This is a follow up question to: Error in Azure Cognitive Search Service when storing document page associated to each chunk extracted from PDF in a custom WebApiSkill

How do I store the vectors generated by AzureOpenAIEmbeddingSkill in indexer given my current setup:

• Custom WebApiSkill:

combined_list = [{'textItems': text, 'numberItems': number} for text, number in zip(chunks, page_numbers)]

# response object for specific pdf
response_record = {
    "recordId": recordId,
    "data": {
        "subdata": combined_list
    }
}
response_body['values'].append(response_record)

• Skillset definition:

{
  ...
  "description": "Skillset to chunk documents and generating embeddings",
  "skills": [
    {
      "@odata.type": "#Microsoft.Skills.Custom.WebApiSkill",
      "name": "splitclean",
      "description": "Custom split skill to chunk documents with specific chunk size and overlap",
      "context": "/document",
      "httpMethod": "POST",
      "timeout": "PT30S",
      "batchSize": 1,
      "degreeOfParallelism": null,
      "authResourceId": null,
      "inputs": [
        {
          "name": "text",
          "source": "/document/content"
        }
      ],
      "outputs": [
        {
          "name": "subdata",
          "targetName": "subdata"
        }
      ],
      "authIdentity": null
    },
    {
      "name": "#2",
      "description": "Skill to generate embeddings via Azure OpenAI",
      "context": "/document/subdata/*",
      "apiKey": "<redacted>",
      "deploymentId": "embedding-ada-002",
      "dimensions": null,
      "modelName": "experimental",
      "inputs": [
        {
          "name": "text",
          "source": "/document/subdata/*/textItems"
        }
      ],
      "outputs": [
        {
          "name": "embedding",
          "targetName": "vector"
        }
      ],
      "authIdentity": null
    }
  ],
  "cognitiveServices": null,
  "knowledgeStore": null,
  "indexProjections": {
    "selectors": [
      {
        "parentKeyFieldName": "parent_id",
        "sourceContext": "/document/subdata/*",
        "mappings": [
          {
            "name": "chunk",
            "source": "/document/subdata/*/textItems",
            "sourceContext": null,
            "inputs": []
          },
          {
            "name": "vector",
            "source": "/document/subdata/*/vector",
            "sourceContext": null,
            "inputs": []
          },
          {
            "name": "title",
            "source": "/document/metadata_storage_name",
            "sourceContext": null,
            "inputs": []
          },
          {
            "name": "page_number",
            "source": "/document/subdata/*/numberItems",
            "sourceContext": null,
            "inputs": []
          }
        ]
      }
    ],
    "parameters": {
      "projectionMode": "skipIndexingParentDocuments"
    }
  },
  "encryptionKey": null
}

I get the following error in AzureOpenAIEmbeddingSkill:

Web Api response status: 'Unauthorized', Web Api response details: '{"error":{"code":"401","message":"Access denied due to invalid subscription key or wrong API endpoint. Make sure to provide a valid key for an active subscription and use a correct regional API endpoint for your resource."}}'