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In questa guida introduttiva si usa un notebook Jupyter per creare, caricare e interrogare vettori. Gli esempi di codice eseguono queste operazioni usando la libreria client di Ricerca intelligenza artificiale di Azure. La libreria fornisce un'astrazione sull'API REST per l'accesso alle operazioni sugli indici, ad esempio l'inserimento di dati, le operazioni di ricerca e le operazioni di gestione degli indici.
In Azure AI Search, un archivio vettoriale ha uno schema di indice che definisce campi vettoriali e non vettoriali, una configurazione di ricerca vettoriale per algoritmi che creano lo spazio di incorporamento e le impostazioni sulle definizioni di campo vettoriale valutate al momento di query. L'API REST Crea indice crea l'archivio vettoriale.
Note
Questo avvio rapido omette il passaggio di vettorializzazione e fornisce incorporamenti inline. Se si desidera aggiungere la suddivisione in blocchi e la vettorizzazione dei dati predefiniti sui propri contenuti, provare la procedura guidata Importare e vettorializzare i dati per una procedura dettagliata end-to-end.
Prerequisiti
Un account Azure con una sottoscrizione attiva. Creare un account gratuito.
Un servizio di Azure AI Search. Creare un servizio o trovare un servizio esistente nella sottoscrizione corrente.
- È possibile usare un servizio di ricerca gratuito per la maggior parte di questa guida introduttiva, ma è consigliabile usare il livello Basic o superiore per i file di dati di dimensioni maggiori.
- Per eseguire l'esempio di query che richiama il reranking semantico, il servizio di ricerca deve essere al livello Basic o superiore con semantic ranker abilitato.
Visual Studio Code con l'estensione Python e il pacchetto Jupyter.
Git per clonare il repository contenente il notebook jupyter e altri file correlati.
Recuperare informazioni sulla risorsa
Le richieste all'endpoint di ricerca devono essere autenticate e autorizzate. Sebbene sia possibile usare chiavi API o ruoli per questa attività, è consigliabile usare una connessione senza chiave tramite Microsoft Entra ID.
Questo quickstart utilizza DefaultAzureCredential
, che semplifica l'autenticazione sia in scenari di sviluppo che in quelli di produzione. Tuttavia, per gli scenari di produzione, potrebbero essere presenti requisiti più avanzati che richiedono un approccio diverso. Per informazioni su tutte le opzioni, vedere Autenticare le app Python nei servizi di Azure usando Azure SDK per Python .
Clonare il codice e l'ambiente di installazione
Clonare il repository contenente il codice per questa guida introduttiva.
git clone https://github.com/Azure-Samples/azure-search-python-samples
Questo repository include esempi di codice Python per diversi articoli ognuno in una sottocartella separata.
In Visual Studio Code aprire la sottocartella
Quickstart-Vector-Search
.In questa cartella sono presenti tre file:
vector-search-quickstart.ipynb
requirements.txt
sample.env
Rinominare il
sample.env
file.env
in e modificare i valori nel.env
file.Usare l'URL del servizio di ricerca come
AZURE_SEARCH_ENDPOINT
. È possibile trovare l'URL nel portale di Azure. Vai al servizio Ricerca intelligenza artificiale di Azure, nella pagina Panoramica, e cerca il campo URL. Un endpoint di esempio potrebbe essere simile ahttps://mydemo.search.windows.net
.Infine, scegliere un nuovo
AZURE_SEARCH_INDEX_NAME
nome o usare quello fornito nel file.In Visual Studio Code, lavori in un ambiente. Scegliere Terminale dal menu Visualizza oppure premere CTRL+`.
Eseguire i comandi seguenti nel terminale:
python -m venv .venv source .venv/scripts/activate where python
Note
Si presuppone che si usi Git Bash nel terminale e che sia in esecuzione in Windows. Se si usa una shell diversa e/o un sistema operativo diverso, modificare queste istruzioni per l'ambiente specifico.
Se richiesto, consentire a Visual Studio Code di usare il nuovo ambiente.
Il
where python
comando verifica che si stia lavorando dall'ambiente virtuale elencandopython.exe
laQuickstart-Vector-Search\.venv\
cartella e altri percorsi dalla directory del computer.Installare le librerie necessarie eseguendo il comando seguente:
pip install requirements.txt
In Visual Studio Code, apri il
vector-search-quickstart.ipynb
.Note
Se è la prima volta che è stato usato jupyter Notebook (con estensione ipynb) in Visual Studio Code, verrà richiesto di installare il kernel jupyter Notebook ed eventualmente altri strumenti. Scegliere di installare gli strumenti suggeriti per continuare con questa guida introduttiva.
Trovare la cella seguente intitolata "Install packages and set variables" (Installa pacchetti e impostare variabili) e selezionare il pulsante Esegui cella (CTRL + ALT + INVIO) (simile a un tipico pulsante di esecuzione) a sinistra della cella. L'esecuzione della cella carica le variabili di ambiente, crea DefaultAzureCredential e stampa i valori nell'output per verificare che le dipendenze del notebook e
.env
siano configurati correttamente.# 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
L'esecuzione di questa cella produce l'output seguente.
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 ...
Esistono molti altri pacchetti che è possibile visualizzare in un elemento scorrevole (vedere il messaggio sotto i risultati della cella).
Creare l'indice vettoriale
Il codice in vector-search-quickstart.ipynb
usa diversi metodi della azure.search.documents
libreria per creare l'indice vettoriale e i campi ricercabili.
Trovare la cella seguente intitolata "Creare un indice" ed eseguire la cella per creare l'indice.
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')
Se l'indice viene creato correttamente, viene visualizzato il risultato seguente sotto la cella:
vector-search-quickstart created
Considerazioni chiave durante la creazione dell'indice vettoriale con :
azure.search.documents
Per definire un indice, creare un elenco di campi. Ogni campo viene creato usando un metodo helper che definisce il tipo di campo e le relative impostazioni.
Questo particolare indice supporta più funzionalità di ricerca, ad esempio:
- Ricerca di parole chiave full-text (
SearchableField(name="HotelName", ...)
,SearchableField(name="Description", ...)
) - Ricerca vettoriale (abilita la ricerca ibrida collocando campi vettoriali e non vettoriali) (
DescriptionVector
) - Ricerca semantica (
semantic_search=SemanticSearch(configurations=[semantic_config])
) - Ricerca in base a facet (
facetable=True
) - Ricerca semantica (
semantic_search=SemanticSearch(configurations=[semantic_config])
) - Ricerca spaziale geografica (
Location
campo èGeographyPoint
) - Filtro, ordinamento (molti campi contrassegnati come filtrabili e ordinabili)
- Ricerca di parole chiave full-text (
Caricamento di documenti
La creazione e il caricamento dell'indice sono passaggi separati. Lo schema dell'indice è stato creato nel passaggio precedente. È ora necessario caricare i documenti nell'indice.
In Ricerca di intelligenza artificiale di Azure l'indice archivia tutto il contenuto ricercabile, mentre il motore di ricerca esegue query su tale indice.
Trovare la cella nella sezione intitolata "Creare il payload dei documenti" ed eseguirla. Questa cella contiene il codice seguente (troncato per brevità):
# 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> ]
Questa cella carica una variabile denominata
documents
con un oggetto JSON che descrive ogni documento, insieme alla versione vettorializzata della descrizione dell'articolo. Questo vettore abilita la ricerca di somiglianza, in cui la corrispondenza si basa sul significato anziché sulle parole chiave esatte.Importante
Il codice in questo esempio non è eseguibile. Diversi caratteri o righe vengono rimossi a fini di brevità. Eseguire invece il codice nel notebook di Jupyter.
Trovare la cella nella sezione intitolata "Caricare i documenti" ed eseguirla. Questa cella contiene il codice seguente (troncato per brevità):
# 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)
In questo modo viene creata un'istanza del client di ricerca chiamando il
SearchClient()
costruttore , quindi viene chiamato ilupload_documents()
metodo sull'oggetto .Dopo aver eseguito la cella, lo stato di ogni documento viene stampato sotto di essa:
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
Considerazioni chiave sul
upload_documents()
metodo e questo esempio:Il codice interagisce con un indice di ricerca specifico ospitato nel servizio Ricerca intelligenza artificiale di Azure tramite
SearchClient
, che è l'oggetto principale fornito dalazure-search-documents
pacchetto.SearchClient
fornisce l'accesso alle operazioni sugli indici, ad esempio:- Inserimento -
upload_documents()
dati,merge_documents()
,delete_documents()
e così via. - Operazioni -
search()
di ricerca,autocomplete()
,suggest()
- Operazioni di gestione degli indici
- Inserimento -
I campi vettoriali contengono valori a virgola mobile. L'attributo dimensions ha un minimo di 2 e un massimo di 4096 valori a virgola mobile ciascuno. Questo argomento di avvio rapido imposta l'attributo dimensions su 1.536 perché è la dimensione degli incorporamenti generati dal modello text-embedding-ada-002 di Azure OpenAI.
Eseguire le query
Ora che i documenti vengono caricati, è possibile eseguire query vettoriali su di esse chiamando search_client.search()
e passando un oggetto VectorizedQuery, i campi restituiti, il numero di risultati e così via.
Nelle sezioni successive vengono eseguite query sull'indice hotels-vector-quickstart
. Le query includono:
- Ricerca a vettore singolo
- Ricerca a vettore singolo con filtro
- Ricerca ibrida
- Ricerca semantica ibrida con filtro
Creare la stringa di query vettoriale
Le query vettoriali di esempio si basano su due stringhe:
- Stringa di ricerca:
historic hotel walk to restaurants and shopping
- Stringa di query vettoriale (vettorializzata in una rappresentazione matematica):
quintessential lodging near running trails, eateries, retail
La stringa di query vettoriale è semanticamente simile alla stringa di ricerca, ma include termini che non esistono nell'indice di ricerca. Se si esegue una ricerca di parole chiave per quintessential lodging near running trails, eateries, retail
, i risultati sono zero. Questo esempio viene usato per mostrare come ottenere risultati pertinenti anche se non sono presenti termini corrispondenti.
- Trovare la cella nella sezione intitolata "Creare la stringa di query vettoriale" ed eseguirla. Questa carica la variabile
vector
con i dati di query vettorializzati necessari per eseguire tutte le ricerche nelle sezioni successive.
Ricerca vettoriale singola
Il primo esempio illustra uno scenario di base in cui si desidera trovare descrizioni di documenti che corrispondano strettamente alla stringa di ricerca.
Trova la cella sotto la sezione intitolata "Ricerca vettore singolo" ed esegui la cella. Questo blocco contiene la richiesta di eseguire query sull'indice di ricerca.
# 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.")
Questa query vettoriale viene abbreviata per motivi di brevità. Il
vectorQueries.vector
contiene il testo vettorializzato dell'input della query,fields
determina quali campi vettoriali vengono ricercati ek
specifica il numero di vicini più prossimi da restituire.La stringa di query vettoriale è
quintessential lodging near running trails, eateries, retail
, che viene vettorializzata in 1.536 incorporamenti per questa query.La risposta per l'equivalente vettore di
quintessential lodging near running trails, eateries, retail
include sette risultati, ma il codice specifica in modo che vengano restituititop=5
solo i primi cinque risultati. Inoltre, vengono restituiti solo i campi specificati daselect
.search_client.search()
restituisce un oggetto dict-like. Ogni risultato fornisce un punteggio di ricerca accessibile tramitescore = result.get("@search.score", "N/A")
. Anche se non viene visualizzato in questo esempio, in una ricerca di somiglianza, la risposta includek
sempre i risultati ordinati in base al punteggio di somiglianza del valore.Dopo aver eseguito la cella, lo stato di ogni documento viene stampato sotto di essa:
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
Ricerca vettoriale singola con filtro
È possibile aggiungere filtri, ma i filtri vengono applicati al contenuto non di filtro nell'indice. In questo esempio, il filtro si applica al campo Tags
per filtrare tutti gli hotel che non forniscono il Wi-Fi gratuito.
Trovare la cella seguente intitolata "Ricerca a vettore singolo con filtro" ed eseguire la cella. Questa cella contiene la richiesta di eseguire una query sull'indice di ricerca.
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.")
Dopo aver eseguito la cella, lo stato di ogni documento viene stampato sotto di essa:
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']
La query è la stessa dell'esempio di ricerca vettoriale singola precedente, ma include un filtro di esclusione post-elaborazione e restituisce solo i tre hotel che dispongono di Wi-Fi gratuito.
Nell'esempio di filtro successivo viene usato un filtro geografico. Eseguire la cella nella sezione intitolata "Query vettoriale con un filtro geografico". Questo blocco contiene la richiesta di eseguire query sull'indice di ricerca.
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.")
La query corrisponde all'esempio di ricerca a vettore singolo precedente, ma include un filtro di esclusione post-elaborazione e restituisce solo i due hotel entro 300 chilometri.
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.
Ricerca ibrida
La ricerca ibrida è costituita da query con parole chiave e query vettoriali in una singola richiesta di ricerca. Questo esempio esegue simultaneamente la query vettoriale e la ricerca full-text:
Stringa di ricerca:
historic hotel walk to restaurants and shopping
Stringa di query vettoriale (vettorializzata in una rappresentazione matematica):
quintessential lodging near running trails, eateries, retail
Trova la cella sotto la sezione intitolata "Ricerca ibrida" ed esegui la cella. Questo blocco contiene la richiesta di eseguire query sull'indice di ricerca.
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.")
Esaminare la risposta:
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']
Poiché la Fusione del Rank Reciproco (RRF) unisce i risultati, aiuta a esaminare gli input. I risultati seguenti provengono solo dalla query full-text. I primi due risultati sono Sublime Palace Hotel e History Lion Resort. Il Sublime Palace Hotel ha un punteggio di pertinenza BM25 più elevato.
{ "@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" },
Nella query di solo vettore, che usa HNSW per trovare corrispondenze, sublime Palace Hotel scende alla quarta posizione. Historic Lion, secondo nella ricerca full-text e terzo nella ricerca vettoriale, non riscontra lo stesso intervallo di fluttuazione, quindi appare come una corrispondenza principale in un set di risultati omogeneizzato.
"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" } ]
Ricerca semantica ibrida con un filtro
Ecco l'ultima query della raccolta. Questa query ibrida con classificazione semantica viene filtrata per mostrare solo gli hotel entro un raggio di 500 chilometri da Washington D.C. È possibile impostare vectorFilterMode
su Null, che equivale al valore predefinito (preFilter
per gli indici più recenti e postFilter
per quelli meno recenti).
Trovare la cella seguente intitolata "Ricerca ibrida semantica" ed eseguire la cella. Questo blocco di codice contiene la richiesta di eseguire una query sull'indice di ricerca.
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.")
Esaminare l'output sotto la cella. La risposta è costituita da tre hotel, filtrati in base alla posizione e facet in base a
StateProvince
, e classificati in modo semantico per alzare di livello i risultati più vicini alla query della stringa di ricerca (historic hotel walk to restaurants and shopping
).L'Hotel Swirling Currents ora si sposta al primo posto. Senza classifica semantica, Il Nordick's Valley Hotel è il numero uno. Con la classificazione semantica, i modelli di comprensione della macchina riconoscono che
historic
si applica a "hotel, a pochi passi da ristoranti e negozi".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
Aspetti chiave:
La ricerca vettoriale viene specificata tramite la proprietà
vectors.value
. La ricerca di parole chiave viene specificata tramite la proprietàsearch
.In una ricerca ibrida è possibile integrare la ricerca vettoriale con la ricerca full-text sulle parole chiave. I filtri, il controllo ortografico e la classificazione semantica si applicano solo ai contenuti testuali e non ai vettori. In questa query finale non esiste un
answer
semantico perché il sistema non ha prodotto una query sufficientemente forte.I risultati effettivi includono più dettagli, tra cui didascalie semantiche ed evidenziazioni. I risultati sono stati modificati per la leggibilità. Per ottenere la struttura completa della risposta, eseguire la richiesta nel client REST.
Eseguire la pulizia
Quando si lavora nella propria sottoscrizione, alla fine di un progetto è opportuno verificare se le risorse create sono ancora necessarie. L'esecuzione continua delle risorse può avere un costo. È possibile eliminare le singole risorse oppure il gruppo di risorse per eliminare l'intero set di risorse.
È possibile trovare e gestire le risorse nel portale di Azure usando il collegamento Tutte le risorse o Gruppi di risorse nel riquadro più a sinistra.
Se si desidera mantenere il servizio di ricerca, ma eliminare l'indice e i documenti, è possibile usare il SearchIndexClient
metodo dell'oggetto delete_index()
. Trovare la cella sotto la sezione intitolata "Pulizia" ed eseguire la cella se si vuole eliminare l'indice hotels-vector-quickstart
.
index_client.delete_index(index_name)
print(f"Index '{index_name}' deleted successfully.")
Passaggi successivi
- Esamina il repository di esempi di codice per le funzionalità di ricerca vettoriale in Azure AI Search per Python
- Esamina gli altri esempi di codice Python e Ricerca AI di Azure nel repository azure-search-python-samples
In questa guida introduttiva si usano le API REST di Ricerca Intelligenza Artificiale di Azure per creare, caricare ed eseguire query sui vettori.
In Azure AI Search, un archivio vettoriale ha uno schema di indice che definisce campi vettoriali e non vettoriali, una configurazione di ricerca vettoriale per algoritmi che creano lo spazio di incorporamento e le impostazioni sulle definizioni di campo vettoriale valutate al momento di query. L'API REST Crea indice crea l'archivio vettoriale.
Note
Questo avvio rapido omette il passaggio di vettorializzazione e fornisce incorporamenti inline. Se si desidera aggiungere la suddivisione in blocchi e la vettorizzazione dei dati predefiniti sui propri contenuti, provare la procedura guidata Importare e vettorializzare i dati per una procedura dettagliata end-to-end.
Prerequisiti
Un account Azure con una sottoscrizione attiva. Creare un account gratuito.
Un servizio di Azure AI Search. Creare un servizio o trovare un servizio esistente nella sottoscrizione corrente.
- È possibile usare un servizio di ricerca gratuito per la maggior parte di questa guida introduttiva, ma è consigliabile usare il livello Basic o superiore per i file di dati di dimensioni maggiori.
- Per eseguire l'esempio di query che richiama il reranking semantico, il servizio di ricerca deve essere al livello Basic o superiore con semantic ranker abilitato.
Visual Studio Code con un client REST.
Recuperare informazioni sulla risorsa
Le richieste all'endpoint di ricerca devono essere autenticate e autorizzate. È possibile usare chiavi API o ruoli per questa attività. È consigliabile usare una connessione senza chiave tramite Microsoft Entra ID.
Selezionare la scheda corrispondente al metodo di autenticazione preferito. Usare lo stesso metodo per tutte le richieste in questo argomento di avvio rapido.
Accedere al portale di Azure e trovare il servizio di ricerca.
Nella home page Panoramica trovare l'URL. Un endpoint di esempio potrebbe essere simile a
https://mydemo.search.windows.net
.Seguire i passaggi dell'avvio rapido senza chiave per ottenere il token Microsoft Entra.
Il token viene ottenuto quando si esegue il comando
az account get-access-token
nel passaggio 3 dell'avvio rapido precedente.az account get-access-token --scope https://search.azure.com/.default --query accessToken --output tsv
Creare o scaricare il file di codice
Si usa un file .rest
o .http
per eseguire tutte le richieste in questo avvio rapido. È possibile scaricare il file REST contenente il codice per questo avvio rapido oppure creare un nuovo file in Visual Studio Code e copiarvi il codice.
In Visual Studio Code, creare un nuovo file con un'estensione
.rest
o.http
. Ad esempio:az-search-vector-quickstart.rest
. Copiare e incollare il contenuto non elaborato del file Azure-Samples/azure-search-rest-samples/blob/main/Quickstart-vectors/az-search-vector-quickstart.rest in questo nuovo file.Nella parte superiore del file, sostituire il valore segnaposto per
@baseUrl
con l'URL del servizio di ricerca. Per istruzioni su come trovare l'URL del servizio di ricerca, vedere la sezione Recuperare le informazioni sulla risorsa.@baseUrl = PUT-YOUR-SEARCH-SERVICE-URL-HERE
Nella parte superiore del file, sostituire il valore segnaposto per l'autenticazione. Vedere la sezione Recuperare informazioni sulla risorsa per istruzioni su come ottenere il token o la chiave API di Microsoft Entra.
Per l'autenticazione senza chiave tramite Microsoft Entra ID consigliata, è necessario sostituire
@apiKey
con la variabile@token
.@token = PUT-YOUR-MICROSOFT-ENTRA-TOKEN-HERE
Se si preferisce usare una chiave API, sostituire
@apiKey
con la chiave copiata dal portale di Azure.@apiKey = PUT-YOUR-ADMIN-KEY-HERE
Per l'autenticazione senza chiave tramite Microsoft Entra ID consigliata, è necessario sostituire
api-key: {{apiKey}}
conAuthorization: Bearer {{token}}
nelle intestazioni della richiesta. Sostituire tutte le istanze diapi-key: {{apiKey}}
che si trovano nel file.
Creare un indice vettoriale
Usare l'API REST Crea indice per creare un indice vettoriale e configurare le strutture di dati fisiche nel servizio di ricerca.
Lo schema dell’indice in questo esempio è organizzato attorno al contenuto su hotel. I dati di esempio sono costituiti da descrizioni vettoriali e non vettoriali di hotel fittizi. Questo schema include configurazioni per l'indicizzazione vettoriale e le query e per la classificazione semantica.
In Visual Studio Code, aprire il file
az-search-vector-quickstart.rest
creato in precedenza.Trovare il blocco di codice
### Create a new index
nel file. Questo blocco contiene la richiesta di creare l'indicehotels-vector-quickstart
nel servizio di ricerca.### 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" } ] } } ] } }
Selezionare Invia richiesta. Si dovrebbe avere una risposta
HTTP/1.1 201 Created
.Il corpo della risposta deve includere la rappresentazione JSON dello schema dell'indice.
{ "@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" } ] } } ] } }
Considerazioni chiave sull'API REST Crea indice:
La raccolta
fields
include un campo chiave obbligatorio e campi di testo e vettore (ad esempioDescription
eDescriptionVector
) per la ricerca di testo e vettoriale. Il colocating di campi vettoriali e non vettoriali nello stesso indice consente query ibride. Ad esempio, è possibile combinare filtri, ricerca di testo con classificazione semantica e vettori in una singola operazione di query.I campi vettoriali devono essere uno dei tipi di dati EDM usati per i vettori, ad esempio
type: Collection(Edm.Single)
. I campi vettoriali hanno anche le proprietàdimensions
evectorSearchProfile
.La sezione
vectorSearch
è una matrice di configurazioni e profili approssimativi dell'algoritmo adiacente più vicino. Gli algoritmi supportati includono piccoli mondi navigabili gerarchici e vicini più prossimi k esaustivi. Per altre informazioni, vedere Assegnazione dei punteggi per pertinenza nella ricerca vettoriale.La configurazione
semantic
(facoltativa) consente di eseguire il reranking dei risultati della ricerca. È possibile eseguire il reranking dei risultati nelle query di tiposemantic
per i campi stringa specificati nella configurazione. Per altre informazioni, vedere Panoramica della classificazione semantica.
Caricamento di documenti
La creazione e il caricamento dell'indice sono passaggi separati. Lo schema dell'indice è stato creato nel passaggio precedente. È ora necessario caricare i documenti nell'indice.
In Ricerca di intelligenza artificiale di Azure l'indice contiene tutti i dati e le query ricercabili eseguiti nel servizio di ricerca. Per le chiamate REST, i dati vengono forniti come documenti JSON. Usare l'API REST Documents- Index per questa attività. L'URI viene esteso per includere la raccolta docs
e l'operazione index
.
Formulare una richiesta di caricamento di documenti per caricare documenti sull'indice del
hotels-vector-quickstart
servizio di ricerca.### 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.", "DescriptionVector": 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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": [ -82.452843, 27.384417 ] } }, { "@search.action": "mergeOrUpload", "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.", "DescriptionVector": 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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.", "DescriptionVector": 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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.", "DescriptionVector": 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"Category": "Boutique", "Tags": [ "continental breakfast", "air conditioning", "free wifi" ], "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" }, "Location": { "type": "Point", "coordinates": [ -77.03241, 38.90166 ], "crs": { "type": "name", "properties": { "name": "EPSG:4326" } } } }, { "@search.action": "mergeOrUpload", "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.", "DescriptionVector": 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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.", "DescriptionVector": 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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" } } } } ] }
Selezionare Invia richiesta. Si dovrebbe avere una risposta
HTTP/1.1 200 OK
. Il corpo della risposta deve includere la rappresentazione JSON dei documenti di ricerca.
Aspetti chiave sulla richiesta Documenti - API REST Indice:
I documenti nel payload sono costituiti da campi definiti nello schema dell'indice.
I campi vettoriali contengono valori a virgola mobile. L'attributo dimensions ha un minimo di 2 e un massimo di
4096
valori a virgola mobile ciascuno. Questo avvio rapido imposta l'attributo dimensioni su 1.536, poiché si tratta delle dimensioni degli incorporamenti generati dal modello text-embedding-3-small di Azure OpenAI.
Eseguire le query
Ora che i documenti vengono caricati, è possibile eseguire query vettoriali su di esse usando Documenti - Post di ricerca (REST).
Nelle sezioni successive vengono eseguite query sull'indice hotels-vector-quickstart
. Le query includono:
- Ricerca vettoriale singola
- Ricerca vettoriale singola con filtro
- Ricerca ibrida
- Ricerca ibrida semantica
Le query di esempio sono basate su due stringhe:
- Stringa di ricerca:
historic hotel walk to restaurants and shopping
- Stringa di query vettoriale (vettorializzata in una rappresentazione matematica):
quintessential lodging near running trails, eateries, retail
La stringa di query vettoriale è semanticamente simile alla stringa di ricerca, ma include termini che non esistono nell'indice di ricerca. Se si esegue una ricerca di parole chiave per quintessential lodging near running trails, eateries, retail
, i risultati sono zero in una ricerca di parole chiave pura senza classificazione semantica. Questo esempio viene usato per mostrare come ottenere risultati pertinenti usando vettori, anche se non sono presenti termini corrispondenti.
Ricerca vettoriale singola
Formulare la richiesta. La query è una rappresentazione in virgola mobile a 1536 dimensioni di alloggio ideale vicino a sentieri per correre, ristoranti, vendita al dettaglio. La query esegue la ricerca in
DescriptionVector
e restituisce i risultati k-5.### 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": [ { "vector"": 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"k": 5, "fields": "DescriptionVector", "kind": "vector", "exhaustive": true } ] }
Considerazioni chiave sull'API REST Documenti - Cerca post:
vectorQueries.vector
è la stringa di query vettoriale. Si tratta di una rappresentazione vettoriale di alloggi tipici vicino a sentieri per correre, ristoranti, negozi, che è vettorizzato in 1.536 incorporamenti per questa query.fields
determina i campi vettoriali in cui viene eseguita la ricerca.kind
impostato suvector
significa che la stringa di query è un vettore. Sekind
è stato impostato sutext
, è necessaria una funzionalità aggiuntiva (un vettore) per codificare una stringa di testo leggibile in un vettore in fase di query. I vettorizzatori sono stati omessi da questa guida introduttiva per semplificare l'esercizio.k
specifica il numero di vicini più vicini da restituire nella risposta. Uncount
parametro specifica il numero di corrispondenze trovate nell'indice. L'inclusione del conteggio è una procedura consigliata per le query, ma è meno utile per la ricerca di somiglianza in cui l'algoritmo può trovare un certo grado di somiglianza in quasi tutti i documenti.
Selezionare Invia richiesta. Si dovrebbe avere una risposta
HTTP/1.1 200 OK
. Il corpo della risposta deve includere la rappresentazione JSON dei risultati della ricerca.La risposta per il vettore equivalente di
quintessential lodging near running trails, eateries, retail
include i risultati k-5, anche se il motore di ricerca ha trovato 7 corrispondenze. I risultati principali sono considerati i più semanticamente simili alla query. Ogni risultato fornisce un punteggio di ricerca e i campi elencati inselect
. In una ricerca di somiglianza, la risposta include sempre risultatik
ordinati in base al punteggio di somiglianza del valore.{ "@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" ] } ] }
Ricerca a vettore singolo con filtro
È possibile aggiungere filtri, ma i filtri vengono applicati al contenuto non di filtro nell'indice. In questo esempio, il filtro si applica al campo Tags
per filtrare tutti gli hotel che non forniscono il Wi-Fi gratuito.
Formulare la richiesta. Questa è la stessa richiesta di quella precedente, con un filtro aggiuntivo e un parametro della modalità filtro.
### 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 }, ] }
Selezionare Invia richiesta. Si dovrebbe avere una risposta
HTTP/1.1 200 OK
. Il corpo della risposta deve includere la rappresentazione JSON dei risultati della ricerca.La query corrisponde all'esempio di ricerca a vettore singolo precedente, ma include un filtro di esclusione post-elaborazione e restituisce solo i due hotel che dispongono di Wi-Fi gratuito.
{ "@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" ] } ] }
Ecco un'altra query che usa un filtro geografico, limitando i risultati agli hotel entro 300 chilometri intorno a Washington D.C.
### 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 }, ] }
Esaminare la risposta. È limitata a due hotel vicino a Washington D.C, con una struttura facet che fornisce l'aggregazione.
"@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" } } ]
Ricerca ibrida
La ricerca ibrida è costituita da query con parole chiave e query vettoriali in una singola richiesta di ricerca. Questo esempio esegue simultaneamente la query vettoriale e la ricerca full-text:
- Stringa di ricerca:
historic hotel walk to restaurants and shopping
- Stringa di query vettoriale (vettorializzata in una rappresentazione matematica):
quintessential lodging near running trails, eateries, retail
Formulare la query ibrida.
### 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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Selezionare Invia richiesta. Si dovrebbe avere una risposta
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. Il corpo della risposta deve includere la rappresentazione JSON dei risultati della ricerca.
Poiché si tratta di una query ibrida, i risultati vengono classificati in base al valore RRF (Reciprocal Rank Fusion). Si noti che @search.score
i valori hanno una base diversa e sono valori uniformemente più piccoli. RRF valuta i punteggi di ricerca di più risultati di ricerca, accetta l'inverso e quindi unisce e ordina i risultati combinati. Viene restituito il numero top
di risultati.
Esaminare la risposta, costituita dalle prime 5 corrispondenze di 7 documenti corrispondenti nell'indice:
{
"@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."
}
]
}
Poiché RRF unisce i risultati, consente di esaminare gli input singolarmente.
I seguenti risultati provengono dalla parte full-text della query: hotel storico situato a breve distanza da ristoranti e negozi. Nella query full-text i primi tre risultati sono Sublime Palace Hotel, Stay-Kay City Hotel e Luxury Lion Resort. Il Sublime Palace Hotel ha un punteggio di pertinenza BM25 più elevato. Nella query fusa, solo due di queste corrispondenze vengono visualizzate nei primi 3 risultati mentre la seconda corrispondenza (Stay-Kay City Hotel) non è visualizzata nei primi 5 risultati.
"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."
},
...
]
Nella query della parte vettoriale (sistemazione ideale vicino a percorsi per corsa, ristoranti, negozi) è una stringa diversa, quindi dovremmo aspettarci risultati diversi. Questa query restituisce Nordick's Valley Motel, Luxury Lion Resort e Sublime Palace Hotel come prime tre corrispondenze. Nella query fusa, questi risultati vengono visualizzati nei primi 3, ma in ordine inverso.
"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."
},
...
]
Ricerca semantica ibrida
Ecco l'ultima query della raccolta. Questa query ibrida aggiunge una classificazione semantica di livello L2 che applica la comprensione automatica del testo sui risultati classificati a livello L1, promuovendo corrispondenze più rilevanti in cima.
Formulare la richiesta.
### 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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Selezionare Invia richiesta. Si dovrebbe avere una risposta
HTTP/1.1 200 OK
. Il corpo della risposta deve includere la rappresentazione JSON dei risultati della ricerca.
Esaminare la risposta, costituita da una riclassificazione semantica dei risultati classificati dall'algoritmo RRF della query ibrida. La classificazione semantica si basa sugli input di testo. In una query di testo o ibrida, questo input è la parte di testo della query (passeggiata dell'hotel storico per ristoranti e negozi). Per usare la classificazione semantica in una query vettoriale pura, ad esempio il primo esempio o per controllare in modo esplicito il testo usato per la classificazione semantica, fornire una stringa semanticQuery.
Dopo il reranking semantico, Swirling Currents Hotel con il suo riferimento a accesso a piedi a shopping, ristoranti, intrattenimento e il centro cittadino si posiziona al primo posto. Il modello di comprensione automatico promuove la breve distanza da negozi e ristoranti come corrispondenza più stretta rispetto a raggiungere ristoranti e negozi a piedi.
Prima del riordinamento semantico, Sublime Palace, con il suo riferimento a essere a pochi passi dai siti e dai luoghi d'interesse della città, circondato dalla straordinaria bellezza di chiese, edifici, negozi e monumenti, era al primo posto.
{
"@odata.count": 7,
"@search.answers": [],
"value": [
{
"@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"
}
]
}
Suggerimento
I risultati classificati semanticamente possono includere più dettagli, tra cui risposte semantiche, sottotitoli ed evidenziazioni. L'aggiunta di altri parametri alla richiesta produce i dettagli aggiuntivi. Per altre informazioni, vedere Configurare una query semantica.
Eseguire la pulizia
Quando si lavora nella propria sottoscrizione, alla fine di un progetto è opportuno verificare se le risorse create sono ancora necessarie. L'esecuzione continua delle risorse può avere un costo. È possibile eliminare le singole risorse oppure il gruppo di risorse per eliminare l'intero set di risorse.
È possibile trovare e gestire le risorse nel portale di Azure usando il collegamento Tutte le risorse o Gruppi di risorse nel riquadro più a sinistra.
Se si vuole conservare il servizio di ricerca, ma eliminare l'indice e i documenti, è possibile usare il comando DELETE
nel client REST. Questo comando (alla fine del file az-search-vector-quickstart.rest
) elimina l'indice hotels-vector-quickstart
:
### Delete an index
DELETE {{baseUrl}}/indexes/hotels-vector-quickstart?api-version=2024-07-01 HTTP/1.1
Content-Type: application/json
Authorization: Bearer {{token}}
Passaggi successivi
Come passaggio successivo, è consigliabile imparare a richiamare le chiamate API REST senza chiavi API.
È anche possibile esaminare il codice demo per Python, C# o JavaScript.