Chatbot with Session Memory and Vectorstore Retrieval

This project is a chatbot application with a Python backend and a React frontend. The chatbot leverages session memory and a vectorstore to retrieve information. The frontend is a custom and simple interface using React, and the connection between the backend and frontend is established using WebSockets.

Features

• Session Memory: Maintains conversation context across multiple interactions.
• Vectorstore Retrieval: Retrieves relevant information from a vectorstore to answer queries.
• WebSocket Communication: Real-time communication between the frontend and backend.

Table of Contents

• Installation
• Usage
• Configuration
• Project Structure
• Contributing
• License

Installation

Backend

1. Clone the repository:

   git clone https://github.com/nydasco/rag_based_chatbot.git
   cd rag_based_chatbot

2. Set up folders and LLM:

   mkdir processed
   mkdir to_process
   mkdir backend/llm

   Download Meta-Llama-3-8B-Instruct-Q8_0.gguf from HuggingFace into the backend/llm folder.

3. Set up a virtual environment:

   cd backend
   python -m venv venv
   source venv/bin/activate

4. Install the required dependencies:

   pip install -r requirements.txt

5. Upload some data: Place pdf files to process into the /to_process folder.

   python process_files.py

6. Run the backend server:

   python backend.py

Frontend

1. Navigate to the frontend directory:

   cd nydasbot

2. Install the required dependencies:

   npm install

3. Start the frontend development server:

   npm start

Usage

Once both the backend and frontend servers are running, open your web browser and navigate to http://localhost:3000. You should see the chatbot interface.

• Type your message in the input field and press Enter or click the "Send" button.
• The chatbot will process your message and respond based on the session context and retrieved information from the vectorstore.

Configuration

The backend configuration is managed through a parameters.toml file. This has been configured to work, however you may want to change some of the setting to better suit your environment.