Chatbot LLM Project

This project implements a chatbot using a GPT-2 language model. The chatbot is trained on a combined dataset of question-answer pairs and dialogue exchanges, enabling it to handle various conversational contexts. The backend is built using FastAPI, and the frontend is a simple ReactJS application.

As of now this is day 1 effort that's committed as initial commit. Its still not able to generate correct responses and has still a long way to go.

Table of Contents

• Requirements
• Installation
• Data Preparation
• Training the Model
• Running the Backend
• Running the Frontend
• Testing the Chatbot
• Acknowledgments

Requirements

• Python 3.8 or higher
• Node.js and npm
• pip (Python package installer)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/chatbot-llm.git
   cd chatbot-llm

2. Set up the Python environment:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
   pip install -r requirements.txt

3. Set up the ReactJS frontend:

   cd llm_frontend
   npm install
   cd ..

Data Preparation

1. Create your datasets:

   • qa_dataset.json (example):

   [
       {"question": "What is AI?", "answer": "AI stands for Artificial Intelligence."},
       {"question": "Who wrote '1984'?", "answer": "George Orwell wrote '1984'."}
   ]

   • dialogue_dataset.json (example):

   [
       {"context": "Hello! How can I help you today?", "response": "Hi! I'm looking for information on your services."},
       {"context": "Sure, what do you need help with?", "response": "Can you tell me more about your pricing plans?"}
   ]

2. Preprocess the datasets:

   python preprocess.py

Training the Model

Train the GPT-2 model on the combined dataset:

python train.py

Running the Backend

1. Ensure the virtual environment is activated:

source venv/bin/activate  # On Windows use `venv\Scripts\activate`

2. Start the FastAPI server:

uvicorn main:app --reload

Running the Frontend

1. Navigate to the frontend directory:

cd llm_frontend

2. Start the React application:

npm start

Testing the Chatbot

1. Open your browser and navigate to http://localhost:3000.
2. Enter a prompt in the input field and click "Submit".
3. The chatbot should respond based on the trained model.