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Use these checks after deploying (on-premise or SageMaker) to confirm the service is healthy and producing expected results.

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1. Service health

curl -s http://localhost:8080/ping | python3 -m json.tool
# {"status": "ok", "models": ["h1", "tissue-seg"]}

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2. Model availability (SDK)

available_backbones() lists the models the Bioptimus SDK can construct (read from its bundled configs) — it does not query the server. The /ping response in step 1 is the source of truth for what the deployed endpoint actually serves. 
from bioptimus.models.backbones import Backbone
print(Backbone.available_backbones())
# ['h1', 'm-optimus', 'tissue-seg']

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3. Output shape checks

ModelExpected output length
H-Optimus (/api/embed/h1)1536
M-Optimus embedding1536
M-Optimus predictionnumber of output genes (see /api/metadata/m-optimus)
Tissue segmentationH×W (262,144 for a 512×512 tile)