Document supported and unsuppored SVS variants
Nobody has claimed this yet.
Assessment
- Difficulty
- 1/5
- Estimated time
- Under an hour
- Newbie friendliness
- 68/100
- Issue type
- Documentation
- Clarity
- Mostly clear
- Activity status
- Stale
- Tech stack
- python
- Domain
- documentation
Research direction
Review the installation steps and the supported PyPI SVS variant, then compare them with the unsupported variant at https://github.com/intel/ScalableVectorSearch. Update the documentation to identify the supported and unsupported variants and state that the unsupported one should be removed before installing svsbench.
Written by the indexing model from the issue text.
Description
Currently, the SVS variant on PyPI is supported and automatically installed when the installation steps are followed. The SVS variant at https://github.com/intel/ScalableVectorSearch is not supported and should be removed before installing svsbench. This should be documented.
- Dominant language
- Python
- Stars
- 5
- Forks
- 4
- PR merge metrics
- No merged PRs in 30d
Contributor guide
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.
Similar issues
-
Difficulty 2/5 1-3 hours Newbie friendliness 88/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 82/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 78/100
-
enhancement
Difficulty 2/5 1-3 hours Newbie friendliness 72/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 74/100