

We welcome contributions from the community! To contribute, please follow these steps:

1. Fork the Repository: Create a copy of this repository under your own GitHub account.

2. Clone Your Fork: bash git clone https://github.com/anandsundaramoorthysa/REP05.ANAND.ChatBot.git cd REP05.ANAND.ChatBot

3. Create a New Branch: Create a branch for your changes. bash git checkout -b your-feature-branch

4. Make Your Changes: Edit the files and commit your changes. bash git add . git commit -m "Describe your changes"

5. Push Your Changes: Push the changes to your forked repository. bash git push origin your-feature-branch

6. Submit a Pull Request: Go to the original repository and submit a pull request for review.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact Me

If you have any questions or would like to collaborate, feel free to reach out:

• Email: sanand03072005@gmail.com

• LinkedIn: ANAND SUNDARAMOORTHY SA

Acknowledge

We acknowledge the use of pre-trained models from Hugging Face and other open-source libraries that made this project possible.