使用检索操作或 MCP 端点来查询知识库

• 如果通过 Azure OpenAI 响应 API 调用 MCP 终结点，则需要：

  • 在 Foundry 资源上部署的 LLM 和认知服务 OpenAI 用户角色（或 API 密钥）。 可以重复使用知识库中指定的 LLM 和资源（如果适用）。

  • Azure.AI.OpenAI 包：dotnet add package Azure.AI.OpenAI

• 所需 Azure.Search.Documents 软件包：

  • 对于 2026-08-01-preview 功能，最新的预览包：dotnet add package Azure.Search.Documents --prerelease

  • 对于 2026-04-01 功能，最新稳定版软件包：dotnet add package Azure.Search.Documents

• 对于无密钥身份验证，请使用 Azure.Identity 软件包：dotnet add package Azure.Identity

• 如果通过 Azure OpenAI 响应 API 调用 MCP 终结点，则需要：

  • 在 Foundry 资源上部署的 LLM 和认知服务 OpenAI 用户角色（或 API 密钥）。 可以重复使用知识库中指定的 LLM 和资源（如果适用）。

  • openai 包：pip install openai

• 所需 azure-search-documents 软件包：

  • 对于 2026-08-01-preview 功能，最新的预览包：pip install --pre azure-search-documents

  • 对于 2026-04-01 功能，最新稳定版软件包：pip install azure-search-documents

• 对于无密钥身份验证，请使用 azure-identity 软件包：pip install azure-identity

• 所需的搜索服务 REST API 版本：

  • 对于预览功能： 2026-08-01-preview

  • 对于正式发布的功能：2026-04-01

• 对于无密钥身份验证，请在每个 HTTP 请求的标头中包含AuthorizationMicrosoft Entra ID令牌。

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

var client = new KnowledgeBaseRetrievalClient(
    new Uri("<search-endpoint>"),
    "product-catalog-kb",
    new DefaultAzureCredential());

var request = new KnowledgeBaseRetrievalRequest
{
    IncludeActivity = true
};
request.Intents.Add(
    new KnowledgeRetrievalSemanticIntent(
        "Find the power adapter for SKU 88421."));
request.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams("product-catalog-ks")
    {
        AlwaysQuerySource = true,
        IncludeReferences = true,
        ResultsProcessing = KnowledgeSourceResultsProcessing.None
    });

var result = await client.RetrieveAsync(request);
Console.WriteLine(
    $"References with a reranker score: "
    + $"{result.Value.References.Count(x => x.RerankerScore.HasValue)}");

参考：KnowledgeBaseRetrievalClient、 SearchIndexKnowledgeSourceParams

from azure.identity import DefaultAzureCredential
from azure.search.documents.knowledgebases import (
    KnowledgeBaseRetrievalClient,
)
from azure.search.documents.knowledgebases.models import (
    KnowledgeBaseRetrievalRequest,
    KnowledgeRetrievalSemanticIntent,
    SearchIndexKnowledgeSourceParams,
)

client = KnowledgeBaseRetrievalClient(
    endpoint="<search-endpoint>",
    knowledge_base_name="product-catalog-kb",
    credential=DefaultAzureCredential(),
)

request = KnowledgeBaseRetrievalRequest(
    intents=[
        KnowledgeRetrievalSemanticIntent(
            search="Find the power adapter for SKU 88421."
        )
    ],
    include_activity=True,
    knowledge_source_params=[
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="product-catalog-ks",
            always_query_source=True,
            include_references=True,
            results_processing="none",
        )
    ],
)

result = client.retrieve(request)
reranked_count = sum(
    reference.reranker_score is not None
    for reference in result.references
)
print("References with a reranker score:", reranked_count)

参考：KnowledgeBaseRetrievalClient、 SearchIndexKnowledgeSourceParams

@search-endpoint = <search-endpoint>
@search-access-token = <search-access-token> // Run: az account get-access-token --scope https://search.azure.com/.default --query accessToken -o tsv
@knowledge-base-name = product-catalog-kb

POST {{search-endpoint}}/knowledgebases/{{knowledge-base-name}}/retrieve?api-version=2026-08-01-preview
Content-Type: application/json
Authorization: Bearer {{search-access-token}}

{
  "intents": [
    {
      "type": "semantic",
      "search": "Find the power adapter for SKU 88421."
    }
  ],
  "includeActivity": true,
  "knowledgeSourceParams": [
    {
      "knowledgeSourceName": "product-catalog-ks",
      "kind": "searchIndex",
      "alwaysQuerySource": true,
      "includeReferences": true,
      "resultsProcessing": "none"
    }
  ]
}

参考：知识检索 - 检索

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

var client = new KnowledgeBaseRetrievalClient(
    new Uri("<search-endpoint>"),
    "<knowledge-base-name>",
    new DefaultAzureCredential());

var request = new KnowledgeBaseRetrievalRequest
{
    OutputMode = KnowledgeRetrievalOutputMode.ExtractiveData,
    RetrievalReasoningEffort =
        new KnowledgeRetrievalMinimalReasoningEffort(),
    IncludeActivity = true,
};
request.Intents.Add(
    new KnowledgeRetrievalSemanticIntent("What is the return policy?"));
request.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams(
        "<knowledge-source-name>")
    {
        ResultsProcessing = KnowledgeSourceResultsProcessing.None,
        IncludeReferences = true,
    });

var eventCounts = new Dictionary<string, int>();

await foreach (var item in client.RetrieveStreamAsync(request))
{
    eventCounts.TryGetValue(item.EventType, out var count);
    eventCounts[item.EventType] = count + 1;
}

foreach (var (eventType, count) in eventCounts)
{
    Console.WriteLine($"{eventType}: {count}");
}

参考：KnowledgeBaseRetrievalClient

from collections import Counter

from azure.identity import DefaultAzureCredential
from azure.search.documents.indexes.models import (
    KnowledgeSourceResultsProcessing,
)
from azure.search.documents.knowledgebases import (
    KnowledgeBaseRetrievalClient,
)
from azure.search.documents.knowledgebases.models import (
    KnowledgeBaseRetrievalRequest,
    KnowledgeRetrievalMinimalReasoningEffort,
    KnowledgeRetrievalOutputMode,
    KnowledgeRetrievalSemanticIntent,
    SearchIndexKnowledgeSourceParams,
)


client = KnowledgeBaseRetrievalClient(
    endpoint="<search-endpoint>",
    knowledge_base_name="<knowledge-base-name>",
    credential=DefaultAzureCredential(),
)

request = KnowledgeBaseRetrievalRequest(
    intents=[
        KnowledgeRetrievalSemanticIntent(
            search="What is the return policy?"
        )
    ],
    output_mode=KnowledgeRetrievalOutputMode.EXTRACTIVE_DATA,
    retrieval_reasoning_effort=KnowledgeRetrievalMinimalReasoningEffort(),
    include_activity=True,
    knowledge_source_params=[
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="<knowledge-source-name>",
            results_processing=KnowledgeSourceResultsProcessing.NONE,
            include_references=True,
        )
    ],
)

event_counts = Counter()

with client.retrieve_stream(request) as stream:
    for event in stream:
        event_counts[event.event_type] += 1

for event_type, count in event_counts.items():
    print(f"{event_type}: {count}")

参考：KnowledgeBaseRetrievalClient

若要启用流式传输，请在检索请求中包含 Accept: text/event-stream 标头。 如果没有此标头，检索操作将返回其标准 JSON 响应。

POST {{search-endpoint}}/knowledgebases/{{knowledge-base-name}}/retrieve?api-version=2026-08-01-preview
Content-Type: application/json
Accept: text/event-stream
Authorization: Bearer {{search-access-token}}

{
    "intents": [
        {
            "type": "semantic",
            "search": "What is the return policy?"
        }
    ],
    "outputMode": "extractiveData",
    "retrievalReasoningEffort": {
        "kind": "minimal"
    },
    "includeActivity": true,
    "knowledgeSourceParams": [
        {
            "knowledgeSourceName": "{{knowledge-source-name}}",
            "kind": "searchIndex",
            "resultsProcessing": "none",
            "includeReferences": true
        }
    ]
}

参考：知识检索 - 检索

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

var kbClient = new KnowledgeBaseRetrievalClient(
    endpoint: new Uri("<search-endpoint>"),
    knowledgeBaseName: "<knowledge-base-name>",
    credential: new DefaultAzureCredential()
);

var retrievalRequest = new KnowledgeBaseRetrievalRequest();

retrievalRequest.Messages.Add(
    new KnowledgeBaseMessage(
        content: new[] {
            new KnowledgeBaseMessageTextContent(
                "You are a support agent. Answer questions based on published documentation. "
                + "If you don't know the answer, say so."
            )
        }
    ) { Role = "assistant" }
);

retrievalRequest.Messages.Add(
    new KnowledgeBaseMessage(
        content: new[] {
            new KnowledgeBaseMessageTextContent(
                "What is the process for submitting an expense report?"
            )
        }
    ) { Role = "user" }
);

// Apply a filter to search only published documents
var searchIndexParams = new SearchIndexKnowledgeSourceParams(
    knowledgeSourceName: "internal-documentation-ks"
);
searchIndexParams.FilterAddOn = "status eq 'published'";

retrievalRequest.KnowledgeSourceParams.Add(searchIndexParams);

var result = await kbClient.RetrieveAsync(retrievalRequest);
Console.WriteLine(
    (result.Value.Response[0].Content[0] as KnowledgeBaseMessageTextContent)!.Text
);

from azure.identity import DefaultAzureCredential
from azure.search.documents.knowledgebases import KnowledgeBaseRetrievalClient
from azure.search.documents.knowledgebases.models import (
    KnowledgeBaseMessage,
    KnowledgeBaseMessageTextContent,
    KnowledgeBaseRetrievalRequest,
    SearchIndexKnowledgeSourceParams,
)

kb_client = KnowledgeBaseRetrievalClient(
    endpoint="<search-endpoint>",
    knowledge_base_name="<knowledge-base-name>",
    credential=DefaultAzureCredential(),
)

request = KnowledgeBaseRetrievalRequest(
    messages=[
        KnowledgeBaseMessage(
            role="assistant",
            content=[
                KnowledgeBaseMessageTextContent(
                    text="You are a support agent. Answer questions based on published documentation. "
                    "If you don't know the answer, say so."
                )
            ],
        ),
        KnowledgeBaseMessage(
            role="user",
            content=[
                KnowledgeBaseMessageTextContent(
                    text="What is the process for submitting an expense report?"
                )
            ],
        ),
    ],
    knowledge_source_params=[
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="internal-documentation-ks",
            # Apply a filter to search only published documents
            filter_add_on="status eq 'published'",
        )
    ],
)

result = kb_client.retrieve(request)
print(result.response[0].content[0].text)

POST {{search-endpoint}}/knowledgebases/{{knowledge-base-name}}/retrieve?api-version=2026-08-01-preview
Content-Type: application/json
Authorization: Bearer {{search-access-token}}

{
    "messages": [
        {
            "role": "assistant",
            "content": [
                {
                    "type": "text",
                    "text": "You are a support agent. Answer questions based on published documentation. If you don't know the answer, say so."
                }
            ]
        },
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "What is the process for submitting an expense report?"
                }
            ]
        }
    ],
    "knowledgeSourceParams": [
        {
            "knowledgeSourceName": "internal-documentation-ks",
            "kind": "searchIndex",
            "filterAddOn": "status eq 'published'"
        }
    ]
}

searchIndexParams.FilterAddOn = "(status eq 'published' or status eq 'internal') and created ge 2025-01-01";

filter_add_on="(status eq 'published' or status eq 'internal') and created ge 2025-01-01"

{
    "knowledgeSourceName": "internal-documentation-ks",
    "kind": "searchIndex",
    "filterAddOn": "(status eq 'published' or status eq 'internal') and created ge 2025-01-01"
}

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

var endpoint = new Uri("<search-endpoint>");
var retrievalClient = new KnowledgeBaseRetrievalClient(
    endpoint,
    "product-kb",
    new DefaultAzureCredential());

var languageBoost =
    new SearchIndexKnowledgeSourceFieldValueBoost(
        "language",
        2.0);
languageBoost.FieldValues.Add("ja-JP");
var queryHintOverrides =
    new SearchIndexKnowledgeSourceQueryHints();
queryHintOverrides.Boosts.Add(languageBoost);

var request = new KnowledgeBaseRetrievalRequest
{
    RetrievalReasoningEffort =
        new KnowledgeRetrievalLowReasoningEffort(),
    IncludeActivity = true
};
request.Messages.Add(
    new KnowledgeBaseMessage([
        new KnowledgeBaseMessageTextContent(
            "Find Japanese service guidance for Model-X200.")
    ])
    {
        Role = "user"
    });
request.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams(
        "product-docs-ks")
    {
        QueryHintOverrides = queryHintOverrides
    });

var result = await retrievalClient.RetrieveAsync(request);

参考：KnowledgeBaseRetrievalClient、 SearchIndexKnowledgeSourceParams

from azure.identity import DefaultAzureCredential
from azure.search.documents.indexes.models import (
    SearchIndexKnowledgeSourceFieldValueBoost,
    SearchIndexKnowledgeSourceQueryHints,
)
from azure.search.documents.knowledgebases import (
    KnowledgeBaseRetrievalClient,
)
from azure.search.documents.knowledgebases.models import (
    KnowledgeBaseMessage,
    KnowledgeBaseMessageTextContent,
    KnowledgeBaseRetrievalRequest,
    KnowledgeRetrievalLowReasoningEffort,
    SearchIndexKnowledgeSourceParams,
)

retrieval_client = KnowledgeBaseRetrievalClient(
    endpoint="<search-endpoint>",
    credential=DefaultAzureCredential(),
    knowledge_base_name="product-kb",
)

query_hint_overrides = SearchIndexKnowledgeSourceQueryHints(
    boosts=[
        SearchIndexKnowledgeSourceFieldValueBoost(
            field="language",
            field_values=["ja-JP"],
            boost=2.0,
        )
    ]
)

request = KnowledgeBaseRetrievalRequest(
    messages=[
        KnowledgeBaseMessage(
            role="user",
            content=[
                KnowledgeBaseMessageTextContent(
                    text="Find Japanese service guidance for Model-X200."
                )
            ],
        )
    ],
    knowledge_source_params=[
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="product-docs-ks",
            query_hint_overrides=query_hint_overrides,
        )
    ],
    retrieval_reasoning_effort=(
        KnowledgeRetrievalLowReasoningEffort()
    ),
    include_activity=True,
)

result = retrieval_client.retrieve(request)

参考：KnowledgeBaseRetrievalClient、 SearchIndexKnowledgeSourceParams

POST {{search-endpoint}}/knowledgebases('product-kb')/retrieve?api-version=2026-08-01-preview
Content-Type: application/json
Authorization: Bearer {{search-access-token}}

{
  "messages": [{
    "role": "user",
    "content": [{
      "type": "text",
      "text": "Find Japanese service guidance for Model-X200."
    }]
  }],
  "knowledgeSourceParams": [{
    "knowledgeSourceName": "product-docs-ks",
    "kind": "searchIndex",
    "queryHintOverrides": {
      "boosts": [{
        "kind": "fieldValue",
        "field": "language",
        "fieldValues": ["ja-JP"],
        "boost": 2.0
      }]
    }
  }],
  "retrievalReasoningEffort": {"kind": "low"},
  "includeActivity": true
}

参考：知识检索 - 检索

在 .NET SDK 中，将令牌作为 querySourceAuthorization 上的 RetrieveAsync 参数传递：

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

// Service credential: Authenticates to the search service
var serviceCredential = new DefaultAzureCredential();

// User identity token: Represents the end user for document-level permissions filtering
var userTokenContext = new Azure.Core.TokenRequestContext(
    new[] { "https://search.azure.com/.default" }
);
string userToken = (await serviceCredential.GetTokenAsync(userTokenContext)).Token;

// Create the retrieval client with the service credential
var kbClient = new KnowledgeBaseRetrievalClient(
    endpoint: new Uri("<search-endpoint>"),
    knowledgeBaseName: "<knowledge-base-name>",
    credential: serviceCredential
);

var request = new KnowledgeBaseRetrievalRequest();
request.Messages.Add(
    new KnowledgeBaseMessage(
        content: new[] {
            new KnowledgeBaseMessageTextContent(
                "What companies are in the financial sector?")
        }
    ) { Role = "user" }
);

// Pass the user identity token for permissions filtering
var result = await kbClient.RetrieveAsync(
    request, querySourceAuthorization: userToken);

var text = (result.Value.Response[0].Content[0] as KnowledgeBaseMessageTextContent)!.Text;
Console.WriteLine(text);

参考：KnowledgeBaseRetrievalClient、 KnowledgeBaseRetrievalRequest

在 Python SDK 中，在 query_source_authorization 上将令牌作为 retrieve 参数传递：

from azure.identity import DefaultAzureCredential, get_bearer_token_provider
from azure.search.documents.knowledgebases import KnowledgeBaseRetrievalClient
from azure.search.documents.knowledgebases.models import (
    KnowledgeBaseMessage, KnowledgeBaseMessageTextContent,
    KnowledgeBaseRetrievalRequest,
)

# Service credential: Authenticates to the search service
service_credential = DefaultAzureCredential()

# User identity token: Represents the end user for document-level permissions filtering
user_token_provider = get_bearer_token_provider(
    service_credential, "https://search.azure.com/.default")
user_token = user_token_provider()

# Create the retrieval client with the service credential
kb_client = KnowledgeBaseRetrievalClient(
    endpoint="<search-endpoint>",
    knowledge_base_name="<knowledge-base-name>",
    credential=service_credential,
)

request = KnowledgeBaseRetrievalRequest(
    messages=[
        KnowledgeBaseMessage(
            role="user",
            content=[KnowledgeBaseMessageTextContent(
                text="What companies are in the financial sector?")],
        )
    ]
)

# Pass the user identity token for permissions filtering
result = kb_client.retrieve(
    retrieval_request=request, query_source_authorization=user_token)
print(result.response[0].content[0].text)

参考：KnowledgeBaseRetrievalClient、 KnowledgeBaseRetrievalRequest

在 REST API 中，包含 x-ms-query-source-authorization 具有用户访问令牌的标头：

@search-endpoint = <search-endpoint>
@search-access-token = <search-access-token> // Service credential
@user-access-token = <user-access-token> // User identity token

POST {{search-endpoint}}/knowledgebases/{{knowledge-base-name}}/retrieve?api-version=2026-08-01-preview
Authorization: Bearer {{search-access-token}}
Content-Type: application/json
x-ms-query-source-authorization: {{user-access-token}}

{
    "messages": [
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "What companies are in the financial sector?"
                }
            ]
        }
    ]
}

参考：知识检索 - 检索

using System;
using System.Net.Http;
using System.Net.Http.Headers;
using Azure.Core;
using Azure.Identity;

// citationUrl comes from a retrieve response
string citationUrl = "<citation-url>";

var credential = new DefaultAzureCredential();
AccessToken token = await credential.GetTokenAsync(
    new TokenRequestContext(
        new[] { "https://search.azure.com/.default" }));

using var httpClient = new HttpClient();
httpClient.DefaultRequestHeaders.Authorization =
    new AuthenticationHeaderValue("Bearer", token.Token);

string document = await httpClient.GetStringAsync(citationUrl);
Console.WriteLine(document);

Reference：DefaultAzureCredential

import json
from urllib.request import Request, urlopen

from azure.identity import DefaultAzureCredential

# citation_url comes from a retrieve response
citation_url = "<citation-url>"

credential = DefaultAzureCredential()
token = credential.get_token("https://search.azure.com/.default")
document_request = Request(
    citation_url,
    headers={"Authorization": f"Bearer {token.token}"},
)
with urlopen(document_request) as response:
    document = json.load(response)

print(json.dumps(document, indent=2))

Reference：DefaultAzureCredential

GET {{citation-url}}
Authorization: Bearer {{search-access-token}}

参考：文档 - 获取

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

var kbClient = new KnowledgeBaseRetrievalClient(
    new Uri("<search-endpoint>"),
    "<knowledge-base-name>",
    new DefaultAzureCredential()
);

var retrievalRequest = new KnowledgeBaseRetrievalRequest();
retrievalRequest.Messages.Add(
    new KnowledgeBaseMessage(
        content: new[]
        {
            new KnowledgeBaseMessageTextContent(
                "Which policy applies to returns?"
            )
        }
    ) { Role = "user" }
);
retrievalRequest.IncludeActivity = true;
retrievalRequest.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams(
        "<knowledge-source-name>"
    )
    {
        ResultsProcessing = KnowledgeSourceResultsProcessing.None
    }
);

var result = await kbClient.RetrieveAsync(retrievalRequest);
foreach (var activity in result.Value.Activity)
{
    KnowledgeBaseActivityRecordModel? model = activity switch
    {
        KnowledgeBaseModelQueryPlanningActivityRecord queryPlanning =>
            queryPlanning.Model,
        KnowledgeBaseModelAnswerSynthesisActivityRecord answerSynthesis =>
            answerSynthesis.Model,
        KnowledgeBaseModelWebSummarizationActivityRecord webSummarization =>
            webSummarization.Model,
        _ => null
    };

    if (model is not null)
    {
        Console.WriteLine(
            $"modelName={model.ModelName}, deploymentId={model.DeploymentId}");
    }
}

参考：KnowledgeBaseRetrievalClient、 KnowledgeBaseRetrievalRequest

from azure.identity import DefaultAzureCredential
from azure.search.documents.knowledgebases import (
    KnowledgeBaseRetrievalClient,
)
from azure.search.documents.knowledgebases.models import (
    KnowledgeBaseMessage,
    KnowledgeBaseMessageTextContent,
    KnowledgeBaseModelAnswerSynthesisActivityRecord,
    KnowledgeBaseModelQueryPlanningActivityRecord,
    KnowledgeBaseModelWebSummarizationActivityRecord,
    KnowledgeBaseRetrievalRequest,
    SearchIndexKnowledgeSourceParams,
)

kb_client = KnowledgeBaseRetrievalClient(
    "<search-endpoint>",
    DefaultAzureCredential(),
    knowledge_base_name="<knowledge-base-name>",
)

model_activity_types = (
    KnowledgeBaseModelQueryPlanningActivityRecord,
    KnowledgeBaseModelAnswerSynthesisActivityRecord,
    KnowledgeBaseModelWebSummarizationActivityRecord,
)

request = KnowledgeBaseRetrievalRequest(
    messages=[
        KnowledgeBaseMessage(
            role="user",
            content=[
                KnowledgeBaseMessageTextContent(
                    text="Which policy applies to returns?"
                )
            ],
        )
    ],
    include_activity=True,
    knowledge_source_params=[
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="<knowledge-source-name>",
            results_processing="none",
        )
    ],
)

result = kb_client.retrieve(request)
for entry in result.activity or []:
    if isinstance(entry, model_activity_types) and entry.model:
        print(
            "modelName=", entry.model.model_name,
            "deploymentId=", entry.model.deployment_id,
        )

参考：KnowledgeBaseRetrievalClient、 KnowledgeBaseRetrievalRequest

POST {{search-endpoint}}/knowledgebases/{{knowledge-base-name}}/retrieve?api-version=2026-08-01-preview
Authorization: Bearer {{search-access-token}}
Content-Type: application/json

{
    "messages": [
        {
            "role": "user",
            "content": [
                { "type": "text", "text": "Which policy applies to returns?" }
            ]
        }
    ],
    "includeActivity": true,
    "knowledgeSourceParams": [
        {
            "knowledgeSourceName": "{{knowledge-source-name}}",
            "kind": "searchIndex",
            "resultsProcessing": "none"
        }
    ]
}

参考：知识检索 - 检索

var retrievalRequest = new KnowledgeBaseRetrievalRequest();
retrievalRequest.Messages.Add(
    new KnowledgeBaseMessage(
        content: new[] {
            new KnowledgeBaseMessageTextContent("Which HR policy applies?")
        }
    ) { Role = "user" }
);
retrievalRequest.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams("hr-policy-ks")
    {
        FailOnError = true,
        AlwaysQuerySource = true
    }
);
retrievalRequest.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams("hr-faq-ks")
);

var result = await kbClient.RetrieveAsync(retrievalRequest);

参考：SearchIndexKnowledgeSourceParams

request = KnowledgeBaseRetrievalRequest(
    messages=[
        KnowledgeBaseMessage(
            role="user",
            content=[KnowledgeBaseMessageTextContent(text="Which HR policy applies?")],
        )
    ],
    knowledge_source_params=[
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="hr-policy-ks",
            fail_on_error=True,
            always_query_source=True,
        ),
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="hr-faq-ks",
        ),
    ],
)

result = kb_client.retrieve(request)

参考：SearchIndexKnowledgeSourceParams

POST {{search-endpoint}}/knowledgebases/{{knowledge-base-name}}/retrieve?api-version=2026-08-01-preview
Authorization: Bearer {{search-access-token}}
Content-Type: application/json

{
    "messages": [
        {
            "role": "user",
            "content": [
                { "type": "text", "text": "Which HR policy applies?" }
            ]
        }
    ],
    "knowledgeSourceParams": [
        {
            "knowledgeSourceName": "hr-policy-ks",
            "kind": "searchIndex",
            "failOnError": true,
            "alwaysQuerySource": true
        },
        {
            "knowledgeSourceName": "hr-faq-ks",
            "kind": "searchIndex"
        }
    ]
}

参考：知识检索 - 检索

var retrievalRequest = new KnowledgeBaseRetrievalRequest();
retrievalRequest.Messages.Add(
    new KnowledgeBaseMessage(
        content: new[] {
            new KnowledgeBaseMessageTextContent(
                "Explain the official SSO provisioning steps.")
        }
    ) { Role = "user" }
);
retrievalRequest.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams("product-docs-ks")
);
retrievalRequest.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams("troubleshooting-ks")
    {
        NeverQuerySource = true
    }
);

var result = await kbClient.RetrieveAsync(retrievalRequest);

参考：SearchIndexKnowledgeSourceParams

request = KnowledgeBaseRetrievalRequest(
    messages=[
        KnowledgeBaseMessage(
            role="user",
            content=[
                KnowledgeBaseMessageTextContent(
                    text="Explain the official SSO provisioning steps."
                )
            ],
        )
    ],
    knowledge_source_params=[
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="product-docs-ks",
        ),
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="troubleshooting-ks",
            never_query_source=True,
        ),
    ],
)

result = kb_client.retrieve(request)

参考：SearchIndexKnowledgeSourceParams

POST {{search-endpoint}}/knowledgebases/{{knowledge-base-name}}/retrieve?api-version=2026-08-01-preview
Authorization: Bearer {{search-access-token}}
Content-Type: application/json

{
    "messages": [
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Explain the official SSO provisioning steps."
                }
            ]
        }
    ],
    "knowledgeSourceParams": [
        {
            "knowledgeSourceName": "product-docs-ks",
            "kind": "searchIndex"
        },
        {
            "knowledgeSourceName": "troubleshooting-ks",
            "kind": "searchIndex",
            "neverQuerySource": true
        }
    ]
}

参考：知识检索 - 检索

var retrievalRequest = new KnowledgeBaseRetrievalRequest();
retrievalRequest.Messages.Add(
    new KnowledgeBaseMessage(
        content: new[] {
            new KnowledgeBaseMessageTextContent("What safety procedures apply?")
        }
    ) { Role = "user" }
);
retrievalRequest.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams("operations-ks")
    {
        MaxOutputDocuments = 50
    }
);

var result = await kbClient.RetrieveAsync(retrievalRequest);

参考：SearchIndexKnowledgeSourceParams

request = KnowledgeBaseRetrievalRequest(
    messages=[
        KnowledgeBaseMessage(
            role="user",
            content=[KnowledgeBaseMessageTextContent(text="What safety procedures apply?")],
        )
    ],
    knowledge_source_params=[
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="operations-ks",
            max_output_documents=50,
        ),
    ],
)

result = kb_client.retrieve(request)

参考：SearchIndexKnowledgeSourceParams

POST {{search-endpoint}}/knowledgebases/operations-kb/retrieve?api-version=2026-08-01-preview
Authorization: Bearer {{search-access-token}}
Content-Type: application/json

{
    "messages": [
        {
            "role": "user",
            "content": [
                { "type": "text", "text": "What safety procedures apply?" }
            ]
        }
    ],
    "knowledgeSourceParams": [
        {
            "knowledgeSourceName": "operations-ks",
            "kind": "searchIndex",
            "maxOutputDocuments": 50
        }
    ]
}

参考：知识检索 - 检索

var retrievalRequest = new KnowledgeBaseRetrievalRequest();
retrievalRequest.Messages.Add(
    new KnowledgeBaseMessage(
        content: new[] {
            new KnowledgeBaseMessageTextContent("What is the return policy?")
        }
    ) { Role = "user" }
);
retrievalRequest.OutputMode = "extractedData";
retrievalRequest.MaxOutputDocuments = 3;
retrievalRequest.MaxOutputSizeInTokens = 6000;

var result = await kbClient.RetrieveAsync(retrievalRequest);

参考：KnowledgeBaseRetrievalRequest

request = KnowledgeBaseRetrievalRequest(
    messages=[
        KnowledgeBaseMessage(
            role="user",
            content=[KnowledgeBaseMessageTextContent(text="What is the return policy?")],
        )
    ],
    output_mode="extractedData",
    max_output_documents=3,
    max_output_size_in_tokens=6000,
)

result = kb_client.retrieve(request)

参考：KnowledgeBaseRetrievalRequest

POST {{search-endpoint}}/knowledgebases/{{knowledge-base-name}}/retrieve?api-version=2026-08-01-preview
Authorization: Bearer {{search-access-token}}
Content-Type: application/json

{
    "messages": [
        {
            "role": "user",
            "content": [
                { "type": "text", "text": "What is the return policy?" }
            ]
        }
    ],
    "outputMode": "extractedData",
    "maxOutputDocuments": 3,
    "maxOutputSizeInTokens": 6000
}

参考：知识检索 - 检索

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

string searchEndpoint = "<search-endpoint>";

var options = new SearchClientOptions(
    SearchClientOptions.ServiceVersion.V2026_08_01_Preview);
var kbClient = new KnowledgeBaseRetrievalClient(
    new Uri(searchEndpoint),
    "your-knowledge-base",
    new DefaultAzureCredential(),
    options);

KnowledgeBaseRetrievalRequest CreateRequest()
{
    var request = new KnowledgeBaseRetrievalRequest();
    request.Intents.Add(new KnowledgeRetrievalSemanticIntent(
        "Summarize the latest support guidance."));
    return request;
}

var inherited = await kbClient.RetrieveAsync(CreateRequest());
Console.WriteLine(
    $"Stored defaults: {inherited.Value.References.Count} references");

KnowledgeBaseRetrievalRequest overriddenRequest = CreateRequest();
overriddenRequest.MaxRuntimeInSeconds = 20;
overriddenRequest.MaxOutputDocuments = 1;
overriddenRequest.MaxOutputSize = 5000;

var overridden = await kbClient.RetrieveAsync(overriddenRequest);
Console.WriteLine(
    $"Request overrides: {overridden.Value.References.Count} references");

参考：KnowledgeBaseRetrievalClient、 KnowledgeBaseRetrievalRequest

from azure.identity import DefaultAzureCredential
from azure.search.documents.knowledgebases import KnowledgeBaseRetrievalClient
from azure.search.documents.knowledgebases.models import (
    KnowledgeBaseRetrievalRequest,
    KnowledgeRetrievalSemanticIntent,
)

kb_client = KnowledgeBaseRetrievalClient(
    endpoint="<search-endpoint>",
    knowledge_base_name="your-knowledge-base",
    credential=DefaultAzureCredential(),
    api_version="2026-08-01-preview",
)


def create_request(**limits):
    return KnowledgeBaseRetrievalRequest(
        intents=[
            KnowledgeRetrievalSemanticIntent(
                search="Summarize the latest support guidance.",
            )
        ],
        **limits,
    )


inherited = kb_client.retrieve(create_request())
print(f"Stored defaults: {len(inherited.references or [])} references")

overridden = kb_client.retrieve(
    create_request(
        max_runtime_in_seconds=20,
        max_output_documents=1,
        max_output_size=5000,
    )
)
print(f"Request overrides: {len(overridden.references or [])} references")

参考：KnowledgeBaseRetrievalClient、 KnowledgeBaseRetrievalRequest

首先，发送省略三个请求范围限制字段的请求。

POST {{search-endpoint}}/knowledgebases/your-knowledge-base/retrieve?api-version=2026-08-01-preview
Content-Type: application/json
Authorization: Bearer {{search-access-token}}

{
  "intents": [
    {
      "type": "semantic",
      "search": "Summarize the latest support guidance."
    }
  ]
}

接下来，针对一次请求覆盖这三个值。

POST {{search-endpoint}}/knowledgebases/your-knowledge-base/retrieve?api-version=2026-08-01-preview
Content-Type: application/json
Authorization: Bearer {{search-access-token}}

{
  "intents": [
    {
      "type": "semantic",
      "search": "Summarize the latest support guidance."
    }
  ],
  "maxRuntimeInSeconds": 20,
  "maxOutputDocuments": 1,
  "maxOutputSize": 5000
}

参考：知识检索 - 检索

var retrievalRequest = new KnowledgeBaseRetrievalRequest();
retrievalRequest.Messages.Add(
    new KnowledgeBaseMessage(
        content: new[] {
            new KnowledgeBaseMessageTextContent("What companies are in the financial sector?")
        }
    ) { Role = "user" }
);
retrievalRequest.RetrievalReasoningEffort = new KnowledgeRetrievalLowReasoningEffort();
retrievalRequest.OutputMode = "answerSynthesis";
retrievalRequest.MaxRuntimeInSeconds = 30;
retrievalRequest.MaxOutputSizeInTokens = 6000;

var result = await kbClient.RetrieveAsync(retrievalRequest);
Console.WriteLine(
    (result.Value.Response[0].Content[0] as KnowledgeBaseMessageTextContent)!.Text
);

参考：KnowledgeBaseRetrievalClient、 KnowledgeBaseRetrievalRequest

from azure.search.documents.knowledgebases.models import (
    KnowledgeRetrievalLowReasoningEffort,
    KnowledgeRetrievalOutputMode,
)

request = KnowledgeBaseRetrievalRequest(
    messages=[
        KnowledgeBaseMessage(
            role="user",
            content=[KnowledgeBaseMessageTextContent(text="What companies are in the financial sector?")],
        )
    ],
    retrieval_reasoning_effort=KnowledgeRetrievalLowReasoningEffort(),
    output_mode=KnowledgeRetrievalOutputMode.ANSWER_SYNTHESIS,
    max_runtime_in_seconds=30,
    max_output_size_in_tokens=6000,
)

result = kb_client.retrieve(request)
print(result.response[0].content[0].text)

参考：KnowledgeBaseRetrievalClient、 KnowledgeBaseRetrievalRequest

POST {{search-endpoint}}/knowledgebases/kb-override/retrieve?api-version=2026-08-01-preview
Authorization: Bearer {{search-access-token}}
Content-Type: application/json

{
    "messages": [
        {
            "role": "user",
            "content": [
                { "type": "text", "text": "What companies are in the financial sector?" }
            ]
        }
    ],
    "retrievalReasoningEffort": { "kind": "low" },
    "outputMode": "answerSynthesis",
    "maxRuntimeInSeconds": 30,
    "maxOutputSizeInTokens": 6000
}

参考：知识检索 - 检索

var retrievalRequest = new KnowledgeBaseRetrievalRequest();
retrievalRequest.Messages.Add(
    new KnowledgeBaseMessage(
        content: new[] {
            new KnowledgeBaseMessageTextContent("What companies are in the financial sector?")
        }
    ) { Role = "user" }
);
retrievalRequest.IncludeActivity = true;
retrievalRequest.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams("demo-financials-ks")
    {
        IncludeReferences = true,
        IncludeReferenceSourceData = true
    }
);

retrievalRequest.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams("demo-communicationservices-ks")
    {
        IncludeReferences = false,
        IncludeReferenceSourceData = false
    }
);

retrievalRequest.KnowledgeSourceParams.Add(
    new SearchIndexKnowledgeSourceParams("demo-healthcare-ks")
    {
        IncludeReferences = true,
        IncludeReferenceSourceData = false,
        AlwaysQuerySource = true
    }
);

var result = await kbClient.RetrieveAsync(retrievalRequest);
Console.WriteLine(
    (result.Value.Response[0].Content[0] as KnowledgeBaseMessageTextContent)!.Text
);

参考：KnowledgeBaseRetrievalClient、 KnowledgeBaseRetrievalRequest

from azure.search.documents.knowledgebases.models import SearchIndexKnowledgeSourceParams

request = KnowledgeBaseRetrievalRequest(
    messages=[
        KnowledgeBaseMessage(
            role="user",
            content=[KnowledgeBaseMessageTextContent(text="What companies are in the financial sector?")],
        )
    ],
    include_activity=True,
    knowledge_source_params=[
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="demo-financials-ks",
            include_references=True,
            include_reference_source_data=True,
        ),
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="demo-communicationservices-ks",
            include_references=False,
            include_reference_source_data=False,
        ),
        SearchIndexKnowledgeSourceParams(
            knowledge_source_name="demo-healthcare-ks",
            include_references=True,
            include_reference_source_data=False,
            always_query_source=True,
        ),
    ],
)

result = kb_client.retrieve(request)
print(result.response[0].content[0].text)

参考：KnowledgeBaseRetrievalClient、 SearchIndexKnowledgeSourceParams

POST {{search-endpoint}}/knowledgebases/kb-medium-example/retrieve?api-version=2026-08-01-preview
Authorization: Bearer {{search-access-token}}
Content-Type: application/json

{
    "messages": [
        {
            "role": "user",
            "content": [
                { "type": "text", "text": "What companies are in the financial sector?" }
            ]
        }
    ],
    "includeActivity": true,
    "knowledgeSourceParams": [
        {
            "knowledgeSourceName": "demo-financials-ks",
            "kind": "searchIndex",
            "includeReferences": true,
            "includeReferenceSourceData": true
        },
        {
            "knowledgeSourceName": "demo-communicationservices-ks",
            "kind": "searchIndex",
            "includeReferences": false,
            "includeReferenceSourceData": false
        },
        {
            "knowledgeSourceName": "demo-healthcare-ks",
            "kind": "searchIndex",
            "includeReferences": true,
            "includeReferenceSourceData": false,
            "alwaysQuerySource": true
        }
    ]
}

参考：知识检索 - 检索

var retrievalRequest = new KnowledgeBaseRetrievalRequest();
retrievalRequest.Intents.Add(
    new KnowledgeRetrievalSemanticIntent("what is a brokerage")
);

var result = await kbClient.RetrieveAsync(retrievalRequest);
Console.WriteLine(
    (result.Value.Response[0].Content[0] as KnowledgeBaseMessageTextContent)!.Text
);

参考：KnowledgeBaseRetrievalClient、 KnowledgeBaseRetrievalRequest

from azure.search.documents.knowledgebases.models import (
    KnowledgeBaseRetrievalRequest,
    KnowledgeRetrievalSemanticIntent,
)

request = KnowledgeBaseRetrievalRequest(
    intents=[
        KnowledgeRetrievalSemanticIntent(
            search="what is a brokerage",
        )
    ]
)

result = kb_client.retrieve(request)
print(result.response[0].content[0].text)

参考：KnowledgeBaseRetrievalClient、 KnowledgeBaseRetrievalRequest

POST {{search-endpoint}}/knowledgebases/kb-minimal/retrieve?api-version=2026-08-01-preview
Authorization: Bearer {{search-access-token}}
Content-Type: application/json

{
    "intents": [
        {
            "type": "semantic",
            "search": "what is a brokerage"
        }
    ]
}

参考：知识检索 - 检索

#pragma warning disable OPENAI001

using Azure.AI.OpenAI;
using Azure.Core;
using Azure.Identity;
using OpenAI.Responses;
using System;
using System.Collections.Generic;

string openAiEndpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")!; // Example: https://<resource-name>.openai.azure.com
string mcpServerUrl = Environment.GetEnvironmentVariable("AZURE_SEARCH_MCP_ENDPOINT")!; // Example: https://<search-service-name>.search.windows.net/knowledgebases/<knowledge-base-name>/mcp?api-version=<api-version>
DefaultAzureCredential credential = new();

// Create the Azure OpenAI Responses client
AzureOpenAIClient azureClient = new(new Uri(openAiEndpoint), credential);
ResponsesClient openAIClient = azureClient.GetResponsesClient();

// Get a bearer token for Azure AI Search
string searchToken = credential.GetToken(
    new TokenRequestContext(new[] { "https://search.azure.com/.default" })
).Token;

// Configure the MCP tool for knowledge base retrieval
McpTool mcpTool = ResponseTool.CreateMcpTool(
    serverLabel: "search_kb",
    serverUri: new Uri(mcpServerUrl),
    headers: new Dictionary<string, string>
    {
        ["Authorization"] = $"Bearer {searchToken}",
    },
    allowedTools: new McpToolFilter { ToolNames = { "knowledge_base_retrieve" } },
    toolCallApprovalPolicy: new McpToolCallApprovalPolicy(
        GlobalMcpToolCallApprovalPolicy.NeverRequireApproval)
);

// Build the response request with the MCP tool attached
CreateResponseOptions options = new()
{
    Model = "MODEL_NAME",
    InputItems =
    {
        ResponseItem.CreateUserMessageItem(
            "What causes the strongest nighttime brightness patterns in this dataset?")
    },
    Tools = { mcpTool }
};

ResponseResult response = await openAIClient.CreateResponseAsync(options);
Console.WriteLine(response.GetOutputText());

参考：使用 Azure OpenAI 响应 API

import os
from azure.identity import DefaultAzureCredential, get_bearer_token_provider
from openai import AzureOpenAI

openai_endpoint = os.environ["AZURE_OPENAI_ENDPOINT"] # Example: https://<resource-name>.openai.azure.com
mcp_server_url = os.environ["AZURE_SEARCH_MCP_ENDPOINT"] # Example: https://<search-service-name>.search.windows.net/knowledgebases/<knowledge-base-name>/mcp?api-version=<api-version>
credential = DefaultAzureCredential()

# Create token providers for Azure OpenAI and Azure AI Search
openai_token_provider = get_bearer_token_provider(
    credential, "https://cognitiveservices.azure.com/.default"
)
search_token_provider = get_bearer_token_provider(
    credential, "https://search.azure.com/.default"
)

# Create the Azure OpenAI client
client = AzureOpenAI(
    azure_endpoint=openai_endpoint,
    azure_ad_token_provider=openai_token_provider,
    api_version=os.environ["OPENAI_API_VERSION"], # Example: 2025-04-01-preview
)

# Create a response using the MCP tool configuration
response = client.responses.create(
    model="MODEL_NAME",
    input="What causes the strongest nighttime brightness patterns in this dataset?",
    tools=[
        {
            "type": "mcp",
            "server_label": "search_kb",
            "server_url": mcp_server_url,
            "allowed_tools": ["knowledge_base_retrieve"],
            "headers": {
                "Authorization": f"Bearer {search_token_provider()}"
            },
            "require_approval": "never",
        }
    ],
)

print(response.output_text)

参考：使用 Azure OpenAI 响应 API

// This code snippet is currently unavailable.

#pragma warning disable OPENAI001

using OpenAI.Responses;
using System;
using System.Collections.Generic;

string mcpServerUrl = Environment.GetEnvironmentVariable("AZURE_SEARCH_MCP_ENDPOINT")!; // Example: https://<search-service-name>.search.windows.net/knowledgebases/<knowledge-base-name>/mcp?api-version=<api-version>
string searchAdminKey = Environment.GetEnvironmentVariable("AZURE_SEARCH_ADMIN_KEY")!; // Example: <search-api-key>

McpTool mcpTool = ResponseTool.CreateMcpTool(
    serverLabel: "search_kb",
    serverUri: new Uri(mcpServerUrl),
    headers: new Dictionary<string, string> { ["api-key"] = searchAdminKey },
    allowedTools: new McpToolFilter { ToolNames = { "knowledge_base_retrieve" } },
    toolCallApprovalPolicy: new McpToolCallApprovalPolicy(
        GlobalMcpToolCallApprovalPolicy.NeverRequireApproval)
);

参考：使用 Azure OpenAI 响应 API

import os

mcp_server_url = os.environ["AZURE_SEARCH_MCP_ENDPOINT"] # Example: https://<search-service-name>.search.windows.net/knowledgebases/<knowledge-base-name>/mcp?api-version=<api-version>
search_admin_key = os.environ["AZURE_SEARCH_ADMIN_KEY"] # Example: <search-api-key>

tools = [
    {
        "type": "mcp",
        "server_label": "search_kb",
        "server_url": mcp_server_url,
        "allowed_tools": ["knowledge_base_retrieve"],
        "headers": {"api-key": search_admin_key},
        "require_approval": "never",
    }
]

参考：使用 Azure OpenAI 响应 API

// This code snippet is currently unavailable.