ProfSync Backend

ProfSync is a professor rating and review system similar to Rate My Professor. This repository contains the backend code for the ProfSync application, which includes a chatbot capable of handling both professor-specific queries and casual conversations.

Features

• Express.js server setup with CORS support
• Integration with Google's Generative AI (Gemini) for message classification and response generation
• Pinecone vector database integration for efficient similarity search
• Conversation memory management for context preservation
• Dynamic response formatting for both professor-specific and casual conversations

Prerequisites

Before you begin, ensure you have met the following requirements:

• Node.js installed
• npm (Node Package Manager) installed
• Pinecone account and API key
• Google Generative AI API key

Installation

1. Clone the repository:

   git clone [repository-url]
   

2. Navigate to the project directory:

   cd profsync-backend
   

3. Install the dependencies:

   npm install
   

4. Create a .env file in the root directory and add the following environment variables:

   REACT_APP_GOOGLE_API_KEY=[Your Google API Key]
   REACT_APP_PINECONE_API_KEY=[Your Pinecone API Key]
   REACT_APP_PINECONE_INDEX_NAME=[Your Pinecone Index Name]
   PORT=5000
   

Usage

To start the server, run:

npm start

The server will start running on http://localhost:5000.

API Endpoints

POST /api/send-message

Send a message to the chatbot.

Request body:

{
  "message": "Your message here"
}

Response:

{
  "response": "HTML formatted response from the chatbot"
}

Architecture

1. Message Classification: Incoming messages are classified as either "Professor-Specific" or "Casual Conversation" using Google's Generative AI.

2. Embedding Generation: For professor-specific queries, the message is converted into an embedding using Google's text-embedding-004 model.

3. Pinecone Search: The embedding is used to search for similar entries in the Pinecone vector database.

4. Response Generation:

   • For professor-specific queries, the Pinecone results are summarized using Google's Generative AI.
   • For casual conversations, a generic response is generated.

5. Response Formatting: The final response is formatted into HTML for easy rendering on the frontend.

Other code modules

• Frontend module can be accessed here.
• Code to generate and store data to pinecone can be accessed here

Contributing

Contributions to ProfSync are welcome. Please follow these steps:

1. Fork the repository
2. Create a new branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

This project is licensed under the Apache License, Version 2.0

Contact

For any questions or inquiries about this project, please contact [Your Name] at [your email or preferred contact method].