sb-ai-alibaba Rag20250715
1、
package com.ds.aiaibabarag.config;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.document.Document;
import org.springframework.ai.embedding.EmbeddingModel;
import org.springframework.ai.vectorstore.SimpleVectorStore;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import java.util.List;
@Configuration
public class RagConfig {
@Bean
ChatClient chatClient(ChatClient.Builder builder) {
return builder
.defaultSystem("你是一个Java开发语言的专家,对于用户的使用需求作出解答。")
.build();
}
@Bean
VectorStore vectorStore(EmbeddingModel embeddingModel) {
SimpleVectorStore simpleVectorStore = SimpleVectorStore
.builder(embeddingModel)
.build();
//生成说明文档
List<Document> documents=List.of(new Document(
"产品说明:名称: java开发语言\n"+
"产品描述:java是一种面向对像开发语言。\n"+
"特性:\n"+
"1. 封装\n"+
"2. 继承\n"+
"3. 多态\n"));
//将文档添加到向量存储中
simpleVectorStore.add(documents);
return simpleVectorStore;
}
}
2、
package com.ds.aiaibabarag.controller;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.client.advisor.QuestionAnswerAdvisor;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RestController;
@RestController
public class RagController {
@Autowired
private ChatClient chatClient;
@Autowired
private VectorStore vectorStore;
@GetMapping("/rag")
public String rag(String input) {
String content = chatClient.prompt()
.user(input)
.advisors(new QuestionAnswerAdvisor(vectorStore))
.call()
.content();
return content;
}
}
3、