OneCut

OneCut is an AI-powered, browser-based video editor built to transform long-form recordings into high-impact highlights. It combines intelligent clip detection, a professional timeline editor, and scalable export workflows so creators can publish faster without sacrificing quality.

Why OneCut

• Reduce hours of manual editing with AI-assisted highlight generation.
• Keep full creative control with a multi-track timeline and precision tools.
• Produce platform-ready videos for YouTube, TikTok, Instagram, and more.
• Run a modern full-stack architecture designed for real-time media workflows.

Core Features

AI Editing Engine

• Smart highlight detection for interviews, tutorials, podcasts, and similar formats.
• Configurable prompt-based instructions for tailored output.
• Short-form and long-form clip generation modes.
• Scene-aware analysis pipeline for better content segmentation.

Professional Web Editor

• Multi-track timeline with drag-and-drop interactions.
• Frame-level trimming and clip splitting.
• Playback speed controls and aspect-ratio presets (16:9, 9:16, 1:1).
• Text, stickers, transitions, and visual effects.

Captions, Audio, and Voice

• Automatic caption generation with timing synchronization.
• Caption style presets for different publishing formats.
• AI voiceover support and music layering.
• Audio cleanup and volume balancing workflows.

Export and Delivery

• Hybrid rendering pipeline with FFmpeg and browser rendering.
• Progress-tracked export jobs with real-time updates.
• Optimized output profiles for major social/video platforms.

Product Workflow

1. Upload source footage to your project.
2. Analyze content with AI to generate initial highlight candidates.
3. Edit in the timeline (captions, cuts, transitions, overlays, audio).
4. Export a final render in your preferred platform format.

Tech Stack

Frontend (client)

• Next.js 15
• React 18
• Tailwind CSS 4
• FFmpeg.wasm
• Socket.IO Client

Backend (server)

• Node.js + Express
• TypeScript
• Supabase (Auth + PostgreSQL)
• Google Cloud Storage
• Google Vertex AI / Google GenAI
• FFmpeg + Puppeteer (hybrid export)

Repository Structure

OneCut/
├── client/                 # Next.js app (UI/editor)
├── server/                 # Express API + media/AI processing
├── _db/                    # SQL schema and migrations
├── render.yaml             # Deployment config
└── README.md

Getting Started

Prerequisites

• Node.js 18+
• npm
• Supabase project
• Google Cloud project with required APIs (Storage, Vertex AI, Video Transcoder)
• ElevenLabs API key (if using voiceover features)

1) Clone and install

git clone <your-repo-url>
cd OneCut
npm install
cd client && npm install
cd ../server && npm install

2) Configure environment variables

Create client/.env.local:

NEXT_PUBLIC_SUPABASE_URL=your_supabase_url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your_supabase_anon_key
NEXT_PUBLIC_API_URL=http://localhost:3001

Create server/.env:

SUPABASE_URL=your_supabase_url
SUPABASE_SERVICE_KEY=your_supabase_service_key
GOOGLE_CLOUD_STORAGE_BUCKET=your_bucket_name
GOOGLE_APPLICATION_CREDENTIALS=path/to/service-account.json
VERTEX_AI_PROJECT_ID=your_project_id
VERTEX_AI_LOCATION=us-central1
ELEVENLABS_API_KEY=your_elevenlabs_api_key
PORT=3001

3) Apply database schema

Run SQL files inside _db/ against your Supabase/PostgreSQL instance (for example: users.sql, projects.sql, assets.sql, clips.sql, tracks.sql, etc.).

4) Start development servers

Backend:

cd server
npm run dev

Frontend (new terminal):

cd client
npm run dev

Open http://localhost:3000.

API Overview

All protected endpoints require a Supabase JWT:

Authorization: Bearer <access_token>

Representative endpoints:

• POST /api/projects - create project
• POST /api/assets/upload-to-gcs - upload source media
• POST /api/quickclips/start - trigger AI clip generation
• GET /api/timeline/:projectId - fetch timeline data
• POST /api/export/start - start export
• GET /api/export/status/:jobId - export progress/status

Architecture Notes

• Hybrid render system: FFmpeg handles media operations while browser rendering preserves rich visual fidelity.
• Real-time job updates: Socket-based status updates for processing and export stages.
• AI pipeline: Analysis, transcription, scene understanding, and clip proposal generation.

Development

Client build:

cd client
npm run build

Server build:

cd server
npm run build

Contributing

Contributions are welcome. Recommended flow:

1. Fork the repository.
2. Create a feature branch.
3. Implement and test your changes.
4. Open a pull request with a clear description and test notes.

Security

Do not commit secrets, service-account files, or production API keys. Use local environment files and your deployment secret manager.

License

Add your project license here (for example, MIT, Apache-2.0, or proprietary/internal use).

Support

For bug reports and feature requests, open a GitHub issue with reproduction steps and environment details.

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OneCut is built to make professional, AI-assisted editing faster, more accessible, and production-ready.