Sift

Course course planning for Texas A&M CSCE students. Sift combines grade distributions, professor ratings, prerequisite chains, and transcript data to generate personalized course recommendations.

Tech Stack

Layer	Technology
Frontend	Next.js 16 (App Router), TypeScript, Tailwind CSS v4, shadcn/ui, TanStack Query
Backend	Express.js (TypeScript)
Database	Supabase (PostgreSQL)
Data Sources	Anex grade distributions, RateMyProfessors
Transcript Parsing	pdf-parse + Claude API

Setup

Prerequisites

• Node.js 20+
• A Supabase project
• An Anthropic API key (for transcript parsing)

1. Install dependencies

npm install
cd client && npm install
cd ../server && npm install

2. Configure environment variables

client/.env.local

NEXT_PUBLIC_API_URL=http://localhost:3001

server/.env

PORT=3001
FRONTEND_URL=http://localhost:3000
SUPABASE_URL=<your-supabase-url>
SUPABASE_ANON_KEY=<your-supabase-anon-key>
ANTHROPIC_API_KEY=<your-anthropic-api-key>

3. Populate the database

Run the scraper to pull grade distributions from Anex and professor ratings from RateMyProfessors:

cd server && npm run scrape

4. Run the dev servers

# From root — starts both client and server
npm run dev

Or individually:

cd client && npm run dev    # http://localhost:3000
cd server && npm run dev    # http://localhost:3001

Project Structure

sift/
├── client/          # Next.js frontend
├── server/          # Express API server
│   └── scripts/     # Data scraping scripts
└── supabase/        # Database migrations