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Use the @bijection/connectors/mlflow entrypoint to declare MLflow models resources.

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Availability

This page describes the pinned source package. Published availability is unestablished for this artifact. Source build and package availability.

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Resources and modes

Declare a resource in application code, then bind deployment-specific settings and credentials. See typed resources, connections and source inspection.

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Model

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registry: registry

The following example matches configuration standard.
The function references identify application policy queries. Implement those policies in your application; the references alone grant no authority.

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Configuration: standard

Case: mlflow/model/registry/standard. Connection and resource configuration are declared by this exact case. Credential kind: http. Keep credential material in the private credential inventory.
Native admission analysis is available for this exact declaration. Collection: records
Commands
Recorded checks Hosted qualification: unestablished for this catalog configuration. Installed connections report their own identity, authority and current status.

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Provider guidance

mlflow.model.registry({ registeredName, governingRule, access? }) observes the selected registered model through ordinary HTTP acquisition, keyed by its stable name. A model with no versions is still a valid observed record. Concrete version selection and artifact identities belong to the capture adapter. Bind its endpoint and mlflow.credential(name) through deployment bindings. Acquisition is a live provider observation, not an atomic snapshot or complete alias history. MLflow has no registry incarnation token; replacing a registry requires a new connection. setAlias, registerVersion, createTrackingRun, logBatch and finishTrackingRun are explicit native commands. A successful response confirms the provider acknowledgement; it does not accept a Bijection prediction. Unanswered writes retain unknown delivery and are never automatically resent. Current registry reads cannot establish attribution of an unanswered mutation. setAlias({alias, version}) requires the explicit concrete version. Alias updates are unconditional: MLflow supplies no compare-and-swap here. Binary capture belongs to @bijection/pipelines/mlflow, the dataset owner and the customer’s bijection-pipelines[mlflow] adapter. Inference consumes exact retained artifact dataset references; actors do not receive registry credentials.

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Provider references

Provider references and prerequisites are maintained in the connector guidance above. No separate provider-documentation review date is recorded.

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Source and evidence

Canonical connector source, native analysis and check receipts. Connector artifact: 905888ea276a2a28e36981a79e8142b2547ea451c3e63162cb6915ad4a7d1305. The resource declaration examples above are compiled and compared with exact catalog declarations. Recorded checks apply only to their source, declaration and runtime identities. Configure a connection and inspect its status to establish deployment-specific readiness.