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agents-flex-llm/agents-flex-llm-qwen/src/test/java/com/agentsflex/llm/qwen/test/QwenTest.java

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+package com.agentsflex.llm.qwen.test;
+
+import com.agentsflex.core.document.Document;
+import com.agentsflex.core.llm.ChatOptions;
+import com.agentsflex.core.llm.Llm;
+import com.agentsflex.core.llm.exception.LlmException;
+import com.agentsflex.core.llm.response.AiMessageResponse;
+import com.agentsflex.core.message.AiMessage;
+import com.agentsflex.core.prompt.FunctionPrompt;
+import com.agentsflex.core.store.VectorData;
+import com.agentsflex.core.util.LogUtil;
+import com.agentsflex.llm.qwen.QwenChatOptions;
+import com.agentsflex.llm.qwen.QwenChatOptions.SearchOptions;
+import com.agentsflex.llm.qwen.QwenLlm;
+import com.agentsflex.llm.qwen.QwenLlmConfig;
+import org.junit.Test;
+
+public class QwenTest {
+
+    public static void main(String[] args) throws InterruptedException {
+        QwenLlmConfig config = new QwenLlmConfig();
+
+        //https://bailian.console.aliyun.com/?apiKey=1#/api-key
+        config.setApiKey("sk-28a6be3236****");
+        config.setModel("qwen-plus");
+
+        Llm llm = new QwenLlm(config);
+        llm.chatStream("请写一个小兔子战胜大灰狼的故事", (context, response) -> {
+            AiMessage message = response.getMessage();
+            LogUtil.println(">>>> " + message.getContent());
+        });
+
+        Thread.sleep(10000);
+    }
+
+    @Test(expected = LlmException.class)
+    public void testForcedSearch() throws InterruptedException {
+        QwenLlmConfig config = new QwenLlmConfig();
+        config.setApiKey("sk-28a6be3236****");
+        config.setModel("qwen-max");
+
+        Llm llm = new QwenLlm(config);
+        QwenChatOptions options = new QwenChatOptions();
+        options.setEnableSearch(true);
+        options.setSearchOptions(new SearchOptions().setForcedSearch(true));
+
+        String responseStr = llm.chat("今天是几号？", options);
+
+        System.out.println(responseStr);
+    }
+
+    @Test
+    public void testFunctionCalling() throws InterruptedException {
+        QwenLlmConfig config = new QwenLlmConfig();
+        config.setApiKey("sk-28a6be3236****");
+        config.setModel("qwen-turbo");
+
+        Llm llm = new QwenLlm(config);
+
+        FunctionPrompt prompt = new FunctionPrompt("今天北京的天气怎么样", WeatherFunctions.class);
+        AiMessageResponse response = llm.chat(prompt);
+
+        System.out.println(response.callFunctions());
+        // "Today it will be dull and overcast in 北京"
+    }
+
+    @Test
+    public void testEmbedding() throws InterruptedException {
+        QwenLlmConfig config = new QwenLlmConfig();
+        config.setApiKey("sk-28a6be3236****");
+        config.setModel("qwen-turbo");
+
+        Llm llm = new QwenLlm(config);
+        VectorData vectorData = llm.embed(Document.of("test"));
+
+        System.out.println(vectorData);
+    }
+
+    /**
+     * 动态替换模型
+     */
+    @Test
+    public void testDynamicModel() throws InterruptedException {
+        // 默认模型
+        QwenLlmConfig config = new QwenLlmConfig();
+        config.setApiKey("sk-28a6be3236****");
+        config.setModel("qwen-turbo");
+
+        // 运行时动态替换模型
+        ChatOptions options = new QwenChatOptions();
+        options.setModel("deepseek-r1");
+
+        Llm llm = new QwenLlm(config);
+        llm.chatStream("请写一个小兔子战胜大灰狼的故事", (context, response) -> {
+            AiMessage message = response.getMessage();
+            System.err.println(message.getReasoningContent());
+            System.out.println(message.getFullContent());
+            System.out.println();
+        }, options);
+        Thread.sleep(10000);
+    }
+
+    /**
+     * 测试千问3 开启思考模式的开关
+     */
+    @Test
+    public void testQwen3Thinking() throws InterruptedException {
+        QwenLlmConfig config = new QwenLlmConfig();
+        config.setApiKey("sk-28a6be3236****");
+        config.setModel("qwen3-235b-a22b");
+
+        Llm llm = new QwenLlm(config);
+        QwenChatOptions options = new QwenChatOptions();
+        options.setEnableThinking(false);
+        //options.setThinkingBudget(1024);
+
+        llm.chatStream("你是谁", (context, response) -> {
+            AiMessage message = response.getMessage();
+            System.err.println(message.getReasoningContent());
+            System.out.println(message.getFullContent());
+            System.out.println();
+        }, options);
+        Thread.sleep(10000);
+    }
+
+}