PartSelect Chatbot

This project is a chatbot designed to assist users with machine parts on the PartSelect e-commerce website. It integrates a FAISS vector database for relevance checking, Puppeteer for fetching part details, and the DeepSeek API for generating natural responses.

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Setup Instructions

1. Clone the Repository

git clone https://github.com/Ding-jinyu/Intsalily-CaseStudy.git

2. Set Up Environment Variables

1. Navigate to the backend directory:

   cd backend
   

2. Create a .env file:

   touch .env
   

3. Add the following keys to the .env file:

   DEEPSEEK_API_KEY=your_deepseek_api_key_here
   OPENAI_API_KEY=your_openai_api_key_here
   

   Replace your_deepseek_api_key_here your_openai_api_key_here with your actual API key.

3. Start the FAISS Microservice

1. Navigate to the backend directory:

   cd backend
   

2. Run the FAISS microservice:

   python faiss_microservice.py
   

   This will start the FAISS server on port 5002.

4. Start the Backend Server

1. In the backend directory, start the backend server:

   node server.js
   

   This will start the backend server on port 5001.

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5. Start the Frontend

1. Navigate to the frontend directory:

   cd ../frontend
   

2. Start the frontend development server:

   npm start
   

   This will start the frontend on port 3000. Open your browser and navigate to http://localhost:3000 to view the chatbot.

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Project Structure

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partselect-chatbot/
├── backend/
│   ├── server.js               # Backend server (Node.js/Express)
│   ├── faiss_microservice.py   # FAISS vector database server
│   ├── .env                    # Environment variables for API keys
│   └── ...                     # Other backend files
├── frontend/
│   ├── public/                 # Static assets and HTML template
│   ├── src/                    # React components and styles
│   └── ...                     # Other frontend files
└── README.md                   # Project documentation