Which Azure resources need to be created to retrieve the key information required for the skill set, and where can that information be confirmed?

RAG構築を目的としたAIエージェント向けナレッジとしてAzure AI Searchを準備しています。

Azure AI Searchから同テナントのSharePointを参照してインデックス作成する際、スキルセット（PDF抽出＋OCR＋チャンク＋埋め込み＋projection）を作成してインデクサーに紐づけます。

以下のようにスキルセットJSONを用意していますが、４つのキー情報等はそれぞれどのAzureリソースを作成し、どのAzure Portal画面のメニューで確認すればよいでしょうか？

[知りたい情報]

(a) <<AZURE_AI_SERVICES_KEY>>

(b) <<AZURE_OPENAI_RESOURCE_URI>>

(c) <<AZURE_OPENAI_EMBEDDING_DEPLOYMENT>>

(d) <<AZURE_OPENAI_API_KEY>>

[スキルセットJSON]

{
  "name": "sp-rag-skillset",
  "description": "SharePoint PDFs: extract + OCR + chunk + embeddings (RAG).",
  "cognitiveServices": {
    "@odata.type": "#Microsoft.Azure.Search.CognitiveServicesByKey",
    "key": "<<AZURE_AI_SERVICES_KEY>>"
  },
  "skills": [
    {
      "@odata.type": "#Microsoft.Skills.Util.DocumentExtractionSkill",
      "name": "#extract",
      "context": "/document",
      "inputs": [
        { "name": "document", "source": "/document" }
      ],
      "outputs": [
        { "name": "content", "targetName": "extractedText" },
        { "name": "normalized_images", "targetName": "images" }
      ]
    },
    {
      "@odata.type": "#Microsoft.Skills.Vision.OcrSkill",
      "name": "#ocr",
      "context": "/document/images/*",
      "inputs": [
        { "name": "image", "source": "/document/images/*" }
      ],
      "outputs": [
        { "name": "text", "targetName": "ocrText" }
      ],
      "defaultLanguageCode": "ja",
      "detectOrientation": true
    },
    {
      "@odata.type": "#Microsoft.Skills.Text.MergeSkill",
      "name": "#merge",
      "context": "/document",
      "inputs": [
        { "name": "text", "source": "/document/extractedText" },
        { "name": "itemsToInsert", "source": "/document/images/*/ocrText" }
      ],
      "outputs": [
        { "name": "mergedText", "targetName": "fullText" }
      ]
    },
    {
      "@odata.type": "#Microsoft.Skills.Text.SplitSkill",
      "name": "#split",
      "context": "/document",
      "inputs": [
        { "name": "text", "source": "/document/fullText" }
      ],
      "outputs": [
        { "name": "textItems", "targetName": "chunks" }
      ],
      "textSplitMode": "pages",
      "maximumPageLength": 2000,
      "pageOverlapLength": 200
    },
    {
      "@odata.type": "#Microsoft.Skills.Text.AzureOpenAIEmbeddingSkill",
      "name": "#embed",
      "context": "/document/chunks/*",
      "inputs": [
        { "name": "text", "source": "/document/chunks/*" }
      ],
      "outputs": [
        { "name": "embedding", "targetName": "chunkVector" }
      ],
      "resourceUri": "<<AZURE_OPENAI_RESOURCE_URI>>",
      "deploymentId": "<<AZURE_OPENAI_EMBEDDING_DEPLOYMENT>>",
      "apiKey": "<<AZURE_OPENAI_API_KEY>>",
      "dimensions": 1536
    }
  ],
  "indexProjections": {
    "selectors": [
      {
        "targetIndexName": "sp-rag-chunks-index",
        "parentKeyFieldName": "parent_url",
        "sourceContext": "/document/chunks/*",
        "mappings": [
          { "name": "chunk_id", "source": "=concat(/document/metadata_storage_path, '|', string(@index))" },
          { "name": "parent_url", "source": "/document/metadata_storage_path" },

          { "name": "title", "source": "/document/metadata_title" },
          { "name": "fileName", "source": "/document/metadata_storage_name" },

          { "name": "content", "source": "/document/chunks/*" },
          { "name": "contentVector", "source": "/document/chunks/*/chunkVector" },

          { "name": "chunkIndex", "source": "=@index" },

          { "name": "acl", "source": "/document/acl" }
        ]
      }
    ],
    "parameters": { "projectionMode": "skipIndexingParentDocuments" }
  }
}