feat: 支持多语言提示词本地化和界面优化

- 添加 prompt_locale 参数支持简体中文、繁体中文和英文提示词本地化
- 移除内置 agents 配置以简化系统架构
- 更新 ContextBuilder 使用动态提示词模板而非硬编码内容
- 在 AgentLoop、Web 接口和 AgentService 中传递 locale 参数
- 添加输出语言指令确保用户界面内容按指定语言生成
- 扩展前端 LanguageSwitcher 组件支持三种语言选项
- 优化 Header 和侧边栏组件的响应式布局和文本截断处理
- 更新测试用例验证不同语言环境下的提示词正确性

app-instance/backend/tests/unit/test_context_builder.py

@@ -26,3 +26,26 @@ def test_context_builder_injects_current_date_and_time() -> None:
     assert "Local UTC offset: +08:00" in system_prompt
     assert '"today", "tomorrow", "now", "this week", and "next month"' in system_prompt
     assert result.messages[-1] == {"role": "user", "content": "今天几号？"}
+
+
+def test_context_builder_uses_simplified_main_agent_prompt_by_default() -> None:
+    system_prompt = ContextBuilder().build_system_prompt(ContextBuildInput())
+
+    assert "你是海狸 (Beaver)" in system_prompt
+    assert "博维资讯系统有限公司研发的 AI 助手" in system_prompt
+    assert "使用简体中文进行面向用户的回复" in system_prompt
+
+
+def test_context_builder_uses_traditional_main_agent_prompt_for_zh_hant() -> None:
+    system_prompt = ContextBuilder().build_system_prompt(ContextBuildInput(prompt_locale="zh-Hant"))
+
+    assert "你是海狸 (Beaver)" in system_prompt
+    assert "博維資訊系統有限公司研發的 AI 助手" in system_prompt
+    assert "使用繁體中文進行面向使用者的回覆" in system_prompt
+
+
+def test_context_builder_uses_english_main_agent_prompt_for_en() -> None:
+    system_prompt = ContextBuilder().build_system_prompt(ContextBuildInput(prompt_locale="en"))
+
+    assert "You are Beaver, an AI assistant developed by Boway Information Systems Co., Ltd." in system_prompt
+    assert "Use English for user-facing replies" in system_prompt

app-instance/backend/tests/unit/test_task_mode_feedback.py

@@ -15,6 +15,7 @@ class StubProvider(LLMProvider):
     def __init__(self, responses: list[LLMResponse]) -> None:
         super().__init__()
         self._responses = list(responses)
+        self.seen_messages: list[list[dict]] = []
 
     async def chat(
         self,
@@ -26,6 +27,7 @@ class StubProvider(LLMProvider):
     ) -> LLMResponse:
         if not self._responses:
             raise AssertionError("No stubbed provider responses left")
+        self.seen_messages.append(messages)
         return self._responses.pop(0)
 
     def get_default_model(self) -> str:
@@ -99,6 +101,52 @@ def test_task_run_records_evidence_and_waits_for_acceptance(tmp_path: Path) -> N
     assert "validated" not in event_types
 
 
+def test_task_mode_injects_prompt_locale_output_language(tmp_path: Path) -> None:
+    service = AgentService(
+        loader=EngineLoader(
+            workspace=tmp_path,
+            task_execution_planner=StubTaskExecutionPlanner(),
+        )
+    )
+    main_provider = StubProvider(
+        [
+            LLMResponse(
+                content="Done",
+                finish_reason="stop",
+                provider_name="stub",
+                model="stub-model",
+            )
+        ]
+    )
+    bundle = ProviderBundle(
+        main_runtime=SimpleNamespace(model="stub-model", provider_name="stub"),
+        main_provider=main_provider,
+        auxiliary_runtime=SimpleNamespace(model="stub-model", provider_name="stub"),
+        auxiliary_provider=StubProvider([_route_response("new_task", "Product summary")]),
+    )
+
+    result = asyncio.run(
+        service.process_direct(
+            "Summarize the uploaded report in English",
+            session_id="web:locale-task",
+            prompt_locale="en",
+            provider_bundle=bundle,
+        )
+    )
+
+    assert result.task_id
+    assert main_provider.seen_messages
+    system_prompt = main_provider.seen_messages[-1][0]["content"]
+    assert "Use English for user-facing replies" in system_prompt
+    assert "Output language: English." in system_prompt
+
+    task_service = service.create_loop().boot().task_service
+    assert task_service is not None
+    task = task_service.get_task(result.task_id)
+    assert task is not None
+    assert task.metadata["prompt_locale"] == "en"
+
+
 def test_unrelated_simple_chat_auto_accepts_active_task(tmp_path: Path) -> None:
     service = AgentService(
         loader=EngineLoader(

app-instance/backend/tests/unit/test_websocket_chat.py

@@ -73,6 +73,7 @@ def test_websocket_message_returns_chat_metadata_and_session_updated() -> None:
                 {
                     "type": "message",
                     "content": "hello",
+                    "prompt_locale": "zh-Hant",
                     "metadata": {"source": "test"},
                     "attachments": [{"file_id": "file-1", "name": "a.txt"}],
                 }
@@ -89,6 +90,7 @@ def test_websocket_message_returns_chat_metadata_and_session_updated() -> None:
             "user_id": None,
             "title": None,
             "execution_context": None,
+            "prompt_locale": "zh-Hant",
             "model": None,
             "provider_name": None,
             "embedding_model": None,
@@ -134,6 +136,7 @@ def test_websocket_message_uses_direct_processing_when_loop_is_not_running() ->
             "user_id": None,
             "title": None,
             "execution_context": None,
+            "prompt_locale": None,
             "model": None,
             "provider_name": None,
             "embedding_model": None,
@@ -149,7 +152,10 @@ def test_rest_chat_uses_direct_processing_when_loop_is_not_running() -> None:
     app = create_app(service=service, manage_service_lifecycle=False)
 
     with TestClient(app) as client:
-        response = client.post("/api/chat", json={"session_id": "web:alpha", "message": "hello"})
+        response = client.post(
+            "/api/chat",
+            json={"session_id": "web:alpha", "message": "hello", "prompt_locale": "en"},
+        )
 
     assert response.status_code == 200
     assert service.calls == [
@@ -160,6 +166,7 @@ def test_rest_chat_uses_direct_processing_when_loop_is_not_running() -> None:
             "user_id": None,
             "title": None,
             "execution_context": None,
+            "prompt_locale": "en",
             "model": None,
             "provider_name": None,
             "embedding_model": None,