problem-framing(extract-worker): document embedding
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@winsomeglint is already working on this.
Since Jun 12, 2026.
- Dominant language
- Python
- Stars
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- Forks
- 0
- Avg merge
- 2h 5m
- Merged PRs (30d)
- 18
Description
Precisely define/scope semantic vectors usages inside DS
- similar doc search (MLT vector)
- hybrid search
- RAG
Inputs
- document in markdown formats
- embedding configuration
Outputs
- document embedded as chunks stored in a vector DB
Success metrics (TBD)
Element to help us define success:
- what storage and vector size can we afford ?
- review embedding leaderboard: https://huggingface.co/spaces/mteb/leaderboard
- where do we want to store vectors (storage ES ?) ?
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