vocab mapping: use OCL embeddings
Open
Nobody has claimed this yet.
- Dominant language
- Jupyter Notebook
- Stars
- 5
- Forks
- 10
- Avg merge
- 2d 20h
- Merged PRs (30d)
- 17
Description
Allow the vocab mapper to call out to datasets already embedded in OCL
This would allow us to map to any set of concepts already loaded into OCL
This would not replace our own embedded datasets in pinecone
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.
Research direction
Start by locating the vocab mapper entry point and how it currently uses the embedded Pinecone datasets. Determine how it could call datasets and embeddings already loaded into OCL without replacing the existing datasets. Done means the mapper can map against OCL-loaded concept sets while retaining its own Pinecone-backed datasets.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100