ProfRateAI is an innovative Next.js application designed to help students find the ideal professor based on their preferences . By leveraging Pinecone for Retrieval-Augmented Generation (RAG), this tool provides fast and accurate information about professors from a review database . Whether you're looking for engaging lectures, manageable workloads, or specific teaching styles, ProfRateAI aims to enhance the course selection process for students.
- AI-Powered Recommendations: Utilizes advanced AI to provide personalized professor recommendations .
- RAG Model Integration: Implements Retrieval-Augmented Generation for quick and relevant information retrieval .
- User-Friendly Chat Interface: Offers an intuitive chat-based interaction for easy querying .
- Comprehensive Professor Profiles: Provides detailed insights based on real student reviews .
- Multi-Criteria Search: Allows students to find professors based on various factors such as teaching style, course difficulty, and subject area .
- Frontend: React.js with Next.js framework
- Backend: Node.js
- AI/ML: Pinecone for vector database, Hugging Face for embeddings
- APIs: Groq for natural language processing
- Styling: Material-UI (MUI) for responsive design
- Data Storage: JSON for review data
To set up ProfRateAI locally, follow these steps:
- Clone the repository:
git clone https://github.com/wilscooding/ProfRateAI.git
- Navigate to the project directory:
cd ProfRateAI
- Install dependencies:
npm install
- Set up environment variables:
Create a
.env.local
file in the root directory and add the following:
PINECONE_API_KEY=your_pinecone_api_key, GROQ_API_KEY=your_groq_api_key, HUGGINGFACE_API_KEY=your_huggingface_api_key
- Run the development server:
npm run dev
After starting the development server, open your browser and navigate to http://localhost:3000
. You'll be greeted with the ProfRateAI landing page. From there, you can:
- Start a chat session to query about professors.
- Input your preferences and requirements for course instructors.
- Receive AI-generated recommendations based on the available professor reviews.
Contributions to ProfRateAI are welcome! To contribute:
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature
) - Commit your changes (
git commit -m 'Add some AmazingFeature'
) - Push to the branch (
git push origin feature/AmazingFeature
) - Open a Pull Request.