LectureFlow

AI-Powered Lecture Notes Generator with Multi-Agent Orchestration

Transform any YouTube lecture into comprehensive notes, flashcards, quizzes, and podcast discussions.

Live Demo · API Docs

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Features

Feature	Description
Real-Time Streaming	ChatGPT-style SSE streaming shows notes generating live
Multi-Agent AI	LangGraph orchestrates 3 agents running in parallel
Smart Caching	99% cost reduction on repeat videos (7-day cache)
Study Tools	Auto-generated flashcards and quizzes
Audio Podcast	NotebookLM-style two-host discussions
PDF Export	Download professional markdown-formatted notes

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Tech Stack

Frontend

• Next.js 15 with App Router and Server Components
• React 19 with Streaming SSR
• Tailwind CSS v4 with OKLCH colors
• shadcn/ui + Magic UI for animations

Backend

• FastAPI with async/await
• LangGraph 1.0 multi-agent orchestration
• Gemini 2.5 Flash for summarization
• GPT-4o-mini for concept extraction
• ElevenLabs for podcast TTS

Infrastructure

• PostgreSQL with SQLAlchemy 2.0 async
• Docker + Cloudflare Tunnel for backend API
• Cloudflare Workers for frontend hosting

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Architecture

┌─────────────────────────────────────────────────────────────┐
│                    Frontend (Next.js 15)                     │
│  EventSource SSE → Real-time streaming UI                   │
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────┐
│                    Backend (FastAPI)                         │
│  ┌─────────────────────────────────────────────────────┐    │
│  │              LangGraph StateGraph                    │    │
│  │                                                      │    │
│  │    Agent 1: Transcript Extractor                    │    │
│  │         │                                            │    │
│  │         ├────────────┬────────────┐                 │    │
│  │         ▼            ▼            ▼                 │    │
│  │    Agent 2:     Agent 3:     Agent 4:              │    │
│  │    Notes Gen    Concepts     Study Tools           │    │
│  │    (Gemini)     (GPT-4o)     (GPT-4o)              │    │
│  │    [PARALLEL]   [PARALLEL]   [ON-DEMAND]           │    │
│  │         │            │            │                 │    │
│  │         └────────────┴────────────┘                 │    │
│  │                      │                               │    │
│  │                      ▼                               │    │
│  │              Save to PostgreSQL                      │    │
│  └─────────────────────────────────────────────────────┘    │
└─────────────────────────────────────────────────────────────┘

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Quick Start

Prerequisites

• Python 3.12+
• Node.js 20+
• PostgreSQL (or Neon free tier)
• API Keys: Gemini, OpenAI, ElevenLabs

Backend

cd backend
python -m venv venv && source venv/bin/activate
pip install -r requirements.txt
cp .env.example .env  # Add your API keys
alembic upgrade head
uvicorn app.main:app --reload

Frontend

cd frontend
npm install
npm run dev

Open http://localhost:3000

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API Endpoints

Method	Endpoint	Description
GET	/api/process/stream	SSE streaming processing
POST	/api/study-materials/generate	Generate flashcards & quiz
POST	/api/podcast/generate	Generate audio podcast
GET	/api/history	List processing history
GET	/api/presets	Demo video presets

Full API docs: http://localhost:8000/docs

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Deployment

Backend (Docker + Cloudflare Tunnel)

cd backend
cp .env.example .env.docker  # Add your API keys + tunnel token
docker compose --env-file .env.docker up -d
docker compose exec api alembic upgrade head

See docker-compose.yml for infrastructure configuration.

Frontend (Cloudflare Workers)

cd frontend
npm install
npm run deploy

Environment variables are configured in wrangler.toml.

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Project Structure

lectureflow/
├── frontend/                 # Next.js 15 application
│   ├── src/app/             # App Router pages
│   ├── src/components/      # React components
│   └── wrangler.toml        # Cloudflare Workers config
└── backend/                  # FastAPI application
    ├── app/
    │   ├── main.py          # FastAPI app & endpoints
    │   ├── models.py        # Pydantic models
    │   ├── agents/          # LangGraph orchestration
    │   ├── tools/           # AI processing tools
    │   └── database/        # SQLAlchemy models
    ├── docker-compose.yml   # Docker orchestration
    └── Dockerfile           # Container build

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Performance

Metric	Value
Fresh processing	15-30 seconds
Cached processing	< 1 second
Cost savings	99% on repeat videos

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License

MIT License - see LICENSE for details.

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Built with LangGraph · FastAPI · Next.js