https://github.com/auraoneai/eval-adapter
Adapters between rubric-spec and common evaluation framework inputs.
https://github.com/auraoneai/eval-adapter
adapters ai-evaluation evals rubric
Last synced: 6 days ago
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Adapters between rubric-spec and common evaluation framework inputs.
- Host: GitHub
- URL: https://github.com/auraoneai/eval-adapter
- Owner: auraoneai
- License: mit
- Created: 2026-05-12T01:32:58.000Z (23 days ago)
- Default Branch: main
- Last Pushed: 2026-05-12T02:37:56.000Z (22 days ago)
- Last Synced: 2026-05-12T03:25:31.835Z (22 days ago)
- Topics: adapters, ai-evaluation, evals, rubric
- Language: Python
- Homepage: https://auraone.ai/open
- Size: 11.7 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Security: SECURITY.md
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README
# eval-adapter
`eval-adapter` lets one rubric-spec v1 rubric and run config drive synthetic-compatible runs across Inspect AI, LM Eval Harness, OpenAI Evals, PromptFoo, DeepEval, LangSmith exports, and Phoenix exports.
## Quickstart
```bash
pip install eval-adapter
eval-adapter run --config examples/unified_config_sample.yaml --runner all
```
The runner modules normalize each framework shape into one `EvalRunResult` containing
`item_count`, per-criterion scores, weights, weighted scores, and source metadata.
LangSmith and Phoenix exports can be imported from their feedback/trace shapes; see
`examples/sample_exports.json`.
## What This Is Not
This is not a hosted eval platform and includes no paid or customer data.