Stap 4: De .NET-zoekcode verkennen
In de vorige lessen hebt u zoekopdrachten toegevoegd aan een statische web-app. In deze les worden de essentiƫle stappen beschreven waarmee integratie tot stand wordt gebracht. Als u op zoek bent naar een cheatsheet over het integreren van zoekopdrachten in uw web-app, wordt in dit artikel uitgelegd wat u moet weten.
Azure SDK Azure.Search.Documents
De functie-app maakt gebruik van de Azure SDK voor Azure AI Search:
- NuGet: Azure.Search.Documents
- Referentiedocumentatie: Clientbibliotheek
De functie-app wordt geverifieerd via de SDK voor de Azure AI Search-API in de cloud met behulp van uw resourcenaam, resourcesleutel en indexnaam. De geheimen worden opgeslagen in de instellingen van de statische web-app en opgehaald naar de functie als omgevingsvariabelen.
Geheimen configureren in een local.settings.json-bestand
{
"IsEncrypted": false,
"Values": {
"AzureWebJobsStorage": "",
"FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
"SearchApiKey": "",
"SearchServiceName": "",
"SearchIndexName": "good-books"
},
"Host": {
"CORS": "*"
}
}
Azure-functie: de catalogus doorzoeken
De zoek-API gebruikt een zoekterm en zoekt in de documenten in de zoekindex en retourneert een lijst met overeenkomsten.
De Azure-functie haalt de zoekconfiguratiegegevens op en voldoet aan de query.
using Azure;
using Azure.Core.Serialization;
using Azure.Search.Documents;
using Azure.Search.Documents.Models;
using Microsoft.Azure.Functions.Worker;
using Microsoft.Azure.Functions.Worker.Http;
using Microsoft.Extensions.Logging;
using System.Net;
using System.Text.Json;
using System.Text.Json.Serialization;
using WebSearch.Models;
using SearchFilter = WebSearch.Models.SearchFilter;
namespace WebSearch.Function
{
public class Search
{
private static string searchApiKey = Environment.GetEnvironmentVariable("SearchApiKey", EnvironmentVariableTarget.Process);
private static string searchServiceName = Environment.GetEnvironmentVariable("SearchServiceName", EnvironmentVariableTarget.Process);
private static string searchIndexName = Environment.GetEnvironmentVariable("SearchIndexName", EnvironmentVariableTarget.Process) ?? "good-books";
private readonly ILogger<Lookup> _logger;
public Search(ILogger<Lookup> logger)
{
_logger = logger;
}
[Function("search")]
public async Task<HttpResponseData> RunAsync(
[HttpTrigger(AuthorizationLevel.Anonymous, "post")] HttpRequestData req,
FunctionContext executionContext)
{
string requestBody = await new StreamReader(req.Body).ReadToEndAsync();
var data = JsonSerializer.Deserialize<RequestBodySearch>(requestBody);
// Azure AI Search
Uri serviceEndpoint = new($"https://{searchServiceName}.search.windows.net/");
SearchClient searchClient = new(
serviceEndpoint,
searchIndexName,
new AzureKeyCredential(searchApiKey)
);
SearchOptions options = new()
{
Size = data.Size,
Skip = data.Skip,
IncludeTotalCount = true,
Filter = CreateFilterExpression(data.Filters)
};
options.Facets.Add("authors");
options.Facets.Add("language_code");
SearchResults<SearchDocument> searchResults = searchClient.Search<SearchDocument>(data.SearchText, options);
var facetOutput = new Dictionary<string, IList<FacetValue>>();
foreach (var facetResult in searchResults.Facets)
{
facetOutput[facetResult.Key] = facetResult.Value
.Select(x => new FacetValue { value = x.Value.ToString(), count = x.Count })
.ToList();
}
// Data to return
var output = new SearchOutput
{
Count = searchResults.TotalCount,
Results = searchResults.GetResults().ToList(),
Facets = facetOutput
};
var response = req.CreateResponse(HttpStatusCode.Found);
// Serialize data
var serializer = new JsonObjectSerializer(
new JsonSerializerOptions(JsonSerializerDefaults.Web));
await response.WriteAsJsonAsync(output, serializer);
return response;
}
public static string CreateFilterExpression(List<SearchFilter> filters)
{
if (filters is null or { Count: <= 0 })
{
return null;
}
List<string> filterExpressions = new();
List<SearchFilter> authorFilters = filters.Where(f => f.field == "authors").ToList();
List<SearchFilter> languageFilters = filters.Where(f => f.field == "language_code").ToList();
List<string> authorFilterValues = authorFilters.Select(f => f.value).ToList();
if (authorFilterValues.Count > 0)
{
string filterStr = string.Join(",", authorFilterValues);
filterExpressions.Add($"{"authors"}/any(t: search.in(t, '{filterStr}', ','))");
}
List<string> languageFilterValues = languageFilters.Select(f => f.value).ToList();
foreach (var value in languageFilterValues)
{
filterExpressions.Add($"language_code eq '{value}'");
}
return string.Join(" and ", filterExpressions);
}
}
}
Client: Zoeken vanuit de catalogus
Roep de Azure-functie aan in de React-client met de volgende code.
import React, { useEffect, useState } from 'react';
import axios from 'axios';
import CircularProgress from '@mui/material/CircularProgress';
import { useLocation, useNavigate } from "react-router-dom";
import Results from '../../components/Results/Results';
import Pager from '../../components/Pager/Pager';
import Facets from '../../components/Facets/Facets';
import SearchBar from '../../components/SearchBar/SearchBar';
import "./Search.css";
export default function Search() {
let location = useLocation();
const navigate = useNavigate();
const [ results, setResults ] = useState([]);
const [ resultCount, setResultCount ] = useState(0);
const [ currentPage, setCurrentPage ] = useState(1);
const [ q, setQ ] = useState(new URLSearchParams(location.search).get('q') ?? "*");
const [ top ] = useState(new URLSearchParams(location.search).get('top') ?? 8);
const [ skip, setSkip ] = useState(new URLSearchParams(location.search).get('skip') ?? 0);
const [ filters, setFilters ] = useState([]);
const [ facets, setFacets ] = useState({});
const [ isLoading, setIsLoading ] = useState(true);
let resultsPerPage = top;
useEffect(() => {
setIsLoading(true);
setSkip((currentPage-1) * top);
const body = {
q: q,
top: top,
skip: skip,
filters: filters
};
axios.post( '/api/search', body)
.then(response => {
console.log(JSON.stringify(response.data))
setResults(response.data.results);
setFacets(response.data.facets);
setResultCount(response.data.count);
setIsLoading(false);
} )
.catch(error => {
console.log(error);
setIsLoading(false);
});
}, [q, top, skip, filters, currentPage]);
// pushing the new search term to history when q is updated
// allows the back button to work as expected when coming back from the details page
useEffect(() => {
navigate('/search?q=' + q);
setCurrentPage(1);
setFilters([]);
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [q]);
let postSearchHandler = (searchTerm) => {
//console.log(searchTerm);
setQ(searchTerm);
}
var body;
if (isLoading) {
body = (
<div className="col-md-9">
<CircularProgress />
</div>);
} else {
body = (
<div className="col-md-9">
<Results documents={results} top={top} skip={skip} count={resultCount}></Results>
<Pager className="pager-style" currentPage={currentPage} resultCount={resultCount} resultsPerPage={resultsPerPage} setCurrentPage={setCurrentPage}></Pager>
</div>
)
}
return (
<main className="main main--search container-fluid">
<div className="row">
<div className="col-md-3">
<div className="search-bar">
<SearchBar postSearchHandler={postSearchHandler} q={q}></SearchBar>
</div>
<Facets facets={facets} filters={filters} setFilters={setFilters}></Facets>
</div>
{body}
</div>
</main>
);
}
Azure Function: Suggesties uit de catalogus
De Suggestie-API gebruikt een zoekterm terwijl een gebruiker typt en zoektermen zoals boektitels en auteurs in de documenten in de zoekindex voorstelt, en retourneert een kleine lijst met overeenkomsten.
De zoeksugger, sg
wordt gedefinieerd in het schemabestand dat wordt gebruikt tijdens het bulksgewijs uploaden.
using Azure;
using Azure.Core.Serialization;
using Azure.Search.Documents;
using Azure.Search.Documents.Models;
using Microsoft.Azure.Functions.Worker;
using Microsoft.Azure.Functions.Worker.Http;
using Microsoft.Extensions.Logging;
using System.Net;
using System.Text.Json;
using WebSearch.Models;
namespace WebSearch.Function
{
public class Suggest
{
private static string searchApiKey = Environment.GetEnvironmentVariable("SearchApiKey", EnvironmentVariableTarget.Process);
private static string searchServiceName = Environment.GetEnvironmentVariable("SearchServiceName", EnvironmentVariableTarget.Process);
private static string searchIndexName = Environment.GetEnvironmentVariable("SearchIndexName", EnvironmentVariableTarget.Process) ?? "good-books";
private readonly ILogger<Lookup> _logger;
public Suggest(ILogger<Lookup> logger)
{
_logger = logger;
}
[Function("suggest")]
public async Task<HttpResponseData> RunAsync(
[HttpTrigger(AuthorizationLevel.Anonymous, "post")] HttpRequestData req,
FunctionContext executionContext)
{
// Get Document Id
string requestBody = await new StreamReader(req.Body).ReadToEndAsync();
var data = JsonSerializer.Deserialize<RequestBodySuggest>(requestBody);
// Azure AI Search
Uri serviceEndpoint = new($"https://{searchServiceName}.search.windows.net/");
SearchClient searchClient = new(
serviceEndpoint,
searchIndexName,
new AzureKeyCredential(searchApiKey)
);
SuggestOptions options = new()
{
Size = data.Size
};
var suggesterResponse = await searchClient.SuggestAsync<BookModel>(data.SearchText, data.SuggesterName, options);
// Data to return
var searchSuggestions = new Dictionary<string, List<SearchSuggestion<BookModel>>>
{
["suggestions"] = suggesterResponse.Value.Results.ToList()
};
var response = req.CreateResponse(HttpStatusCode.Found);
// Serialize data
var serializer = new JsonObjectSerializer(
new JsonSerializerOptions(JsonSerializerDefaults.Web));
await response.WriteAsJsonAsync(searchSuggestions, serializer);
return response;
}
}
}
Client: Suggesties uit de catalogus
De Functie-API Voorstellen wordt aangeroepen in de React-app \client\src\components\SearchBar\SearchBar.js
als onderdeel van de initialisatie van onderdelen:
import React, {useState, useEffect} from 'react';
import axios from 'axios';
import Suggestions from './Suggestions/Suggestions';
import "./SearchBar.css";
export default function SearchBar(props) {
let [q, setQ] = useState("");
let [suggestions, setSuggestions] = useState([]);
let [showSuggestions, setShowSuggestions] = useState(false);
const onSearchHandler = () => {
props.postSearchHandler(q);
setShowSuggestions(false);
}
const suggestionClickHandler = (s) => {
document.getElementById("search-box").value = s;
setShowSuggestions(false);
props.postSearchHandler(s);
}
const onEnterButton = (event) => {
if (event.keyCode === 13) {
onSearchHandler();
}
}
const onChangeHandler = () => {
var searchTerm = document.getElementById("search-box").value;
setShowSuggestions(true);
setQ(searchTerm);
// use this prop if you want to make the search more reactive
if (props.searchChangeHandler) {
props.searchChangeHandler(searchTerm);
}
}
useEffect(_ =>{
const timer = setTimeout(() => {
const body = {
q: q,
top: 5,
suggester: 'sg'
};
if (q === '') {
setSuggestions([]);
} else {
axios.post( '/api/suggest', body)
.then(response => {
console.log(JSON.stringify(response.data))
setSuggestions(response.data.suggestions);
} )
.catch(error => {
console.log(error);
setSuggestions([]);
});
}
}, 300);
return () => clearTimeout(timer);
}, [q, props]);
var suggestionDiv;
if (showSuggestions) {
suggestionDiv = (<Suggestions suggestions={suggestions} suggestionClickHandler={(s) => suggestionClickHandler(s)}></Suggestions>);
} else {
suggestionDiv = (<div></div>);
}
return (
<div >
<div className="input-group" onKeyDown={e => onEnterButton(e)}>
<div className="suggestions" >
<input
autoComplete="off" // setting for browsers; not the app
type="text"
id="search-box"
className="form-control rounded-0"
placeholder="What are you looking for?"
onChange={onChangeHandler}
defaultValue={props.q}
onBlur={() => setShowSuggestions(false)}
onClick={() => setShowSuggestions(true)}>
</input>
{suggestionDiv}
</div>
<div className="input-group-btn">
<button className="btn btn-primary rounded-0" type="submit" onClick={onSearchHandler}>
Search
</button>
</div>
</div>
</div>
);
};
Azure-functie: een specifiek document ophalen
De Documentzoek-API heeft een id en retourneert het documentobject uit de zoekindex.
using Azure;
using Azure.Core.Serialization;
using Azure.Search.Documents;
using Azure.Search.Documents.Models;
using Microsoft.Azure.Functions.Worker;
using Microsoft.Azure.Functions.Worker.Http;
using Microsoft.Extensions.Logging;
using System.Net;
using System.Text.Json;
using WebSearch.Models;
namespace WebSearch.Function
{
public class Lookup
{
private static string searchApiKey = Environment.GetEnvironmentVariable("SearchApiKey", EnvironmentVariableTarget.Process);
private static string searchServiceName = Environment.GetEnvironmentVariable("SearchServiceName", EnvironmentVariableTarget.Process);
private static string searchIndexName = Environment.GetEnvironmentVariable("SearchIndexName", EnvironmentVariableTarget.Process) ?? "good-books";
private readonly ILogger<Lookup> _logger;
public Lookup(ILogger<Lookup> logger)
{
_logger = logger;
}
[Function("lookup")]
public async Task<HttpResponseData> RunAsync(
[HttpTrigger(AuthorizationLevel.Anonymous, "get", "post")] HttpRequestData req,
FunctionContext executionContext)
{
// Get Document Id
var query = System.Web.HttpUtility.ParseQueryString(req.Url.Query);
string documentId = query["id"].ToString();
// Azure AI Search
Uri serviceEndpoint = new($"https://{searchServiceName}.search.windows.net/");
SearchClient searchClient = new(
serviceEndpoint,
searchIndexName,
new AzureKeyCredential(searchApiKey)
);
var getDocumentResponse = await searchClient.GetDocumentAsync<SearchDocument>(documentId);
// Data to return
var output = new LookupOutput
{
Document = getDocumentResponse.Value
};
var response = req.CreateResponse(HttpStatusCode.Found);
response.Headers.Add("Content-Type", "application/json; charset=utf-8");
// Serialize data
var serializer = new JsonObjectSerializer(
new JsonSerializerOptions(JsonSerializerDefaults.Web));
await response.WriteAsJsonAsync(output, serializer);
return response;
}
}
}
Client: Specifiek document ophalen
Deze functie-API wordt aangeroepen in de React-app \client\src\pages\Details\Detail.js
als onderdeel van de initialisatie van onderdelen:
import React, { useState, useEffect } from "react";
import { useParams } from 'react-router-dom';
import Rating from '@mui/material/Rating';
import CircularProgress from '@mui/material/CircularProgress';
import axios from 'axios';
import "./Details.css";
export default function Details() {
let { id } = useParams();
const [document, setDocument] = useState({});
const [selectedTab, setTab] = useState(0);
const [isLoading, setIsLoading] = useState(true);
useEffect(() => {
setIsLoading(true);
// console.log(id);
axios.get('/api/lookup?id=' + id)
.then(response => {
console.log(JSON.stringify(response.data))
const doc = response.data.document;
setDocument(doc);
setIsLoading(false);
})
.catch(error => {
console.log(error);
setIsLoading(false);
});
}, [id]);
// View default is loading with no active tab
let detailsBody = (<CircularProgress />),
resultStyle = "nav-link",
rawStyle = "nav-link";
if (!isLoading && document) {
// View result
if (selectedTab === 0) {
resultStyle += " active";
detailsBody = (
<div className="card-body">
<h5 className="card-title">{document.original_title}</h5>
<img className="image" src={document.image_url} alt="Book cover"></img>
<p className="card-text">{document.authors?.join('; ')} - {document.original_publication_year}</p>
<p className="card-text">ISBN {document.isbn}</p>
<Rating name="half-rating-read" value={parseInt(document.average_rating)} precision={0.1} readOnly></Rating>
<p className="card-text">{document.ratings_count} Ratings</p>
</div>
);
}
// View raw data
else {
rawStyle += " active";
detailsBody = (
<div className="card-body text-left">
<pre><code>
{JSON.stringify(document, null, 2)}
</code></pre>
</div>
);
}
}
return (
<main className="main main--details container fluid">
<div className="card text-center result-container">
<div className="card-header">
<ul className="nav nav-tabs card-header-tabs">
<li className="nav-item"><button className={resultStyle} onClick={() => setTab(0)}>Result</button></li>
<li className="nav-item"><button className={rawStyle} onClick={() => setTab(1)}>Raw Data</button></li>
</ul>
</div>
{detailsBody}
</div>
</main>
);
}
C#-modellen ter ondersteuning van functie-app
De volgende modellen worden gebruikt ter ondersteuning van de functies in deze app.
using Azure.Search.Documents.Models;
using System.Text.Json.Serialization;
namespace WebSearch.Models
{
public class RequestBodyLookUp
{
[JsonPropertyName("id")]
public string Id { get; set; }
}
public class RequestBodySuggest
{
[JsonPropertyName("q")]
public string SearchText { get; set; }
[JsonPropertyName("top")]
public int Size { get; set; }
[JsonPropertyName("suggester")]
public string SuggesterName { get; set; }
}
public class RequestBodySearch
{
[JsonPropertyName("q")]
public string SearchText { get; set; }
[JsonPropertyName("skip")]
public int Skip { get; set; }
[JsonPropertyName("top")]
public int Size { get; set; }
[JsonPropertyName("filters")]
public List<SearchFilter> Filters { get; set; }
}
public class SearchFilter
{
public string field { get; set; }
public string value { get; set; }
}
public class FacetValue
{
public string value { get; set; }
public long? count { get; set; }
}
class SearchOutput
{
[JsonPropertyName("count")]
public long? Count { get; set; }
[JsonPropertyName("results")]
public List<SearchResult<SearchDocument>> Results { get; set; }
[JsonPropertyName("facets")]
public Dictionary<String, IList<FacetValue>> Facets { get; set; }
}
class LookupOutput
{
[JsonPropertyName("document")]
public SearchDocument Document { get; set; }
}
public class BookModel
{
public string id { get; set; }
public decimal? goodreads_book_id { get; set; }
public decimal? best_book_id { get; set; }
public decimal? work_id { get; set; }
public decimal? books_count { get; set; }
public string isbn { get; set; }
public string isbn13 { get; set; }
public string[] authors { get; set; }
public decimal? original_publication_year { get; set; }
public string original_title { get; set; }
public string title { get; set; }
public string language_code { get; set; }
public double? average_rating { get; set; }
public decimal? ratings_count { get; set; }
public decimal? work_ratings_count { get; set; }
public decimal? work_text_reviews_count { get; set; }
public decimal? ratings_1 { get; set; }
public decimal? ratings_2 { get; set; }
public decimal? ratings_3 { get; set; }
public decimal? ratings_4 { get; set; }
public decimal? ratings_5 { get; set; }
public string image_url { get; set; }
public string small_image_url { get; set; }
}
}
Volgende stappen
Als u meer wilt weten over azure AI Search-ontwikkeling, kunt u deze volgende zelfstudie over indexering proberen: