fess
Open-source, self-hosted enterprise & site search server built on OpenSearch. Crawls web / file / DB / cloud sources, 20+ languages, REST API, and AI/RAG & semantic search. Apache-2.0.
Could not verifysource: GitHubhomepageJavaApache-2.0commit 78abc12b37f7
Java, Apache-2.0 licensed. The project labels itself: ai search, crawler, docker, elasticsearch, elasticsearch alternative, enterprise search, full text search and java.
Argusic could not get fess running. An Argusic agent installed it in 4 minutes and hit 3 errors and fixed every one without help on a clean machine with no GPU, and the whole session was recorded.
The project builds (mvn compile), packages (mvn package), and passes 7,634 unit tests. The Fess Tomcat server starts on port 8080 but returns HTTP 404 on all URLs because the SuggestHelper.init() fails against standard OpenSearch 3.0.0 which lacks the _shard_doc index sort field required by the fess-suggest PIT implementation.
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 47.5 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.
- Java and Maven not pre-installed3 minutes
- Parent POM fess-parent:15.9.0-SNAPSHOT not resolvable offline2 minutes
- Fess's SuggestHelper.init() fails with search_phase_execution_exception: No mapping found for [_shard_doc] in order to sort on
- Install time
- 4 minutes
- Cold machine to finish
- 79 minutes
- Errors hit and fixed
- 3 hit, 3 fixed with no human help
- How the result was proved
- not verified - web context failed to deploy; SuggestHelper.init() blocks Lasta Di container initialization
- Model tokens used
- 874,938
- Exact commit tested
- 78abc12b37f7
- 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
- Whether it works at all
- this run verified nothing, so this page makes no claim either way
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
- OpenSearch 3.0.0 with those plugins starts and the configsync feature works.
- Fess's index-creation logic runs fully against real OpenSearch (all ~30 indexes created).
- Tomcat boots and listens on port 8080.
**What does not work:**
- The web application context fails during `SuggestHelper.init()` because the PIT-based `_shard_doc…
exec
/bin/sh -lc "echo \"ARGUSIC_RESULT: {\\\"install_succeeded\\\": true, \\\"launch_succeeded\\\": fal…
succeeded in 0ms:
The assessment has been recorded. The key finding is that Fess compiles and packages successfully, …
tokens used
874,938
The assessment has been recorded. The key finding is that Fess compiles and packages successfully, …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
- Installed in 4 minutes.
- Recovered from all 3 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.
- Measured 2 times, so the result is not a one-off.
What did not, or is not known
- An agent with no time limit did not get it running.
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 | 2/3 | Did not run | 45.00 | 0.16 | |
| Argusic Runner | 1/3 | Did not run | 50.00 | 0.53 |
Topics (from GitHub)
ai-searchcrawlerdockerelasticsearchelasticsearch-alternativeenterprise-searchfull-text-searchjavallmlucenemcpopensearchragrest-apisearchsearch-engineself-hostedsemantic-searchsite-search
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/fess)Questions
- Does fess run?
- Argusic could not verify that fess runs. Argusic installed and launched it on a clean machine in 4 minutes, hitting 3 errors on the way, and recorded the session.
- How did Argusic test fess?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 78abc12b37f7. 2 attempts are recorded, and the full method is on the methodology page.
- What did it cost to test fess?
- The run that produced this verdict cost $0.53: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does fess take to install?
- 4 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 fess need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing fess?
- 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.
- Where is the evidence for fess?
- All 2 recorded runs are on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.