diff --git a/src/main/java/xyz/wbsite/ai/Test.java b/src/main/java/xyz/wbsite/ai/Test.java
index 375f0c2..219cfe4 100644
--- a/src/main/java/xyz/wbsite/ai/Test.java
+++ b/src/main/java/xyz/wbsite/ai/Test.java
@@ -1,11 +1,9 @@
 package xyz.wbsite.ai;
 
 import cn.hutool.core.collection.CollUtil;
+import dev.langchain4j.agent.tool.*;
 import dev.langchain4j.data.document.Document;
-import dev.langchain4j.data.message.AiMessage;
-import dev.langchain4j.data.message.ChatMessage;
-import dev.langchain4j.data.message.SystemMessage;
-import dev.langchain4j.data.message.UserMessage;
+import dev.langchain4j.data.message.*;
 import dev.langchain4j.data.segment.TextSegment;
 import dev.langchain4j.memory.chat.MessageWindowChatMemory;
 import dev.langchain4j.model.StreamingResponseHandler;
@@ -17,10 +15,15 @@ import dev.langchain4j.model.output.Response;
 import dev.langchain4j.rag.content.retriever.EmbeddingStoreContentRetriever;
 import dev.langchain4j.service.AiServices;
 import dev.langchain4j.service.TokenStream;
+import dev.langchain4j.service.tool.DefaultToolExecutor;
+import dev.langchain4j.service.tool.ToolExecutor;
 import dev.langchain4j.store.embedding.EmbeddingStoreIngestor;
 import dev.langchain4j.store.embedding.inmemory.InMemoryEmbeddingStore;
 
+import java.util.ArrayList;
 import java.util.List;
+import java.util.UUID;
+import java.util.function.Consumer;
 
 /**
  * 主函数入口
@@ -30,8 +33,8 @@ public class Test {
     public static void main(String[] args) {
 //        testSimpleChat(args);
 //        testStreamChat(args);
-        testRagChat(args);
-//        testTool(args);
+//        testRagChat(args);
+        testTool(args);
     }
 
     public static void testSimpleChat(String[] args) {
@@ -138,62 +141,57 @@ public class Test {
     }
 
     public static void testTool(String[] args) {
-//        ChatLanguageModel model = OllamaChatModel.builder()
-//                .baseUrl("http://36.138.207.178:11434")
-//                .modelName("qwen2.5:7b")
-//                .logRequests(true)
-//                .logResponses(true)
-//                .build();
-//
-//        List<ChatMessage> chatMessages = new ArrayList<>();
-//        chatMessages.add(UserMessage.from("请问，泰州市的天气怎么样？"));
-//
-//        Object weatherTools = new Object() {
-//            @Tool("返回某一城市的天气情况")
-//            public String getWeather(@P("应返回天气预报的城市") String city) {
-//                System.out.println(city);
-//                return "天气阴转多云，1~6℃";
-//            }
-//        };
-//
-//        List<ToolSpecification> toolSpecifications = ToolSpecifications.toolSpecificationsFrom(weatherTools);
-//
-//        ChatRequest chatRequest = ChatRequest.builder()
-//                .messages(chatMessages)
-//                .parameters(ChatRequestParameters.builder()
-//                        .toolSpecifications(toolSpecifications)
-//                        .build())
-//                .build();
-//
-//
-//        ChatResponse chatResponse = model.chat(chatRequest);
-//        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());
+        OpenAiChatModel model = OpenAiChatModel.builder()
+                .baseUrl("http://36.138.207.178:11434/v1")
+                .apiKey("1")
+                .modelName("qwen2.5:7b")
+                .build();
+
+        List<ChatMessage> chatMessages = new ArrayList<>();
+        chatMessages.add(UserMessage.from("请问，泰州市的天气怎么样？"));
+
+        Object weatherTools = new Object() {
+            @Tool("返回某一城市的天气情况")
+            public String getWeather(@P("应返回天气预报的城市") String city) {
+                System.out.println(city);
+                return "天气阴转多云，1~6℃";
+            }
+        };
+
+        List<ToolSpecification> toolSpecifications = ToolSpecifications.toolSpecificationsFrom(weatherTools);
+
+        ChatRequest chatRequest = ChatRequest.builder()
+                .messages(chatMessages)
+                .toolSpecifications(toolSpecifications)
+                .build();
+
+
+        ChatResponse chatResponse = model.chat(chatRequest);
+        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)
+                .toolSpecifications(toolSpecifications)
+                .build();
+        ChatResponse finalChatResponse = model.chat(chatRequest2);
+        System.out.println(finalChatResponse.aiMessage().text());
     }
 
     // 创建一个助手接口