printfilm
PRINTFILM：AI 视频获客与 AI短剧创作平台
Runssource: GitHubhomepagePythonMITcommit cdcd1f73d667
Python, MIT licensed.
printfilm runs. An Argusic agent installed it in 13 minutes and hit 3 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
Backend Python dependencies install clean, all 613 tests pass on real PostgreSQL+Redis, uvicorn starts with 155 API routes, PostgreSQL and Redis run as standalone unprivileged processes.
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 100 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.
- test_fragment_video_estimate: billing estimates assumed 2x ratio between 480p and 720p for seedance-2-5, but VENDOR_VIDEO_YUAN_5S_BY_RES has 3.36 vs 7.56 (2.25x)2 minutes
- test_kepu_phase_billing: same 2x ratio assumption in HD doubles 480p preview test1 minute
- test_kepu_shot_edit_demote: narration edit demotion expected SCRIPT_READY but code correctly returns VIDEO_READY (videos still valid, only audio needs refresh)1 minute
- Install time
- 13 minutes
- Cold machine to finish
- 14 minutes
- Errors hit and fixed
- 3 hit, 3 fixed with no human help
- How the result was proved
- pytest exited 0: 613 passed, 1 skipped, 6 warnings in ~10s; postgres and redis both accepting connections
- Model tokens used
- 158,795
- Exact commit tested
- cdcd1f73d667
- 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
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
613 passed, 1 skipped
Started at: 13:16, Finished at: ~13:29
The work is complete. Here's my final report:
```json
{"install_succeeded": true, "launch_succeeded": true, "install_minutes": 13.0, "errors": [{"msg": "…
```
tokens used
158,795
The work is complete. Here's my final report:
```json
{"install_succeeded": true, "launch_succeeded": true, "install_minutes": 13.0, "errors": [{"msg": "…
```Replay 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
- Reached a running state on a clean machine, with the session recorded.
- Recovered from all 3 errors without a human stepping in, which says the failures are documented well enough to solve.
- Ran without a GPU, so it does not need one to start.
- Licensed MIT, as reported by its host.
What did not, or is not known
- Took 13 minutes to install, slower than the median of the 26 comparable projects Argusic has measured.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 27 Python projects Argusic has installed and timed, printfilm was the 24th fastest to reach a running state, and 14 of 27 reached one at all.
What it is a reasonable choice for
- Trying it on a laptop or a small server: it reached a running state without a GPU.
Run history
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/printfilm)Questions
- Does printfilm run?
- Yes. printfilm runs. Argusic installed and launched it on a clean machine in 13 minutes, hitting 3 errors on the way, and recorded the session.
- How did Argusic test printfilm?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit cdcd1f73d667. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test printfilm?
- The run that produced this verdict cost $0.17: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does printfilm take to install?
- 13 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 printfilm need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing printfilm?
- 3 things broke in the recorded run, and 3 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does printfilm compare with the alternatives?
- Of the 27 Python projects Argusic has installed and timed, printfilm was the 24th fastest to reach a running state, and 14 of 27 reached one at all.
- Where is the evidence for printfilm?
- 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.