Support arbitrarily dimensional embedding spaces

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Assessment

Difficulty
2/5
Estimated time
1-3 hours
Newbie friendliness
70/100
Issue type
Feature
Clarity
Clearly specified
Activity status
Active
Tech stack
yaml
Domain
data

Research direction

Start with embedding_schema.yaml and the EmbeddingSpace and EmbeddingLocation definitions it contains: today they hard-code x/y coordinates. Read how coordinates are represented and where the schema validates entries, then add explicit dimensionality metadata on EmbeddingSpace and a validation rule that each coordinate list in EmbeddingLocation matches that dimensionality. Done means the schema accepts a 3+-dimensional example, rejects mismatched coordinate lengths, and any existing 2D fixtures still validate.

Written by the indexing model from the issue text.

Description

enhancement schema

embedding_schema.yaml
EmbeddingSpace and EmbeddingLocation currently support only 2D embeddings with x/y coordinates. Extend the schema to represent an arbitrary number of dimensions, with explicit dimensionality metadata and validation that coordinate lengths match the embedding space.

Dominant language
Python
Stars
4
Forks
1
Avg merge
3d 14h
Merged PRs (30d)
8

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