arazzo: 1.0.1
info:
  title: Amazon Rekognition Video Label Detection Job
  summary: Start an asynchronous video label detection job, poll until it succeeds, then read the results.
  description: >-
    The standard asynchronous stored-video analysis pattern for Amazon
    Rekognition. The workflow starts a label detection job for a video in S3,
    polls GetLabelDetection on the returned JobId until the JobStatus is no
    longer IN_PROGRESS, branches on SUCCEEDED versus FAILED, and on success
    reads the detected labels. Each step spells out its AWS JSON 1.1 request
    inline, including the protocol-required X-Amz-Target header.
  version: 1.0.0
sourceDescriptions:
- name: rekognitionApi
  url: ../openapi/amazon-rekognition-openapi.yml
  type: openapi
workflows:
- workflowId: video-label-detection-job
  summary: Start a video label detection job, poll until done, and read results.
  description: >-
    Kicks off asynchronous label detection for a stored video, polls the job
    until it reaches a terminal state, and retrieves the labels on success.
  inputs:
    type: object
    required:
    - videoBucket
    - videoName
    properties:
      videoBucket:
        type: string
        description: S3 bucket holding the video to analyze.
      videoName:
        type: string
        description: S3 object key of the video file.
      minConfidence:
        type: number
        description: Minimum confidence for labels detected in the video.
        default: 75.0
  steps:
  - stepId: startJob
    description: Start the asynchronous label detection job for the stored video.
    operationId: startLabelDetection
    parameters:
    - name: X-Amz-Target
      in: header
      value: RekognitionService.StartLabelDetection
    requestBody:
      contentType: application/x-amz-json-1.1
      payload:
        Video:
          S3Object:
            Bucket: $inputs.videoBucket
            Name: $inputs.videoName
        MinConfidence: $inputs.minConfidence
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      jobId: $response.body#/JobId
  - stepId: pollJob
    description: >-
      Poll the label detection job until it leaves the IN_PROGRESS state, then
      branch on the terminal status.
    operationId: getLabelDetection
    parameters:
    - name: X-Amz-Target
      in: header
      value: RekognitionService.GetLabelDetection
    requestBody:
      contentType: application/x-amz-json-1.1
      payload:
        JobId: $steps.startJob.outputs.jobId
        MaxResults: 100
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      jobStatus: $response.body#/JobStatus
      labels: $response.body#/Labels
      labelModelVersion: $response.body#/LabelModelVersion
    onSuccess:
    - name: stillRunning
      type: goto
      stepId: pollJob
      criteria:
      - context: $response.body
        condition: $.JobStatus == 'IN_PROGRESS'
        type: jsonpath
    - name: succeeded
      type: goto
      stepId: readResults
      criteria:
      - context: $response.body
        condition: $.JobStatus == 'SUCCEEDED'
        type: jsonpath
    onFailure:
    - name: jobFailed
      type: end
      criteria:
      - context: $response.body
        condition: $.JobStatus == 'FAILED'
        type: jsonpath
  - stepId: readResults
    description: Read the full label detection results for the succeeded job.
    operationId: getLabelDetection
    parameters:
    - name: X-Amz-Target
      in: header
      value: RekognitionService.GetLabelDetection
    requestBody:
      contentType: application/x-amz-json-1.1
      payload:
        JobId: $steps.startJob.outputs.jobId
        MaxResults: 100
        SortBy: TIMESTAMP
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      jobStatus: $response.body#/JobStatus
      labels: $response.body#/Labels
      videoMetadata: $response.body#/VideoMetadata
  outputs:
    jobId: $steps.startJob.outputs.jobId
    jobStatus: $steps.readResults.outputs.jobStatus
    labels: $steps.readResults.outputs.labels