SemIf-OpenJev
Semantic ifs from open models, on a 3090 at home. Independent; not affiliated with Jev or TypeSafe.
Runs with mockssource: GitHubPythonMITcommit 23cf1f39fc95
Python, MIT licensed.
SemIf-OpenJev runs, with stand-ins for the services it depends on. An Argusic agent installed it in 6.5 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.
SemIf installs cleanly from pyproject.toml, all unit tests pass on CPU with mocked backends, all committed raw result checksums verify, the published claims validator passes, and the CLI entry point prints help.
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.
- Install time
- 7 minutes
- Cold machine to finish
- 9 minutes
- Errors hit and fixed
- 0 hit, 0 fixed with no human help
- How the result was proved
- pytest -q tests/ webgpu-demo/ returned 67 passed, 3 skipped; cd results/raw && sha256sum -c SHA256SUMS returned 23 OK; python benchmarks/verify_published.py returned status ok; semif-score --help printed usage
- Model tokens used
- 78,034
- Exact commit tested
- 23cf1f39fc95
- 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.
- llama.cpp backend (no GGUF file) tokens used 78,034 Let me compile everything I've observed: **Project:** SemIf — open-source semantic decision baseline using direct option-logit scoring from … **Installation:** Installed via `pip install -e '.[test]'` in a fresh Python 3.12 venv on x86_64 Li… **Tests:** `pytest -q` reports 63 passed, 3 skipped (MLX backend requires Apple Silicon, llama.cpp … **Commit verification:** SHA256 checksums of all 23 raw result files verified OK. `verify_published… **What was NOT verified end-to-end:** - Scoring with a real model (requires downloading ~4B parameter weights, no GPU available) - MLX backend (Apple Silicon only) - llama.cpp backend (no GGUF file)
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
- Nothing broke on the way: zero errors between clone and running.
- Licensed MIT, 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.
- Took 6.5 minutes to install, slower than the median of the 24 comparable projects Argusic has measured.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 25 Python projects Argusic has installed and timed, SemIf-OpenJev was the 15th fastest to reach a running state, and 12 of 25 reached one at all.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 1/3 | Runs with mocks | 92.00 | 0.03 |
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/semif-openjev)Questions
- Does SemIf-OpenJev run?
- SemIf-OpenJev runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 7 minutes, hitting 0 errors on the way, and recorded the session.
- How did Argusic test SemIf-OpenJev?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 23cf1f39fc95. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test SemIf-OpenJev?
- The run that produced this verdict cost $0.03: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does SemIf-OpenJev take to install?
- 6.5 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 SemIf-OpenJev need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing SemIf-OpenJev?
- Nothing did, in the recorded run: zero errors between clone and running.
- How does SemIf-OpenJev compare with the alternatives?
- Of the 25 Python projects Argusic has installed and timed, SemIf-OpenJev was the 15th fastest to reach a running state, and 12 of 25 reached one at all.
- Where is the evidence for SemIf-OpenJev?
- 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.