EmbeddingModel For ESVectorStore

[ElectricSly]

I'm trying to use the ESVectorStore in ordedr to do RAG, but I can't seem to find the right EmbeddingModel class for this. Should i define it myself or is there a soecific class that shoud be used ?

This is my config class as for now :
package com.example.demo.config;

import com.example.demo.util.PDFExtractor;
import org.apache.http.auth.AuthScope;
import org.apache.http.auth.UsernamePasswordCredentials;
import org.apache.http.client.CredentialsProvider;
import org.apache.http.impl.client.BasicCredentialsProvider;
import org.elasticsearch.client.RestClient;
import org.elasticsearch.client.RestClientBuilder;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.ai.document.Document;
import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.vectorstore.ElasticsearchVectorStore;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.ai.transformer.splitter.TokenTextSplitter;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.beans.factory.annotation.Autowired;

import java.io.File;
import java.io.IOException;
import java.util.Arrays;
import java.util.List;
import java.util.Objects;

@configuration
public class RagConfigurationElastic {

private static final Logger log = LoggerFactory.getLogger(RagConfigurationElastic.class);

@Value("vector-store.json")
private String vectorStoreName;

@Value("${spring.elasticsearch.uris}")
private String elasticsearchUris;

@Value("${spring.elasticsearch.username}")
private String elasticsearchUsername;

@Value("${spring.elasticsearch.password}")
private String elasticsearchPassword;

@Value("${spring.ai.vectorstore.elasticsearch.index-name:spring-ai-document-index}")
private String indexName;

@Autowired
private EmbeddingModel embeddingModel;

@Bean
public RestClient restClient() {
    RestClientBuilder builder = RestClient.builder(Arrays.toString(elasticsearchUris.split(",")))
            .setRequestConfigCallback(requestConfigBuilder -> requestConfigBuilder)
            .setHttpClientConfigCallback(httpClientBuilder -> {
                CredentialsProvider credentialsProvider = new BasicCredentialsProvider();
                credentialsProvider.setCredentials(AuthScope.ANY,
                        new UsernamePasswordCredentials(elasticsearchUsername, elasticsearchPassword));
                return httpClientBuilder.setDefaultCredentialsProvider(credentialsProvider);
            });
    return builder.build();
}

@Bean
public ElasticsearchVectorStore elasticsearchVectorStore(RestClient restClient) {
    ElasticsearchVectorStore elasticsearchVectorStore = new ElasticsearchVectorStore(
            restClient, embeddingModel, true
    );
    
    updateVectorStoreFromFolder(elasticsearchVectorStore, "pdfToUpload", "pdfUploaded");
    return elasticsearchVectorStore;
}
private void updateVectorStoreFromFolder(VectorStore vectorStore, String upFolder, String doFolder) {
    try {
        File folderFile = new File(upFolder);
        if (!folderFile.exists()) {
            log.error("Folder {} does not exist", upFolder);
            return;
        }
        if (!folderFile.isDirectory()) {
            log.error("Folder {} is not a directory", upFolder);
            return;
        }
        for (File file : Objects.requireNonNull(folderFile.listFiles())) {
            if (updateVectorStoreFromPDF(vectorStore, upFolder + "/" + file.getName())) {
                if (file.renameTo(new File(doFolder + "/" + file.getName()))) {
                    log.info("Moved the file successfully");
                }
            }
        }
    } catch (Exception e) {
        log.error("Error updating vector store from folder", e);
    }
}

private boolean updateVectorStoreFromPDF(VectorStore vectorStore, String filename) {
    try {
        File pdfFile = new File(filename);
        String pdfText = PDFExtractor.extractText(pdfFile);
        if (pdfText.isEmpty()) {
            log.info("Extracted text is empty. Please check the PDFExtractor.");
            return false;
        }
        vectorStore.add(splitter(pdfText));
        log.info("Documents added to vector store.");
    } catch (IOException e) {
        log.error("Error extracting text from PDF file", e);
        return false;
    }
    return true;
}

private List<Document> splitter(String pdfText) {
    Document document = new Document(pdfText);
    TokenTextSplitter tokenTextSplitter = new TokenTextSplitter();
    List<Document> splitDocuments = tokenTextSplitter.apply(List.of(document));
    log.info("Number of documents after split: {}", splitDocuments.size());
    return splitDocuments;
}

}

[ElectricSly]

It was a version problem, it didn't use the latest version so I was missing the EmbeddingModel class : /