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Create a search index knowledge source

Note

Azure AI Search is available through the Azure portal, REST APIs, and Azure SDKs. It also underpins Foundry IQ, the managed knowledge layer that transforms enterprise content into reusable, permission-aware knowledge bases for agents in the Microsoft Foundry portal.

Note

This agentic retrieval feature is generally available in the 2026-04-01 REST API via programmatic access. The Azure portal and Microsoft Foundry portal continue to provide preview-only access to all agentic retrieval features. For migration guidance, see Migrate agentic retrieval code to the latest version.

If you choose to use a preview REST API, you can access capabilities that aren't yet generally available for this feature. Preview features are provided without a service-level agreement and aren't recommended for production workloads. For more information, see Supplemental Terms of Use for Microsoft Azure Previews.

Important

These features and functionality are part of the 2026-08-01-preview REST API. The 2026-08-01-preview is licensed to you as part of your Azure subscription and is subject to the terms applicable to "Previews" in the Microsoft Product Terms, the Microsoft Products and Services Data Protection Addendum ("DPA"), and the Supplemental Terms of Use for Microsoft Azure Previews.

The 2026-08-01-preview supports connections to other Microsoft services and third-party services. Use of these services is subject to their respective terms and might result in data processing or storage outside of the Azure compliance boundary, as well as data flowing into the Azure compliance boundary.

It's your responsibility to manage whether your data will flow outside of your organization's compliance and geographic boundaries and any related implications, and that appropriate permissions, boundaries, and approvals are provisioned.

You're responsible for carefully reviewing and testing applications you build in the context of your specific use cases and making all appropriate decisions and customizations. This includes implementing your own responsible AI mitigations, such as metaprompts, content filters, or other safety systems, and ensuring your applications meet appropriate quality, reliability, security, and trustworthiness standards. For more information, see the Azure AI Search Transparency Note.

A search index knowledge source connects an existing Azure AI Search index, including its indexed text and vectors, to an agentic retrieval pipeline. Knowledge sources are created independently, referenced in a knowledge base, and used as grounding data when the knowledge base is queried at runtime.

Usage support

Azure portal Microsoft Foundry portal .NET SDK Python SDK Java SDK JavaScript SDK REST API
✔️ ✔️ ✔️ ✔️ ✔️ ✔️ ✔️

Prerequisites

  • Required Azure.Search.Documents package:

    • For 2026-08-01-preview features, the latest preview package: dotnet add package Azure.Search.Documents --prerelease

    • For 2026-04-01 features, the latest stable package: dotnet add package Azure.Search.Documents

  • For keyless authentication, the Azure.Identity package: dotnet add package Azure.Identity

  • Required azure-search-documents package:

    • For 2026-08-01-preview features, the latest preview package: pip install --pre azure-search-documents

    • For 2026-04-01 features, the latest stable package: pip install azure-search-documents

  • For keyless authentication, the azure-identity package: pip install azure-identity

Limitations

Agentic retrieval doesn't make retrieve requests honor the underlying index's scoring profiles, including defaultScoringProfile. Retrieve responses don't surface @search.rerankerBoostedScore.

Check for existing knowledge sources

A knowledge source is a top-level, reusable object. Knowing about existing knowledge sources is helpful for either reuse or naming new objects.

Run the following code to list knowledge sources by name and type.

// 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}");
}

Reference: 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})")

Reference: SearchIndexClient

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

Reference: Knowledge Sources - List

You can also return a single knowledge source by name to review its JSON definition.

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));

Reference: 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))

Reference: SearchIndexClient

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

Reference: Knowledge Sources - Get

The following JSON is an example response for a search index knowledge source. Notice that the knowledge source specifies a single index name and which fields in the index to include in the query.

{
  "name": "my-search-index-ks",
  "kind": "searchIndex",
  "description": "A sample search index knowledge source.",
  "encryptionKey": null,
  "searchIndexParameters": {
    "searchIndexName": "my-search-index",
    "semanticConfigurationName": null,
    "sourceDataFields": [],
    "searchFields": []
  }
}

Create a knowledge source

Run the following code to create a search index knowledge source.

Note

Starting with the 2026-05-01-preview API version, semanticConfigurationName is optional on search index knowledge sources. Earlier API versions still require semanticConfigurationName. If your knowledge source needs to support both older and newer API versions, keep specifying semanticConfigurationName.

// Create a search index knowledge source
using Azure.Search.Documents.Indexes;
using Azure.Search.Documents.Indexes.Models;
using Azure.Identity;

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

var indexKnowledgeSource = new SearchIndexKnowledgeSource(
    name: knowledgeSourceName,
    searchIndexParameters: new SearchIndexKnowledgeSourceParameters(searchIndexName: indexName)
    {
        SearchFields = { new SearchIndexFieldReference(name: "page_chunk") },
        SourceDataFields = { new SearchIndexFieldReference(name: "id"), new SearchIndexFieldReference(name: "page_chunk"), new SearchIndexFieldReference(name: "page_number") }
    }
);

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

Reference: SearchIndexClient, SearchIndexKnowledgeSource

# Create a search index knowledge source
from azure.identity import DefaultAzureCredential
from azure.search.documents.indexes import SearchIndexClient
from azure.search.documents.indexes.models import SearchIndexKnowledgeSource, SearchIndexKnowledgeSourceParameters, SearchIndexFieldReference

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

knowledge_source = SearchIndexKnowledgeSource(
    name = "my-search-index-ks",
    description= "This knowledge source pulls from an existing index designed for agentic retrieval.",
    encryption_key = None,
    search_index_parameters = SearchIndexKnowledgeSourceParameters(
        search_index_name = "search_index_name",
        source_data_fields = [
            SearchIndexFieldReference(name="description"),
            SearchIndexFieldReference(name="category"),
        ],
        search_fields = [
            SearchIndexFieldReference(name="id")
        ],
    )
)

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

Reference: SearchIndexClient

### Create a search index knowledge source
PUT {{search-endpoint}}/knowledgesources/my-search-index-ks?api-version=2026-08-01-preview
Authorization: Bearer {{search-access-token}}
Content-Type: application/json

{
    "name": "my-search-index-ks",
    "kind": "searchIndex",
    "description": "This knowledge source pulls from an existing index designed for agentic retrieval.",
    "encryptionKey": null,
    "searchIndexParameters": {
        "searchIndexName": "<index-name>",
        "sourceDataFields": [
          { "name": "description" },
          { "name": "category" }
        ]
    }
}

Reference: Knowledge Sources - Create or Update

Persist a base filter on a knowledge source (preview)

Important

These features and functionality are part of the 2026-08-01-preview REST API. The 2026-08-01-preview is licensed to you as part of your Azure subscription and is subject to the terms applicable to "Previews" in the Microsoft Product Terms, the Microsoft Products and Services Data Protection Addendum ("DPA"), and the Supplemental Terms of Use for Microsoft Azure Previews.

Starting with the 2026-05-01-preview API version, a search index knowledge source can persist a default filter through the baseFilter property. Use baseFilter when the same filter expression should apply to every retrieve request that uses the knowledge source, so callers don't have to repeat the filter on every call.

The following example stores a base filter on a search index knowledge source.

var knowledgeSource = new SearchIndexKnowledgeSource(
    name: "public-docs-ks",
    searchIndexParameters: new SearchIndexKnowledgeSourceParameters(searchIndexName: "public-docs-index")
    {
        BaseFilter = "isPublished eq true and accessScope eq 'public'"
    }
);

await indexClient.CreateOrUpdateKnowledgeSourceAsync(knowledgeSource);

Reference: SearchIndexKnowledgeSourceParameters

knowledge_source = SearchIndexKnowledgeSource(
    name="public-docs-ks",
    search_index_parameters=SearchIndexKnowledgeSourceParameters(
        search_index_name="public-docs-index",
        base_filter="isPublished eq true and accessScope eq 'public'",
    ),
)

index_client.create_or_update_knowledge_source(knowledge_source)

Reference: SearchIndexKnowledgeSourceParameters

PUT {{search-endpoint}}/knowledgesources/public-docs-ks?api-version=2026-08-01-preview
Content-Type: application/json
Authorization: Bearer {{search-access-token}}

{
  "name": "public-docs-ks",
  "kind": "searchIndex",
  "searchIndexParameters": {
    "searchIndexName": "public-docs-index",
    "baseFilter": "isPublished eq true and accessScope eq 'public'"
  }
}

Reference: Knowledge Sources - Create or Update

At retrieve time, knowledgeSourceParams.filterAddOn adds request-specific constraints to the stored base filter:

var retrievalRequest = new KnowledgeBaseRetrievalRequest();
retrievalRequest.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams("public-docs-ks")
    {
        FilterAddOn = "category eq 'Benefits'"
    }
);

request = KnowledgeBaseRetrievalRequest(
    knowledge_source_params=[
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="public-docs-ks",
            filter_add_on="category eq 'Benefits'",
        ),
    ],
)

{
  "knowledgeSourceParams": [
    {
      "knowledgeSourceName": "public-docs-ks",
      "kind": "searchIndex",
      "filterAddOn": "category eq 'Benefits'"
    }
  ]
}

The effective filter is composed as:

baseFilter AND filterAddOn

Because the filters are combined with AND, filterAddOn can only narrow the persisted base filter. It can't replace or broaden it.

Configure query hints (preview)

Starting with the 2026-08-01-preview API version, query hints guide the query-planning model to generate filters and ranking boosts from a user's request. Store default hints in searchIndexParameters.queryHints, which can hold both filters and boosts.

The following example stores one filter hint and one fieldValue boost on a knowledge source for product-docs-index, which has a filterable productFamily field and a searchable language field.

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

var endpoint = new Uri("<search-endpoint>");
var indexClient = new SearchIndexClient(
    endpoint,
    new DefaultAzureCredential());

var queryHints = new SearchIndexKnowledgeSourceQueryHints();
queryHints.Filters.Add(
    new SearchIndexKnowledgeSourceFilterHint(
        "productFamily",
        ["Model-X100", "Model-X200"])
    {
        FilterInstructions =
            "Filter only when the user names a model."
    });

var languageBoost =
    new SearchIndexKnowledgeSourceFieldValueBoost(
        "language",
        2.0);
languageBoost.FieldValues.Add("en-US");
languageBoost.FieldValues.Add("ja-JP");
languageBoost.BoostInstructions =
    "Prefer the language requested by the user.";
queryHints.Boosts.Add(languageBoost);

var knowledgeSource = new SearchIndexKnowledgeSource(
    "product-docs-ks",
    new SearchIndexKnowledgeSourceParameters(
        "product-docs-index")
    {
        QueryHints = queryHints
    });

await indexClient.CreateOrUpdateKnowledgeSourceAsync(
    knowledgeSource);

Reference: SearchIndexKnowledgeSourceParameters

from azure.identity import DefaultAzureCredential
from azure.search.documents.indexes import SearchIndexClient
from azure.search.documents.indexes.models import (
    SearchIndexKnowledgeSource,
    SearchIndexKnowledgeSourceFieldValueBoost,
    SearchIndexKnowledgeSourceFilterHint,
    SearchIndexKnowledgeSourceParameters,
    SearchIndexKnowledgeSourceQueryHints,
)

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

query_hints = SearchIndexKnowledgeSourceQueryHints(
    filters=[
        SearchIndexKnowledgeSourceFilterHint(
            field="productFamily",
            field_values=["Model-X100", "Model-X200"],
            filter_instructions=(
                "Filter only when the user names a model."
            ),
        )
    ],
    boosts=[
        SearchIndexKnowledgeSourceFieldValueBoost(
            field="language",
            field_values=["en-US", "ja-JP"],
            boost=2.0,
            boost_instructions=(
                "Prefer the language requested by the user."
            ),
        )
    ],
)

knowledge_source = SearchIndexKnowledgeSource(
    name="product-docs-ks",
    search_index_parameters=SearchIndexKnowledgeSourceParameters(
        search_index_name="product-docs-index",
        query_hints=query_hints,
    ),
)

index_client.create_or_update_knowledge_source(knowledge_source)

Reference: SearchIndexKnowledgeSourceParameters

PUT {{search-endpoint}}/knowledgesources('product-docs-ks')?api-version=2026-08-01-preview
Content-Type: application/json
Authorization: Bearer {{search-access-token}}

{
  "name": "product-docs-ks",
  "kind": "searchIndex",
  "searchIndexParameters": {
    "searchIndexName": "product-docs-index",
    "queryHints": {
      "filters": [{
        "field": "productFamily",
        "fieldValues": ["Model-X100", "Model-X200"],
        "filterInstructions": "Filter only when the user names a model."
      }],
      "boosts": [{
        "kind": "fieldValue",
        "field": "language",
        "fieldValues": ["en-US", "ja-JP"],
        "boost": 2.0,
        "boostInstructions": "Prefer the language requested by the user."
      }]
    }
  }
}

Reference: Knowledge Sources - Create or Update

Configure each hint according to the following requirements:

Hint Field requirements fieldValues behavior Collection limits
Filter field must identify a filterable index field. Required. List the exhaustive set of allowed values. If the request doesn't map to a listed value, the planner is instructed not to filter on that field. Up to five hints with unique fields. Each value can contain up to 128 characters, and all values in one hint can contain up to 2,048 characters combined.
fieldValue boost field must identify a searchable field that uses a language, standard, or default analyzer. Optional examples. If you omit them, use boostInstructions to explain which value to select from the request. Up to five hints with unique fields. Each hint can contain up to 20 values, with 128 characters per value and 1,024 characters combined.
multiWordExpression boost Omit field. The index must contain at least one searchable field that uses a language, standard, or default analyzer. Optional examples of domain-specific phrases. One hint. It can contain up to 20 values, with 128 characters per value and 1,024 characters combined.

For either boost kind, boost is required and must be a finite number greater than 1.0. Higher values give matching documents more influence in ranking without excluding other documents. Limit each optional filterInstructions or boostInstructions value to 1,024 characters.

Use a multiWordExpression boost for domain-specific phrases whose meaning isn't captured by the individual words. Provide example phrases in fieldValues, or omit them and let boostInstructions and the user's request guide phrase selection:

{
  "boosts": [{
    "kind": "multiWordExpression",
    "fieldValues": ["deferred tax", "wash sale"],
    "boost": 3.0,
    "boostInstructions": "Boost domain terms used as complete phrases."
  }]
}

When you design query hints, keep the following behaviors in mind:

  • Hints are best effort, so the model might not generate a filter or boost for every request. For required constraints, such as authorization boundaries, use document-level access control or a deterministic filter instead.

  • Hints need model-driven query planning, so they aren't applied when the retrieval reasoning effort is minimal. At other effort levels, a GPT-4o or GPT-4.1 family model returns HTTP 400 when the stored queryHints object contains a filter. The service checks stored filters before applying queryHintOverrides, so an empty or boosts-only override doesn't bypass this validation. Stored fieldValue and multiWordExpression boosts alone don't trigger the validation.

  • Generated filters combine with baseFilter and filterAddOn by using AND. A generated boost rewrites the query in full Lucene syntax while preserving the original terms.

  • Query hints use indexed values as grounding. They don't configure analyzers or enable language detection. The language values in these examples are ordinary index metadata.

To replace stored hints for a single retrieve request and verify the generated filter or boost, see Override stored query hints at query time (preview).

Assign to a knowledge base

If you're satisfied with the knowledge source, add it to a knowledge base.

Query a knowledge base

After the knowledge base is configured, call the retrieve action or MCP endpoint to query the knowledge source.

Delete a knowledge source

Before you can delete a knowledge source, you must delete any knowledge base that references it or update the knowledge base definition to remove the reference. For knowledge sources that generate an index and indexer pipeline, all generated objects are also deleted. However, if you used an existing index to create a knowledge source, your index isn't deleted.

If you try to delete a knowledge source that's in use, the action fails and returns a list of affected knowledge bases.

To delete a knowledge source:

  1. Get a list of all knowledge bases on your search service.

    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}");
}

    Reference: SearchIndexClient

    An example response might look like the following:

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

  2. Get an individual knowledge base definition to check for knowledge source references.

    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);

    Reference: SearchIndexClient

    An example response might look like the following:

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

  3. Either delete the knowledge base or, if you have multiple knowledge sources, update the knowledge base to remove the source. This example shows deletion.

    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.");

    Reference: SearchIndexClient

  4. Delete the knowledge source.

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

    Reference: SearchIndexClient

  1. Get a list of all knowledge bases on your search service.

    # 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}")

    Reference: SearchIndexClient

    An example response might look like the following:

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

  2. Get an individual knowledge base definition to check for knowledge source references.

    # 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)

    Reference: SearchIndexClient

    An example response might look like the following:

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

  3. Either delete the knowledge base or, if you have multiple knowledge sources, update the knowledge base to remove the source. This example shows deletion.

    # 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.")

    Reference: SearchIndexClient

  4. Delete the knowledge source.

    # 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.")

    Reference: SearchIndexClient

  1. Get a list of all knowledge bases on your search service.

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

    Reference: Knowledge Bases - List

    An example response might look like the following:

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

  2. Get an individual knowledge base definition to check for knowledge source references.

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

    Reference: Knowledge Bases - Get

    An example response might look like the following:

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

  3. Either delete the knowledge base or, if you have multiple knowledge sources, update the knowledge base to remove the source. This example shows deletion.

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

    Reference: Knowledge Bases - Delete

  4. Delete the knowledge source.

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

    Reference: Knowledge Sources - Delete

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