Nanonets Upload Training Images and Train

arazzo: 1.0.1
info:
  title: Nanonets Upload Training Images and Train
  summary: Upload annotated local training images to an OCR model, then kick off training.
  description: >-
    Prepares a Nanonets OCR model for a new training run. The workflow uploads
    one or more locally-stored, annotated training images to the target model and
    then triggers training on the freshly uploaded data. 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: ocrApi
  url: ../openapi/nanonets-ocr-api-openapi.yml
  type: openapi
workflows:
- workflowId: upload-training-images-and-train
  summary: Upload annotated training images by file and start a training run.
  description: >-
    Uploads annotated local training images to a Nanonets OCR model and then
    queues a training job on the model.
  inputs:
    type: object
    required:
    - authorization
    - modelId
    - file
    - data
    properties:
      authorization:
        type: string
        description: HTTP Basic credential header value (Basic <base64 of apiKey:>).
      modelId:
        type: string
        description: Unique identifier for the Nanonets OCR model to train.
      file:
        type: string
        description: Binary contents of the training image to upload.
      data:
        type: string
        description: JSON string describing the annotation for each uploaded file.
  steps:
  - stepId: uploadTrainingImages
    description: Upload the annotated local training image(s) to the model.
    operationId: ocrModelUploadFileByModelIdPost
    parameters:
    - name: Authorization
      in: header
      value: $inputs.authorization
    - name: model_id
      in: path
      value: $inputs.modelId
    requestBody:
      contentType: multipart/form-data
      payload:
        file: $inputs.file
        data: $inputs.data
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      uploadResponse: $response.body
  - stepId: trainModel
    description: Trigger training (or retraining) on the model after the upload completes.
    operationId: ocrModelTrainByModelIdPost
    parameters:
    - name: Authorization
      in: header
      value: $inputs.authorization
    - name: model_id
      in: path
      value: $inputs.modelId
    successCriteria:
    - condition: $statusCode == 200
    outputs:
      trainResponse: $response.body
  outputs:
    uploadResponse: $steps.uploadTrainingImages.outputs.uploadResponse
    trainResponse: $steps.trainModel.outputs.trainResponse