Embedding spaces API
Create vector spaces, upsert asset or frame vectors, and run scoped similarity search.
Endpoints
Method
Endpoint
Purpose
Create, upsert, and search
curl --fail-with-body --silent --show-error \
-X POST "$UNITLAB_API_URL/api/sdk/embedding-spaces/" \
-H "Authorization: Api-Key $UNITLAB_API_KEY" \
-H "Content-Type: application/json" \
--data '{"name":"vision-encoder-2026-07","dimensions":3,"model_name":"encoder@sha256:..."}'
curl --fail-with-body --silent --show-error \
-X POST "$UNITLAB_API_URL/api/sdk/embedding-spaces/SPACE_ID/vectors/" \
-H "Authorization: Api-Key $UNITLAB_API_KEY" \
-H "Content-Type: application/json" \
--data '{"items":[{"asset_id":"ASSET_A","vector":[0.1,0.2,0.3]},{"asset_id":"ASSET_B","frame_index":4,"vector":[0.3,0.2,0.1]}]}'
curl --fail-with-body --silent --show-error \
-X POST "$UNITLAB_API_URL/api/sdk/embedding-spaces/SPACE_ID/search/" \
-H "Authorization: Api-Key $UNITLAB_API_KEY" \
-H "Content-Type: application/json" \
--data '{"vector":[0.1,0.2,0.3],"limit":25,"project_id":"PROJECT_ID","level":"frame"}'Request operating contract
Concern
Required behavior