Not
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I föregående lektioner lade du till sökning i en statisk webbapp. Den här lektionen belyser de viktigaste stegen för att upprätta integrering. Om du letar efter ett fuskark om hur du integrerar sökning i din webbapp förklarar den här artikeln vad du behöver veta.
Azure SDK Azure.Search.Documents
Funktionsappen använder Azure SDK för Azure AI Search:
- NuGet: Azure.Search.Documents
- Referensdokumentation: Klientbibliotek
Funktionsappen autentiserar via SDK:n till det molnbaserade Azure AI Search-API:et med hjälp av resursnamnet, resursnyckeln och indexnamnet. Hemligheterna lagras i inställningarna för den statiska webbappen och hämtas till funktionen som miljövariabler.
Konfigurera hemligheter i en local.settings.json-fil
{
"IsEncrypted": false,
"Values": {
"AzureWebJobsStorage": "",
"FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
"SearchApiKey": "",
"SearchServiceName": "",
"SearchIndexName": "good-books"
},
"Host": {
"CORS": "*"
}
}
Azure-funktion: Sök i katalogen
Sök-API:et tar en sökterm och söker i dokumenten i sökindexet och returnerar en lista med matchningar. Via API:et Föreslå skickas partiella strängar till sökmotorn som användartyper, vilket föreslår söktermer som boktitlar och författare i dokumenten i sökindexet och returnerar en liten lista med matchningar.
Azure-funktionen hämtar sökkonfigurationsinformationen och uppfyller frågan.
Sökförslagsverktygetsg, , definieras i schemafilen som används vid massuppladdning.
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);
}
}
}
Klient: Sök från katalogen
Anropa Azure-funktionen i React-klienten på \client\src\pages\Search\Search.jsx med följande kod för att söka efter böcker.
import React, { useEffect, useState, Suspense } from 'react';
import fetchInstance from '../../url-fetch';
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;
// Handle page changes in a controlled manner
function handlePageChange(newPage) {
setCurrentPage(newPage);
}
// Calculate skip value and fetch results when relevant parameters change
useEffect(() => {
// Calculate skip based on current page
const calculatedSkip = (currentPage - 1) * top;
// Only update if skip has actually changed
if (calculatedSkip !== skip) {
setSkip(calculatedSkip);
return; // Skip the fetch since skip will change and trigger another useEffect
}
// Proceed with fetch
setIsLoading(true);
const body = {
q: q,
top: top,
skip: skip,
filters: filters
};
fetchInstance('/api/search', { body, method: 'POST' })
.then(response => {
setResults(response.results);
setFacets(response.facets);
setResultCount(response.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) => {
setQ(searchTerm);
}
// filters should be applied across entire result set,
// not just within the current page
const updateFilterHandler = (newFilters) => {
// Reset paging
setSkip(0);
setCurrentPage(1);
// Set filters
setFilters(newFilters);
};
return (
<main className="main main--search container-fluid">
<div className="row">
<div className="search-bar-column col-md-3">
<div className="search-bar-column-container">
<SearchBar postSearchHandler={postSearchHandler} query={q} width={false}></SearchBar>
</div>
<Facets facets={facets} filters={filters} setFilters={updateFilterHandler}></Facets>
</div>
<div className="search-bar-results">
{isLoading ? (
<div className="col-md-9">
<CircularProgress />
</div>
) : (
<div className="search-results-container">
<Results documents={results} top={top} skip={skip} count={resultCount} query={q}></Results>
<Pager className="pager-style" currentPage={currentPage} resultCount={resultCount} resultsPerPage={resultsPerPage} onPageChange={handlePageChange}></Pager>
</div>
)}
</div>
</div>
</main>
);
}
Klient: Förslag från katalogen
Suggest-API:et anropas i React-appen som \client\src\components\SearchBar\SearchBar.jsx en del av Materialgränssnittets automatiska kompletteringskomponent. Den här komponenten använder indatatexten för att söka efter författare och böcker som matchar indatatexten och visar sedan de möjliga matchningarna vid valbara objekt i listrutan.
import React, { useState, useEffect } from 'react';
import { TextField, Autocomplete, Button, Box } from '@mui/material';
import fetchInstance from '../../url-fetch';
import './SearchBar.css';
export default function SearchBar({ postSearchHandler, query, width }) {
const [q, setQ] = useState(() => query || '');
const [suggestions, setSuggestions] = useState([]);
const search = (value) => {
postSearchHandler(value);
};
useEffect(() => {
if (q) {
const body = { q, top: 5, suggester: 'sg' };
fetchInstance('/api/suggest', { body, method: 'POST' })
.then(response => {
setSuggestions(response.suggestions.map(s => s.text));
})
.catch(error => {
console.log(error);
setSuggestions([]);
});
}
}, [q]);
const onInputChangeHandler = (event, value) => {
setQ(value);
};
const onChangeHandler = (event, value) => {
setQ(value);
search(value);
};
const onEnterButton = (event) => {
// if enter key is pressed
if (event.key === 'Enter') {
search(q);
}
};
return (
<div
className={width ? "search-bar search-bar-wide" : "search-bar search-bar-narrow"}
>
<Box className="search-bar-box">
<Autocomplete
className="autocomplete"
freeSolo
value={q}
options={suggestions}
onInputChange={onInputChangeHandler}
onChange={onChangeHandler}
disableClearable
renderInput={(params) => (
<TextField
{...params}
id="search-box"
className="form-control rounded-0"
placeholder="What are you looking for?"
onBlur={() => setSuggestions([])}
onClick={() => setSuggestions([])}
/>
)}
/>
<div className="search-button" >
<Button variant="contained" color="primary" onClick={() => {
search(q)
}
}>
Search
</Button>
</div>
</Box>
</div>
);
}
Azure-funktion: Hämta specifikt dokument
API:et för dokumentsökning tar ett ID och returnerar dokumentobjektet från sökindexet.
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);
// Serialize data
var serializer = new JsonObjectSerializer(
new JsonSerializerOptions(JsonSerializerDefaults.Web));
await response.WriteAsJsonAsync(output, serializer);
return response;
}
}
}
Klient: Hämta specifikt dokument
Det här funktions-API:et anropas i React-appen som \client\src\pages\Details\Details.jsx en del av komponentinitiering:
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 Tabs from '@mui/material/Tabs';
import Tab from '@mui/material/Tab';
import Box from '@mui/material/Box';
import fetchInstance from '../../url-fetch';
import "./Details.css";
function CustomTabPanel(props) {
const { children, value, index, ...other } = props;
return (
<div
className="tab-panel"
role="tabpanel"
hidden={value !== index}
id={`simple-tabpanel-${index}`}
aria-labelledby={`simple-tab-${index}`}
{...other}
// Ensure it takes full width
>
{value === index && <Box className="tab-panel-value">{children}</Box>}
</div>
);
}
export default function BasicTabs() {
const { id } = useParams();
const [document, setDocument] = useState({});
const [value, setValue] = React.useState(0);
const [isLoading, setIsLoading] = useState(true);
useEffect(() => {
setIsLoading(true);
fetchInstance('/api/lookup', { query: { id } })
.then(response => {
console.log(JSON.stringify(response))
const doc = response.document;
setDocument(doc);
setIsLoading(false);
})
.catch(error => {
console.log(error);
setIsLoading(false);
});
}, [id]);
const handleChange = (event, newValue) => {
setValue(newValue);
};
if (isLoading || !id || Object.keys(document).length === 0) {
return (
<div className="loading-container">
<CircularProgress />
<p>Loading...</p>
</div>
);
}
return (
<Box className="details-box-parent">
<Box className="details-tab-box-header">
<Tabs value={value} onChange={handleChange} aria-label="book-details-tabs">
<Tab label="Result" />
<Tab label="Raw Data" />
</Tabs>
</Box>
<CustomTabPanel value={value} index={0} className="tab-panel box-content">
<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>
</CustomTabPanel>
<CustomTabPanel value={value} index={1} className="tab-panel">
<div className="card-body text-left card-text details-custom-tab-panel-json-div" >
<pre><code>
{JSON.stringify(document, null, 2)}
</code></pre>
</div>
</CustomTabPanel>
</Box>
);
}
C#-modeller som stöder funktionsapp
Följande modeller används för att stödja funktionerna i den här appen.
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; }
}
}
Nästa steg
Om du vill lära dig mer om Azure AI Search-utveckling kan du prova nästa självstudie om indexering: