ai-moive-studio
自然语言驱动的无限画布工作流 Agent，让 AI 视频创作第一次真正变成可编辑的工作流。 AICON 面向创作者，提供从剧本拆解、分镜生成、素材生成、视频合成到内容分发的一整套能力。 不是只给你一个输入框，而是让你用自然语言和无限画布一起驱动创作，把文本、图片、视频节点组织成完整链路，真正把“从灵感到 成片”放进一个系统里完成。
Runs with mockssource: GitHubhomepagePythonApache-2.0commit 4e0810eab1d8
Python, Apache-2.0 licensed. The project labels itself: ai, ai agents, ai video, image to video, infinite canvas, movie, self hosted and storyboard.
ai-moive-studio runs, with stand-ins for the services it depends on. An Argusic agent installed it in 0.8 minutes and hit 5 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
Backend FastAPI server starts and serves root, health, and API v1 endpoints on port 8000. Frontend builds to dist/. 57 backend unit tests and 15 frontend utility tests pass.
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 92 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
What went wrong, in the agent's own words
The agent's own words, worst first, never rewritten into advice.
- Stale test imports: src.api.upload, src.api.files, src.api.projects, src.core.auth0_auth5 minutes
- Missing system library libmagic (python-magic dependency)3 minutes
- Missing FileProcessingStatus and SupportedFileType enums referenced by tests2 minutes
- Stale test import: src.tasks.task (module is src.tasks.project)0.5 minutes
- No PostgreSQL/Redis/MinIO (no Docker) - API register fails
- Install time
- under a minute
- Cold machine to finish
- 22 minutes
- Errors hit and fixed
- 5 hit, 5 fixed with no human help
- How the result was proved
- curl http://127.0.0.1:8000/ returned 200 with 欢迎使用AICG内容分发平台; curl http://127.0.0.1:8000/health returned 200 with healthy; uv run pytest tests/unit/... returned 57 passed; npx vitest run src/tests/unit/utils/ returned 15 passed; npx vite build exited with built in 15.18s
- Model tokens used
- 283,864
- Exact commit tested
- 4e0810eab1d8
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
- Behaviour against real services
- this run was verified against stand-in services only
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
Here's the final verification:
- **Backend**: `uv sync` installed all deps. Server starts at `127.0.0.1:8000`, returns 200 on `/` …
- **Frontend**: `npm install` succeeded. `vite build` produced `dist/index.html`. 15 frontend utili…
- **Backend tests**: 57 passing unit tests (canvas assistant, gateway, model catalog, tasks base).
- **Auth/DB**: Registration endpoint returns 500 because PostgreSQL isn't running (no Docker in con…
exec
/bin/sh -lc "echo '{\"install_succeeded\": true, \"launch_succeeded\": true, \"install_minutes\": 0…
succeeded in 0ms:
{"install_succeeded": true, "launch_succeeded": true, "install_minutes": 0.8, "errors": [{"msg": "M…
2026-10-06T19:38:35.044611Z ERROR codex_core::session: failed to record rollout items: thread 01a11…
tokens used
283,864Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Installed in 0.8 minutes, faster than the median of the 99 comparable projects Argusic has measured.
- Recovered from all 5 errors without a human stepping in, which says the failures are documented well enough to solve.
- Licensed Apache-2.0, as reported by its host.
What did not, or is not known
- Only reached a running state against stand-in services, so nothing here proves it works against the real ones.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 100 ai projects Argusic has installed and timed, ai-moive-studio was the 13th fastest to reach a running state, and 69 of 100 reached one at all.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 1/3 | Runs with mocks | 92.00 | 0.14 |
Topics (from GitHub)
aiai-agentsai-videoimage-to-videoinfinite-canvasmovieself-hostedstoryboardtext-to-videovideovideo-generationworkflow-automation
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/ai-moive-studio)Questions
- Does ai-moive-studio run?
- ai-moive-studio runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 1 minutes, hitting 5 errors on the way, and recorded the session.
- How did Argusic test ai-moive-studio?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 4e0810eab1d8. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test ai-moive-studio?
- The run that produced this verdict cost $0.14: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does ai-moive-studio take to install?
- 0.8 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does ai-moive-studio need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing ai-moive-studio?
- 5 things broke in the recorded run, and 5 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does ai-moive-studio compare with the alternatives?
- Of the 100 ai projects Argusic has installed and timed, ai-moive-studio was the 13th fastest to reach a running state, and 69 of 100 reached one at all.
- Where is the evidence for ai-moive-studio?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.