LLPhant
LLPhant - A comprehensive PHP Generative AI Framework using OpenAI GPT 4. Inspired by Langchain
Runssource: GitHubPHPMITcommit d85d902e91ee
PHP, MIT licensed. The project labels itself: agent, autophp, embeddings, genai, generative ai, gpt4, langchain and laravel.
LLPhant runs. An Argusic agent installed it in 3 minutes and hit 2 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
Static PHP 8.2.32 and Composer 2.7.9 installed; all 119 Composer dependencies resolved; 223 unit tests pass in 0.3s; PHPStan static analysis passes with 0 errors; Laravel Pint style check passes on 294 files
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.
- No PHP interpreter or Composer installed on host2 minutes
- ext-mongodb not available in static PHP build, blocking composer install1 minute
- Install time
- 3 minutes
- Cold machine to finish
- 6 minutes
- Errors hit and fixed
- 2 hit, 2 fixed with no human help
- How the result was proved
- composer test:unit exited 0, 223 passed (417 assertions); phpstan analyse exited 0 with no errors; pint --test passed on 294 files
- Model tokens used
- 64,033
- Exact commit tested
- d85d902e91ee
- 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.
──────────────────────────────────────────────────────────────────── Laravel
PASS ......................................................... 294 files
All checks pass. Let me compile the final result
exec
/bin/sh -lc 'cd /work/repo && export PATH="/home/runner/bin:$PATH" && /tmp/php vendor/bin/pest test…
succeeded in 270ms:
Tests: 2 warnings, 223 passed (417 assertions)
Duration: 0.29s
All tasks complete. Here is the final result:
tokens used
64,033
All tasks complete. Here is the final result: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.
- Installed in 3 minutes, faster than the median of the 71 comparable projects Argusic has measured.
- Recovered from all 2 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
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Of the 72 agent projects Argusic has installed and timed, LLPhant was the 24th fastest to reach a running state, and 49 of 72 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.
- A quick evaluation: it was running 3 minutes after the clone.
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
Topics (from GitHub)
agentautophpembeddingsgenaigenerative-aigpt4langchainlaravelllamaindexopenaiphpsymfonyvector-database
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/llphant)Questions
- Does LLPhant run?
- Yes. LLPhant runs. Argusic installed and launched it on a clean machine in 3 minutes, hitting 2 errors on the way, and recorded the session.
- How did Argusic test LLPhant?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit d85d902e91ee. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test LLPhant?
- The run that produced this verdict cost $0.02: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does LLPhant take to install?
- 3 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 LLPhant need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing LLPhant?
- 2 things broke in the recorded run, and 2 were fixed without human help. Each one, and the time it cost, is listed on this page.
- How does LLPhant compare with the alternatives?
- Of the 72 agent projects Argusic has installed and timed, LLPhant was the 24th fastest to reach a running state, and 49 of 72 reached one at all.
- Where is the evidence for LLPhant?
- 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.