aaa

exampleAiApp01/README.md

@@ -1,17 +1,29 @@
-# 提示词智能优化 Android App
+# 提示词智能优化（本地模型）Android App
 
-调用提示词大师 3 号专家接口，实现智能提示词生成。
+基于《生成专业提示词代码逻辑分析》，本地调用 LLM 实现智能提示词生成，**不依赖远程 Flask API**。
+
+## 功能
+
+- **两阶段专家逻辑**：先做意图分析（技术/创意/分析/咨询），再按领域选择专家模板生成提示词
+- **本地模型调用**：通过 OpenAI 兼容接口（如 Ollama）本地推理
+- **配置灵活**：支持设置 API 地址和模型名称
 
 ## 环境
 
-- Android Studio（推荐使用 AGP 8.7+、Gradle 8.9）
+- Android Studio（推荐 AGP 8.7+、Gradle 8.9）
 - minSdk 24，targetSdk 34
 - Java 17
 
-## 接口
+## 使用前准备
 
-- 地址：`POST http://101.43.95.130:5002/api/open/expert-generate-3`
+1. **安装 Ollama（或其他 OpenAI 兼容服务）**
-- 参数：`input_text`（必填）、`temperature`、`max_tokens`、`timeout`、`uid`
+   - 官网：https://ollama.ai
+   - 运行：`ollama run qwen2:0.5b`（或其它兼容模型）
+
+2. **配置 API 地址**
+   - 模拟器：`http://10.0.2.2:11434/v1/`（10.0.2.2 指向宿主机 localhost）
+   - 真机：`http://<电脑局域网 IP>:11434/v1/`（如 `http://192.168.1.100:11434/v1/`）
+   - 在 App 内点击「设置」可修改地址和模型名
 
 ## 构建
 
@@ -24,6 +36,6 @@ cd exampleAiApp01
 
 ## 注意事项
 
-- 需配置网络权限，并允许明文 HTTP（101.43.95.130 为 HTTP）
+- 需配置网络权限，并允许明文 HTTP（`network_security_config.xml` 已配置）
-- 确保设备可访问 `101.43.95.130:5002`
+- 确保设备与 Ollama 所在电脑处于同一局域网（真机）或使用模拟器
 - 如缺少启动图标，可在 Android Studio 中通过 `File > New > Image Asset` 生成

exampleAiApp01/app/src/main/AndroidManifest.xml

@@ -10,6 +10,10 @@
         android:supportsRtl="true"
         android:theme="@style/Theme.PromptOptimizer"
         android:usesCleartextTraffic="true">
+        <activity
+            android:name=".SettingsActivity"
+            android:exported="false"
+            android:theme="@style/Theme.PromptOptimizer" />
         <activity
             android:name=".MainActivity"
             android:exported="true"

exampleAiApp01/app/src/main/java/com/example/promptoptimizer/MainActivity.java

@@ -3,6 +3,7 @@ package com.example.promptoptimizer;
 import android.content.ClipData;
 import android.content.ClipboardManager;
 import android.content.Context;
+import android.content.Intent;
 import android.os.Bundle;
 import android.util.Log;
 import android.view.View;
@@ -13,20 +14,19 @@ import android.widget.Toast;
 
 import androidx.appcompat.app.AppCompatActivity;
 
-import com.example.promptoptimizer.api.ExpertGenerate3Api;
+import com.example.promptoptimizer.llm.LocalLlmClient;
-import com.example.promptoptimizer.model.ExpertGenerate3Request;
+import com.example.promptoptimizer.llm.PromptGenerator;
 import com.example.promptoptimizer.model.ExpertGenerate3Response;
 import com.google.android.material.button.MaterialButton;
 import com.google.android.material.card.MaterialCardView;
 
 import java.util.Arrays;
-
+import java.util.concurrent.ExecutorService;
-import retrofit2.Call;
+import java.util.concurrent.Executors;
-import retrofit2.Callback;
-import retrofit2.Response;
 
 /**
- * 提示词智能优化 - 主界面
+ * 提示词智能优化 - 本地模型调用（两阶段专家逻辑）
+ * 参考《生成专业提示词代码逻辑分析》
  */
 public class MainActivity extends AppCompatActivity {
 
@@ -34,6 +34,7 @@ public class MainActivity extends AppCompatActivity {
 
     private EditText etInput;
     private MaterialButton btnGenerate;
+    private MaterialButton btnSettings;
     private ProgressBar progressBar;
     private TextView tvLoading;
     private MaterialCardView cardResult;
@@ -42,14 +43,21 @@ public class MainActivity extends AppCompatActivity {
     private MaterialButton btnCopy;
 
     private boolean isSubmitting = false;
+    private LocalLlmClient llmClient;
+    private PromptGenerator promptGenerator;
+    private final ExecutorService executor = Executors.newSingleThreadExecutor();
 
     @Override
     protected void onCreate(Bundle savedInstanceState) {
         super.onCreate(savedInstanceState);
         setContentView(R.layout.activity_main);
 
+        llmClient = new LocalLlmClient(this);
+        promptGenerator = new PromptGenerator(llmClient);
+
         etInput = findViewById(R.id.etInput);
         btnGenerate = findViewById(R.id.btnGenerate);
+        btnSettings = findViewById(R.id.btnSettings);
         progressBar = findViewById(R.id.progressBar);
         tvLoading = findViewById(R.id.tvLoading);
         cardResult = findViewById(R.id.cardResult);
@@ -59,6 +67,15 @@ public class MainActivity extends AppCompatActivity {
 
         btnGenerate.setOnClickListener(v -> doGenerate());
         btnCopy.setOnClickListener(v -> copyPrompt());
+        if (btnSettings != null) {
+            btnSettings.setOnClickListener(v -> startActivity(new Intent(this, SettingsActivity.class)));
+        }
+    }
+
+    @Override
+    protected void onResume() {
+        super.onResume();
+        llmClient.resetApi();
     }
 
     private void doGenerate() {
@@ -76,45 +93,27 @@ public class MainActivity extends AppCompatActivity {
         btnGenerate.setEnabled(false);
         cardResult.setVisibility(View.GONE);
 
-        ExpertGenerate3Request request = new ExpertGenerate3Request(input);
+        executor.execute(() -> {
-        ExpertGenerate3Api api = RetrofitClient.getApi();
+            try {
-
+                ExpertGenerate3Response result = promptGenerator.generate(input, 0.7f, 1000);
-        api.generate(request).enqueue(new Callback<ExpertGenerate3Response>() {
+                runOnUiThread(() -> {
-            @Override
-            public void onResponse(Call<ExpertGenerate3Response> call,
-                                   Response<ExpertGenerate3Response> response) {
                     isSubmitting = false;
                     progressBar.setVisibility(View.GONE);
                     tvLoading.setVisibility(View.GONE);
                     btnGenerate.setEnabled(true);
-
+                    showResult(result);
-                if (response.isSuccessful() && response.body() != null) {
+                });
-                    ExpertGenerate3Response body = response.body();
+            } catch (Exception e) {
-                    if (body.getCode() == 200 && body.getData() != null) {
+                Log.e(TAG, "本地生成失败", e);
-                        showResult(body);
+                runOnUiThread(() -> {
-                    } else {
-                        String msg = body.getMessage() != null ? body.getMessage() : getString(R.string.error_network);
-                        Log.w(TAG, "API 业务错误: code=" + body.getCode() + ", message=" + msg);
-                        Toast.makeText(MainActivity.this, msg, Toast.LENGTH_LONG).show();
-                    }
-                } else {
-                    String err = "HTTP " + response.code() + (response.errorBody() != null ? ": " + response.message() : "");
-                    Log.e(TAG, "API 请求失败: " + err);
-                    Toast.makeText(MainActivity.this, getString(R.string.error_network) + " " + err,
-                            Toast.LENGTH_LONG).show();
-                }
-            }
-
-            @Override
-            public void onFailure(Call<ExpertGenerate3Response> call, Throwable t) {
                     isSubmitting = false;
                     progressBar.setVisibility(View.GONE);
                     tvLoading.setVisibility(View.GONE);
                     btnGenerate.setEnabled(true);
-                String detail = t != null ? t.getMessage() : "unknown";
+                    Toast.makeText(MainActivity.this,
-                Log.e(TAG, "网络请求失败: " + detail, t);
+                            getString(R.string.error_network) + ": " + e.getMessage(),
-                Toast.makeText(MainActivity.this, getString(R.string.error_network) + ": " + detail,
                             Toast.LENGTH_LONG).show();
+                });
             }
         });
     }
@@ -151,4 +150,10 @@ public class MainActivity extends AppCompatActivity {
             Toast.makeText(this, R.string.toast_copied, Toast.LENGTH_SHORT).show();
         }
     }
+
+    @Override
+    protected void onDestroy() {
+        executor.shutdown();
+        super.onDestroy();
+    }
 }

exampleAiApp01/app/src/main/java/com/example/promptoptimizer/SettingsActivity.java

@@ -0,0 +1,49 @@
+package com.example.promptoptimizer;
+
+import android.os.Bundle;
+import android.widget.Button;
+import android.widget.EditText;
+import android.widget.Toast;
+
+import androidx.appcompat.app.AppCompatActivity;
+
+import com.example.promptoptimizer.llm.LlmConfig;
+import com.google.android.material.textfield.TextInputEditText;
+
+/**
+ * 本地 LLM 配置
+ */
+public class SettingsActivity extends AppCompatActivity {
+
+    private TextInputEditText etBaseUrl;
+    private TextInputEditText etModel;
+    private Button btnSave;
+    private LlmConfig config;
+
+    @Override
+    protected void onCreate(Bundle savedInstanceState) {
+        super.onCreate(savedInstanceState);
+        setContentView(R.layout.activity_settings);
+
+        config = new LlmConfig(this);
+        etBaseUrl = findViewById(R.id.etBaseUrl);
+        etModel = findViewById(R.id.etModel);
+        btnSave = findViewById(R.id.btnSave);
+
+        etBaseUrl.setText(config.getBaseUrl());
+        etModel.setText(config.getModel());
+
+        btnSave.setOnClickListener(v -> {
+            String url = etBaseUrl.getText() != null ? etBaseUrl.getText().toString().trim() : "";
+            String model = etModel.getText() != null ? etModel.getText().toString().trim() : "";
+            if (url.isEmpty()) {
+                Toast.makeText(this, "请填写 API 地址", Toast.LENGTH_SHORT).show();
+                return;
+            }
+            config.setBaseUrl(url);
+            config.setModel(model.isEmpty() ? "qwen2:0.5b" : model);
+            Toast.makeText(this, "已保存", Toast.LENGTH_SHORT).show();
+            finish();
+        });
+    }
+}

exampleAiApp01/app/src/main/java/com/example/promptoptimizer/llm/ChatCompletionRequest.java

@@ -0,0 +1,48 @@
+package com.example.promptoptimizer.llm;
+
+import com.google.gson.annotations.SerializedName;
+import java.util.List;
+
+/**
+ * OpenAI 兼容的 Chat Completions 请求
+ */
+public class ChatCompletionRequest {
+
+    @SerializedName("model")
+    private String model;
+
+    @SerializedName("messages")
+    private List<Message> messages;
+
+    @SerializedName("temperature")
+    private Float temperature;
+
+    @SerializedName("max_tokens")
+    private Integer maxTokens;
+
+    @SerializedName("stream")
+    private Boolean stream = false;
+
+    public ChatCompletionRequest(String model, List<Message> messages, Float temperature, Integer maxTokens) {
+        this.model = model;
+        this.messages = messages;
+        this.temperature = temperature;
+        this.maxTokens = maxTokens;
+    }
+
+    public static class Message {
+        @SerializedName("role")
+        private String role;
+
+        @SerializedName("content")
+        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; }
+    }
+}

exampleAiApp01/app/src/main/java/com/example/promptoptimizer/llm/ChatCompletionResponse.java

@@ -0,0 +1,37 @@
+package com.example.promptoptimizer.llm;
+
+import com.google.gson.annotations.SerializedName;
+import java.util.List;
+
+/**
+ * OpenAI 兼容的 Chat Completions 响应
+ */
+public class ChatCompletionResponse {
+
+    @SerializedName("choices")
+    private List<Choice> choices;
+
+    public String getContent() {
+        if (choices != null && !choices.isEmpty()) {
+            Choice c = choices.get(0);
+            if (c != null && c.getMessage() != null) {
+                return c.getMessage().getContent();
+            }
+        }
+        return null;
+    }
+
+    public static class Choice {
+        @SerializedName("message")
+        private Message message;
+
+        public Message getMessage() { return message; }
+    }
+
+    public static class Message {
+        @SerializedName("content")
+        private String content;
+
+        public String getContent() { return content; }
+    }
+}

exampleAiApp01/app/src/main/java/com/example/promptoptimizer/llm/LlmConfig.java

@@ -0,0 +1,41 @@
+package com.example.promptoptimizer.llm;
+
+import android.content.Context;
+import android.content.SharedPreferences;
+
+/**
+ * 本地 LLM 配置
+ */
+public class LlmConfig {
+
+    private static final String PREFS = "llm_config";
+    private static final String KEY_BASE_URL = "base_url";
+    private static final String KEY_MODEL = "model";
+
+    // 默认：Ollama 本地。模拟器用 10.0.2.2 访问宿主机
+    private static final String DEFAULT_BASE_URL = "http://10.0.2.2:11434/v1/";
+    private static final String DEFAULT_MODEL = "qwen2:0.5b";
+
+    private final SharedPreferences prefs;
+
+    public LlmConfig(Context context) {
+        prefs = context.getApplicationContext().getSharedPreferences(PREFS, Context.MODE_PRIVATE);
+    }
+
+    public String getBaseUrl() {
+        return prefs.getString(KEY_BASE_URL, DEFAULT_BASE_URL);
+    }
+
+    public void setBaseUrl(String url) {
+        if (url != null && !url.endsWith("/")) url = url + "/";
+        prefs.edit().putString(KEY_BASE_URL, url).apply();
+    }
+
+    public String getModel() {
+        return prefs.getString(KEY_MODEL, DEFAULT_MODEL);
+    }
+
+    public void setModel(String model) {
+        prefs.edit().putString(KEY_MODEL, model != null ? model : DEFAULT_MODEL).apply();
+    }
+}

exampleAiApp01/app/src/main/java/com/example/promptoptimizer/llm/LocalLlmApi.java

@@ -0,0 +1,14 @@
+package com.example.promptoptimizer.llm;
+
+import retrofit2.Call;
+import retrofit2.http.Body;
+import retrofit2.http.POST;
+
+/**
+ * OpenAI 兼容的 LLM API（Ollama / 本地部署等）
+ */
+public interface LocalLlmApi {
+
+    @POST("chat/completions")
+    Call<ChatCompletionResponse> chat(@Body ChatCompletionRequest request);
+}

exampleAiApp01/app/src/main/java/com/example/promptoptimizer/llm/LocalLlmClient.java

@@ -0,0 +1,52 @@
+package com.example.promptoptimizer.llm;
+
+import android.content.Context;
+
+import java.util.concurrent.TimeUnit;
+
+import okhttp3.OkHttpClient;
+import okhttp3.logging.HttpLoggingInterceptor;
+import retrofit2.Retrofit;
+import retrofit2.converter.gson.GsonConverterFactory;
+
+/**
+ * 本地 LLM 客户端（支持 Ollama 等 OpenAI 兼容 API）
+ */
+public class LocalLlmClient {
+
+    private final LlmConfig config;
+    private LocalLlmApi api;
+
+    public LocalLlmClient(Context context) {
+        config = new LlmConfig(context);
+    }
+
+    public LocalLlmApi getApi() {
+        if (api == null) {
+            HttpLoggingInterceptor interceptor = new HttpLoggingInterceptor();
+            interceptor.setLevel(HttpLoggingInterceptor.Level.BODY);
+
+            OkHttpClient client = new OkHttpClient.Builder()
+                    .connectTimeout(120, TimeUnit.SECONDS)
+                    .readTimeout(120, TimeUnit.SECONDS)
+                    .writeTimeout(120, TimeUnit.SECONDS)
+                    .addInterceptor(interceptor)
+                    .build();
+
+            Retrofit retrofit = new Retrofit.Builder()
+                    .baseUrl(config.getBaseUrl())
+                    .client(client)
+                    .addConverterFactory(GsonConverterFactory.create())
+                    .build();
+            api = retrofit.create(LocalLlmApi.class);
+        }
+        return api;
+    }
+
+    public void resetApi() {
+        api = null;
+    }
+
+    public String getBaseUrl() { return config.getBaseUrl(); }
+    public String getModel() { return config.getModel(); }
+}

exampleAiApp01/app/src/main/java/com/example/promptoptimizer/llm/PromptGenerator.java

@@ -0,0 +1,186 @@
+package com.example.promptoptimizer.llm;
+
+import android.util.Log;
+
+import com.example.promptoptimizer.model.ExpertGenerate3Response;
+import com.google.gson.Gson;
+import com.google.gson.JsonSyntaxException;
+
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+import retrofit2.Response;
+
+/**
+ * 两阶段专家提示词生成（参考《生成专业提示词代码逻辑分析》）
+ * 第一阶段：意图分析 → 第二阶段：领域专家生成
+ */
+public class PromptGenerator {
+
+    private static final String TAG = "PromptGenerator";
+
+    private static final String INTENT_PROMPT = "你是一位资深的意图分析专家，请分析用户输入的意图和需求。\n\n" +
+            "你必须严格按照以下JSON格式返回，不要添加任何其他内容：\n" +
+            "{\n" +
+            "    \"core_intent\": \"技术\",\n" +
+            "    \"domain\": \"具体专业领域\",\n" +
+            "    \"key_requirements\": [\"需求1\", \"需求2\"],\n" +
+            "    \"expected_output\": \"期望输出的具体形式\",\n" +
+            "    \"constraints\": [\"约束1\", \"约束2\"],\n" +
+            "    \"keywords\": [\"关键词1\", \"关键词2\"]\n" +
+            "}\n\n" +
+            "注意：\n" +
+            "1. 严格遵守JSON格式\n" +
+            "2. core_intent必须是以下之一：技术、创意、分析、咨询\n" +
+            "3. 数组至少包含1个元素\n" +
+            "4. 所有字段都必须存在\n" +
+            "5. 不要包含注释\n" +
+            "6. 不要添加任何额外的文本";
+
+    private static final Map<String, String> EXPERT_TEMPLATES = new HashMap<>();
+    static {
+        EXPERT_TEMPLATES.put("技术", "你是一位专业的技术领域提示工程师。基于以下意图分析，生成一个专业的技术任务提示词：\n\n意图分析：\n{analysis}\n\n请生成的提示词包含：\n1. 明确的技术背景和上下文\n2. 具体的技术要求和规范\n3. 性能和质量标准\n4. 技术约束条件\n5. 预期交付成果\n6. 评估标准\n\n使用专业技术术语，确保提示词的可执行性和可验证性。");
+        EXPERT_TEMPLATES.put("创意", "你是一位专业的创意领域提示工程师。基于以下意图分析，生成一个创意设计提示词：\n\n意图分析：\n{analysis}\n\n请生成的提示词包含：\n1. 创意方向和灵感来源\n2. 风格和氛围要求\n3. 目标受众定义\n4. 设计元素规范\n5. 创意表现形式\n6. 评估标准\n\n使用专业创意术语，确保提示词的创新性和可执行性。");
+        EXPERT_TEMPLATES.put("分析", "你是一位专业的数据分析提示工程师。基于以下意图分析，生成一个数据分析提示词：\n\n意图分析：\n{analysis}\n\n请生成的提示词包含：\n1. 分析目标和范围\n2. 数据要求和规范\n3. 分析方法和工具\n4. 输出格式要求\n5. 关键指标定义\n6. 质量控制标准\n\n使用专业分析术语，确保提示词的科学性和可操作性。");
+        EXPERT_TEMPLATES.put("咨询", "你是一位专业的咨询领域提示工程师。基于以下意图分析，生成一个咨询服务提示词：\n\n意图分析：\n{analysis}\n\n请生成的提示词包含：\n1. 咨询问题界定\n2. 背景信息要求\n3. 分析框架设定\n4. 建议输出格式\n5. 实施考虑因素\n6. 效果评估标准\n\n使用专业咨询术语，确保提示词的专业性和实用性。");
+    }
+
+    private static final String FALLBACK_TEMPLATE = "你是一位专业的通用领域提示工程师。基于以下意图分析，生成一个专业的提示词：\n\n意图分析：\n{analysis}\n\n请生成的提示词包含：\n1. 明确的目标定义\n2. 具体要求和规范\n3. 质量标准\n4. 约束条件\n5. 预期输出\n6. 评估标准\n\n确保提示词的清晰性和可执行性。";
+
+    private final LocalLlmClient llmClient;
+    private final Gson gson = new Gson();
+
+    public PromptGenerator(LocalLlmClient llmClient) {
+        this.llmClient = llmClient;
+    }
+
+    /**
+     * 同步执行两阶段生成（需在后台线程调用）
+     */
+    public ExpertGenerate3Response generate(String userInput, float temperature, int maxTokens) throws Exception {
+        String model = llmClient.getModel();
+        LocalLlmApi api = llmClient.getApi();
+
+        // 第一阶段：意图分析
+        List<ChatCompletionRequest.Message> intentMessages = Arrays.asList(
+                new ChatCompletionRequest.Message("system", INTENT_PROMPT),
+                new ChatCompletionRequest.Message("user", userInput)
+        );
+        ChatCompletionRequest intentReq = new ChatCompletionRequest(model, intentMessages, 0.1f, 1024);
+        Response<ChatCompletionResponse> intentResp = api.chat(intentReq).execute();
+        if (!intentResp.isSuccessful() || intentResp.body() == null) {
+            throw new Exception("意图分析请求失败: " + (intentResp.errorBody() != null ? intentResp.errorBody().string() : intentResp.code()));
+        }
+        String intentRaw = intentResp.body().getContent();
+        if (intentRaw == null || intentRaw.isEmpty()) {
+            throw new Exception("意图分析返回为空");
+        }
+        intentRaw = intentRaw.replace("```json", "").replace("```", "").trim();
+
+        IntentAnalysis intent = parseIntent(intentRaw);
+        if (intent == null) {
+            throw new Exception("意图分析解析失败");
+        }
+
+        // 第二阶段：领域专家生成
+        String template = EXPERT_TEMPLATES.getOrDefault(intent.coreIntent, FALLBACK_TEMPLATE);
+        String analysisStr = gson.toJson(intent.toMap());
+        String expertPrompt = template.replace("{analysis}", analysisStr);
+
+        List<ChatCompletionRequest.Message> expertMessages = Arrays.asList(
+                new ChatCompletionRequest.Message("system", expertPrompt),
+                new ChatCompletionRequest.Message("user", userInput)
+        );
+        ChatCompletionRequest expertReq = new ChatCompletionRequest(model, expertMessages, temperature, maxTokens);
+        Response<ChatCompletionResponse> expertResp = api.chat(expertReq).execute();
+        if (!expertResp.isSuccessful() || expertResp.body() == null) {
+            throw new Exception("提示词生成请求失败: " + expertResp.code());
+        }
+        String generated = expertResp.body().getContent();
+        if (generated == null || generated.isEmpty()) {
+            throw new Exception("生成结果为空");
+        }
+
+        ExpertGenerate3Response result = new ExpertGenerate3Response();
+        result.setCode(200);
+        result.setMessage("success");
+        ExpertGenerate3Response.ResponseData data = new ExpertGenerate3Response.ResponseData();
+        data.setIntentAnalysis(intent.toIntentAnalysis());
+        data.setGeneratedPrompt(generated.trim());
+        result.setData(data);
+        return result;
+    }
+
+    @SuppressWarnings("unchecked")
+    private IntentAnalysis parseIntent(String json) {
+        try {
+            Map<String, Object> map = gson.fromJson(json, Map.class);
+            if (map == null) return null;
+
+            IntentAnalysis ia = new IntentAnalysis();
+            ia.coreIntent = safeStr(map.get("core_intent"), "技术");
+            if (!Arrays.asList("技术", "创意", "分析", "咨询").contains(ia.coreIntent)) {
+                ia.coreIntent = "技术";
+            }
+            ia.domain = safeStr(map.get("domain"), "未指定");
+            ia.expectedOutput = safeStr(map.get("expected_output"), "未指定");
+            ia.keyRequirements = toStrList(map.get("key_requirements"));
+            ia.constraints = toStrList(map.get("constraints"));
+            ia.keywords = toStrList(map.get("keywords"));
+            return ia;
+        } catch (JsonSyntaxException e) {
+            Log.e(TAG, "JSON 解析失败: " + e.getMessage());
+            return null;
+        }
+    }
+
+    private static String safeStr(Object o, String def) {
+        return o != null ? String.valueOf(o).trim() : def;
+    }
+
+    @SuppressWarnings("unchecked")
+    private static String[] toStrList(Object o) {
+        if (o instanceof List) {
+            List<?> list = (List<?>) o;
+            List<String> out = new ArrayList<>();
+            for (Object item : list) {
+                out.add(String.valueOf(item));
+            }
+            return out.isEmpty() ? new String[]{"未指定"} : out.toArray(new String[0]);
+        }
+        return new String[]{"未指定"};
+    }
+
+    private static class IntentAnalysis {
+        String coreIntent;
+        String domain;
+        String expectedOutput;
+        String[] keyRequirements;
+        String[] constraints;
+        String[] keywords;
+
+        Map<String, Object> toMap() {
+            Map<String, Object> m = new HashMap<>();
+            m.put("core_intent", coreIntent);
+            m.put("domain", domain);
+            m.put("expected_output", expectedOutput);
+            m.put("key_requirements", keyRequirements != null ? Arrays.asList(keyRequirements) : new ArrayList<>());
+            m.put("constraints", constraints != null ? Arrays.asList(constraints) : new ArrayList<>());
+            m.put("keywords", keywords != null ? Arrays.asList(keywords) : new ArrayList<>());
+            return m;
+        }
+
+        ExpertGenerate3Response.IntentAnalysis toIntentAnalysis() {
+            ExpertGenerate3Response.IntentAnalysis out = new ExpertGenerate3Response.IntentAnalysis();
+            out.setCoreIntent(coreIntent);
+            out.setDomain(domain);
+            out.setExpectedOutput(expectedOutput);
+            out.setKeyRequirements(keyRequirements != null ? keyRequirements : new String[]{"未指定"});
+            out.setConstraints(constraints != null ? constraints : new String[]{"未指定"});
+            return out;
+        }
+    }
+}

exampleAiApp01/app/src/main/res/layout/activity_main.xml

@@ -12,14 +12,27 @@
         android:orientation="vertical"
         android:padding="16dp">
 
-        <TextView
+        <LinearLayout
-            android:layout_width="wrap_content"
+            android:layout_width="match_parent"
             android:layout_height="wrap_content"
-            android:text="提示词智能优化"
+            android:orientation="horizontal"
+            android:gravity="center_vertical"
+            android:layout_marginBottom="16dp">
+            <TextView
+                android:layout_width="0dp"
+                android:layout_height="wrap_content"
+                android:layout_weight="1"
+                android:text="提示词智能优化（本地）"
                 android:textSize="22sp"
                 android:textStyle="bold"
-            android:textColor="#1E3A8A"
+                android:textColor="#1E3A8A" />
-            android:layout_marginBottom="16dp" />
+            <com.google.android.material.button.MaterialButton
+                android:id="@+id/btnSettings"
+                style="@style/Widget.Material3.Button.TextButton"
+                android:layout_width="wrap_content"
+                android:layout_height="wrap_content"
+                android:text="设置" />
+        </LinearLayout>
 
         <com.google.android.material.card.MaterialCardView
             android:layout_width="match_parent"

exampleAiApp01/app/src/main/res/layout/activity_settings.xml

@@ -0,0 +1,65 @@
+<?xml version="1.0" encoding="utf-8"?>
+<ScrollView xmlns:android="http://schemas.android.com/apk/res/android"
+    xmlns:app="http://schemas.android.com/apk/res-auto"
+    android:layout_width="match_parent"
+    android:layout_height="match_parent"
+    android:padding="16dp">
+
+    <LinearLayout
+        android:layout_width="match_parent"
+        android:layout_height="wrap_content"
+        android:orientation="vertical">
+
+        <TextView
+            android:layout_width="wrap_content"
+            android:layout_height="wrap_content"
+            android:text="本地模型配置"
+            android:textSize="20sp"
+            android:textStyle="bold"
+            android:layout_marginBottom="24dp" />
+
+        <com.google.android.material.textfield.TextInputLayout
+            android:layout_width="match_parent"
+            android:layout_height="wrap_content"
+            android:hint="API 地址（Ollama 默认 http://10.0.2.2:11434/v1/）"
+            style="@style/Widget.Material3.TextInputLayout.OutlinedBox"
+            android:layout_marginBottom="16dp">
+
+            <com.google.android.material.textfield.TextInputEditText
+                android:id="@+id/etBaseUrl"
+                android:layout_width="match_parent"
+                android:layout_height="wrap_content"
+                android:inputType="textUri" />
+        </com.google.android.material.textfield.TextInputLayout>
+
+        <com.google.android.material.textfield.TextInputLayout
+            android:layout_width="match_parent"
+            android:layout_height="wrap_content"
+            android:hint="模型名称（如 qwen2:0.5b、llama2）"
+            style="@style/Widget.Material3.TextInputLayout.OutlinedBox"
+            android:layout_marginBottom="24dp">
+
+            <com.google.android.material.textfield.TextInputEditText
+                android:id="@+id/etModel"
+                android:layout_width="match_parent"
+                android:layout_height="wrap_content"
+                android:inputType="text" />
+        </com.google.android.material.textfield.TextInputLayout>
+
+        <com.google.android.material.button.MaterialButton
+            android:id="@+id/btnSave"
+            android:layout_width="match_parent"
+            android:layout_height="wrap_content"
+            android:text="保存" />
+
+        <TextView
+            android:layout_width="match_parent"
+            android:layout_height="wrap_content"
+            android:layout_marginTop="24dp"
+            android:text="说明：\n1. 请先在电脑安装 Ollama，运行 ollama run qwen2:0.5b\n2. 模拟器访问宿主机用 10.0.2.2，真机用电脑局域网 IP\n3. 例如：http://192.168.1.100:11434/v1/"
+            android:textSize="12sp"
+            android:textColor="#666666"
+            android:lineSpacingExtra="4dp" />
+
+    </LinearLayout>
+</ScrollView>

exampleAiApp01/gradlew

@@ -0,0 +1,172 @@
+#!/usr/bin/env sh
+
+##############################################################################
+##
+##  Gradle start up script for UN*X
+##
+##############################################################################
+
+# Attempt to set APP_HOME
+# Resolve links: $0 may be a link
+PRG="$0"
+# Need this for relative symlinks.
+while [ -h "$PRG" ] ; do
+    ls=`ls -ld "$PRG"`
+    link=`expr "$ls" : '.*-> \(.*\)$'`
+    if expr "$link" : '/.*' > /dev/null; then
+        PRG="$link"
+    else
+        PRG=`dirname "$PRG"`"/$link"
+    fi
+done
+SAVED="`pwd`"
+cd "`dirname \"$PRG\"`/" >/dev/null
+APP_HOME="`pwd -P`"
+cd "$SAVED" >/dev/null
+
+APP_NAME="Gradle"
+APP_BASE_NAME=`basename "$0"`
+
+# Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
+DEFAULT_JVM_OPTS=""
+
+# Use the maximum available, or set MAX_FD != -1 to use that value.
+MAX_FD="maximum"
+
+warn () {
+    echo "$*"
+}
+
+die () {
+    echo
+    echo "$*"
+    echo
+    exit 1
+}
+
+# OS specific support (must be 'true' or 'false').
+cygwin=false
+msys=false
+darwin=false
+nonstop=false
+case "`uname`" in
+  CYGWIN* )
+    cygwin=true
+    ;;
+  Darwin* )
+    darwin=true
+    ;;
+  MINGW* )
+    msys=true
+    ;;
+  NONSTOP* )
+    nonstop=true
+    ;;
+esac
+
+CLASSPATH=$APP_HOME/gradle/wrapper/gradle-wrapper.jar
+
+# Determine the Java command to use to start the JVM.
+if [ -n "$JAVA_HOME" ] ; then
+    if [ -x "$JAVA_HOME/jre/sh/java" ] ; then
+        # IBM's JDK on AIX uses strange locations for the executables
+        JAVACMD="$JAVA_HOME/jre/sh/java"
+    else
+        JAVACMD="$JAVA_HOME/bin/java"
+    fi
+    if [ ! -x "$JAVACMD" ] ; then
+        die "ERROR: JAVA_HOME is set to an invalid directory: $JAVA_HOME
+
+Please set the JAVA_HOME variable in your environment to match the
+location of your Java installation."
+    fi
+else
+    JAVACMD="java"
+    which java >/dev/null 2>&1 || die "ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
+
+Please set the JAVA_HOME variable in your environment to match the
+location of your Java installation."
+fi
+
+# Increase the maximum file descriptors if we can.
+if [ "$cygwin" = "false" -a "$darwin" = "false" -a "$nonstop" = "false" ] ; then
+    MAX_FD_LIMIT=`ulimit -H -n`
+    if [ $? -eq 0 ] ; then
+        if [ "$MAX_FD" = "maximum" -o "$MAX_FD" = "max" ] ; then
+            MAX_FD="$MAX_FD_LIMIT"
+        fi
+        ulimit -n $MAX_FD
+        if [ $? -ne 0 ] ; then
+            warn "Could not set maximum file descriptor limit: $MAX_FD"
+        fi
+    else
+        warn "Could not query maximum file descriptor limit: $MAX_FD_LIMIT"
+    fi
+fi
+
+# For Darwin, add options to specify how the application appears in the dock
+if $darwin; then
+    GRADLE_OPTS="$GRADLE_OPTS \"-Xdock:name=$APP_NAME\" \"-Xdock:icon=$APP_HOME/media/gradle.icns\""
+fi
+
+# For Cygwin, switch paths to Windows format before running java
+if $cygwin ; then
+    APP_HOME=`cygpath --path --mixed "$APP_HOME"`
+    CLASSPATH=`cygpath --path --mixed "$CLASSPATH"`
+    JAVACMD=`cygpath --unix "$JAVACMD"`
+
+    # We build the pattern for arguments to be converted via cygpath
+    ROOTDIRSRAW=`find -L / -maxdepth 1 -mindepth 1 -type d 2>/dev/null`
+    SEP=""
+    for dir in $ROOTDIRSRAW ; do
+        ROOTDIRS="$ROOTDIRS$SEP$dir"
+        SEP="|"
+    done
+    OURCYGPATTERN="(^($ROOTDIRS))"
+    # Add a user-defined pattern to the cygpath arguments
+    if [ "$GRADLE_CYGPATTERN" != "" ] ; then
+        OURCYGPATTERN="$OURCYGPATTERN|($GRADLE_CYGPATTERN)"
+    fi
+    # Now convert the arguments - kludge to limit ourselves to /bin/sh
+    i=0
+    for arg in "$@" ; do
+        CHECK=`echo "$arg"|egrep -c "$OURCYGPATTERN" -`
+        CHECK2=`echo "$arg"|egrep -c "^-"`                                 ### Determine if an option
+
+        if [ $CHECK -ne 0 ] && [ $CHECK2 -eq 0 ] ; then                    ### Added a condition
+            eval `echo args$i`=`cygpath --path --ignore --mixed "$arg"`
+        else
+            eval `echo args$i`="\"$arg\""
+        fi
+        i=$((i+1))
+    done
+    case $i in
+        (0) set -- ;;
+        (1) set -- "$args0" ;;
+        (2) set -- "$args0" "$args1" ;;
+        (3) set -- "$args0" "$args1" "$args2" ;;
+        (4) set -- "$args0" "$args1" "$args2" "$args3" ;;
+        (5) set -- "$args0" "$args1" "$args2" "$args3" "$args4" ;;
+        (6) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" ;;
+        (7) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" ;;
+        (8) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" ;;
+        (9) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" "$args8" ;;
+    esac
+fi
+
+# Escape application args
+save () {
+    for i do printf %s\\n "$i" | sed "s/'/'\\\\''/g;1s/^/'/;\$s/\$/' \\\\/" ; done
+    echo " "
+}
+APP_ARGS=$(save "$@")
+
+# Collect all arguments for the java command, following the shell quoting and substitution rules
+eval set -- $DEFAULT_JVM_OPTS $JAVA_OPTS $GRADLE_OPTS "\"-Dorg.gradle.appname=$APP_BASE_NAME\"" -classpath "\"$CLASSPATH\"" org.gradle.wrapper.GradleWrapperMain "$APP_ARGS"
+
+# by default we should be in the correct project dir, but when run from Finder on Mac, the cwd is wrong
+if [ "$(uname)" = "Darwin" ] && [ "$HOME" = "$PWD" ]; then
+  cd "$(dirname "$0")"
+fi
+
+exec "$JAVACMD" "$@"

logs/gunicorn_error.log

@@ -10661,3 +10661,4 @@ werkzeug.routing.exceptions.BuildError: Could not build url for endpoint 'expert
 [2026-03-01 23:45:03 +0800] [28566] [INFO] Booting worker with pid: 28566
 [2026-03-01 23:45:03 +0800] [28566] [INFO] 工作进程 28566 已启动
 [2026-03-01 23:45:03 +0800] [28566] [INFO] 工作进程 28566 初始化完成
+[2026-03-02 00:11:37 +0800] [28391] [INFO] Handling signal: winch