AI Conversational Agent

This project implements an AI conversational agent using two large language models (LLMs) that can engage in a dialogue with each other. The conversation is displayed in a graphical user interface (GUI) and is also spoken aloud using text-to-speech technology.

Features

• Utilizes two LLMs (GPT-2 and DialoGPT) for generating responses
• GUI for displaying the conversation
• Text-to-speech functionality for audible responses
• Sentiment analysis of the conversation
• Conversation logging
• Memory feature to maintain context

Requirements

• Python 3.7+
• PyTorch
• Transformers
• TextBlob
• pyttsx3

Installation

1. Clone this repository:

   git clone https://github.com/Musa-Ali-Kazmi/LLM-Chatterbox.git
   

2. Install the required dependencies:

   pip install torch transformers textblob pyttsx3
   

Usage

Run the main script:

python chatterbox_app.py

1. Select the models for each agent from the dropdown menus.
2. Click "Start Conversation" and enter a topic when prompted.
3. The conversation will begin, and you can watch and listen as the AI agents converse.
4. To end the program, click the "Exit" button.

Customization

• To use different pre-trained models, modify the model initialization in the script.
• Adjust the max_new_tokens parameter in the response generation functions to control response length.
• Modify the GUI layout and design by changing the Tkinter widget properties.

Acknowledgments

• This project uses the Transformers library by Hugging Face.
• Text-to-speech functionality is provided by pyttsx3.
• Sentiment analysis is performed using TextBlob.

GUI Example