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open-video-ai

open-video-ai

open-video

Open-source video generation — Ollama for MiniMax H3. Local director on ComfyUI.

Agent模型 / 推理视觉 / 图像agentcomfyuiminimax-h3open-sourcetext-to-videovideo-generation
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项目介绍

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OpenVideo

OpenVideo

Ollama for video models.
Run MiniMax H3 on your own GPU — install · pull · run — plus a drop-in skill so any coding agent can generate high-quality video.

License Version Website Hugging Face

Ollama → local LLMs.  OpenVideo → local video.
v0.0.1 is exactly that loop for MiniMax H3 — not a multi-model platform yet. ▶ Watch the demo


60-second start

# Linux / macOS — installs ComfyUI engine + pulls H3 weights (resumable, ~54 GB)
curl -fsSL https://open-video.ai/install | bash

# Windows (PowerShell) — prefers WSL2 for the full H3 GPU path
irm https://open-video.ai/install.ps1 | iex

# Same mental model as Ollama: pull → status → run
open-video pull h3                  # verify / resume H3 weights
open-video status                   # engine health + weight inventory (alias: ps)
open-video run "A lone astronaut planting a flag on a red dune at dusk" --duration 8

open-video "sunset waves" --dry-run # plan + validate, no GPU spent
OS Install Generate
Linux curl …/install \| bash NVIDIA GPU · full H3
macOS same curl (setup + dry-run) H3 generation via community/MLX paths; not default
Windows irm …/install.ps1 \| iex WSL2 for H3 GPU; native dry-run OK

Hardware. Local-first; bring your own NVIDIA GPU. open-video recommend-quant picks the right weight tier for your card:

VRAM Quant tier
≥ 22 GB INT8 ConvRot (default, verified)
12–22 GB INT8 + --lowvram offload
9–12 GB W4 ConvRot (~10 GB)
< 9 GB NF4 (~8 GB entry)
Prefer manual clone / pip?
git clone https://github.com/open-video-ai/open-video &amp;&amp; cd open-video
pip install -e .
open-video pull h3
open-video run &quot;waves at sunset, golden hour&quot; --duration 10 --model h3 --output out.mp4
# ComfyUI at http://127.0.0.1:8188 (env OPEN_VIDEO_COMFYUI)
Python API: `from open_video import H3Backend, ComfyUIAdapter` — see [`ARCHITECTURE.md`](ARCHITECTURE.md).

The agent path (what makes this different)

Point any agent host at the skill — it installs/pulls if needed, crafts the official H3 3-field prompt, validates against hard constraints, generates, and reviews:

Skill Use when
skill/h3-video/SKILL.md v0.0.1 default — high-quality single/short H3 clips (T2V / I2V / FL2VA)
skill/open-video/SKILL.md Longer director path (plan → judge → stitch) — evolving

Works with Claude Code, Cursor, Codex, OpenCode, and any host that loads SKILL.md. Quality is encoded, not left to chance: prompt grammar (backends/h3/PROMPT_GRAMMAR.md), a hard validator, and curated presets (open-video list-presets).

Three ways to use it

Interface For Experience
🤖 Skill harness Any agent Load skill/h3-video → agent generates H3 video end-to-end
⌨️ CLI Developers / scripts open-video pull · status · run (Ollama-shaped)
🖥️ Site Discovery open-video.ai — install + docs

What works today vs what is designed next

v0.0.1 (shipped) Designed (not wired yet)
Generate Local MiniMax H3 via ComfyUI — pull / status / run Multi-model backends (Wan, LTX, …)
Agent path skill/h3-video crafts official prompts + drives the CLI Full multi-shot director agent
Judge loop Real VLM judge via env OPEN_VIDEO_VLM_URL/MODEL/KEY + automatic REFINE retries (OPEN_VIDEO_JUDGE_RETRIES, best take kept); honest PASS stub when unset Best-of-N tournament judging
Long film Single clips (H3 shot length) Planner → stitch multi-minute film
Hosted try Site /try is a browser mockup Real hosted generate

The generate → judge → refine loop runs today: point OPEN_VIDEO_VLM_URL at any OpenAI-compatible vision model and low-scoring shots regenerate automatically with a bumped seed (OPEN_VIDEO_JUDGE_RETRIES extra takes, best score kept — full take history in --json).

Why local

Closed tools charge per second and keep your prompts and footage in their pipeline. Open video models are now good enough to matter — what was missing is the simple local loop: install → pull → run, with best-practice prompting built in. v0.0.1 is that loop.

OpenVideo (local) Typical closed SaaS
Model MiniMax H3, open weights on your GPU Vendor-hosted only
Cost Your GPU + electricity Per-second API / subscription
Data Stays on your machine Vendor pipeline
Software license Apache-2.0 Proprietary ToS

Licenses — read this before commercial use

  • Detailed weights terms: docs/WEIGHTS_LICENSE.md.
  • Code (this repo): Apache-2.0. Use it freely.
  • Model weights are NOT covered by this repo's license. MiniMax H3 weights are distributed under the MiniMax H3 Community License (see the model card and upstream MiniMaxAI), which includes territorial and commercial-use restrictions. The installer downloads weights from the upstream mirrors; you are responsible for confirming the license permits your use case and region.
  • License-cleaner second backends (e.g. Wan) are on the roadmap.

How it compares (honest)

What Open software? Local open model? Notes
OpenVideo CLI + skill + H3 on ComfyUI ✅ Apache-2.0 ✅ H3 this project — director/judge loop is scaffolding
Runway Closed SaaS Hosted product
Seedance Closed agentic long video Hosted product
ComfyUI Node-graph engine ✅ GPL via custom nodes The runtime we drive — a dependency, not a competitor

OpenVideo is not a foundation model and not a replacement for ComfyUI. v0.0.1 is the install → pull → run layer plus an agent skill on top of H3.

Contributing

OpenVideo is a plugin surface — contribute what you're good at:

You have Contribute → Effort
A great prompt library/prompts/ — a verified recipe 5 min
A new model (Wan 2.2, Hunyuan, LTX) backends/&lt;model&gt;/ — a backend plugin an afternoon
A scoring method / vision judge judges/ — a judge plugin an afternoon
A new engine (diffusers, SGLang) engines/&lt;engine&gt;/ — an adapter an afternoon
A style LoRA library/ — share it 10 min

See CONTRIBUTING.md for templates and GOVERNANCE.md for how decisions get made. We integrate, we don't reinvent — if a working project already does it, we wrap it as a plugin. Chat lands later; for now use GitHub Issues.

Architecture

Shipped path:

prompt / skill ──→ open-video CLI ──→ backends/h3 ──→ engines/comfyui ──→ mp4

Design target (modules exist as scaffolds; not all wired end-to-end):

concept ──→ planner → crafter → validator → backend → judge → stitcher → film
  • backends/h3/ — MiniMax H3 plugin: prompt grammar, workflows, constraints.
  • engines/comfyui/ — ComfyUI HTTP adapter (submit / wait / fetch).
  • skill/h3-video/ — the agent harness.
  • core/ — shared contracts + judge/planner scaffolding for later phases.

Full design notes: ARCHITECTURE.md.

Status & roadmap

v0.0.1 — shipped: local H3 pull/run, agent skill harness, one-line installer, product site.

  • Next: wire a real vision judge, multi-shot continuity, a license-clean second backend.
  • Later, only when real: hosted generate, desktop packaging, community gallery.

Acknowledgments

Standing on the shoulders of open giants: ComfyUI (the engine), MiniMax H3 (the model), the woodfantasy prompt methodology (MIT-0), and VideoScore (judge direction). We integrate, not reinvent.

Security

Private vulnerability reporting: SECURITY.md.

License

Apache-2.0 © OpenVideo contributors · open-video.ai

OpenVideo · open-video.ai · Apache-2.0