liang-ai/src/main/java/com/ai/controller/MilvusController.java

package com.ai.controller;

import com.ai.service.SimilarService;
import dev.langchain4j.community.model.dashscope.QwenEmbeddingModel;
import dev.langchain4j.data.document.Document;
import dev.langchain4j.data.document.loader.FileSystemDocumentLoader;
import dev.langchain4j.data.document.splitter.DocumentByLineSplitter;
import dev.langchain4j.data.embedding.Embedding;
import dev.langchain4j.data.segment.TextSegment;
import dev.langchain4j.store.embedding.EmbeddingStore;
import jakarta.annotation.Resource;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;

import java.util.List;

@RestController
@RequestMapping("/milvus")
public class MilvusController {

    @Autowired
    private SimilarService similarService;

    @Resource
    private QwenEmbeddingModel embeddingModel;

    @Resource
    private EmbeddingStore<TextSegment> embeddingStore;

    @Value("${rag.path}")
    private String ragPath;

    @RequestMapping("/create")
    public String create() {
        similarService.createCollection();
        return "milvus collection create";
    }

    @RequestMapping("/vector")
    public String vector() {
        similarService.insertProducts();
        return "vector create";
    }

    @RequestMapping("/import")
    public void ImportShopData() {
        List<Document> documents = FileSystemDocumentLoader.loadDocuments(ragPath);
        for (Document document : documents) {
            DocumentByLineSplitter splitter = new DocumentByLineSplitter(150,30);
            List<TextSegment> segments = splitter.split(document);
            List<Embedding> embeddings = embeddingModel.embedAll(segments).content();
            embeddingStore.addAll(embeddings, segments);
        }
    }
}