Indexelt Azure SQL tudásbázis létrehozása (előzetes verzió)

• A legújabb Azure.Search.Documents előzetes csomag: dotnet add package Azure.Search.Documents --prerelease

• Kulcs nélküli hitelesítés esetén a Azure.Identity csomag: dotnet add package Azure.Identity

• A legújabb azure-search-documents előzetes csomag: pip install --pre azure-search-documents

• Kulcs nélküli hitelesítés esetén a azure-identity csomag: pip install azure-identity

• A Search Service REST API 2026-08-01 előzetes verziója .

• Kulcs nélküli hitelesítéshez minden HTTP-kérés fejlécében adjon meg egy Authorization.

// List knowledge sources by name and type
using Azure.Search.Documents.Indexes;

var indexClient = new SearchIndexClient(new Uri(searchEndpoint), credential);
var knowledgeSources = indexClient.GetKnowledgeSourcesAsync();

Console.WriteLine("Knowledge Sources:");

await foreach (var ks in knowledgeSources)
{
    Console.WriteLine($"  Name: {ks.Name}, Type: {ks.GetType().Name}");
}

Referencia:SearchIndexClient

# List knowledge sources by name and type
from azure.core.credentials import AzureKeyCredential
from azure.search.documents.indexes import SearchIndexClient

index_client = SearchIndexClient(endpoint = "search_url", credential = AzureKeyCredential("api_key"))

for ks in index_client.list_knowledge_sources():
    print(f"  - {ks.name} ({ks.kind})")

Referencia:SearchIndexClient

### List knowledge sources by name and type
GET {{search-url}}/knowledgesources?api-version={{api-version}}&$select=name,kind
Authorization: Bearer {{token}}

Referencia:Tudásbázisok – Lista

using Azure.Search.Documents.Indexes;
using System.Text.Json;

var indexClient = new SearchIndexClient(new Uri(searchEndpoint), credential);

// Specify the knowledge source name to retrieve
string ksNameToGet = "earth-knowledge-source";

// Get its definition
var knowledgeSourceResponse = await indexClient.GetKnowledgeSourceAsync(ksNameToGet);
var ks = knowledgeSourceResponse.Value;

// Serialize to JSON for display
var jsonOptions = new JsonSerializerOptions 
{ 
    WriteIndented = true,
    DefaultIgnoreCondition = System.Text.Json.Serialization.JsonIgnoreCondition.Never
};
Console.WriteLine(JsonSerializer.Serialize(ks, ks.GetType(), jsonOptions));

Referencia:SearchIndexClient

# Get a knowledge source definition
from azure.core.credentials import AzureKeyCredential
from azure.search.documents.indexes import SearchIndexClient
import json

index_client = SearchIndexClient(endpoint = "search_url", credential = AzureKeyCredential("api_key"))

ks = index_client.get_knowledge_source("knowledge_source_name")
print(json.dumps(ks.as_dict(), indent = 2))

Referencia:SearchIndexClient

### Get a knowledge source definition
GET {{search-url}}/knowledgesources/{{knowledge-source-name}}?api-version={{api-version}}
Authorization: Bearer {{token}}

Referencia:Tudásforrások – Get

using Azure.Identity;
using Azure.Search.Documents.Indexes;
using Azure.Search.Documents.Indexes.Models;
using Azure.Search.Documents.KnowledgeBases.Models;

var indexClient = new SearchIndexClient(new Uri(searchEndpoint), new DefaultAzureCredential());

var embeddingParams = new AzureOpenAIVectorizerParameters
{
    ResourceUri = new Uri(aoaiEndpoint),
    DeploymentName = aoaiEmbeddingDeployment,
    ModelName = aoaiEmbeddingModel
};

var ingestionParams = new KnowledgeSourceIngestionParameters
{
    NetworkAccessMode = KnowledgeSourceNetworkAccessMode.Public,
    ContentExtractionMode = "minimal",
    EmbeddingModel = new KnowledgeSourceAzureOpenAIVectorizer
    {
        AzureOpenAIParameters = embeddingParams
    }
};

var sqlParams = new IndexedSqlKnowledgeSourceParameters(
    connectionString: sqlConnectionString,
    tableOrView: "dbo.tbl_hotels")
{
    ContentColumns =
    {
        new ContentColumnMapping("hotelName", "HotelName", "Edm.String"),
        new ContentColumnMapping("description", "Description", "Edm.String")
    },
    EmbeddingColumns =
    {
        new EmbeddingColumnMapping("descriptionVector", "Description")
    },
    IngestionParameters = ingestionParams
};

var knowledgeSource = new IndexedSqlKnowledgeSource(
    name: "indexedsqlks",
    indexedSqlParameters: sqlParams)
{
    Description = "Indexed Azure SQL knowledge source."
};

await indexClient.CreateOrUpdateKnowledgeSourceAsync(knowledgeSource);
Console.WriteLine($"Knowledge source '{knowledgeSource.Name}' created or updated successfully.");

Referencia:SearchIndexClient, IndexedSqlKnowledgeSource

from azure.identity import DefaultAzureCredential
from azure.search.documents.indexes import SearchIndexClient
from azure.search.documents.indexes.models import (
    AzureOpenAIVectorizerParameters,
    ContentColumnMapping,
    EmbeddingColumnMapping,
    IndexedSqlKnowledgeSource,
    IndexedSqlKnowledgeSourceParameters,
)
from azure.search.documents.knowledgebases.models import (
    KnowledgeSourceAzureOpenAIVectorizer,
    KnowledgeSourceIngestionParameters,
    KnowledgeSourceNetworkAccessMode,
)

index_client = SearchIndexClient(endpoint="<search-endpoint>", credential=DefaultAzureCredential())

embedding_params = AzureOpenAIVectorizerParameters(
    resource_url="<aoai-endpoint>",
    deployment_name="<aoai-embedding-deployment>",
    model_name="<aoai-embedding-model>",
)

ingestion_params = KnowledgeSourceIngestionParameters(
    network_access_mode=KnowledgeSourceNetworkAccessMode.PUBLIC,
    content_extraction_mode="minimal",
    embedding_model=KnowledgeSourceAzureOpenAIVectorizer(
        azure_open_ai_parameters=embedding_params
    ),
)

knowledge_source = IndexedSqlKnowledgeSource(
    name="indexedsqlks",
    description="Indexed Azure SQL knowledge source.",
    indexed_sql_parameters=IndexedSqlKnowledgeSourceParameters(
        connection_string="Server=tcp:{server}.database.windows.net,1433;Database={db};...;",
        table_or_view="dbo.tbl_hotels",
        content_columns=[
            ContentColumnMapping(
                name="hotelName",
                source_field="HotelName",
                search_field_type="Edm.String",
            ),
            ContentColumnMapping(
                name="description",
                source_field="Description",
                search_field_type="Edm.String",
            ),
        ],
        embedding_columns=[
            EmbeddingColumnMapping(
                name="descriptionVector",
                source_field="Description",
            )
        ],
        ingestion_parameters=ingestion_params,
    ),
)

index_client.create_or_update_knowledge_source(knowledge_source=knowledge_source)
print(f"Knowledge source '{knowledge_source.name}' created or updated successfully.")

Referencia:SearchIndexClient

### Create an indexed Azure SQL knowledge source
PUT {{search-endpoint}}/knowledgesources/indexedsqlks?api-version=2026-08-01-preview
Authorization: Bearer {{search-access-token}}
Content-Type: application/json

{
  "name": "indexedsqlks",
  "kind": "indexedSql",
  "description": "Indexed Azure SQL knowledge source.",
  "indexedSqlParameters": {
    "connectionString": "Server=tcp:{server}.database.windows.net,1433;Database={db};...;",
    "tableOrView": "dbo.tbl_hotels",
    "contentColumns": [
      { "name": "hotelName", "sourceField": "HotelName", "searchFieldType": "Edm.String" },
      { "name": "description", "sourceField": "Description", "searchFieldType": "Edm.String" }
    ],
    "embeddingColumns": [
      { "name": "descriptionVector", "sourceField": "Description" }
    ],
    "ingestionParameters": {
      "networkAccessMode": "public",
      "contentExtractionMode": "minimal",
      "embeddingModel": {
        "kind": "azureOpenAI",
        "azureOpenAIParameters": {
          "resourceUri": "{{aoai-endpoint}}",
          "deploymentId": "{{aoai-embedding-deployment}}",
          "modelName": "{{aoai-embedding-model}}"
        }
      }
    }
  }
}

Referencia:Tudásforrások – Létrehozás vagy frissítés

using Azure.Search.Documents.Indexes;
using System.Text.Json;

var indexClient = new SearchIndexClient(new Uri(searchEndpoint), new AzureKeyCredential(apiKey));

// Get knowledge source ingestion status
var statusResponse = await indexClient.GetKnowledgeSourceStatusAsync(knowledgeSourceName);
var status = statusResponse.Value;

// Serialize to JSON for display
var json = JsonSerializer.Serialize(status, new JsonSerializerOptions { WriteIndented = true });
Console.WriteLine(json);

Referencia:SearchIndexClient

# Check knowledge source ingestion status
from azure.core.credentials import AzureKeyCredential
from azure.search.documents.indexes import SearchIndexClient
import json

index_client = SearchIndexClient(endpoint="search_url", credential=AzureKeyCredential("api_key"))

status = index_client.get_knowledge_source_status("knowledge_source_name")
print(json.dumps(status.as_dict(), indent=2))

Referencia:SearchIndexClient

### Check knowledge source ingestion status
GET {{search-url}}/knowledgesources/{{knowledge-source-name}}/status?api-version={{api-version}}
Authorization: Bearer {{token}}
Content-Type: application/json 

Referencia:Tudásforrások – Állapot lekérése

1. Szerezze be a keresési szolgáltatás összes tudásbázisának listáját.

   using Azure.Search.Documents.Indexes;
   
   var indexClient = new SearchIndexClient(new Uri(searchEndpoint), credential);
   var knowledgeBases = indexClient.GetKnowledgeBasesAsync();
   
   Console.WriteLine("Knowledge Bases:");
   
   await foreach (var kb in knowledgeBases)
   {
       Console.WriteLine($"  - {kb.Name}");
   }
   

   Referencia:SearchIndexClient

   Egy példaválasz az alábbihoz hasonlóan nézhet ki:

    {
        "@odata.context": "https://my-search-service.search.windows.net/$metadata#knowledgebases(name)",
        "value": [
        {
            "name": "my-kb"
        },
        {
            "name": "my-kb-2"
        }
        ]
    }
   

2. Szerezze be az egyéni tudásbázisdefiníciót a tudásbázishivatkozások kereséséhez.

   using Azure.Search.Documents.Indexes;
   using System.Text.Json;
   
   var indexClient = new SearchIndexClient(new Uri(searchEndpoint), credential);
   
   // Specify the knowledge base name to retrieve
   string kbNameToGet = "earth-knowledge-base";
   
   // Get a specific knowledge base definition
   var knowledgeBaseResponse = await indexClient.GetKnowledgeBaseAsync(kbNameToGet);
   var kb = knowledgeBaseResponse.Value;
   
   // Serialize to JSON for display
   string json = JsonSerializer.Serialize(kb, new JsonSerializerOptions { WriteIndented = true });
   Console.WriteLine(json);
   

   Referencia:SearchIndexClient

   Egy példaválasz az alábbihoz hasonlóan nézhet ki:

    {
      "Name": "earth-knowledge-base",
      "KnowledgeSources": [
        {
          "Name": "earth-knowledge-source"
        }
      ],
      "Models": [
        {}
      ],
      "RetrievalReasoningEffort": {},
      "OutputMode": {},
      "ETag": "\u00220x8DE278629D782B3\u0022",
      "EncryptionKey": null,
      "Description": null,
      "RetrievalInstructions": null,
      "AnswerInstructions": null
    }
   

3. Törölje a tudásbázist, vagy ha több tudásbázist használ, frissítse a tudásbázist a forrás eltávolításához. Ez a példa a törlést mutatja be.

   using Azure.Search.Documents.Indexes;
   var indexClient = new SearchIndexClient(new Uri(searchEndpoint), credential);
   
   await indexClient.DeleteKnowledgeBaseAsync(knowledgeBaseName);
   System.Console.WriteLine($"Knowledge base '{knowledgeBaseName}' deleted successfully.");
   

   Referencia:SearchIndexClient

4. Törölje a tudásbázist.

   await indexClient.DeleteKnowledgeSourceAsync(knowledgeSourceName);
   System.Console.WriteLine($"Knowledge source '{knowledgeSourceName}' deleted successfully.");
   

   Referencia:SearchIndexClient

1. Szerezze be a keresési szolgáltatás összes tudásbázisának listáját.

   # Get knowledge bases
   from azure.core.credentials import AzureKeyCredential
   from azure.search.documents.indexes import SearchIndexClient
   
   index_client = SearchIndexClient(endpoint = "search_url", credential = AzureKeyCredential("api_key"))
   
   print("Knowledge Bases:")
   for kb in index_client.list_knowledge_bases():
       print(f"  - {kb.name}")
   

   Referencia:SearchIndexClient

   Egy példaválasz az alábbihoz hasonlóan nézhet ki:

    {
        "@odata.context": "https://my-search-service.search.windows.net/$metadata#knowledgebases(name)",
        "value": [
        {
            "name": "my-kb"
        },
        {
            "name": "my-kb-2"
        }
        ]
    }
   

2. Szerezze be az egyéni tudásbázisdefiníciót a tudásbázishivatkozások kereséséhez.

   # Get a knowledge base definition
   from azure.core.credentials import AzureKeyCredential
   from azure.search.documents.indexes import SearchIndexClient
   
   index_client = SearchIndexClient(endpoint = "search_url", credential = AzureKeyCredential("api_key"))
   kb = index_client.get_knowledge_base("knowledge_base_name")
   print(kb)
   

   Referencia:SearchIndexClient

   Egy példaválasz az alábbihoz hasonlóan nézhet ki:

    {
      "name": "my-kb",
      "description": null,
      "retrievalInstructions": null,
      "answerInstructions": null,
      "outputMode": null,
      "knowledgeSources": [
        {
          "name": "my-blob-ks"
        }
      ],
      "models": [],
      "encryptionKey": null,
      "retrievalReasoningEffort": {
        "kind": "low"
      }
    }
   

3. Törölje a tudásbázist, vagy ha több tudásbázist használ, frissítse a tudásbázist a forrás eltávolításához. Ez a példa a törlést mutatja be.

   # Delete a knowledge base
   from azure.core.credentials import AzureKeyCredential 
   from azure.search.documents.indexes import SearchIndexClient
   
   index_client = SearchIndexClient(endpoint = "search_url", credential = AzureKeyCredential("api_key"))
   index_client.delete_knowledge_base("knowledge_base_name")
   print(f"Knowledge base deleted successfully.")
   

   Referencia:SearchIndexClient

4. Törölje a tudásbázist.

   # Delete a knowledge source
   from azure.core.credentials import AzureKeyCredential 
   from azure.search.documents.indexes import SearchIndexClient
   
   index_client = SearchIndexClient(endpoint = "search_url", credential = AzureKeyCredential("api_key"))
   index_client.delete_knowledge_source("knowledge_source_name")
   print(f"Knowledge source deleted successfully.")
   

   Referencia:SearchIndexClient

1. Szerezze be a keresési szolgáltatás összes tudásbázisának listáját.

   ### Get knowledge bases
   GET {{search-url}}/knowledgebases?api-version={{api-version}}&$select=name
   Authorization: Bearer {{token}}
   

   Referencia:Tudásbázisok – Lista

   Egy példaválasz az alábbihoz hasonlóan nézhet ki:

    {
        "@odata.context": "https://my-search-service.search.windows.net/$metadata#knowledgebases(name)",
        "value": [
        {
            "name": "my-kb"
        },
        {
            "name": "my-kb-2"
        }
        ]
    }
   

2. Szerezze be az egyéni tudásbázisdefiníciót a tudásbázishivatkozások kereséséhez.

   ### Get a knowledge base definition
   GET {{search-url}}/knowledgebases/{{knowledge-base-name}}?api-version={{api-version}}
   Authorization: Bearer {{token}}
   

   Referencia:Tudásbázisok – Get

   Egy példaválasz az alábbihoz hasonlóan nézhet ki:

    {
      "name": "my-kb",
      "description": null,
      "retrievalInstructions": null,
      "answerInstructions": null,
      "outputMode": null,
      "knowledgeSources": [
        {
          "name": "my-blob-ks"
        }
      ],
      "models": [],
      "encryptionKey": null,
      "retrievalReasoningEffort": {
        "kind": "low"
      }
    }
   

3. Törölje a tudásbázist, vagy ha több tudásbázist használ, frissítse a tudásbázist a forrás eltávolításához. Ez a példa a törlést mutatja be.

   ### Delete a knowledge base
   DELETE {{search-url}}/knowledgebases/{{knowledge-base-name}}?api-version={{api-version}}
   Authorization: Bearer {{token}}
   

   Referencia:Tudásbázisok – Törlés

4. Törölje a tudásbázist.

   ### Delete a knowledge source
   DELETE {{search-url}}/knowledgesources/{{knowledge-source-name}}?api-version={{api-version}}
   Authorization: Bearer {{token}}
   

   Referencia:Tudásforrások – Törlés