上传备份

pom.xml

@@ -32,6 +32,18 @@
             <layout>default</layout>
         </pluginRepository>
     </pluginRepositories>
+    <build>
+        <plugins>
+            <plugin>
+                <groupId>org.apache.maven.plugins</groupId>
+                <artifactId>maven-compiler-plugin</artifactId>
+                <configuration>
+                    <source>8</source>
+                    <target>8</target>
+                </configuration>
+            </plugin>
+        </plugins>
+    </build>
 
     <dependencies>
         <!-- 糊涂工具，包含常用API，避免重复造轮子 -->

src/main/java/xyz/wbsite/ai/Main.java

@@ -2,25 +2,29 @@ package xyz.wbsite.ai;
 
 import cn.hutool.core.thread.ThreadUtil;
 import cn.hutool.json.JSONUtil;
-import com.fasterxml.jackson.annotation.JsonUnwrapped;
+import dev.langchain4j.agent.tool.*;
-import dev.langchain4j.agent.tool.ToolExecutionRequest;
+import dev.langchain4j.data.document.Document;
-import dev.langchain4j.agent.tool.ToolSpecification;
+import dev.langchain4j.data.document.loader.FileSystemDocumentLoader;
+import dev.langchain4j.data.document.parser.TextDocumentParser;
 import dev.langchain4j.data.message.*;
+import dev.langchain4j.memory.ChatMemory;
 import dev.langchain4j.model.chat.ChatLanguageModel;
 import dev.langchain4j.model.chat.StreamingChatLanguageModel;
 import dev.langchain4j.model.chat.request.ChatRequest;
 import dev.langchain4j.model.chat.request.ChatRequestParameters;
-import dev.langchain4j.model.chat.request.ChatRequestParametersBuilder;
-import dev.langchain4j.model.chat.request.DefaultChatRequestParameters;
-import dev.langchain4j.model.chat.request.json.JsonObjectSchema;
 import dev.langchain4j.model.chat.response.ChatResponse;
 import dev.langchain4j.model.chat.response.StreamingChatResponseHandler;
 import dev.langchain4j.model.ollama.OllamaChatModel;
 import dev.langchain4j.model.ollama.OllamaStreamingChatModel;
-import dev.langchain4j.model.openai.OpenAiChatModel;
+import dev.langchain4j.service.AiServices;
-import dev.langchain4j.model.openai.OpenAiStreamingChatModel;
+import dev.langchain4j.service.tool.DefaultToolExecutor;
 import dev.langchain4j.service.tool.ToolExecutor;
 
+import java.util.ArrayList;
+import java.util.List;
+import java.util.UUID;
+import java.util.function.Consumer;
+
 /**
  * 主函数入口
  */
@@ -29,8 +33,8 @@ public class Main {
     public static void main(String[] args) {
 //        testSimpleChat(args);
 //        testStreamChat(args);
-//        testTool(args);
+        testTool(args);
-        testRagChat(args);
+//        testRagChat(args);
     }
 
     public static void testSimpleChat(String[] args) {
@@ -116,34 +120,59 @@ public class Main {
     public static void testTool(String[] args) {
         ChatLanguageModel model = OllamaChatModel.builder()
                 .baseUrl("http://36.138.207.178:11434")
-                .modelName("deepseek-r1:32B")
+                .modelName("qwen2.5:7b")
+                .logRequests(true)
+                .logResponses(true)
                 .build();
 
-        ToolSpecification build1 = ToolSpecification.builder()
+        List<ChatMessage> chatMessages = new ArrayList<>();
-                .name("获取天气")
+        chatMessages.add(UserMessage.from("请问，泰州市的天气怎么样？"));
-                .description("返回指定城市的天气")
+
-                .parameters(JsonObjectSchema.builder().addStringProperty("城市").build())
+        Object weatherTools = new Object() {
-                .build();
+            @Tool("返回某一城市的天气情况")
-        ToolExecutor toolExecutor = new ToolExecutor() {
+            public String getWeather(@P("应返回天气预报的城市") String city) {
-            public String execute(ToolExecutionRequest toolExecutionRequest, Object o) {
+                System.out.println(city);
-                System.out.println();
+                return "天气阴转多云，1~6℃";
-                return "=============";
             }
         };
 
-        ChatRequestParameters build2 = DefaultChatRequestParameters.builder().toolSpecifications(build1).build();
+        List<ToolSpecification> toolSpecifications = ToolSpecifications.toolSpecificationsFrom(weatherTools);
 
-        ChatRequest build = ChatRequest.builder()
+        ChatRequest chatRequest = ChatRequest.builder()
-                .messages(new ChatMessage[]{
+                .messages(chatMessages)
-                        UserMessage.from("请问，泰州市明天的天气怎么样？"),
+                .parameters(ChatRequestParameters.builder()
-                        SystemMessage.from("请使用天气工具"),
+                        .toolSpecifications(toolSpecifications)
-                })
+                        .build())
-                .parameters(build2)
                 .build();
 
 
-        ChatResponse chat = model.chat(build);
+        ChatResponse chatResponse = model.chat(chatRequest);
-        System.out.println(chat.aiMessage().text());
+        AiMessage aiMessage = chatResponse.aiMessage();
+        chatMessages.add(aiMessage);
+        if (aiMessage.hasToolExecutionRequests()) {
+            System.out.println("LLM决定调用工具");
+            System.out.println(chatResponse.aiMessage());
+            List<ToolExecutionRequest> toolExecutionRequests = chatResponse.aiMessage().toolExecutionRequests();
+            toolExecutionRequests.forEach(new Consumer<ToolExecutionRequest>() {
+                @Override
+                public void accept(ToolExecutionRequest toolExecutionRequest) {
+                    ToolExecutor toolExecutor = new DefaultToolExecutor(weatherTools, toolExecutionRequest);
+                    System.out.println("Now let's execute the tool " + toolExecutionRequest.name());
+                    String result = toolExecutor.execute(toolExecutionRequest, UUID.randomUUID().toString());
+                    ToolExecutionResultMessage toolExecutionResultMessages = ToolExecutionResultMessage.from(toolExecutionRequest, result);
+                    chatMessages.add(toolExecutionResultMessages);
+                }
+            });
+        }
 
+        // STEP 4: Model generates final response
+        ChatRequest chatRequest2 = ChatRequest.builder()
+                .messages(chatMessages)
+                .parameters(ChatRequestParameters.builder()
+                        .toolSpecifications(toolSpecifications)
+                        .build())
+                .build();
+        ChatResponse finalChatResponse = model.chat(chatRequest2);
+        System.out.println(finalChatResponse.aiMessage().text());
     }
 }