georgeguimaraes / tribunal
LLM evaluation framework for Elixir: evaluate and test LLM outputs, detect hallucinations, measure response quality
Why this job: says: llm evaluation, evaluation framework; topics: evaluation, llm-evaluation, testing
What it does
If you build LLM features in Elixir, there's no native way to answer "is this output any good, and did my last change make it worse?" Regular tests can't assert on faithfulness, relevance, or whether a jailbreak got through, and the mature eval tools (DeepEval, RAGAS, promptfoo) all live in Python, off your stack and out of your CI.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 14 days ago
- Stars
- 119
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v3.1.0
- Released 24 days ago
- Built with
- Elixir
- 100% of the code
Is it looked after?
- Contributors
- 4
- Last 90 days
- Issues
- 100% closed
- 0 still open
- Pull requests
- 49 merged
- 3 waiting
- Releases
- 15
- 15 in the last year
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Elixir 100%
Topics
- ai
- elixir
- evaluation
- hallucination-detection
- llm
- llm-evaluation
- testing
Project record
- JobEvals and observability
- StatusListed
- Commits119
- Forks3
- Watching3
- Stars in 28 days+2
- CreatedJan 12, 2026
- First seen by usNov 7, 2026
- CheckedNov 9, 2026