共用方式為

快速入門：向量搜尋

在本快速入門中，您會使用 Jupyter Notebook 來建立、載入和查詢向量。 程式代碼範例會使用 Azure AI 搜尋服務客戶端連結庫來執行這些作業。 程式庫提供 REST API 的抽象層，用於存取索引作業，例如資料匯入、搜尋操作和索引管理。

在 Azure AI 搜尋服務中，「向量存放區」具有定義向量和非向量欄位的索引結構描述、建立內嵌空間之演算法的向量搜尋設定，以及向量欄位定義上可於查詢時間進行評估的設定。 建立索引 REST API 會建立向量存放區。

附註

本快速入門省略向量化步驟，並提供內置內嵌。 如果您想要將 內建數據區塊化和向量化 新增至您自己的內容，請嘗試 匯入並向量化數據精靈 ，以完成端到端指南。

必要條件

擷取資源資訊

對搜尋端點發出的要求必須經過驗證和授權。 雖然此工作可以使用 API 金鑰或角色，但建議您 透過 Microsoft Entra ID 使用無密鑰連線。

本快速入門使用 DefaultAzureCredential，可簡化開發和生產案例中的驗證。 不過，針對生產案例，您可能有更進階的需求，需要不同的方法。 請參閱 使用適用於 Python 的 Azure SDK 向 Azure 服務驗證 Python 應用程式 ，以瞭解所有選項。

複製程式代碼和設定環境

  1. 複製包含本快速入門程式代碼的存放庫。

    git clone https://github.com/Azure-Samples/azure-search-python-samples

    這個倉庫包含了幾篇文章的 Python 程式代碼範例，每篇文章位於不同的子資料夾中。

  2. 在 Visual Studio Code 中，開啟子資料夾 Quickstart-Vector-Search。

    此資料夾中有三個檔案：

    • vector-search-quickstart.ipynb
    • requirements.txt
    • sample.env

  3. 將 sample.env 檔案重新命名為 .env ，並修改檔案中的 .env 值。

    使用搜尋服務 URL 作為 AZURE_SEARCH_ENDPOINT。 您可以在 Azure 入口網站中找到 URL。 移至您的 Azure AI 搜尋服務，在 總覽 頁面上尋找 URL 欄位。 範例端點看起來會像是 https://mydemo.search.windows.net。

    最後，選擇新的 AZURE_SEARCH_INDEX_NAME 名稱，或使用檔案中提供的名稱。

  4. 在 Visual Studio Code 中，在環境中工作。 在 [ 檢視] 功能表上，選取 [ 終端機...]，或選取 Ctrl+`。

  5. 在終端機執行下列命令：

    python -m venv .venv
source .venv/scripts/activate
where python

    附註

    這假設您在終端機中使用 Git Bash，且是在 Windows 上執行。 如果您使用不同的殼層和/或不同的作系統，請針對您的特定環境調整這些指示。

    如果出現提示，請允許 Visual Studio Code 使用新的環境。

    where python 命令會透過列出 Quickstart-Vector-Search\.venv\ 資料夾的 python.exe 以及機器目錄的其他位置，來驗證您是從虛擬環境作業。

  6. 執行下列命令來安裝必要的庫：

    pip install requirements.txt

  7. 在 Visual Studio Code 中，開啟 vector-search-quickstart.ipynb。

    附註

    如果這是您第一次在 Visual Studio Code 中使用 Jupyter Notebook （.ipynb），系統會提示您安裝 Jupyter Notebook 核心，並可能安裝其他工具。 選擇安裝建議的工具，以繼續進行本快速入門。

  8. 尋找標題為 [安裝套件並設定變數] 的下一節，然後選取單元格左側的 [執行單元格] 按鈕 [Ctrl + Alt + Enter] 按鈕（ 看起來像一般執行按鈕）。 執行儲存格會載入環境變數、建立 DefaultAzureCredential，並將值列印到輸出中，以確認筆記本的相依性與 .env 已正確設定。

    # Load environment variables from .env file
# Rename the samples.env to .env and fill in the values
from azure.identity import DefaultAzureCredential
from dotenv import load_dotenv
import os

load_dotenv(override=True) # take environment variables from .env.

search_endpoint = os.environ["AZURE_SEARCH_ENDPOINT"]
credential = DefaultAzureCredential()
index_name = os.getenv("AZURE_SEARCH_INDEX", "vector-search-quickstart")

print(f"Using Azure Search endpoint: {search_endpoint}")
print(f"Using Azure Search index: {index_name}")
!pip list

    執行此儲存格會產生下列輸出。

    Using Azure Search endpoint: https://<search-service-name>.search.windows.net
Using Azure Search index: <vector-index-name>
Package                 Version
----------------------- -----------
aiohappyeyeballs        2.6.1
aiohttp                 3.12.13
aiosignal               1.3.2
asttokens               3.0.0
attrs                   25.3.0
azure-ai-agents         1.0.0
azure-ai-projects       1.0.0b11
azure-common            1.1.28
azure-core              1.34.0
azure-identity          1.23.0
azure-search-documents  11.6.0b12
azure-storage-blob      12.25.1
...

    您可以在可捲動的元素中檢視更多套件（請參閱儲存格結果下方的訊息）。

建立向量索引

vector-search-quickstart.ipynb中的程式碼使用azure.search.documents程式庫中的幾種方法來建立向量索引和可搜尋的欄位。

  1. 尋找標題為「建立索引」的下一節單元格，然後執行單元格來建立索引。

    from azure.search.documents.indexes import SearchIndexClient
from azure.search.documents import SearchClient
from azure.search.documents.models import VectorizedQuery
from azure.search.documents.indexes.models import (
    SimpleField,
    ComplexField,
    SearchField,
    SearchFieldDataType,    
    SearchableField,
    SearchIndex,
    SemanticConfiguration,
    SemanticField,
    SemanticPrioritizedFields,
    SemanticSearch,
    VectorSearch, 
    VectorSearchProfile,
    HnswAlgorithmConfiguration,
    ExhaustiveKnnAlgorithmConfiguration    
)

# Create a search schema
index_client = SearchIndexClient(
    endpoint=search_endpoint, credential=credential)
fields = [
    SimpleField(name="HotelId", type=SearchFieldDataType.String, key=True, filterable=True),
    SearchableField(name="HotelName", type=SearchFieldDataType.String, sortable=True),
    SearchableField(name="Description", type=SearchFieldDataType.String),
    SearchField(
        name="DescriptionVector",
        type=SearchFieldDataType.Collection(SearchFieldDataType.Single),
        searchable=True,
        vector_search_dimensions=1536,
        vector_search_profile_name="my-vector-profile"
    ),
    SearchableField(name="Category", type=SearchFieldDataType.String, sortable=True, filterable=True, facetable=True),
    SearchField(name="Tags", type=SearchFieldDataType.Collection(SearchFieldDataType.String), searchable=True, filterable=True, facetable=True),
    SimpleField(name="ParkingIncluded", type=SearchFieldDataType.Boolean, filterable=True, sortable=True, facetable=True),
    SimpleField(name="LastRenovationDate", type=SearchFieldDataType.DateTimeOffset, filterable=True, sortable=True, facetable=True),
    SimpleField(name="Rating", type=SearchFieldDataType.Double, filterable=True, sortable=True, facetable=True),
    ComplexField(name="Address", fields=[
        SearchableField(name="StreetAddress", type=SearchFieldDataType.String),
        SearchableField(name="City", type=SearchFieldDataType.String, filterable=True, sortable=True, facetable=True),
        SearchableField(name="StateProvince", type=SearchFieldDataType.String, filterable=True, sortable=True, facetable=True),
        SearchableField(name="PostalCode", type=SearchFieldDataType.String, filterable=True, sortable=True, facetable=True),
        SearchableField(name="Country", type=SearchFieldDataType.String, filterable=True, sortable=True, facetable=True),
    ]),
    SimpleField(name="Location", type=SearchFieldDataType.GeographyPoint, filterable=True, sortable=True),
]

vector_search = VectorSearch(
        algorithms=[
            HnswAlgorithmConfiguration(name="my-hnsw-vector-config-1", kind="hnsw"),
            ExhaustiveKnnAlgorithmConfiguration(name="my-eknn-vector-config", kind="exhaustiveKnn")
        ],
        profiles=[
            VectorSearchProfile(name="my-vector-profile", algorithm_configuration_name="my-hnsw-vector-config-1")
        ]
    )

semantic_config = SemanticConfiguration(
        name="my-semantic-config",
        prioritized_fields=SemanticPrioritizedFields(
           title_field=SemanticField(field_name="HotelName"), 
           content_fields=[SemanticField(field_name="Description")], 
           keywords_fields=[SemanticField(field_name="Category")]
        )
    )

# Create the semantic settings with the configuration
semantic_search = SemanticSearch(configurations=[semantic_config])

semantic_settings = SemanticSearch(configurations=[semantic_config])
scoring_profiles = []
suggester = [{'name': 'sg', 'source_fields': ['Tags', 'Address/City', 'Address/Country']}]

# Create the search index with the semantic settings
index = SearchIndex(name=index_name, fields=fields, vector_search=vector_search, semantic_search=semantic_search)
result = index_client.create_or_update_index(index)
print(f' {result.name} created')

    如果已成功建立索引，您會在儲存格下方看到下列結果：

    vector-search-quickstart created

    使用 azure.search.documents建立向量索引時的重要重點：

    • 您可以藉由建立欄位清單來定義索引。 每個欄位都是使用定義欄位類型和其設定的協助程式方法所建立。

    • 此特定索引支援多個搜尋功能，例如：

      • 全文關鍵詞檢索（SearchableField(name="HotelName", ...)，SearchableField(name="Description", ...)）
      • 向量搜尋（藉由共置向量和非向量欄位來啟用混合式搜尋）欄位 （DescriptionVector）
      • 語意搜尋 （semantic_search=SemanticSearch(configurations=[semantic_config])）
      • 多面向搜尋 （facetable=True）
      • 語意搜尋 （semantic_search=SemanticSearch(configurations=[semantic_config])）
      • 地理空間搜尋 （Location 欄位為 GeographyPoint）
      • 篩選、排序（許多欄位標示為可篩選和可排序）

上傳文件

建立和載入索引是單獨的步驟。 您在上一個步驟中建立了索引結構描述。 現在您需要將文件載入索引中。

在 Azure AI 搜尋中，索引會儲存所有可搜尋的內容，而搜尋引擎則會針對該索引執行查詢。

  1. 尋找標題為「建立文件承載」的那一節下方的儲存格，然後執行該儲存格。 此儲存格包含下列程式代碼（為了簡潔起見而截斷）：

       # Create a documents payload
   documents = [
       {
           "@search.action": "mergeOrUpload",
           "HotelId": "1",
           "HotelName": "Stay-Kay City Hotel",
           "Description": "This classic hotel is fully-refurbished and ideally located on the main commercial artery of the city in the heart of New York. A few minutes away is Times Square and the historic center of the city, as well as other places of interest that make New York one of America's most attractive and cosmopolitan cities.",
           "DescriptionVector": [-0.048865054,-0.020307425,
           # <truncated>
           -0.018120624,-0.012772904],
           "Category": "Boutique",
           "Tags": [
               "view",
               "air conditioning",
               "concierge"
           ],
           "ParkingIncluded": "false",
           "LastRenovationDate": "2022-01-18T00:00:00Z",
           "Rating": 3.60,
           "Address": {
               "StreetAddress": "677 5th Ave",
               "City": "New York",
               "StateProvince": "NY",
               "PostalCode": "10022",
               "Country": "USA"
           },
           "Location": {
               "type": "Point",
               "coordinates": [
                   -73.975403,
                   40.760586
               ]
           }
       },
       # <truncated>
   ]

    此數據格會載入名為 documents 的變數，其中包含描述每個檔的 JSON 物件，以及發行項描述的向量化版本。 此向量會啟用相似性搜尋，其中比對是以意義而非確切關鍵詞為基礎。

    這很重要

    此範例中的程式代碼無法執行。 為了簡潔起見，會移除數個字元或幾行。 相反地，請在 Jupyter Notebook 中執行程式代碼。

  2. 尋找標題為「上傳文件」的下一節單元格，並執行該單元格。 此儲存格包含下列程式代碼（為了簡潔起見而截斷）：

    # Upload documents to the index
search_client = SearchClient(endpoint=search_endpoint,
                      index_name=index_name,
                      credential=credential)
try:
    result = search_client.upload_documents(documents=documents)
    for r in result:
        print(f"Key: {r.key}, Succeeded: {r.succeeded}, ErrorMessage: {r.error_message}")
except Exception as ex:
    print("Failed to upload documents:", ex)

# Create the index client which will be used later in the query examples
index_client = SearchIndexClient(endpoint=search_endpoint, credential=credential)

    這會藉由呼叫 SearchClient() 建構函式來建立搜尋客戶端的實例，然後在 物件上呼叫 upload_documents() 方法。

    執行儲存格之後，每個文件的狀態會顯示在它下方：

    Key: 1, Succeeded: True, ErrorMessage: None
Key: 2, Succeeded: True, ErrorMessage: None
Key: 3, Succeeded: True, ErrorMessage: None
Key: 4, Succeeded: True, ErrorMessage: None
Key: 48, Succeeded: True, ErrorMessage: None
Key: 49, Succeeded: True, ErrorMessage: None
Key: 13, Succeeded: True, ErrorMessage: None

    upload_documents() 方法與此範例的重要內容：

    • 您的程式代碼會透過 SearchClient，與裝載於 Azure AI 搜尋服務中的特定搜尋索引互動，這是套件所提供的 azure-search-documents 主要物件。 SearchClient提供索引作業的存取權，例如：

      • 數據擷取 - upload_documents()、 merge_documents()、 delete_documents()等
      • 搜尋工作 - search()、 、 autocomplete()suggest()
      • 索引管理作業

    • 向量欄位包含浮點值。 維度屬性至少有 2 個，每個浮點值最多 4096 個。 本快速入門會將維度屬性設定為 1,536，因為這是 Azure OpenAI text-embedding-ada-002 模型所產生的內嵌大小。

執行查詢

現在文件已載入，您可以呼叫 search_client.search() 並傳入 VectorizedQuery 物件、要返回的欄位、結果數量，以及其他相關參數，來對其發出向量查詢。

在下一節中，我們會對 hotels-vector-quickstart 索引執行查詢。 查詢包括：

建立向量查詢字串

範例向量查詢是以兩個字串為基礎：

  • 搜尋字串：historic hotel walk to restaurants and shopping
  • 向量查詢字串 (向量化為數學表示法)：quintessential lodging near running trails, eateries, retail

向量查詢字串在語意上類似於搜尋字串，但包含搜尋索引中不存在的字詞。 如果您對 quintessential lodging near running trails, eateries, retail 執行關鍵詞搜尋，則結果為零。 我們使用此範例示範如何取得相關結果，即使沒有相符的字詞也一樣。

  • 尋找標題為「建立向量查詢字串」的章節下的儲存格，然後執行該儲存格。 這會載入 vector 變數，其中包含執行下一節中所有搜尋所需的向量化查詢數據。

第一個範例示範一個基本案例，其中您想要尋找最符合搜尋字元串的檔描述。

  • 尋找標題為「單一向量搜尋」的那一節下方的單元格，然後執行此單元格。 此區塊包含查詢搜尋索引的要求。

    # IMPORTANT: Before you run this code, make sure the documents were successfully
# created in the previous step. Sometimes it may take a few seconds for the index to be ready.
# Check the "Document count" for the index in the Azure portal.

# Execute vector search
if vector:
     try:
         vector_query = VectorizedQuery(
             vector=vector,
             k_nearest_neighbors=5,
             fields="DescriptionVector",
             kind="vector",
             exhaustive=True
         )

         results = search_client.search(
             vector_queries=[vector_query],
             select=["HotelId", "HotelName", "Description", "Category", "Tags"],
             top=5,
             include_total_count=True
         )

         print(f"Total results: {results.get_count()}")
         for result in results:
             doc = result  # result is a dict-like object
             print(f"- HotelId: {doc['HotelId']}, HotelName: {doc['HotelName']}, Category: {doc.get('Category')}")
     except Exception as ex:
         print("Vector search failed:", ex)
else:
    print("No vector loaded, skipping search.")

    為了簡潔起見，此向量查詢會縮短。 vectorQueries.vector 包含查詢輸入的向量化文字，fields 決定要搜尋的向量欄位，而 k 指定要傳回的最近鄰數目。

    向量查詢字串是 quintessential lodging near running trails, eateries, retail，其會向量化為此查詢的 1,536 個內嵌。

    向量對等的 quintessential lodging near running trails, eateries, retail 回應包含七個結果，但程式代碼會 top=5 指定只傳回前五個結果。 此外，只會傳回 所 select 指定的欄位。

    search_client.search() 會傳回類似字典的物件。 每個結果都會提供搜尋分數，您可以使用 score = result.get("@search.score", "N/A") 來存取。 雖然在此範例中未顯示相似度搜尋，但回應一律會包含 k 依值相似度分數排序的結果。

    執行單元格之後，每個文件的狀態會顯示在其下方：

    Total results: 5
- HotelId: 48, HotelName: Nordick's Valley Motel, Category: Boutique
- HotelId: 13, HotelName: Luxury Lion Resort, Category: Luxury
- HotelId: 4, HotelName: Sublime Palace Hotel, Category: Boutique
- HotelId: 49, HotelName: Swirling Currents Hotel, Category: Suite
- HotelId: 2, HotelName: Old Century Hotel, Category: Boutique

使用篩選的單一向量搜尋

您可以新增篩選，但篩選條件會套用於索引中的非向量內容。 在此範例中，篩選會套用於 Tags 欄位，篩選排除任何不提供免費 Wi-Fi 的旅館。

  1. 尋找標題為「單一向量搜尋與篩選」的下方程式碼區塊，然後執行該區塊。 此儲存格包含查詢搜尋索引的要求。

    if vector:
   try:
       vector_query = VectorizedQuery(
           vector=vector,
           k_nearest_neighbors=5,
           fields="DescriptionVector",
           kind="vector",
           exhaustive=True
       )

       results = search_client.search(
           vector_queries=[vector_query],
           filter="Tags/any(tag: tag eq 'free wifi')",  # <--- NOTICE THE FILTER IS ADDED HERE
           select=["HotelId", "HotelName", "Description", "Category", "Tags"],
           top=7,
           include_total_count=True
       )

       print(f"Total filtered results: {results.get_count()}")
       for result in results:
           doc = result
           print(f"- HotelId: {doc['HotelId']}, HotelName: {doc['HotelName']}, Tags: {doc.get('Tags')}")
   except Exception as ex:
       print("Vector search with filter failed:", ex)
else:
   print("No vector loaded, skipping search.")

    執行儲存格之後，每個文件的狀態會顯示在其下方：

    Total filtered results: 2
- HotelId: 48, HotelName: Nordick's Valley Motel, Tags: ['continental breakfast', 'air conditioning', 'free wifi']
- HotelId: 2, HotelName: Old Century Hotel, Tags: ['pool', 'free wifi', 'air conditioning', 'concierge']

    此查詢與前一個單一向量搜尋範例相同，但包含後置處理的排除篩選，並只傳回具有免費 Wi-Fi 的三家旅館。

  2. 下一個篩選範例會使用 地理篩選。 在標題為「使用地理篩選條件進行向量查詢」的區段中執行儲存格。 此區塊包含查詢搜尋索引的要求。

    if vector:
   try:
      vector_query = VectorizedQuery(
      vector=vector,
      k_nearest_neighbors=5,
      fields="DescriptionVector",
      kind="vector",
      exhaustive=True
   )

   results = search_client.search(
      include_total_count=True,
      top=5,
      select=[
          "HotelId", "HotelName", "Category", "Description", "Address/City", "Address/StateProvince"
      ],
      facets=["Address/StateProvince"],
      filter="geo.distance(Location, geography'POINT(-77.03241 38.90166)') le 300",
      vector_filter_mode="postFilter",
      vector_queries=[vector_query]
   )

   print(f"Total semantic hybrid results: {results.get_count()}")
   for result in results:
      doc = result
      score = result.get("@search.score", "N/A")
      print(f"- HotelId: {doc['HotelId']}")
      print(f"  HotelName: {doc['HotelName']}")
      print(f"  Score: {score}")
      print(f"  City/State: {doc['Address']['City']}, {doc['Address']['StateProvince']}")
      print(f"  Description: {doc.get('Description')}\n")

   except Exception as ex:
      print("Semantic hybrid search failed:", ex)
else:
   print("No vector loaded, skipping search.")

    查詢與先前 的單一向量搜尋範例相同，但它包含後置處理排除篩選條件，而且只會傳回 300 公里內的兩家酒店。

    Total semantic hybrid results: 2
- HotelId: 48
  HotelName: Nordick's Valley Motel
  Score: 0.6605852246284485
  City/State: Washington D.C., null
  Description: Only 90 miles (about 2 hours) from the nation's capital and nearby most everything the historic valley has to offer. Hiking? Wine Tasting? Exploring the caverns? It's all nearby and we have specially priced packages to help make our B&B your home base for fun while visiting the valley.

- HotelId: 49
  HotelName: Swirling Currents Hotel
  Score: 0.602634072303772
  City/State: Arlington, VA
  Description: Spacious rooms, glamorous suites and residences, rooftop pool, walking access to shopping, dining, entertainment and the city center. Each room comes equipped with a microwave, a coffee maker and a minifridge. In-room entertainment includes complimentary Wi-Fi and flat-screen TVs.

混合式搜尋是由單一搜尋要求中的關鍵字查詢和向量查詢所組成。 此範例會同時執行向量查詢和全文搜索：

  • 搜尋字串：historic hotel walk to restaurants and shopping

  • 向量查詢字串 (向量化為數學表示法)：quintessential lodging near running trails, eateries, retail

  • 尋找標題為「混合式搜尋」的下一節單元格，然後執行單元格。 此區塊包含查詢搜尋索引的要求。

    if vector:
     try:
         vector_query = VectorizedQuery(
             vector=vector,
             k_nearest_neighbors=5,
             fields="DescriptionVector",
             kind="vector",
             exhaustive=True
         )

         results = search_client.search(
             include_total_count=True,
             search_text="historic hotel walk to restaurants and shopping",  # keyword part
             select=["HotelId", "HotelName", "Description", "Category", "Tags"],
             top=5,
             vector_queries=[vector_query]
         )

         print(f"Total hybrid results: {results.get_count()}")
         for result in results:
             doc = result
             score = result.get("@search.score", "N/A")
             print(f"- Score: {score}")
             print(f"  HotelId: {doc['HotelId']}")            
             print(f"  HotelName: {doc['HotelName']}")
             print(f"  Description: {doc.get('Description')}")
             print(f"  Category: {doc.get('Category')}")
             print(f"  Tags: {doc.get('Tags', 'N/A')}\n")

    except Exception as ex:
       print("Hybrid search failed:", ex)
else:
    print("No vector loaded, skipping search.")

    檢閱回應：

    Total hybrid results: 7
- Score: 0.03279569745063782
   HotelId: 4
   HotelName: Sublime Palace Hotel
   Description: Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Cliff is part of a lovingly restored 19th century resort, updated for every modern convenience.
   Category: Boutique
   Tags: ['concierge', 'view', 'air conditioning']

- Score: 0.032522473484277725
   HotelId: 13
   HotelName: Luxury Lion Resort
   Description: Unmatched Luxury. Visit our downtown hotel to indulge in luxury accommodations. Moments from the stadium and transportation hubs, we feature the best in convenience and comfort.
   Category: Luxury
   Tags: ['bar', 'concierge', 'restaurant']

- Score: 0.03205128386616707
   HotelId: 48
   HotelName: Nordick's Valley Motel
   Description: Only 90 miles (about 2 hours) from the nation's capital and nearby most everything the historic valley has to offer. Hiking? Wine Tasting? Exploring the caverns? It's all nearby and we have specially priced packages to help make our B&B your home base for fun while visiting the valley.
   Category: Boutique
   Tags: ['continental breakfast', 'air conditioning', 'free wifi']

- Score: 0.0317460335791111
   HotelId: 49
   HotelName: Swirling Currents Hotel
   Description: Spacious rooms, glamorous suites and residences, rooftop pool, walking access to shopping, dining, entertainment and the city center. Each room comes equipped with a microwave, a coffee maker and a minifridge. In-room entertainment includes complimentary Wi-Fi and flat-screen TVs.
   Category: Suite
   Tags: ['air conditioning', 'laundry service', '24-hour front desk service']

- Score: 0.03125
   HotelId: 2
   HotelName: Old Century Hotel
   Description: The hotel is situated in a nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts. The hotel also regularly hosts events like wine tastings, beer dinners, and live music.
   Category: Boutique
   Tags: ['pool', 'free wifi', 'air conditioning', 'concierge']

    由於倒數排名融合 (RRF) 會合併結果，因此有助於檢閱輸入。 下列結果僅來自全文檢索搜尋查詢。 前兩名的結果是 Sublime Palace Hotel 和 History Lion Resort。 Sublime Palace Hotel 的 BM25 相關性分數較高。

    {
     "@search.score": 2.2626662,
     "HotelName": "Sublime Palace Hotel",
     "Description": "Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Palace is part of a lovingly restored 1800 palace."
},
{
     "@search.score": 0.86421645,
     "HotelName": "Luxury Lion Resort",
     "Description": "Unmatched Luxury.  Visit our downtown hotel to indulge in luxury accommodations. Moments from the stadium, we feature the best in comfort"
},

    在僅限向量的查詢中 (其使用 HNSW 尋找相符項目)，Sublime Palace Hotel 會下降到第四個位置。 Historic Lion 在全文檢索搜尋中排名第二，在向量搜尋中排名第三，並未經歷相同的波動範圍，因此成為同質化結果集中的最高相符項目。

    "value": [
     {
         "@search.score": 0.857736,
         "HotelId": "48",
         "HotelName": "Nordick's Valley Motel",
         "Description": "Only 90 miles (about 2 hours) from the nation's capital and nearby most everything the historic valley has to offer.  Hiking? Wine Tasting? Exploring the caverns?  It's all nearby and we have specially priced packages to help make our B&B your home base for fun while visiting the valley.",
         "Category": "Boutique"
     },
     {
         "@search.score": 0.8399129,
         "HotelId": "49",
         "HotelName": "Swirling Currents Hotel",
         "Description": "Spacious rooms, glamorous suites and residences, rooftop pool, walking access to shopping, dining, entertainment and the city center.",
         "Category": "Luxury"
     },
     {
         "@search.score": 0.8383954,
         "HotelId": "13",
         "HotelName": "Luxury Lion Resort",
         "Description": "Unmatched Luxury.  Visit our downtown hotel to indulge in luxury accommodations. Moments from the stadium, we feature the best in comfort",
         "Category": "Resort and Spa"
     },
     {
         "@search.score": 0.8254346,
         "HotelId": "4",
         "HotelName": "Sublime Palace Hotel",
         "Description": "Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Palace is part of a lovingly restored 1800 palace.",
         "Category": "Boutique"
     },
     {
         "@search.score": 0.82380056,
         "HotelId": "1",
         "HotelName": "Stay-Kay City Hotel",
         "Description": "The hotel is ideally located on the main commercial artery of the city in the heart of New York.",
         "Category": "Boutique"
     },
     {
         "@search.score": 0.81514084,
         "HotelId": "2",
         "HotelName": "Old Century Hotel",
         "Description": "The hotel is situated in a  nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts.",
         "Category": "Boutique"
     },
     {
         "@search.score": 0.8133763,
         "HotelId": "3",
         "HotelName": "Gastronomic Landscape Hotel",
         "Description": "The Hotel stands out for its gastronomic excellence under the management of William Dough, who advises on and oversees all of the Hotel’s restaurant services.",
         "Category": "Resort and Spa"
     }
]

使用篩選的語意混合式搜尋

以下是集合中的最後一個查詢。 此具有語意排名的混合式查詢會經過篩選，只顯示位於華盛頓特區 500 公里半徑內的旅館。您可以將 vectorFilterMode 設定為 null，這相當於預設值 (較新索引的 preFilter 和較舊索引的 postFilter)。

  • 尋找標題為「語意混合式搜尋」下方的儲存格，然後執行該儲存格。 此程式代碼區塊包含查詢搜尋索引的要求。

    if semantic_hybrid_query_vector:
    try:
       vector_query = VectorizedQuery(
          vector=vector,
          k_nearest_neighbors=5,
          fields="DescriptionVector",
          kind="vector",
          exhaustive=True
       )

       results = search_client.search(
          include_total_count=True,
          search_text="historic hotel walk to restaurants and shopping",
          select=[
             "HotelId", "HotelName", "Category", "Description"
          ],
          query_type="semantic",
          semantic_configuration_name="my-semantic-config",
          top=7,            
          vector_queries=[vector_query]
       )

       print(f"Total semantic hybrid results: {results.get_count()}")
       for result in results:
          doc = result
          score = result.get("@search.score", "N/A")
          reranker_score = result.get("@search.reranker_score", "N/A")
          print(f"- Score: {score}")
          print(f"  Re-ranker Score: {reranker_score}")
          print(f"  HotelId: {doc['HotelId']}")
          print(f"  HotelName: {doc['HotelName']}")
          print(f"  Description: {doc.get('Description')}")
          print(f"  Category: {doc.get('Category')}")

except Exception as ex:
    print("Semantic hybrid search failed:", ex)
else:
    print("No vector loaded, skipping search.")

    查看儲存格下方的輸出。 回應中有三家旅館，依位置篩選，並根據 StateProvince 進行 Facet 篩選，然後經過語意排名以提升最接近搜尋字串查詢的結果 (historic hotel walk to restaurants and shopping)。

    Swirling Currents Hotel 現在成為最佳位置。 沒有語意排名，Nordick's Valley Motel 是首選。 使用語意排名，機器理解模型認識到，historic 適用於「旅館，餐飲 (餐廳) 和購物地點在步行距離內」。

    Total semantic hybrid results: 7
- Score: 0.0317460335791111
   Re-ranker Score: 2.6550590991973877
   HotelId: 49
   HotelName: Swirling Currents Hotel
   Description: Spacious rooms, glamorous suites and residences, rooftop pool, walking access to shopping, dining, entertainment and the city center. Each room comes equipped with a microwave, a coffee maker and a minifridge. In-room entertainment includes complimentary Wi-Fi and flat-screen TVs.
   Category: Suite
- Score: 0.03279569745063782
   Re-ranker Score: 2.599761724472046
   HotelId: 4
   HotelName: Sublime Palace Hotel
   Description: Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Cliff is part of a lovingly restored 19th century resort, updated for every modern convenience.
   Category: Boutique
- Score: 0.03125
   Re-ranker Score: 2.3480887413024902
   HotelId: 2
   HotelName: Old Century Hotel
   Description: The hotel is situated in a nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts. The hotel also regularly hosts events like wine tastings, beer dinners, and live music.
   Category: Boutique
- Score: 0.016393441706895828
   Re-ranker Score: 2.2718777656555176
   HotelId: 1
   HotelName: Stay-Kay City Hotel
   Description: This classic hotel is fully-refurbished and ideally located on the main commercial artery of the city in the heart of New York. A few minutes away is Times Square and the historic center of the city, as well as other places of interest that make New York one of America's most attractive and cosmopolitan cities.
   Category: Boutique
- Score: 0.01515151560306549
   Re-ranker Score: 2.0582215785980225
   HotelId: 3
   HotelName: Gastronomic Landscape Hotel
   Description: The Gastronomic Hotel stands out for its culinary excellence under the management of William Dough, who advises on and oversees all of the Hotel’s restaurant services.
   Category: Suite

    重要心得：

    • 向量搜尋是透過 vectors.value 屬性來指定。 關鍵字搜尋是透過 search 屬性來指定。

    • 在混合式搜尋中，您可以將向量搜尋與關鍵字的全文檢索搜尋整合。 篩選、拼字檢查和語意排名僅適用於文字內容，而非向量。 在此最終查詢中，沒有語意 answer，因為系統不會產生足夠強的語意。

    • 實際結果包含更多詳細資料，包括語意標題和醒目提示。 結果已針對可讀性進行修改。 若要取得回應的完整結構，請在 REST 用戶端中執行要求。

清除

使用您自己的訂用帳戶時，在專案結束後確認您是否還需要您建立的資源，是很好的做法。 讓資源繼續執行可能會產生費用。 您可以個別刪除資源，或刪除資源群組以刪除整組資源。

您可以使用 Azure 入口網站最左邊窗格中的 [所有資源] 或 [資源群組] 連結，來尋找和管理資源。

如果您想要保留搜尋服務，但刪除索引和檔，您可以使用 SearchIndexClient 物件的 delete_index() 方法。 在標題為「清除」的部分找到以下儲存格，然後執行該儲存格以刪除 hotels-vector-quickstart 索引：

index_client.delete_index(index_name)
print(f"Index '{index_name}' deleted successfully.")

後續步驟

在本快速入門中，您會使用 Azure AI 搜尋 REST API 來建立、載入和查詢向量。

在 Azure AI 搜尋服務中，「向量存放區」具有定義向量和非向量欄位的索引結構描述、建立內嵌空間之演算法的向量搜尋設定，以及向量欄位定義上可於查詢時間進行評估的設定。 建立索引 REST API 會建立向量存放區。

附註

本快速入門省略向量化步驟，並提供內置內嵌。 如果您想要將 內建數據區塊化和向量化 新增至您自己的內容，請嘗試 匯入並向量化數據精靈 ，以完成端到端指南。

必要條件

擷取資源資訊

對搜尋端點發出的要求必須經過驗證和授權。 您可以針對這項工作使用 API 金鑰或角色。 建議您透過 Microsoft Entra ID 使用無金鑰連線。

選取對應至您慣用驗證方法的索引標籤。 在本快速入門中，針對所有要求使用相同的方法。

  1. 登入 Azure 入口網站，然後尋找您的搜尋服務。

  2. 在 [概觀] 首頁上，尋找 URL。 範例端點看起來會像是 https://mydemo.search.windows.net。

    概觀頁面上 URL 屬性的螢幕擷取畫面。

  3. 請遵循無金鑰快速入門中的步驟，取得您的 Microsoft Entra 權杖。

    當您在上一個快速入門的步驟 3 中執行 az account get-access-token 命令時，您會取得權杖。

    az account get-access-token --scope https://search.azure.com/.default --query accessToken --output tsv

建立或下載程式碼檔案

您可以使用一或 .rest 個 .http 檔案來執行本快速入門中的所有要求。 您可以下載包含本快速入門程式碼的 REST 檔案，或在 Visual Studio Code 中建立新檔案並將程式碼複製到其中。

  1. 在 Visual Studio Code 中，建立具有 .rest 或 .http 副檔名的新檔案。 例如：az-search-vector-quickstart.rest。 將 Azure-Samples/azure-search-rest-samples/blob/main/Quickstart-vectors/az-search-vector-quickstart.rest 檔案的原始內容複製並貼到此新檔案。

  2. 在檔案頂端，將 @baseUrl 的預留位置值取代為您的搜尋服務 URL。 如需如何尋找搜尋服務 URL 的指示，請參閱擷取資源資訊一節。

    @baseUrl = PUT-YOUR-SEARCH-SERVICE-URL-HERE

  3. 在檔案頂端，取代驗證的預留位置值。 如需如何取得Microsoft Entra 權杖或 API 金鑰的指示，請參閱擷取資源資訊一節。

    針對透過 Microsoft Entra ID 的建議無金鑰驗證，您必須將 @apiKey 取代為 @token 變數。

    @token = PUT-YOUR-MICROSOFT-ENTRA-TOKEN-HERE

    如果您想要使用 API 金鑰，請將 @apiKey 取代為您從 Azure 入口網站複製的金鑰。

    @apiKey = PUT-YOUR-ADMIN-KEY-HERE

  4. 針對透過 Microsoft Entra ID 的建議無金鑰驗證，您必須在要求標頭中將 api-key: {{apiKey}} 取代為 Authorization: Bearer {{token}}。 取代您在檔案中找到的所有 api-key: {{apiKey}} 執行個體。

建立向量索引

您使用建立索引 REST API 建立向量索引，並在您的搜尋服務上設定實體資料結構。

此範例中的索引結構描述會針對旅館內容進行組織。 範例數據是由虛構旅館的向量和非向量描述所組成。 此架構包含向量索引編製和查詢的設定，以及語意排名的設定。

  1. 在 Visual Studio Code 中，開啟您稍早建立的 az-search-vector-quickstart.rest 檔案。

  2. 在檔案中尋找程式 ### Create a new index 程式碼區塊。 此區塊包含在搜尋服務上建立 hotels-vector-quickstart 索引的要求。

    ### Create a new index
POST  {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
Content-Type: application/json
Authorization: Bearer {{token}}

{
    "name": "hotels-vector-quickstart",
    "fields": [
        {
            "name": "HotelId", 
            "type": "Edm.String",
            "searchable": false, 
            "filterable": true, 
            "retrievable": true, 
            "sortable": false, 
            "facetable": false,
            "key": true
        },
        {
            "name": "HotelName", 
            "type": "Edm.String",
            "searchable": true, 
            "filterable": false, 
            "retrievable": true, 
            "sortable": true, 
            "facetable": false
        },
        {
            "name": "Description", 
            "type": "Edm.String",
            "searchable": true, 
            "filterable": false, 
            "retrievable": true, 
            "sortable": false, 
            "facetable": false
        },
        {
            "name": "DescriptionVector",
            "type": "Collection(Edm.Single)",
            "searchable": true,
            "retrievable": true,
            "dimensions": 1536,
            "vectorSearchProfile": "my-vector-profile"
        },
        {
            "name": "Category", 
            "type": "Edm.String",
            "searchable": true, 
            "filterable": true, 
            "retrievable": true, 
            "sortable": true, 
            "facetable": true
        },
        {
            "name": "Tags",
            "type": "Collection(Edm.String)",
            "searchable": true,
            "filterable": true,
            "retrievable": true,
            "sortable": false,
            "facetable": true
        },
                {
            "name": "ParkingIncluded",
            "type": "Edm.Boolean",
            "searchable": false,
            "filterable": true,
            "retrievable": true,
            "sortable": true,
            "facetable": true
        },
        {
            "name": "LastRenovationDate",
            "type": "Edm.DateTimeOffset",
            "searchable": false,
            "filterable": true,
            "retrievable": true,
            "sortable": true,
            "facetable": true
        },
        {
            "name": "Rating",
            "type": "Edm.Double",
            "searchable": false,
            "filterable": true,
            "retrievable": true,
            "sortable": true,
            "facetable": true
        },
        {
            "name": "Address", 
            "type": "Edm.ComplexType",
            "fields": [
                {
                    "name": "StreetAddress", "type": "Edm.String",
                    "searchable": true, "filterable": false, "retrievable": true, "sortable": false, "facetable": false
                },
                {
                    "name": "City", "type": "Edm.String",
                    "searchable": true, "filterable": true, "retrievable": true, "sortable": true, "facetable": true
                },
                {
                    "name": "StateProvince", "type": "Edm.String",
                    "searchable": true, "filterable": true, "retrievable": true, "sortable": true, "facetable": true
                },
                {
                    "name": "PostalCode", "type": "Edm.String",
                    "searchable": true, "filterable": true, "retrievable": true, "sortable": true, "facetable": true
                },
                {
                    "name": "Country", "type": "Edm.String",
                    "searchable": true, "filterable": true, "retrievable": true, "sortable": true, "facetable": true
                }
            ]
        },
        {
            "name": "Location",
            "type": "Edm.GeographyPoint",
            "searchable": false, 
            "filterable": true, 
            "retrievable": true, 
            "sortable": true, 
            "facetable": false
        }
    ],
    "vectorSearch": {
        "algorithms": [
            {
                "name": "hnsw-vector-config",
                "kind": "hnsw",
                "hnswParameters": 
                {
                    "m": 4,
                    "efConstruction": 400,
                    "efSearch": 500,
                    "metric": "cosine"
                }
            },
            {
                "name": "eknn-vector-config",
                "kind": "exhaustiveKnn",
                "exhaustiveKnnParameters": 
                {
                    "metric": "cosine"
                }
            }
        ],
        "profiles": [      
            {
                "name": "my-vector-profile",
                "algorithm": "hnsw-vector-config"
            }
      ]
    },
    "semantic": {
        "configurations": [
            {
                "name": "semantic-config",
                "prioritizedFields": {
                    "titleField": {
                        "fieldName": "HotelName"
                    },
                    "prioritizedContentFields": [
                        { "fieldName": "Description" }
                    ],
                    "prioritizedKeywordsFields": [
                        { "fieldName": "Category" }
                    ]
                }
            }
        ]
    }
}

  3. 選取 [傳送要求]。 您應該會有 HTTP/1.1 201 Created 回應。

    回應本文應該包含索引結構描述的 JSON 表示法。

    {
    "@odata.context": "https://my-demo-search.search.windows.net/$metadata#indexes/$entity",
    "@odata.etag": "\"0x8DD2E70E6C36D8E\"",
    "name": "hotels-vector-quickstart",
    "defaultScoringProfile": null,
    "fields": [
    {
        "name": "HotelId",
        "type": "Edm.String",
        "searchable": false,
        "filterable": true,
        "retrievable": true,
        "sortable": false,
        "facetable": false,
        "key": true,
        "indexAnalyzer": null,
        "searchAnalyzer": null,
        "analyzer": null,
        "dimensions": null,
        "vectorSearchProfile": null,
        "synonymMaps": []
    },
    [MORE FIELD DEFINITIONS OMITTED FOR BREVITY]
    ],
    "scoringProfiles": [],
    "corsOptions": null,
    "suggesters": [],
    "analyzers": [],
    "tokenizers": [],
    "tokenFilters": [],
    "charFilters": [],
    "encryptionKey": null,
    "similarity": {
    "@odata.type": "#Microsoft.Azure.Search.BM25Similarity",
    "k1": null,
    "b": null
    },
    "vectorSearch": {
    "algorithms": [
        {
        "name": "hnsw-vector-config",
        "kind": "hnsw",
        "hnswParameters": {
            "metric": "cosine",
            "m": 4,
            "efConstruction": 400,
            "efSearch": 500
        },
        "exhaustiveKnnParameters": null
        },
        "exhaustiveKnnParameters": null
        },
        {
        "name": "eknn-vector-config",
        "kind": "exhaustiveKnn",
        "hnswParameters": null,
        "exhaustiveKnnParameters": {
            "metric": "cosine"
        }
        }
    ],
    "profiles": [
        {
        "name": "my-vector-profile",
        "algorithm": "hnsw-vector-config-1"
        }
    ]
    },
    "semantic": {
    "defaultConfiguration": null,
    "configurations": [
        {
        "name": "semantic-config",
        "prioritizedFields": {
            "titleField": {
            "fieldName": "HotelName"
            },
            "prioritizedContentFields": [
            {
                "fieldName": "Description"
            }
            ],
            "prioritizedKeywordsFields": [
            {
                "fieldName": "Category"
            }
            ]
        }
        }
    ]
    }
}

關於建立索引 REST API 的重要心得：

  • fields 集合包含文字和向量搜尋所需的索引鍵欄位、文字和向量欄位(例如 Description 和 DescriptionVector)。 在同一個索引中共置向量和非向量欄位可啟用混合式查詢。 例如，您可以將篩選、文字搜尋與語意排名和向量合併成單一查詢作業。

  • 向量欄位必須是 用於向量的其中一個 EDM 資料類型，例如 type: Collection(Edm.Single)。 向量欄位也有 dimensions 和 vectorSearchProfile 屬性。

  • vectorSearch 區段是近似最近鄰演算法設定和設定檔的陣列。 支援的演算法包括階層式可導覽小世界 (navigable small world) 和詳盡的 K 最近鄰 (k-nearest neighbor)。 如需詳細資訊，請參閱向量搜尋中的相關性評分。

  • (選擇性) semantic 設定可重新排名搜尋結果。 針對設定中所指定的字串欄位，您可以進行類型 semantic 查詢結果的重新排名。 若要深入了解，請參閱語意排名概觀。

上傳文件

建立和載入索引是單獨的步驟。 您在上一個步驟中建立了索引結構描述。 現在您需要將文件載入索引中。

在 Azure AI 搜尋服務中，索引包含所有可搜尋資料以及對搜尋服務執行的查詢。 針對 REST 呼叫，數據會以 JSON 文件的形式提供。 針對這項工作使用 Documents- Index REST API。 URI 會擴充以包含 docs 集合和 index 作業。

  1. 制定上傳檔要求，以將文件上傳至 hotels-vector-quickstart 搜尋服務上的索引。

    ### Upload documents
POST {{baseUrl}}/indexes/hotels-quickstart-vectors/docs/index?api-version=2024-07-01  HTTP/1.1
Content-Type: application/json
Authorization: Bearer {{token}}

{
    "value": [
        {
            "@search.action": "mergeOrUpload",
            "HotelId": "1",
            "HotelName": "Stay-Kay City Hotel",
            "Description": "This classic hotel is fully-refurbished and ideally located on the main commercial artery of the city in the heart of New York. A few minutes away is Times Square and the historic center of the city, as well as other places of interest that make New York one of America's most attractive and cosmopolitan cities.",
            "DescriptionVector": 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            "Category": "Boutique",
            "Tags": [
                "view",
                "air conditioning",
                "concierge"
            ],
            "ParkingIncluded": false,
            "LastRenovationDate": "2022-01-18T00:00:00Z",
            "Rating": 3.60,
            "Address": {
                "StreetAddress": "677 5th Ave",
                "City": "New York",
                "StateProvince": "NY",
                "PostalCode": "10022",
                "Country": "USA"
            },
            "Location": {
                "type": "Point",
                "coordinates": [
                    -73.975403,
                    40.760586
                ]
            }
        },
        {
            "@search.action": "mergeOrUpload",
            "HotelId": "2",
            "HotelName": "Old Century Hotel",
            "Description": "The hotel is situated in a nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts. The hotel also regularly hosts events like wine tastings, beer dinners, and live music.",
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            "Category": "Boutique",
            "Tags": [
                "pool",
                "free wifi",
                "air conditioning",
                "concierge"
            ],
            "ParkingIncluded": false,
            "LastRenovationDate": "2019-02-18T00:00:00Z",
            "Rating": 3.60,
            "Address": {
                "StreetAddress": "140 University Town Center Dr",
                "City": "Sarasota",
                "StateProvince": "FL",
                "PostalCode": "34243",
                "Country": "USA"
            },
            "Location": {
                "type": "Point",
                "coordinates": [
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                ]
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            "HotelId": "3",
            "HotelName": "Gastronomic Landscape Hotel",
            "Description": "The Gastronomic Hotel stands out for its culinary excellence under the management of William Dough, who advises on and oversees all of the Hotel’s restaurant services.",
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            "Category": "Suite",
            "Tags": [
                "restaurant",
                "bar",
                "continental breakfast"
            ],
            "ParkingIncluded": true,
            "LastRenovationDate": "2015-09-20T00:00:00Z",
            "Rating": 4.80,
            "Address": {
                "StreetAddress": "3393 Peachtree Rd",
                "City": "Atlanta",
                "StateProvince": "GA",
                "PostalCode": "30326",
                "Country": "USA"
            },
            "Location": {
                "type": "Point",
                "coordinates": [
                    33.847848,
                    -84.363602
                ]
            }
        },
        {
            "@search.action": "mergeOrUpload",
            "HotelId": "4",
            "HotelName": "Sublime Palace Hotel",
            "Description": "Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Cliff is part of a lovingly restored 19th century resort, updated for every modern convenience.",
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            "Category": "Boutique",
            "Tags": [
                "concierge",
                "view",
                "air conditioning"
            ],
            "ParkingIncluded": true,
            "LastRenovationDate": "2020-02-06T00:00:00Z",
            "Rating": 4.60,
            "Address": {
                "StreetAddress": "7400 San Pedro Ave",
                "City": "San Antonio",
                "StateProvince": "TX",
                "PostalCode": "78216",
                "Country": "USA"
            },
            "Location": {
                "type": "Point",
                "coordinates": [
                    -98.498923,
                    29.518029
                ]
            }
        },
        {
            "@search.action": "mergeOrUpload",
            "HotelId": "48",
            "HotelName": "Nordick's Valley Motel",
            "Description": "Only 90 miles (about 2 hours) from the nation's capital and nearby most everything the historic valley has to offer. Hiking? Wine Tasting? Exploring the caverns? It's all nearby and we have specially priced packages to help make our B&B your home base for fun while visiting the valley.",
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            "Category": "Boutique",
            "Tags": [
                "continental breakfast",
                "air conditioning",
                "free wifi"
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            "ParkingIncluded": false,
            "LastRenovationDate": "2018-02-19T00:00:00Z",
            "Rating": 4.5,
            "Address": {
                "StreetAddress": "1401 I St NW",
                "City": "Washington D.C.",
                "StateProvince": null,
                "PostalCode": "20005",
                "Country": "USA"
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                "properties": {
                    "name": "EPSG:4326"
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            "HotelId": "49",
            "HotelName": "Swirling Currents Hotel",
            "Description": "Spacious rooms, glamorous suites and residences, rooftop pool, walking access to shopping, dining, entertainment and the city center. Each room comes equipped with a microwave, a coffee maker and a minifridge. In-room entertainment includes complimentary Wi-Fi and flat-screen TVs.",
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           "Category": "Suite",
            "Tags": [
                "air conditioning",
                "laundry service",
                "24-hour front desk service"
            ],
            "ParkingIncluded": true,
            "LastRenovationDate": "2018-01-27T00:00:00Z",
            "Rating": 2.7,
            "Address": {
                "StreetAddress": "1100 S Hayes St",
                "City": "Arlington",
                "StateProvince": "VA",
                "PostalCode": "22202",
                "Country": "USA"
            },
            "Location": {
                "type": "Point",
                "coordinates": [
                -77.060066,
                38.863659
                ],
                "crs": {
                "type": "name",
                "properties": {
                    "name": "EPSG:4326"
                    }
                }
            }
        },
        {
            "@search.action": "mergeOrUpload",
            "HotelId": "13",
            "HotelName": "Luxury Lion Resort",
            "Description": "Unmatched Luxury. Visit our downtown hotel to indulge in luxury accommodations. Moments from the stadium and transportation hubs, we feature the best in convenience and comfort.",
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            "Category": "Luxury",
            "Tags": [
                "bar",
                "concierge",
                "restaurant"
            ],
            "ParkingIncluded": false,
            "LastRenovationDate": "2020-03-18T00:00:00Z",
            "Rating": 4.1,
            "Address": {
                "StreetAddress": "3 Cityplace Dr",
                "City": "St. Louis",
                "StateProvince": "MO",
                "PostalCode": "63141",
                "Country": "USA"
            },
            "Location": {
                "type": "Point",
                "coordinates": [
                -90.44081,
                38.67219
                ],
                "crs": {
                "type": "name",
                "properties": {
                    "name": "EPSG:4326"
                    }
                }
            }
        }
    ]
}

  2. 選取 [傳送要求]。 您應該會有 HTTP/1.1 200 OK 回應。 回應本文應該包含搜尋文件的 JSON 表示法。

文件 - 索引 REST API 要求的重要心得：

  • 承載中的文件是由索引結構描述中定義的欄位所組成。

  • 向量欄位包含浮點值。 維度屬性至少有 2 個，而且每個都有最多 4096 浮點值。 本快速入門會將維度屬性設定為 1,536，因為這是 Azure OpenAI text-embedding-3-small 模型所產生的內嵌大小。

執行查詢

現在已載入文件，您可以使用 文件 - 搜尋郵件（REST）對其執行向量查詢。

在下一節中，我們會對 hotels-vector-quickstart 索引執行查詢。 查詢包括：

範例查詢是以兩個字串為基礎：

  • 搜尋字串：historic hotel walk to restaurants and shopping
  • 向量查詢字串 (向量化為數學表示法)：quintessential lodging near running trails, eateries, retail

向量查詢字串在語意上類似於搜尋字串，但包含搜尋索引中不存在的字詞。 如果您對 quintessential lodging near running trails, eateries, retail進行關鍵詞搜尋，則結果在純關鍵詞搜尋中為零，而沒有語意排名。 我們使用此範例來示範如何使用向量取得相關結果，即使沒有相符的字詞也一樣。

  1. 制定要求。 此查詢是 1536 浮點數表示法，代表靠近跑道、餐廳和零售店的典型住宿。 查詢正在搜尋 DescriptionVector 並傳回 k-5 結果。

    ### Run a single vector query
POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2024-07-01  HTTP/1.1
    Content-Type: application/json
    Authorization: Bearer {{token}}

    {
        "count": true,
        "select": "HotelId, HotelName, Description, Category, Tags",
        "vectorQueries": [
            {
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                "k": 5,
                "fields": "DescriptionVector",
                "kind": "vector",
                "exhaustive": true
            }
        ]
    }

    關於Documents - Search Post REST API 的關鍵重點：

    • vectorQueries.vector是向量查詢字串。 這是 quintessential lodging near running trails, eateries, retail 的向量表示，其向量化為此查詢的 1,536 個內嵌項目。

    • fields 會決定要搜尋的向量字段。

    • kind 設定為 vector 表示查詢字串是向量。 如果 kind 設定為 text，則您需要額外的功能（ 向量化程式）在查詢時將人類可讀取的文字字串編碼為向量。 本快速入門會省略向量化工具，讓練習保持簡單。

    • k 會指定要在回應中傳回的近鄰數目。 參數 count 會指定索引中找到的相符項目數目。 計算數量是進行查詢的最佳做法，但對於相似度搜尋來說，則較為不實用，因為演算法幾乎在任何文件中都能找到某種程度的相似性。

  2. 選取 [傳送要求]。 您應該會有 HTTP/1.1 200 OK 回應。 回應本文應該包含搜尋結果的 JSON 表示法。

    向量的等效項 quintessential lodging near running trails, eateries, retail 的回應包含 k-5 個相符項目，但搜尋引擎找到了 7 個相符項目。 最上層的結果在語意上會被視為與查詢類似的結果。 每個結果都會提供搜尋分數和列在 select 中的欄位。 在相似性搜尋中，回應一律包含依值相似度分數排序的 k 結果。

    {
  "@odata.context": "https://my-demo-search.search.windows.net/indexes('hotels-vector-quickstart')/$metadata#docs(*)",
  "@odata.count": 7,
  "value": [
    {
      "@search.score": 0.6605852,
      "HotelId": "48",
      "HotelName": "Nordick's Valley Motel",
      "Description": "Only 90 miles (about 2 hours) from the nation's capital and nearby most everything the historic valley has to offer. Hiking? Wine Tasting? Exploring the caverns? It's all nearby and we have specially priced packages to help make our B&B your home base for fun while visiting the valley.",
      "Category": "Boutique",
      "Tags": [
        "continental breakfast",
        "air conditioning",
        "free wifi"
      ]
    },
    {
      "@search.score": 0.6333684,
      "HotelId": "13",
      "HotelName": "Luxury Lion Resort",
      "Description": "Unmatched Luxury. Visit our downtown hotel to indulge in luxury accommodations. Moments from the stadium and transportation hubs, we feature the best in convenience and comfort.",
      "Category": "Luxury",
      "Tags": [
        "bar",
        "concierge",
        "restaurant"
      ]
    },
    {
      "@search.score": 0.605672,
      "HotelId": "4",
      "HotelName": "Sublime Palace Hotel",
      "Description": "Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Cliff is part of a lovingly restored 19th century resort, updated for every modern convenience.",
      "Category": "Boutique",
      "Tags": [
        "concierge",
        "view",
        "air conditioning"
      ]
    },
    {
      "@search.score": 0.6026341,
      "HotelId": "49",
      "HotelName": "Swirling Currents Hotel",
      "Description": "Spacious rooms, glamorous suites and residences, rooftop pool, walking access to shopping, dining, entertainment and the city center. Each room comes equipped with a microwave, a coffee maker and a minifridge. In-room entertainment includes complimentary Wi-Fi and flat-screen TVs.",
      "Category": "Suite",
      "Tags": [
        "air conditioning",
        "laundry service",
        "24-hour front desk service"
      ]
    },
    {
      "@search.score": 0.57902366,
      "HotelId": "2",
      "HotelName": "Old Century Hotel",
      "Description": "The hotel is situated in a nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts. The hotel also regularly hosts events like wine tastings, beer dinners, and live music.",
      "Category": "Boutique",
      "Tags": [
        "pool",
        "free wifi",
        "air conditioning",
        "concierge"
      ]
    }
  ]
}

使用篩選的單一向量搜尋

您可以新增篩選，但篩選條件會套用於索引中的非向量內容。 在此範例中，篩選會套用於 Tags 欄位，篩選排除任何不提供免費 Wi-Fi 的旅館。

  1. 制定要求。 這與上一個要求相同，具有額外的篩選和篩選模式參數。

    ### Run a vector query with a filter
POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2024-07-01  HTTP/1.1
    Content-Type: application/json
    Authorization: Bearer {{token}}

    {
        "count": true,
        "select": "HotelId, HotelName, Category, Tags, Description",
        "filter": "Tags/any(tag: tag eq 'free wifi')",
        "vectorFilterMode": "postFilter",
        "vectorQueries": [
        {
            "vector": 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            "k": 5,
            "fields": "DescriptionVector",
            "kind": "vector",
            "exhaustive": true
        },
    ]
}

  2. 選取 [傳送要求]。 您應該會有 HTTP/1.1 200 OK 回應。 回應本文應該包含搜尋結果的 JSON 表示法。

    此查詢與先前 的單一向量搜尋範例相同，但它包含後置處理排除篩選條件，而且只會傳回兩家擁有免費Wi-Fi的酒店。

    {
  "@odata.context": "https://my-demo-search.search.windows.net/indexes('hotels-vector-quickstart')/$metadata#docs(*)",
  "@odata.count": 2,
  "value": [
    {
      "@search.score": 0.6605852,
      "HotelId": "48",
      "HotelName": "Nordick's Valley Motel",
      "Description": "Only 90 miles (about 2 hours) from the nation's capital and nearby most everything the historic valley has to offer. Hiking? Wine Tasting? Exploring the caverns? It's all nearby and we have specially priced packages to help make our B&B your home base for fun while visiting the valley.",
      "Category": "Boutique",
      "Tags": [
        "continental breakfast",
        "air conditioning",
        "free wifi"
      ]
    },
    {
      "@search.score": 0.57902366,
      "HotelId": "2",
      "HotelName": "Old Century Hotel",
      "Description": "The hotel is situated in a nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts. The hotel also regularly hosts events like wine tastings, beer dinners, and live music.",
      "Category": "Boutique",
      "Tags": [
        "pool",
        "free wifi",
        "air conditioning",
        "concierge"
      ]
    }
  ]
}

  3. 以下是另一個使用地理篩選的查詢，將結果限制在華盛頓特區附近 300 公里內的旅館。

    ### Run a vector query with a geo filter
POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2024-07-01  HTTP/1.1
    Content-Type: application/json
    Authorization: Bearer {{token}}

    {
        "count": true,
        "select": "HotelId, HotelName, Description, Address/City, Address/StateProvince",
        "top": 5,
        "facets": [ "Address/StateProvince"],
        "filter": "geo.distance(Location, geography'POINT(-77.03241 38.90166)') le 300",
        "vectorFilterMode": "postFilter",
        "vectorQueries": [
        {
            "vector": 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            "k": 5,
            "fields": "DescriptionVector",
            "kind": "vector",
            "exhaustive": true
        },
    ]
}

  4. 檢閱回應。 它僅限於華盛頓特區附近的兩家旅館，並具有一個提供彙總功能的 Facet 結構。

    "@odata.count": 2,
"@search.facets": {
  "Address/StateProvince": [
    {
      "value": "VA",
      "count": 1
    }
  ]
},
"value": [
  {
    "@search.score": 0.6605852246284485,
    "HotelId": "48",
    "HotelName": "Nordick's Valley Motel",
    "Description": "Only 90 miles (about 2 hours) from the nation's capital and nearby most everything the historic valley has to offer. Hiking? Wine Tasting? Exploring the caverns? It's all nearby and we have specially priced packages to help make our B&B your home base for fun while visiting the valley.",
    "Address": {
      "City": "Washington D.C.",
      "StateProvince": null
    }
  },
  {
    "@search.score": 0.602634072303772,
    "HotelId": "49",
    "HotelName": "Swirling Currents Hotel",
    "Description": "Spacious rooms, glamorous suites and residences, rooftop pool, walking access to shopping, dining, entertainment and the city center. Each room comes equipped with a microwave, a coffee maker and a minifridge. In-room entertainment includes complimentary Wi-Fi and flat-screen TVs.",
    "Address": {
      "City": "Arlington",
      "StateProvince": "VA"
    }
  }
]

混合式搜尋是由單一搜尋要求中的關鍵字查詢和向量查詢所組成。 此範例會同時執行向量查詢和全文檢索搜尋：

  • 搜尋字串：historic hotel walk to restaurants and shopping
  • 向量查詢字串 (向量化為數學表示法)：quintessential lodging near running trails, eateries, retail

  1. 制定混合式查詢。

    ### Run a hybrid query
POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2024-07-01  HTTP/1.1
    Content-Type: application/json
    Authorization: Bearer {{token}}

{
    "count": true,
    "search": "historic hotel walk to restaurants and shopping",
    "select": "HotelName, Description",
    "top": 7,
    "vectorQueries": [
        {
            "vector": 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            "k": 5,
            "fields": "DescriptionVector",
            "kind": "vector",
            "exhaustive": true
        }
    ]
}

  2. 選取 [傳送要求]。 您應該會有 HTTP/1.1 200 OK 回應。 回應本文應該包含搜尋結果的 JSON 表示法。

因為這是混合式查詢，因此結果會依倒數排名融合 (RRF) 進行排名。 請注意， @search.score 值具有不同的基礎，而且是一致的較小值。 RRF 會評估多個搜尋結果的搜尋分數、採用反向排列，然後合併並排序合併的結果。 傳回的結果數目 top。

檢閱回應，其中包含索引中 7 個相符文件的前 k-5 個相符項目：

{
  "@odata.count": 7,
  "value": [
    {
      "@search.score": 0.03279569745063782,
      "HotelName": "Sublime Palace Hotel",
      "Description": "Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Cliff is part of a lovingly restored 19th century resort, updated for every modern convenience."
    },
    {
      "@search.score": 0.032522473484277725,
      "HotelName": "Luxury Lion Resort",
      "Description": "Unmatched Luxury. Visit our downtown hotel to indulge in luxury accommodations. Moments from the stadium and transportation hubs, we feature the best in convenience and comfort."
    },
    {
      "@search.score": 0.03205128386616707,
      "HotelName": "Nordick's Valley Motel",
      "Description": "Only 90 miles (about 2 hours) from the nation's capital and nearby most everything the historic valley has to offer. Hiking? Wine Tasting? Exploring the caverns? It's all nearby and we have specially priced packages to help make our B&B your home base for fun while visiting the valley."
    },
    {
      "@search.score": 0.0317460335791111,
      "HotelName": "Swirling Currents Hotel",
      "Description": "Spacious rooms, glamorous suites and residences, rooftop pool, walking access to shopping, dining, entertainment and the city center. Each room comes equipped with a microwave, a coffee maker and a minifridge. In-room entertainment includes complimentary Wi-Fi and flat-screen TVs."
    },
    {
      "@search.score": 0.03125,
      "HotelName": "Old Century Hotel",
      "Description": "The hotel is situated in a nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts. The hotel also regularly hosts events like wine tastings, beer dinners, and live music."
    }
  ]
}

因為 RRF 會合併結果，可協助個別檢閱輸入。

下列結果來自查詢的文字完整檢索部分：歷史悠久的酒店，步行可至餐廳及購物區域。 在全文查詢中，前三名結果為 Sublime 故宮酒店、Stay-Kay 城市酒店和豪華獅子度假村。 Sublime Palace Hotel 的 BM25 相關性分數較高。 在融合查詢中，這些匹配中只有兩個進入前 3 名，而第二個匹配（Stay-Kay City Hotel）完全未進入前 5 名。

  "value": [
    {
      "@search.score": 1.4868739,
      "HotelName": "Sublime Palace Hotel",
      "Description": "Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Cliff is part of a lovingly restored 19th century resort, updated for every modern convenience."
    },
    {
      "@search.score": 1.2699215,
      "HotelName": "Stay-Kay City Hotel",
      "Description": "This classic hotel is fully-refurbished and ideally located on the main commercial artery of the city in the heart of New York. A few minutes away is Times Square and the historic centre of the city, as well as other places of interest that make New York one of America's most attractive and cosmopolitan cities."
    },
    {
      "@search.score": 1.2456272,
      "HotelName": "Luxury Lion Resort",
      "Description": "Unmatched Luxury. Visit our downtown hotel to indulge in luxury accommodations. Moments from the stadium and transportation hubs, we feature the best in convenience and comfort."
    },
    ...
  ]

在向量部分查詢（最具代表性的住宿，靠近跑步小徑、餐館、零售商店）是一個不同的字串，因此我們應該預期會有不同的結果。 這次查詢返回的前三個匹配結果是 Nordick's Valley Motel、Luxury Lion Resort 和 Sublime Palace Hotel。 在融合查詢中，這些結果位於前 3 名，但順序相反。

  "value": [
    {
      "@search.score": 0.6605852,
      "HotelName": "Nordick's Valley Motel",
      "Description": "Only 90 miles (about 2 hours) from the nation's capital and nearby most everything the historic valley has to offer. Hiking? Wine Tasting? Exploring the caverns? It's all nearby and we have specially priced packages to help make our B&B your home base for fun while visiting the valley."
    },
    {
      "@search.score": 0.6333684,
      "HotelName": "Luxury Lion Resort",
      "Description": "Unmatched Luxury. Visit our downtown hotel to indulge in luxury accommodations. Moments from the stadium and transportation hubs, we feature the best in convenience and comfort."
    },
    {
      "@search.score": 0.605672,
      "HotelName": "Sublime Palace Hotel",
      "Description": "Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Cliff is part of a lovingly restored 19th century resort, updated for every modern convenience."
    },
   ...
  ]

以下是集合中的最後一個查詢。 此混合式查詢會新增 L2 語意排名，其會對 L1 排名結果套用機器閱讀理解，將更相關的相符項目提升到最上層。

  1. 制定要求。

    ### Run a hybrid query with semantic reranking
POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2024-07-01  HTTP/1.1
    Content-Type: application/json
    Authorization: Bearer {{token}}

{
    "count": true,
    "search": "historic hotel walk to restaurants and shopping",
    "select": "HotelName, Description",
    "queryType": "semantic",
    "semanticConfiguration": "semantic-config",
    "top": 5,
    "vectorQueries": [
        {
            "vector": 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  2. 選取 [傳送要求]。 您應該會有 HTTP/1.1 200 OK 回應。 回應本文應該包含搜尋結果的 JSON 表示法。

檢閱回應，其中包含對於混合式查詢的 RRF 排名結果進行的語意排序調整。 語意排名會從文字輸入中運作。 在文字或混合式查詢中，此輸入是查詢的文字部分（歷史悠久的酒店，步行可達餐廳及購物區）。 若要在純向量查詢上使用語意排名，例如第一個範例，或明確控制用於語意排名的文字， 請提供 semanticQuery 字串。

經過語意重新排名，Swirling Currents Hotel 因為其 步行可到購物、餐飲、娛樂和市中心的 便利位置而名列榜首。 機器理解模型會將 walking access to shopping and dining 提升為更接近 walk to restaurants and shopping 的相符項目。

在語意重新排名之前，Sublime Palace，及其參考 walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments 為第一項。

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    {
      "@search.score": 0.0317460335791111,
      "@search.rerankerScore": 2.6550590991973877,
      "HotelId": "49",
      "HotelName": "Swirling Currents Hotel",
      "Description": "Spacious rooms, glamorous suites and residences, rooftop pool, walking access to shopping, dining, entertainment and the city center. Each room comes equipped with a microwave, a coffee maker and a minifridge. In-room entertainment includes complimentary Wi-Fi and flat-screen TVs.",
      "Category": "Suite"
    },
    {
      "@search.score": 0.03279569745063782,
      "@search.rerankerScore": 2.599761724472046,
      "HotelId": "4",
      "HotelName": "Sublime Palace Hotel",
      "Description": "Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Cliff is part of a lovingly restored 19th century resort, updated for every modern convenience.",
      "Category": "Boutique"
    },
    {
      "@search.score": 0.03125,
      "@search.rerankerScore": 2.3480887413024902,
      "HotelId": "2",
      "HotelName": "Old Century Hotel",
      "Description": "The hotel is situated in a nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts. The hotel also regularly hosts events like wine tastings, beer dinners, and live music.",
      "Category": "Boutique"
    },
    {
      "@search.score": 0.03154495730996132,
      "@search.rerankerScore": 2.2718777656555176,
      "HotelId": "1",
      "HotelName": "Stay-Kay City Hotel",
      "Description": "This classic hotel is fully-refurbished and ideally located on the main commercial artery of the city in the heart of New York. A few minutes away is Times Square and the historic center of the city, as well as other places of interest that make New York one of America's most attractive and cosmopolitan cities.",
      "Category": "Boutique"
    },
    {
      "@search.score": 0.03053613007068634,
      "@search.rerankerScore": 2.0582215785980225,
      "HotelId": "3",
      "HotelName": "Gastronomic Landscape Hotel",
      "Description": "The Gastronomic Hotel stands out for its culinary excellence under the management of William Dough, who advises on and oversees all of the Hotel\u2019s restaurant services.",
      "Category": "Suite"
    }
  ]
}

小提示

語意排名的結果可以包含更多詳細數據，包括語意答案、標題和醒目提示。 將更多參數新增至要求會產生額外的詳細數據。 如需詳細資訊，請參閱 設定語意查詢。

清除

使用您自己的訂用帳戶時，在專案結束後確認您是否還需要您建立的資源，是很好的做法。 讓資源繼續執行可能會產生費用。 您可以個別刪除資源，或刪除資源群組以刪除整組資源。

您可以使用 Azure 入口網站最左邊窗格中的 [所有資源] 或 [資源群組] 連結，來尋找和管理資源。

如果您想要保留搜尋服務，但刪除索引和文件，您可以在 REST 用戶端中使用 DELETE 命令。 這個命令 (在 az-search-vector-quickstart.rest 檔案結尾處) 會刪除 hotels-vector-quickstart 索引：

### Delete an index
DELETE  {{baseUrl}}/indexes/hotels-vector-quickstart?api-version=2024-07-01 HTTP/1.1
    Content-Type: application/json
    Authorization: Bearer {{token}}

後續步驟

在下一個步驟中，建議您了解如何在沒有 API 金鑰的情況下叫用 REST API 呼叫。

您也可以檢閱 Python、C# 或 JavaScript 的示範程式碼。