feat: rag的api

ai-rag-app/src/test/java/com/storm/dev/text/RAGApiTest.java

@@ -21,6 +21,7 @@ import org.springframework.ai.vectorstore.SearchRequest;
 import org.springframework.ai.vectorstore.SimpleVectorStore;
 import org.springframework.boot.test.context.SpringBootTest;
 import org.springframework.test.context.junit4.SpringRunner;
+import reactor.core.publisher.Flux;
 
 import java.util.ArrayList;
 import java.util.List;
@@ -61,7 +62,7 @@ public class RAGApiTest {
     @Test
     public void chat() {
         // 构建提问
-        String message = "李永德，哪年出生的";
+        String message = "拆装出库的操作流程是什么？";
 
         // 构建推理模板
         String SYSTEM_PROMPT = """
@@ -72,7 +73,7 @@ public class RAGApiTest {
                     {documents}
                 """;
         // 读取向量库信息
-        SearchRequest request = SearchRequest.query(message).withTopK(5).withFilterExpression("knowledge == '德德'");
+        SearchRequest request = SearchRequest.query(message).withTopK(5).withFilterExpression("knowledge == '富士迈泰国项目软件方案'");
         // 相似性搜索
         List<Document> documents = pgVectorStore.similaritySearch(request);
         String documentsCollectors = documents.stream().map(Document::getContent).collect(Collectors.joining());
@@ -84,7 +85,8 @@ public class RAGApiTest {
         messages.add(ragMessage);
 
         // 提问
-        ChatResponse chatResponse = ollamaChatClient.call(new Prompt(messages, OllamaOptions.create().withModel("deepseek-r1:7b")));
-        log.info("测试结果:{}", JSON.toJSONString(chatResponse));
+//        ChatResponse chatResponse = ollamaChatClient.call(new Prompt(messages, OllamaOptions.create().withModel("deepseek-r1:7b")));
+        Flux<ChatResponse> stream = ollamaChatClient.stream(new Prompt(messages, OllamaOptions.create().withModel("deepseek-r1:7b")));
+        log.info("测试结果:{}", JSON.toJSONString(stream));
     }
 }