Create test criteria.
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- Dominant language
- Python
- Stars
- 103
- Forks
- 16
- Avg merge
- 15h 29m
- Merged PRs (30d)
- 1
Description
Metrics
We need to define the metrics to create test suites and measure results.
I would like to test for hallucinations and response quality according to a grounded set.
Ideally, we would use something like SelfCheckGPT to check for hallucinations.
I'd also like to test recall for document retrieval on a known public dataset with classic vs graph RAG.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No files, tests, or entry points are named. Start by inspecting the repository for existing evaluation and retrieval code, then review the SelfCheckGPT reference and candidate public datasets; done means agreed metrics and test suites that measure hallucinations, response quality, and classic-versus-graph RAG recall.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, search, testing-qa
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100