arazzo: 1.0.1
info:
  title: TensorFlow Serving Preflight and Regress
  summary: Confirm a model is loaded and its signature is known before running regression inference.
  description: >-
    Regression in TensorFlow Serving follows PredictionService.Regress semantics
    and, like classify, takes tf.Example style inputs through the examples array
    rather than the instances array used by predict. It returns a single numeric
    value per input example instead of label and score pairs. This workflow
    checks that the model reports an AVAILABLE version, reads its metadata to
    confirm the regression signature, and then submits the examples for scoring.
    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: regress-preflight
  summary: Check model status, read the signature, then run regression inference.
  description: >-
    Verifies the named model reports an AVAILABLE version, resolves its signature
    metadata, and submits tf.Example inputs for regression, returning one numeric
    result per example.
  inputs:
    type: object
    required:
    - modelName
    - examples
    properties:
      modelName:
        type: string
        description: The name the model was registered under in the ModelServer.
      signatureName:
        type: string
        description: >-
          Optional regression signature to target. When omitted the ModelServer
          uses the model's default serving signature.
      context:
        type: object
        description: Optional context features shared across every supplied example.
      examples:
        type: array
        description: The tf.Example style input records to score, one numeric result returned per example.
        items:
          type: object
  steps:
  - stepId: checkModelStatus
    description: >-
      Confirm the ModelServer has the model loaded and reports a version in the
      AVAILABLE state before any inference is attempted.
    operationId: getModelStatus
    parameters:
    - name: model_name
      in: path
      value: $inputs.modelName
    successCriteria:
    - condition: $statusCode == 200
    - context: $response.body
      condition: $.model_version_status[0].state == 'AVAILABLE'
      type: jsonpath
    outputs:
      servingState: $response.body#/model_version_status/0/state
      servingVersion: $response.body#/model_version_status/0/version
      errorMessage: $response.body#/model_version_status/0/status/error_message
  - stepId: readModelMetadata
    description: >-
      Read the metadata of the latest available version to confirm the model
      exposes a regression signature and to see the features it expects.
    operationId: getModelMetadata
    parameters:
    - name: model_name
      in: path
      value: $inputs.modelName
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      modelSpecName: $response.body#/model_spec/name
      modelSpecVersion: $response.body#/model_spec/version
      signatureMetadata: $response.body#/metadata
  - stepId: runRegression
    description: >-
      Submit the examples for regression against the model's latest available
      version, returning the predicted numeric value for each example.
    operationId: regressModel
    parameters:
    - name: model_name
      in: path
      value: $inputs.modelName
    requestBody:
      contentType: application/json
      payload:
        signature_name: $inputs.signatureName
        context: $inputs.context
        examples: $inputs.examples
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      result: $response.body#/result
      firstValue: $response.body#/result/0
  outputs:
    servingVersion: $steps.checkModelStatus.outputs.servingVersion
    modelSpecVersion: $steps.readModelMetadata.outputs.modelSpecVersion
    result: $steps.runRegression.outputs.result