Overview
OpenMontage turns an AI coding assistant into a video production system. Instead of a fixed orchestrator, the agent itself drives the work: the repository supplies executable capabilities (tools and pipeline definitions), operational guidance (skills that teach OpenMontage's conventions) and technical knowledge (provider documentation), and the assistant reads them to plan and execute a production from a plain-English brief such as "make a 60-second animated explainer about how neural networks learn".
Twelve pipelines cover animated explainers, motion graphics, avatar spokespeople, cinematic edits, batch short-form clipping, documentary montage from open archives, hybrid footage, localisation and dubbing, podcast repurposing, screen demos, talking heads and SVG character animation. Each runs the same seven stages — research, proposal, script, scene plan, assets, edit, compose — with human approval gates at the proposal, script, scene-plan, asset and publish steps, plus pre-compose validation and a post-render self-review that inspects the output with ffprobe and frame extraction.
Generation is provider-pluggable: video through Kling, Runway Gen-4, Veo 3.1, MiniMax, Seedance and local WAN 2.2 or Hunyuan; images through FLUX, Imagen, Grok Imagine, GPT Image 2 and Recraft; speech through ElevenLabs, Google TTS, OpenAI TTS and local Piper. Composition happens in Remotion (React) or HyperFrames (HTML/GSAP). A zero-key path exists — Piper for narration, Archive.org, NASA, Wikimedia Commons, Pexels, Unsplash and Pixabay for media, Remotion or HyperFrames plus FFmpeg for assembly — and paid providers run under cost estimation, a configurable spend cap and a per-action approval threshold.
What it does
- Twelve production pipelines that all follow a research → proposal → script → scene plan → assets → edit → compose flow
- Human approval gates at proposal, script, scene plan, asset and publish, with pre-compose validation and post-render self-review
- Pluggable generation providers for video, image, speech and music, plus local options that need no API key
- Two composition engines: Remotion for React-based rendering and HyperFrames for HTML/GSAP kinetic typography and SVG character rigs
- Budget controls — cost estimates before execution, spend caps, and track-only, warn or hard-limit modes
- Ships assistant-specific configuration for Claude Code, Cursor, GitHub Copilot, Codex and Windsurf over shared AGENT_GUIDE.md and PROJECT_CONTEXT.md
Getting started
OpenMontage is a repository you clone and then open in your AI coding assistant. It needs Python 3.10+, FFmpeg, Node.js 18+ and one of the supported assistants.
Clone and set up
`make setup` creates the virtualenv, installs Python dependencies, installs the Remotion composer's npm packages, adds Piper TTS and copies the example environment file.
git clone https://github.com/calesthio/OpenMontage.git
cd OpenMontage
make setupSet up without make
The same steps, spelled out, for machines without `make`.
python3 -m venv .venv && source .venv/bin/activate && python -m pip install -r requirements.txt && cd remotion-composer && npm install && cd .. && python -m pip install piper-tts && cp .env.example .envBrief the agent
Open the project folder in Claude Code, Cursor, Copilot, Windsurf or Codex — each has its own instructions file in the repo — and describe the video you want. The agent picks a pipeline and walks the stages, stopping at the approval gates.
Make a 60-second animated explainer about how neural networks learnCommands and code are distilled from the project's own documentation — always check the official repo for the latest.
When to use it
- Produce an explainer or short-form video end to end from a written brief instead of a timeline
- Batch-extract vertical clips from a long recording with a repeatable pipeline
- Build videos with no paid API keys using Piper, open archives and FFmpeg
- Keep generation spend bounded when a run touches several paid media providers
How OpenMontage compares
OpenMontage alongside other open-source video generation tools AI/TLDR tracks, ranked by GitHub stars.
| Tool | Stars | What it does |
|---|---|---|
| MoneyPrinterTurbo | ★ 125k | A self-hosted WebUI, API and CLI that turns one topic or keyword into a finished short video — script, stock or generated footage, voiceover, subtitles and music. |
| OpenMontage | ★ 60.4k | Turn a coding agent into a video production studio |
| HyperFrames | ★ 51.9k | HeyGen's HTML-to-video renderer: author a composition in HTML, CSS and JS, preview it in a browser, then render the same input to a deterministic MP4 locally or on AWS Lambda. |
| Toonflow | ★ 15.8k | Infinite-canvas workbench for AI short-drama production, taking a novel through chapter events, script, storyboards and video nodes. |
| Palmier Pro | ★ 14.4k | A Swift-native macOS video editor with generative models in the timeline and a built-in MCP server, so Claude, Codex or Cursor can edit the open project alongside you. |
| Hypit | ★ 11.8k | A markup language and compiler that lets a coding agent rebuild a reference video as an editable workflow — footage, captions, B-roll and effects anchored to words rather than timestamps — and render variants in one command. |
| LTX-2 | ★ 9.5k | Lightricks' official inference package for its LTX-2 audio-video model: a dozen pipelines covering text/image-to-video, keyframe interpolation, audio-to-video, retakes, dubbing and HDR/EXR, plus a LoRA trainer. |
| DramaClaw | ★ 6.2k | Self-hosted AIGC video engine pairing an infinite node canvas with an episode pipeline that carries a manuscript through assets, storyboards, shots, voice-over and export. |