Why this does not return results

Question

Following a script from git hub https://github.com/Azure/azure-search-vector-samples/tree/main/demo-javascript/JavaScriptVectorDemo can anyone help with why this does not return any results when implemeted. also the following happens when trying to run a debugging session. Everything runs fine without error but no results are returned from the search after teh indexer has run

skillsets

{
  "@odata.context": "https://jwlsearchservicepaid.search.windows.net/$metadata#skillsets/$entity",
  "@odata.etag": "\"0x8DC11939D644BD1\"",
  "name": "jwlsearchindexoneblob-skillset",
  "description": null,
  "skills": [
    {
      "@odata.type": "#Microsoft.Skills.Text.SplitSkill",
      "name": "#1",
      "description": null,
      "context": "/document",
      "defaultLanguageCode": "en",
      "textSplitMode": "pages",
      "maximumPageLength": 500,
      "pageOverlapLength": 100,
      "maximumPagesToTake": 0,
      "inputs": [
        {
          "name": "text",
          "source": "/document/content"
        }
      ],
      "outputs": [
        {
          "name": "textItems",
          "targetName": "pages"
        }
      ]
    },
    {
      "@odata.type": "#Microsoft.Skills.Text.AzureOpenAIEmbeddingSkill",
      "name": "#2",
      "description": null,
      "context": "/document/pages/*",
      "resourceUri": "https://jwlausteast.openai.azure.com",
      "apiKey": "###",
      "deploymentId": "ada-002",
      "inputs": [
        {
          "name": "text",
          "source": "/document/pages/*"
        }
      ],
      "outputs": [
        {
          "name": "embedding",
          "targetName": "vector"
        }
      ],
      "authIdentity": null
    }
  ],
  "cognitiveServices": {
    "@odata.type": "#Microsoft.Azure.Search.DefaultCognitiveServices",
    "description": null
  },
  "knowledgeStore": null,
  "indexProjections": null,
  "encryptionKey": null
}

indexer

{
  "@odata.context": "https://jwlsearchservicepaid.search.windows.net/$metadata#indexers/$entity",
  "@odata.etag": "\"0x8DC118DF647D164\"",
  "name": "jwlsearchindexoneblob-indexer",
  "description": "Indexer to chunk documents, generate embeddings, and add to the index",
  "dataSourceName": "jwlsearchindexoneblob-blob",
  "skillsetName": "jwlsearchindexoneblob-skillset",
  "targetIndexName": "jwlsearchindexoneblob",
  "disabled": null,
  "schedule": {
    "interval": "P1D",
    "startTime": "2024-01-10T03:19:38.945Z"
  },
  "parameters": {
    "batchSize": 1,
    "maxFailedItems": 0,
    "maxFailedItemsPerBatch": 0,
    "base64EncodeKeys": null,
    "configuration": {}
  },
  "fieldMappings": [],
  "outputFieldMappings": [],
  "cache": null,
  "encryptionKey": null
}

indexes

{
  "@odata.context": "https://jwlsearchservicepaid.search.windows.net/$metadata#indexes/$entity",
  "@odata.etag": "\"0x8DC118AF9BFC0BB\"",
  "name": "jwlsearchindexoneblob",
  "defaultScoringProfile": null,
  "fields": [
    {
      "name": "parent_id",
      "type": "Edm.String",
      "searchable": true,
      "filterable": true,
      "retrievable": true,
      "sortable": true,
      "facetable": true,
      "key": false,
      "indexAnalyzer": null,
      "searchAnalyzer": null,
      "analyzer": null,
      "normalizer": null,
      "dimensions": null,
      "vectorSearchProfile": null,
      "synonymMaps": []
    },
    {
      "name": "chunk_id",
      "type": "Edm.String",
      "searchable": true,
      "filterable": true,
      "retrievable": true,
      "sortable": true,
      "facetable": true,
      "key": true,
      "indexAnalyzer": null,
      "searchAnalyzer": null,
      "analyzer": "keyword",
      "normalizer": null,
      "dimensions": null,
      "vectorSearchProfile": null,
      "synonymMaps": []
    },
    {
      "name": "title",
      "type": "Edm.String",
      "searchable": true,
      "filterable": false,
      "retrievable": true,
      "sortable": false,
      "facetable": false,
      "key": false,
      "indexAnalyzer": null,
      "searchAnalyzer": null,
      "analyzer": null,
      "normalizer": null,
      "dimensions": null,
      "vectorSearchProfile": null,
      "synonymMaps": []
    },
    {
      "name": "chunk",
      "type": "Edm.String",
      "searchable": true,
      "filterable": false,
      "retrievable": true,
      "sortable": false,
      "facetable": false,
      "key": false,
      "indexAnalyzer": null,
      "searchAnalyzer": null,
      "analyzer": null,
      "normalizer": null,
      "dimensions": null,
      "vectorSearchProfile": null,
      "synonymMaps": []
    },
    {
      "name": "vector",
      "type": "Collection(Edm.Single)",
      "searchable": true,
      "filterable": false,
      "retrievable": true,
      "sortable": false,
      "facetable": false,
      "key": false,
      "indexAnalyzer": null,
      "searchAnalyzer": null,
      "analyzer": null,
      "normalizer": null,
      "dimensions": 1536,
      "vectorSearchProfile": "my-vector-profile",
      "synonymMaps": []
    },
    {
      "name": "category",
      "type": "Edm.String",
      "searchable": true,
      "filterable": true,
      "retrievable": true,
      "sortable": true,
      "facetable": true,
      "key": false,
      "indexAnalyzer": null,
      "searchAnalyzer": null,
      "analyzer": null,
      "normalizer": null,
      "dimensions": null,
      "vectorSearchProfile": null,
      "synonymMaps": []
    }
  ],
  "scoringProfiles": [],
  "corsOptions": null,
  "suggesters": [],
  "analyzers": [],
  "normalizers": [],
  "tokenizers": [],
  "tokenFilters": [],
  "charFilters": [],
  "encryptionKey": null,
  "similarity": {
    "@odata.type": "#Microsoft.Azure.Search.BM25Similarity",
    "k1": null,
    "b": null
  },
  "semantic": {
    "defaultConfiguration": null,
    "configurations": [
      {
        "name": "my-semantic-config",
        "prioritizedFields": {
          "titleField": {
            "fieldName": "title"
          },
          "prioritizedContentFields": [
            {
              "fieldName": "chunk"
            }
          ],
          "prioritizedKeywordsFields": []
        }
      }
    ]
  },
  "vectorSearch": {
    "algorithms": [
      {
        "name": "myHnsw",
        "kind": "hnsw",
        "hnswParameters": {
          "metric": "cosine",
          "m": 4,
          "efConstruction": 400,
          "efSearch": 500
        },
        "exhaustiveKnnParameters": null
      },
      {
        "name": "myExhaustiveKnn",
        "kind": "exhaustiveKnn",
        "hnswParameters": null,
        "exhaustiveKnnParameters": {
          "metric": "cosine"
        }
      }
    ],
    "profiles": [
      {
        "name": "my-vector-profile",
        "algorithm": "myHnsw",
        "vectorizer": "myOpenAIVectorizer"
      },
      {
        "name": "myExhaustiveKnnProfile",
        "algorithm": "myExhaustiveKnn",
        "vectorizer": null
      }
    ],
    "vectorizers": [
      {
        "name": "myOpenAIVectorizer",
        "kind": "azureOpenAI",
        "azureOpenAIParameters": {
          "resourceUri": "https://jwlausteast.openai.azure.com",
          "deploymentId": "ada-002", 
          "apiKey": "####",
          "authIdentity": null
        },
        "customWebApiParameters": null
      }
    ]
  }
}

Answer 1

@John Newsome Thanks for clarification. Please accept my apologies for confusion here. If I have understood right you are using- this repo- https://github.com/Azure/azure-search-vector-samples/tree/main/demo-dotnet/DotNetIntegratedVectorizationDemo and facing below issue- 

failed to create debug session "new debugsession-Invalidskillset: "details": [ { "code": "InvalidSkillset", "message": "One or more skills are invalid. Details: Unexpected properties found on Skill. Parameters: skillset" }. 

I discussed with PG for clarification, and they informed us that a specific piece of documentation needs to be removed. We are currently in the process of coordinating its removal. Once this is complete, we will promptly release the updated information, making the property available for public use. In the meantime, we recommend refraining from utilizing the debug session. Thank you for your understanding and cooperation.