Error in Azure AI Search with OCR Skill

Question

Hi, I was creating an AI Search index to on my png files. I followed the instruction from the below sources, but still getting errors. Please help me out on where I missed in the code.

• https://learn.microsoft.com/en-us/azure/search/cognitive-search-skill-image-analysis
• https://learn.microsoft.com/en-us/azure/search/cognitive-search-skill-ocr

I got the following errors when running the indexer.

The data field 'myLayoutText' in the document with key 'xxxxx' has an invalid value of type 'Collection(Edm.ComplexType)' ('JSON arrays with element type 'Object' map to Collection(Edm.ComplexType)'). The expected type was 'Edm.ComplexType'.

Here is my code:

headers = {
    'Content-Type':'application/json',
    'api-key':search_key
}

data_source_name = 'document-bot-files-datasource'


index_name = 'ocr-index'
index_data = {
        "name" : index_name,
        "fields": [
            { "name": "ID", "type": "Edm.String", "key": True, "searchable": True,"filterable": True, "sortable": True,"facetable":True,"analyzer":"keyword" },
            { "name": "parent_id", "type": "Edm.String", "searchable": True, "filterable": True, "sortable": False,"facetable":False},
        
            { "name": "myText", "type": "Edm.String", "searchable": True, "filterable": False, "sortable": False,"facetable":False},
            { "name": "myLayoutText", "type": "Edm.ComplexType","fields":[
                { "name": "language", "type": "Edm.String", "searchable": False, "filterable": False, "sortable": False,"facetable":False},
                { "name": "text", "type": "Edm.String", "searchable": True, "filterable": False, "sortable": False,"facetable":False},
                { "name": "lines", "type": "Collection(Edm.ComplexType)","fields":[
                    { "name": "boundingBox", "type": "Collection(Edm.ComplexType)", "fields":[
                        { "name": "x", "type": "Edm.Int32", "searchable": False, "filterable": False, "sortable": False,"facetable":False},
                        { "name": "y", "type": "Edm.Int32", "searchable": False, "filterable": False, "sortable": False,"facetable":False},
                    ]},
                    { "name": "text", "type": "Edm.String", "searchable": True, "filterable": False, "sortable": False,"facetable":False},
                ]},
                { "name": "words", "type": "Collection(Edm.ComplexType)","fields":[
                    { "name": "boundingBox", "type": "Collection(Edm.ComplexType)", "fields":[
                        { "name": "x", "type": "Edm.Int32", "searchable": False, "filterable": False, "sortable": False,"facetable":False},
                        { "name": "y", "type": "Edm.Int32", "searchable": False, "filterable": False, "sortable": False,"facetable":False},
                    ]},                    
                    { "name": "text", "type": "Edm.String", "searchable": True, "filterable": False, "sortable": False,"facetable":False},
                ]}
            ]},
        ],
        "vectorSearch": {
        "profiles": [
        {
            "name": "myHnswProfile",
            "algorithm": "myHnsw"
        }
        ],
        "algorithms": [
        {
            "name": "myHnsw",
            "kind": "hnsw",
            "hnswParameters": {
            "m": 4,
            "metric": "cosine"
            }
        }
        ]
    }
    }
index_delete_response = requests.delete(f"{search_endpoint}/indexes/{index_name}?api-version=2020-06-30",headers=headers)
index_response = requests.put(f"{search_endpoint}/indexes('{index_name}')?api-version=2023-11-01",json=index_data,headers=headers)
print("index creation:", index_response.text)

skill_name = 'ocr-skillset'
skill_data = {
  "skills": [
    {
      "description": "Extracts text (plain and structured) from image.",
      "@odata.type": "#Microsoft.Skills.Vision.OcrSkill",
      "context": "/document/normalized_images/*",
      "defaultLanguageCode": '',
      "detectOrientation": True,
      "inputs": [
        {
          "name": "image",
          "source": "/document/normalized_images/*"
        }
      ],
      "outputs": [
        {
          "name": "text",
          "targetName": "myText"
        },
        {
          "name": "layoutText",
          "targetName": "myLayoutText"
        }
      ],
    }
  ]
}
skill_update_response = requests.put(f"{search_endpoint}/skillsets('{skill_name}')?api-version=2023-10-01-Preview",json=skill_data,headers=headers)
print("skill creation update code:", skill_update_response.status_code)
# print("skill creation update code:", skill_update_response.text)

indexer_name = 'ocr-indexer'
indexer_data = {
    "name" : indexer_name,
    "dataSourceName" : data_source_name,
    "targetIndexName" : index_name,
    "skillsetName":skill_name,
    "parameters": {
        "configuration": {
            "indexedFileNameExtensions" : ".pdf,.docx,.txt,.png,.jpeg",
            "dataToExtract": "contentAndMetadata",
            "parsingMode": "default",
            "imageAction": "generateNormalizedImages"
        }
    },
    "schedule" : { },
    "fieldMappings" : [
    ],
    "outputFieldMappings": [
        {
            "sourceFieldName": "/document/normalized_images/*/myText",
            "targetFieldName": "myText"
        },
        {
            "sourceFieldName": "/document/normalized_images/*/myLayoutText",
            "targetFieldName": "myLayoutText"
        },
    ]
    }
indexer_update_response = requests.put(f"{search_endpoint}/indexers/{indexer_name}?api-version=2020-06-30",json=indexer_data,headers=headers)
print("indexer update  code: ",indexer_update_response.status_code)
indexer_reset_response = requests.post(f"{search_endpoint}/indexers/{indexer_name}/reset?api-version=2020-06-30",headers=headers)
print("indexer reset code: ",indexer_reset_response.status_code)
# time.sleep(3)
indexer_run_response = requests.post(f"{search_endpoint}/indexers/{indexer_name}/run?api-version=2020-06-30",headers=headers)
print("indexer rerun code: ",indexer_run_response.status_code)