如何使用base64数据向调查添加多个图像答案?



使用这个SO问题的答案,API SurveyQuestionImage的正确格式是什么?数据字段?,我已经成功地使用API为包含单个图像的问题创建了问题。

我现在试图创建一个有多个图像答案的问题,特别是一个并排的图像问题。我正在使用NuGet包Google.Apis.ConsumerSurveys。. net平台的v2版本1.15.0.564。结果是这样的错误返回:

Google.Apis.Requests.RequestError Server encountered an error processing the request. 
Request Id: 57ae035f00ff0af4b07e61a17d0001737e3430322d747269616c320001707573682d30382d31312d7230360001012f [500] 
Errors [ Message[Server encountered an error processing the request. 
Request Id: 57ae035f00ff0af4b07e61a17d0001737e3430322d747269616c320001707573682d30382d31312d7230360001012f] 
Location[ - ] Reason[INTERNAL_ERROR] Domain[global] ]

这是survey资源的POST主体:

{
  "audience": {
    "ages": null,
    "country": "US",
    "countrySubdivision": null,
    "gender": null,
    "languages": [
      "en-US"
    ],
    "mobileAppPanelId": null,
    "populationSource": "general",
    "ETag": null
  },
  "cost": null,
  "customerData": null,
  "description": "",
  "owners": null,
  "questions": [
    {
      "answerOrder": "randomize",
      "answers": null,
      "hasOther": null,
      "highValueLabel": null,
      "images": [
        {
          "altText": "White",
          "data": "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          "url": null,
          "ETag": null
        }
      ],
      "lastAnswerPositionPinned": null,
      "lowValueLabel": null,
      "mustPickSuggestion": null,
      "numStars": null,
      "openTextPlaceholder": null,
      "openTextSuggestions": null,
      "question": "Which star?",
      "sentimentText": null,
      "singleLineResponse": null,
      "thresholdAnswers": null,
      "type": "sideBySideImages",
      "unitOfMeasurementLabel": null,
      "videoId": null,
      "ETag": null
    }
  ],
  "state": null,
  "surveyUrlId": null,
  "title": "Stars",
  "wantedResponseCount": 100,
  "ETag": null
}

问题:有人知道如何使用GCS API创建具有多个图像答案的问题吗?更具体地说,当发送WebSafe base64编码的PNG图像数据?

"owners"字段必须正确填写;否则,您的请求应按预期工作。

(API中有一个与多选择图像相关的错误,现在已修复)

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