Can embeddings used to calculate the keyword to document distance be exposed as part of KeyBERT API?
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- Dominant language
- Python
- Stars
- 4.2k
- Forks
- 385
- PR merge metrics
- No merged PRs in 30d
Description
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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
The issue body names no files, tests, or output contract. Start by tracing the existing KeyBERT API and the keyword-to-document distance calculation; clarify which embeddings should be exposed and how the public API should represent them before assessing completion.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- api, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100