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It would be great to attach GCP request labels to Vertex calls when running with vertex=True. Vertex AI accepts a labels map on GenerateContentRequest (docs), and those labels flow into Cloud Billing.
Today there's no way to set them, so multiple SDK-based workloads in one GCP project collapse into a single Vertex AI line item.
Evidence
The Vertex request type compiled into the harness already carries labels:
Environment
google-antigravitySDK v0.1.7Description
It would be great to attach GCP request labels to Vertex calls when running with
vertex=True. Vertex AI accepts alabelsmap onGenerateContentRequest(docs), and those labels flow into Cloud Billing.Today there's no way to set them, so multiple SDK-based workloads in one GCP project collapse into a single Vertex AI line item.
Evidence
The Vertex request type compiled into the harness already carries
labels:But no message in the harness config proto (the Python → Go contract) exposes a
labelsfield:And it isn't on the Python config model either:
Proposed Fix
The Vertex request already accepts
labels(see above); the gap is that neither the config proto nor the Python model carries them. A fix would:labelsmap field to the harness config proto, e.g. onVertexEndpoint.GenerateContentRequest.labelsfor each Vertex call in the harness.labels: dict[str, str]option on the Vertex config, as aLocalAgentConfigshorthand alongsideproject/location.Workarounds
UsageMetadata, priced offline — parallel bookkeeping that can't reconcile against the actual invoice (and metadata was historically dropped on finish/tool turns, Finish/tool turns drop SDK usage metadata while equivalent plain text turns do report it #24).google-genaidirectly withGenerateContentConfig(labels=...)— loses the harness (skills, sandbox, policies).