Unable to Enable Vector Search in Azure OpenAI Chat Playground for Azure AI Search Data Source

Question

When I am trying to create a chat playground I can't enable vector search for my "Azure AI Search" data source. The index has embedding included and I have embedding in my deployment.

The steps I have taken to get here.

1. Go to Azure OpenAI Service
2. Added two deployments
   1. gpt-4o-mini
   2. text-embedding-3-large
3. Tried to use chat playground
   1. Selected my deployment
      1. gpt-4o-mini (version: 2024-07-18)
   2. Tried To Add Data Source With Vector Search Enabled
      1. clicked "Add a data Source"
      2. Selected "Azure AI Search" for my data source
      3. Selected my subscription
      4. Selected my Azure AI Search Service
      5. Selected my Azure AI Search Index
      6. At this point I would like to check the "Add vector search ..." checkbox but it is disabled

The checkbox "Add vector search..." is disabled.

Here is the index's json if that helps:

{
  "name": "knowledge-index",
  "fields": [
    {
      "name": "knowledge_id",
      "type": "Edm.String",
      "key": true,
      "retrievable": true,
      "stored": true,
      "searchable": false,
      "filterable": true,
      "sortable": false,
      "facetable": false,
      "synonymMaps": []
    },
    {
      "name": "contact_dt",
      "type": "Edm.String",
      "key": false,
      "retrievable": true,
      "stored": true,
      "searchable": false,
      "filterable": true,
      "sortable": false,
      "facetable": false,
      "synonymMaps": []
    },
    {
      "name": "reference_num",
      "type": "Edm.String",
      "key": false,
      "retrievable": true,
      "stored": true,
      "searchable": true,
      "filterable": true,
      "sortable": true,
      "facetable": true,
      "synonymMaps": []
    },
    {
      "name": "vector",
      "type": "Collection(Edm.Single)",
      "key": false,
      "retrievable": true,
      "stored": true,
      "searchable": true,
      "filterable": false,
      "sortable": false,
      "facetable": false,
      "synonymMaps": [],
      "dimensions": 3072,
      "vectorSearchProfile": "myHnswProfile"
    }
  ],
  "scoringProfiles": [],
  "corsOptions": {
    "allowedOrigins": [
      "*"
    ],
    "maxAgeInSeconds": 300
  },
  "suggesters": [],
  "analyzers": [],
  "tokenizers": [],
  "tokenFilters": [],
  "charFilters": [],
  "normalizers": [],
  "similarity": {
    "@odata.type": "#Microsoft.Azure.Search.BM25Similarity"
  },
  "semantic": {
    "configurations": [
      {
        "name": "mySemanticConfig",
        "prioritizedFields": {
          "titleField": {
            "fieldName": "serial_num"
          },
          "prioritizedContentFields": [
            {
              "fieldName": "text_serial_model"
            }
          ],
          "prioritizedKeywordsFields": []
        }
      }
    ]
  },
  "vectorSearch": {
    "algorithms": [
      {
        "name": "myHnsw",
        "kind": "hnsw",
        "hnswParameters": {
          "m": 4,
          "efConstruction": 400,
          "efSearch": 500,
          "metric": "cosine"
        }
      },
      {
        "name": "myExhaustiveKnn",
        "kind": "exhaustiveKnn",
        "exhaustiveKnnParameters": {
          "metric": "cosine"
        }
      }
    ],
    "profiles": [
      {
        "name": "myHnswProfile",
        "algorithm": "myHnsw",
        "vectorizer": "vectorizer-1732168287035"
      },
      {
        "name": "myExhaustiveKnnProfile",
        "algorithm": "myExhaustiveKnn",
        "vectorizer": "vectorizer-1732168287035"
      },
      {
        "name": "vector-profile-1732168273201",
        "algorithm": "myHnsw",
        "vectorizer": "vectorizer-1732168287035"
      }
    ],
    "vectorizers": [
      {
        "name": "vectorizer-1732168287035",
        "kind": "azureOpenAI",
        "azureOpenAIParameters": {
          "resourceUri": "https://oai-east.openai.azure.com",
          "deploymentId": "text-embedding-3-large",
          "apiKey": "<redacted>",
          "modelName": "text-embedding-3-large"
        }
      }
    ],
    "compressions": []
  },
  "@odata.etag": "\"0x8DD09F1043B4F27\""
}

I would like to use both vector and semantic. If I figure out how to enable vector search will the request converted to vectors and then sent to the model?

My desired result is that I will be able to enable vector search against my index in the chat playground.