TensorFlow Serving Pinned Reproducible Example Scoring

arazzo: 1.0.1
info:
  title: TensorFlow Serving Pinned Reproducible Example Scoring
  summary: Pin a model version and score the same tf.Example inputs through both its classify and regress signatures.
  description: >-
    When a scoring decision has to be defended later, the version that produced
    it cannot be left to whatever the ModelServer happened to consider default at
    the time. This workflow pins an explicit version number for the whole run and
    keeps it fixed across every call, so the result can be reproduced exactly by
    replaying the flow with the same inputs. It suits models that expose both a
    classification and a regression signature over the same tf.Example records,
    where a decision needs both the predicted class and the associated numeric
    estimate captured together against one known version. Every step spells out
    its request inline so the flow can be read and executed without opening the
    underlying OpenAPI description.
  version: 1.0.0
sourceDescriptions:
- name: tensorflowServingApi
  url: ../openapi/tensorflow-serving-openapi.yml
  type: openapi
workflows:
- workflowId: pinned-example-scoring
  summary: Classify and regress the same examples against one explicitly pinned model version.
  description: >-
    Confirms the pinned version is AVAILABLE, records its signature metadata for
    the audit trail, then runs the same tf.Example records through the pinned
    version's classification and regression signatures.
  inputs:
    type: object
    required:
    - modelName
    - version
    - examples
    properties:
      modelName:
        type: string
        description: The name the model was registered under in the ModelServer.
      version:
        type: integer
        description: >-
          The exact model version to pin the whole run to. Supplied explicitly
          rather than resolved, so the run can be replayed against the same model.
      classifySignatureName:
        type: string
        description: Optional classification signature to target on the pinned version.
      regressSignatureName:
        type: string
        description: Optional regression signature to target on the pinned version.
      context:
        type: object
        description: Optional context features shared across every supplied example.
      examples:
        type: array
        description: >-
          The tf.Example style records to score. The same records are sent to
          both signatures so the class and the numeric estimate describe the
          same inputs.
        items:
          type: object
  steps:
  - stepId: checkPinnedVersion
    description: >-
      Confirm the pinned version is loaded and AVAILABLE. If the version has been
      unloaded or garbage collected the run must fail loudly rather than silently
      fall through to a different version.
    operationId: getModelVersionStatus
    parameters:
    - name: model_name
      in: path
      value: $inputs.modelName
    - name: version
      in: path
      value: $inputs.version
    successCriteria:
    - condition: $statusCode == 200
    - context: $response.body
      condition: $.model_version_status[0].state == 'AVAILABLE'
      type: jsonpath
    outputs:
      pinnedState: $response.body#/model_version_status/0/state
      pinnedVersion: $response.body#/model_version_status/0/version
      pinnedErrorMessage: $response.body#/model_version_status/0/status/error_message
  - stepId: readPinnedMetadata
    description: >-
      Capture the pinned version's signature metadata as part of the audit
      record, so the exact model shape behind the scores is retained alongside
      them.
    operationId: getModelVersionMetadata
    parameters:
    - name: model_name
      in: path
      value: $inputs.modelName
    - name: version
      in: path
      value: $inputs.version
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      modelSpecName: $response.body#/model_spec/name
      modelSpecVersion: $response.body#/model_spec/version
      signatureMetadata: $response.body#/metadata
  - stepId: classifyPinned
    description: >-
      Run the examples through the pinned version's classification signature,
      returning the label and score pairs for each record.
    operationId: classifyModelVersion
    parameters:
    - name: model_name
      in: path
      value: $inputs.modelName
    - name: version
      in: path
      value: $inputs.version
    requestBody:
      contentType: application/json
      payload:
        signature_name: $inputs.classifySignatureName
        context: $inputs.context
        examples: $inputs.examples
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      classifyResult: $response.body#/result
  - stepId: regressPinned
    description: >-
      Run the identical examples through the same pinned version's regression
      signature, returning the numeric estimate that accompanies each
      classification.
    operationId: regressModelVersion
    parameters:
    - name: model_name
      in: path
      value: $inputs.modelName
    - name: version
      in: path
      value: $inputs.version
    requestBody:
      contentType: application/json
      payload:
        signature_name: $inputs.regressSignatureName
        context: $inputs.context
        examples: $inputs.examples
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      regressResult: $response.body#/result
  outputs:
    pinnedVersion: $steps.checkPinnedVersion.outputs.pinnedVersion
    signatureMetadata: $steps.readPinnedMetadata.outputs.signatureMetadata
    classifyResult: $steps.classifyPinned.outputs.classifyResult
    regressResult: $steps.regressPinned.outputs.regressResult