feat(box): 实现 AI 对话窗口并添加网络 API 调用

- 新增 LMApi 类实现 API 调用获取 AI 回复
- 修改 LocalWindow 类，添加系统提示信息- 更新 Main 类，引入 Markdown处理库
- 在 build.gradle 中添加相关依赖

build.gradle

@@ -24,28 +24,22 @@ repositories {
 dependencies {
     testImplementation platform('org.junit:junit-bom:5.10.0')
     testImplementation 'org.junit.jupiter:junit-jupiter'
+    // https://mvnrepository.com/artifact/org.commonmark/commonmark
+    implementation 'org.commonmark:commonmark:0.24.0'
+    // https://mvnrepository.com/artifact/org.commonjava.googlecode.markdown4j/markdown4j
+    implementation 'org.commonjava.googlecode.markdown4j:markdown4j:2.2-cj-1.1'
+    // https://mvnrepository.com/artifact/com.google.code.gson/gson
+    implementation 'com.google.code.gson:gson:2.8.9'
 }
 
 application {
     mainClass = 'com.axis.innovators.box.Main'
 }
 
-shadowJar {
+jar {
-    archiveBaseName = 'app'
+    manifest {
-    archiveClassifier = ''
+        attributes 'Main-Class': 'com.axis.innovators.box.Main'
-    archiveVersion = ''
+    }
-}
-
-launch4j {
-    mainClassName = 'com.axis.innovators.box.Main'
-    outfile = version + '.exe'
-    icon = "${projectDir}/logo.ico"
-    jar = shadowJar.archiveFile.get()
-    bundledJrePath = 'jre'
-}
-
-tasks.named('launch4j') {
-    dependsOn shadowJar
 }
 
 test {

src/main/java/com/axis/innovators/box/Main.java

@@ -6,12 +6,13 @@ import com.axis.innovators.box.events.SubscribeEvent;
 import com.axis.innovators.box.gui.FridaWindow;
 import com.axis.innovators.box.gui.LocalWindow;
 import com.axis.innovators.box.gui.MainWindow;
-import com.axis.innovators.box.tools.FolderCreator;
 import com.axis.innovators.box.tools.LibraryLoad;
+import org.markdown4j.Markdown4jProcessor;
 
 import javax.swing.*;
 import java.awt.*;
 import java.awt.event.ActionEvent;
+import java.io.IOException;
 
 /**
  * 主类
@@ -33,7 +34,7 @@ public class Main {
         // 我不想写这个了你们自己实现
     }
 
-    public static void main(String[] args) {
+    public static void main(String[] args) throws IOException {
         // 注册事件
         GlobalEventBus.EVENT_BUS.register(new Main());
         // 设置系统外观

src/main/java/com/axis/innovators/box/gui/LocalWindow.java

@@ -210,6 +210,7 @@ public class LocalWindow extends JDialog {
                             contextHandles.getLast(),
                             temperature,
                             prompt,
+                            "你是一个乐于助人的AI助手，请用友好自然的语气回答用户问题。",
                             this::publish
                     );
                 }

src/main/java/org/tzd/lm/LM.java

@@ -9,7 +9,7 @@ import com.axis.innovators.box.tools.LibraryLoad;
  */
 public class LM {
     public static boolean CUDA = true;
-    public final static String DEEP_SEEK = "G:/deepseek/deepseek/DeepSeek-R1-Distill-Qwen-1.5B-Q8_0/DeepSeek-R1-Distill-Qwen-1.5B-Q8_0.gguf";
+    public final static String DEEP_SEEK = FolderCreator.getModelFolder() + "\\DeepSeek-R1-Distill-Qwen-1.5B-Q8_0.gguf";
 
     static {
         if (!CUDA) {
@@ -28,12 +28,32 @@ public class LM {
         }
         LibraryLoad.loadLibrary("LM");
     }
+    public static long llamaLoadModelFromFile(String pathModel){
+        return llamaLoadModelFromFile(pathModel,
+                false,
+                false,
+                false,
+                false,
+                null
+        );
+    }
+
     /**
      * 加载模型
      * @param pathModel 模型路径
+     * @param vocabOnly 只负重词汇，不负重
+     * @param useMmap 尽可能使用mmap
+     * @param useMlock 强制系统将模型保存在RAM中
+     * @param checkTensors 验证模型张量数据
+     * @param progressCallback 进度回调
      * @return 模型句柄
      */
-    public static native long llamaLoadModelFromFile(String pathModel);
+    public static native long llamaLoadModelFromFile(String pathModel,
+                                                     boolean vocabOnly,
+                                                     boolean useMmap,
+                                                     boolean useMlock,
+                                                     boolean checkTensors,
+                                                     ProgressCallback progressCallback);
 
     /**
      * 释放模型资源
@@ -97,19 +117,20 @@ public class LM {
                                    long ctxHandle,
                                    float temperature,
                                    String prompt,
+                                   String system,
                                    MessageCallback messageCallback){
         return inference(modelHandle,
                 ctxHandle,
                 temperature,
-                0.05f,
+                0.1f,
-                40,
+                100,
-                0.95f,
+                0.9f,
                 0,
-                5,
+                64,
-                2.0f,
+                1.1f,
-                0,
+                0.0f,
-                0,
+                0.0f,
-                prompt,
+                system + "\n用户：" + prompt + "\n助手：",
                 messageCallback
         );
     }
@@ -148,7 +169,7 @@ public class LM {
                                           MessageCallback messageCallback);
 
     /**
-     * 回调接口
+     * 消息回调接口
      */
     public interface MessageCallback {
         /**
@@ -158,12 +179,24 @@ public class LM {
         void onMessage(String message);
     }
 
+    /**
+     * 进度回调接口
+     */
+    public interface ProgressCallback {
+        /**
+         * 进度回调
+         * @param progress 进度（0.0到1.0之间）
+         * @return 如果提供的progress_callback返回true，模型将继续加载。如果返回false，则立即中止模型加载。
+         */
+        boolean onModelLoad(float progress);
+    }
+
     public static void main(String[] args) {
         // 加载模型
         long modelHandle = llamaLoadModelFromFile(DEEP_SEEK);
         // 创建新的上下文
         long ctxHandle = createContext(modelHandle);
-        inference(modelHandle, ctxHandle, 0.2f, "Tell me how gpt works in an easy way, in Chinese", new MessageCallback() {
+        inference(modelHandle, ctxHandle, 0.2f,  "Tell me who you are in English","你是一个乐于助人的AI助手", new MessageCallback() {
             @Override
             public void onMessage(String message) {
                 // 回调输出

src/main/java/org/tzd/lm/LMApi.java

@@ -0,0 +1,91 @@
+package org.tzd.lm;
+
+import java.io.*;
+import java.net.HttpURLConnection;
+import java.net.URI;
+import java.net.URL;
+import java.nio.charset.StandardCharsets;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Map;
+
+import com.google.gson.Gson;
+import com.google.gson.reflect.TypeToken;
+
+/**
+ * @author tzdwindows 7
+ */
+public class LMApi {
+    private static final String API_URL = "https://api.pearktrue.cn/api/deepseek/";
+    private static final Gson GSON = new Gson();
+
+    public static class Message {
+        private String role;
+        private String content;
+
+        public Message(String role, String content) {
+            this.role = role;
+            this.content = content;
+        }
+
+        public String getRole() { return role; }
+        public String getContent() { return content; }
+        public void setRole(String role) { this.role = role; }
+        public void setContent(String content) { this.content = content; }
+    }
+
+    /**
+     * 调用AI接口获取回复
+     * @param messages 消息列表
+     * @return AI回复内容
+     */
+    public String getAIResponse(List<Message> messages) throws IOException {
+        String jsonInput = GSON.toJson(Map.of("messages", messages));
+
+        URL url = URI.create(API_URL).toURL();
+        HttpURLConnection conn = (HttpURLConnection) url.openConnection();
+        conn.setRequestMethod("POST");
+        conn.setRequestProperty("Content-Type", "application/json");
+        conn.setDoOutput(true);
+
+        try(OutputStream os = conn.getOutputStream()) {
+            byte[] input = jsonInput.getBytes(StandardCharsets.UTF_8);
+            os.write(input, 0, input.length);
+        }
+
+        int responseCode = conn.getResponseCode();
+        if (responseCode == HttpURLConnection.HTTP_OK) {
+            try (BufferedReader br = new BufferedReader(
+                    new InputStreamReader(conn.getInputStream(), "GBK"))) {
+                String response = readAllLines(br);
+                Map<String, String> result = GSON.fromJson(response,
+                        new TypeToken<Map<String, String>>(){}.getType());
+                return result.get("message");
+            }
+        } else {
+            throw new IOException("API请求失败，状态码：" + responseCode);
+        }
+    }
+
+    private String readAllLines(BufferedReader reader) throws IOException {
+        StringBuilder sb = new StringBuilder();
+        String line;
+        while ((line = reader.readLine()) != null) {
+            sb.append(line);
+        }
+        return sb.toString();
+    }
+
+    public static void main(String[] args) {
+        List<Message> messages = new ArrayList<>();
+        messages.add(new Message("system", "You are a helpful assistant."));
+        messages.add(new Message("user", "你好啊"));
+
+        try {
+            String reply = new LMApi().getAIResponse(messages);
+            System.out.println(reply);
+        } catch (IOException e) {
+            e.printStackTrace();
+        }
+    }
+}