Your personal knowledge graph in every lecture.

A live learning copilot that turns lectures into personalized knowledge graphs. Students see their understanding update in real time as concepts are discussed and polls are answered; professors get a heatmap of class mastery and polls tied to the lecture.

• PDF → knowledge graph — Upload course material; Claude extracts concepts and prerequisites (e.g. 35+ nodes from a 200-page textbook). Each student has their own graph; mastery is a confidence score (0–1) driven by polls, tutoring, and attendance.
• Live concept detection — Zoom RTMS captures lecture audio; transcripts are run through concept detection (Claude Haiku) and pushed to student graphs and professor heatmap in real time via Socket.IO.
• Contextual polling — AI generates poll questions from what was just said and targets concepts the class is struggling with. Responses update mastery and graph colors (red → yellow → green) instantly.
• Aaron (AI tutor) — Post-lecture Socratic tutor (Claude Sonnet) personalized to each student’s weak nodes; Perplexity Sonar surfaces learning resources (articles, videos) for specific gaps.
• Study groups — Match students by complementary strengths/weaknesses; one-click Zoom link and view of who can teach what.
• Professor dashboard — Live heatmap by concept, per-student graphs, and in-lecture reinforcement suggestions (what to re-explain, which examples to add).

• Python 3.10+
• Node.js 18+
• Supabase project
• API keys: Anthropic (Claude), Perplexity; optionally Zoom, Deepgram

git clone https://github.com/jasonyi33/prereq.git
cd prereq
cp .env.example .env

Edit .env with SUPABASE_URL, SUPABASE_KEY, ANTHROPIC_API_KEY, PERPLEXITY_API_KEY, and FLASK_API_URL (your Flask API base URL). Zoom keys for live RTMS with their SDK.

Create the database tables in Supabase (SQL Editor).

Terminal 1 — Flask API

cd api
pip install -r requirements.txt
python main.py

Then seed demo data (CS229-style course, ~35 concepts, 4 students):

python scripts/seed_demo.py

Terminal 2 — Next.js frontend

cd frontend
npm install
npm run dev

prereq/
├── api/                 # Flask backend
│   ├── main.py
│   ├── requirements.txt
│   └── ...
├── frontend/            # Next.js + Socket.IO
│   ├── server/          # Express + Socket.IO
│   ├── src/app/         # Pages and API routes
│   ├── src/components/
│   └── ...
├── scripts/             # seed_demo.py, etc.
├── CLAUDE.md            # Dev guide and full schema
├── render.yaml          # Render config
└── .env.example

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