Paso 4: Exploración del código de búsqueda de .NET

En las lecciones anteriores, agregó la búsqueda a una aplicación web estática. En esta lección se resaltan los pasos esenciales que establecen la integración. Si busca una hoja de referencia rápida sobre cómo integrar la funcionalidad de búsqueda en su aplicación web, en este artículo se explica lo que debe saber.

Azure SDK Azure.Search.Documents

La aplicación de funciones usa el SDK de Azure AI Search:

• NuGet: Azure.Search.Documents
• Documentación de referencia: Biblioteca cliente

La aplicación de funciones se autentica a través del SDK en la API de Azure AI Search basada en la nube mediante el nombre del recurso, la clave de recurso y el nombre del índice. Los secretos se almacenan en la configuración estática de la aplicación web y se extraen a la función como variables de entorno.

Configuración de secretos en un archivo local.settings.jsen

{
  "IsEncrypted": false,
  "Values": {
    "AzureWebJobsStorage": "",
    "FUNCTIONS_WORKER_RUNTIME": "dotnet-isolated",
    "SearchApiKey": "",
    "SearchServiceName": "",
    "SearchIndexName": "good-books"
  },
  "Host": {
    "CORS": "*"
  }
}

Azure Function: búsqueda en el catálogo

La API de búsqueda toma un término de búsqueda y busca en los documentos del índice de búsqueda, y devuelve una lista de coincidencias. A través de la API de sugerencias, las cadenas parciales se envían al motor de búsqueda como tipos de usuario, sugiriendo términos de búsqueda como títulos de libro y autores en los documentos del índice de búsqueda y devolviendo una pequeña lista de coincidencias.

La función de Azure extrae la información de configuración de búsqueda y cumple la consulta.

El proveedor de sugerencias de búsqueda, sg, se define en el archivo de esquema usado durante la carga masiva.

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);
        }
    }
}

Cliente: búsqueda en el catálogo

Llame a la función de Azure en el cliente de React con el código siguiente.

import React, { useEffect, useState, Suspense } from 'react';
import axios from '../../axios.js';
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} query={q}></Results>
        <Pager className="pager-style" currentPage={currentPage} resultCount={resultCount} resultsPerPage={resultsPerPage} setCurrentPage={setCurrentPage}></Pager>
      </div>
    )
  }

  // 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">
            <SearchBar postSearchHandler={postSearchHandler} query={q}></SearchBar>
          </div>
          <Facets facets={facets} filters={filters} setFilters={updateFilterHandler}></Facets>
        </div>
        {body}
      </div>
    </main>
  );
}

Cliente: sugerencias del catálogo

Se llama a la API de la función Suggest en la aplicación React en \client\src\components\SearchBar\SearchBar.js como parte del componente Autocompletar de la interfaz de usuario de material. Este componente usa el texto de entrada para buscar autores y libros que coincidan con el texto de entrada y, a continuación, muestra esas posibles coincidencias en los elementos seleccionables de la lista desplegable.

import React, { useState, useEffect } from 'react';
import { TextField, Autocomplete, Button, Box } from '@mui/material';
import axios from '../../axios.js';

export default function SearchBar2({ postSearchHandler, query }) {
  const [q, setQ] = useState(() => query || '');
  const [suggestions, setSuggestions] = useState([]);

  const search = (value) => {
    console.log(`search: ${value}`);
    postSearchHandler(value);
  };

  useEffect(() => {
    console.log(`useEffect getSuggestions: ${q}`);
    if (q) {
      axios.post('/api/suggest', { q, top: 5, suggester: 'sg' })
      .then(response => {
          setSuggestions(response.data.suggestions.map(s => s.text));
      }).catch (error =>{
          console.log(error);
          setSuggestions([]);
        });
}}, [q]);


  const onInputChangeHandler = (event, value) => {
    console.log(`onInputChangeHandler: ${value}`);
    setQ(value);
  };


  const onChangeHandler = (event, value) => {
    console.log(`onChangeHandler: ${value}`);
    setQ(value);
    search(value);
  };

  const onEnterButton = (event) => {
    console.log(`onEnterButton: ${q}`);
    // if enter key is pressed
    if (event.key === 'Enter') {
      search(q);
    }
  };

  return (
    <div
      className="input-group"
      style={{ width: '95%', display: 'flex', justifyContent: 'center', alignItems: 'center', margin: '0 auto' }}
    >
      <Box sx={{ display: 'flex', alignItems: 'center', width: '75%', minWidth: '390px' }}>
      <Autocomplete
        freeSolo
        value={q}
        options={suggestions}
        onInputChange={onInputChangeHandler}
        onChange={onChangeHandler}
        disableClearable
        sx={{
          width: '75%',
          '& .MuiAutocomplete-endAdornment': {
            display: 'none'
          }
        }}
        renderInput={(params) => (
          <TextField
            {...params}
            id="search-box"
            className="form-control rounded-0"
            placeholder="What are you looking for?"
            onBlur={() => setSuggestions([])}
            onClick={() => setSuggestions([])}
          />
        )}
      />
      <div className="input-group-btn" style={{ marginLeft: '10px' }}>
        <Button variant="contained" color="primary" onClick={() => {
          console.log(`search button: ${q}`);
          search(q)}
          }>
          Search
        </Button>
      </div>
      </Box>
    </div>
  );
}

Función de Azure: obtención de un documento específico

LaAPI de búsqueda de documentos toma un identificador y devuelve el objeto de documento del índice de búsqueda.

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;
        }
    }
}

Cliente: obtención de un documento específico

Se llama a esta API de función en la aplicación React en \client\src\pages\Details\Detail.js como parte de la inicialización de componentes:

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.js';

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>
  );
}

Modelos de C# para admitir la aplicación de funciones

Los modelos siguientes se usan para dar cabida a las funciones de esta aplicación.

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; }
    }
}

Pasos siguientes

Para seguir aprendiendo más sobre el desarrollo de Azure AI Search, pruebe este siguiente tutorial sobre la indexación:

• Indexación de datos de Azure SQL