技能展示适配持久化 + 参考文献收集与新对话流式修复

- 后端新增 skill_display_adapters 表，持久化每个技能的 display 配置与 sample
  payload；/api/skills 列表、详情、设置接口同步读写
- 新增 /api/skills/{name}/display-sample 端点，编辑器优先加载库中样例
- 前端展示适配面板改为从后端加载持久样例，无样例时提示"自动识别"
- 参考文献收集修复：仅在 bash/shell/python 等执行类工具上从参数推断技能
  名，避免 read_file / web_fetch 误匹配；引用列表纳入最新一条助手消息
- ChatBox 改用「最新 human → 最新 ai」窗口收集引用，并仅保留 citation
  模式
- 修复「新对话」点击后已发消息消失：useThreadStream 只在 threadId 切回
  空值时重置/中止 SSE，避免 onCreated 分配 id 时把刚开始的流打断；
  ChatPage 在 landing 状态隐藏 MessageList，移除 KeyedChatPage remount
- 技能详情对话框：所有者可查看源码与文件 tab（不再要求管理员）
- LocalSandbox：Windows PowerShell 5 路径下把 && 重写为 ;，并以
  UTF-8 解码 subprocess 输出，避免中文乱码
- knowledge-search-v2 mock 样例改为中文固定测试数据

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

offline-backend-20260512/backend/packages/harness/deerflow/persistence/models/__init__.py

@@ -30,7 +30,7 @@ from deerflow.persistence.scheduled_tasks.model import (
     ScheduledTaskSubscriptionRow,
     SchedulerThreadRow,
 )
-from deerflow.persistence.skills.model import SkillRow
+from deerflow.persistence.skills.model import SkillDisplayAdapterRow, SkillRow
 from deerflow.persistence.tags.model import TagAssignmentRow, TagRow
 from deerflow.persistence.thread_meta.model import ThreadMetaRow
 from deerflow.persistence.thread_shares.model import ThreadShareRow
@@ -51,6 +51,7 @@ __all__ = [
     "ScheduledTaskSubscriptionRow",
     "SchedulerThreadRow",
     "SkillRow",
+    "SkillDisplayAdapterRow",
     "TagAssignmentRow",
     "TagRow",
     "ThreadMetaRow",

offline-backend-20260512/backend/packages/harness/deerflow/persistence/skills/model.py

@@ -31,3 +31,16 @@ class SkillRow(Base):
     detail: Mapped[str | None] = mapped_column(Text, nullable=True, default=None)
     created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(UTC))
     updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(UTC), onupdate=lambda: datetime.now(UTC))
+
+
+class SkillDisplayAdapterRow(Base):
+    __tablename__ = "skill_display_adapters"
+
+    skill_name: Mapped[str] = mapped_column(String(64), primary_key=True)
+    # Store JSON as text for maximum MySQL compatibility. Some deployments still
+    # run MySQL variants where native JSON columns or unquoted names such as
+    # ``display`` are not accepted consistently.
+    display_config: Mapped[str | None] = mapped_column(Text, nullable=True, default=None)
+    sample_payload: Mapped[str | None] = mapped_column(Text, nullable=True, default=None)
+    created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(UTC))
+    updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=lambda: datetime.now(UTC), onupdate=lambda: datetime.now(UTC))

offline-backend-20260512/backend/packages/harness/deerflow/sandbox/local/local_sandbox.py

@@ -37,14 +37,26 @@ class LocalSandbox(Sandbox):
         """Return whether the selected shell is a PowerShell executable."""
         return LocalSandbox._shell_name(shell) in {"powershell", "powershell.exe", "pwsh", "pwsh.exe"}
 
-    @staticmethod
-    def _is_cmd_shell(shell: str) -> bool:
-        """Return whether the selected shell is cmd.exe."""
-        return LocalSandbox._shell_name(shell) in {"cmd", "cmd.exe"}
-
-    @staticmethod
-    def _find_first_available_shell(candidates: tuple[str, ...]) -> str | None:
-        """Return the first executable shell path or command found from candidates."""
+    @staticmethod
+    def _is_cmd_shell(shell: str) -> bool:
+        """Return whether the selected shell is cmd.exe."""
+        return LocalSandbox._shell_name(shell) in {"cmd", "cmd.exe"}
+
+    @staticmethod
+    def _normalize_powershell_command(command: str) -> str:
+        """Make bash-style command glue usable in Windows PowerShell 5.
+
+        The public tool is still named ``bash`` for model compatibility, but on
+        Windows local sandbox it may fall back to PowerShell. PowerShell 5 does
+        not support ``&&``, while the sandbox layer prepends commands with
+        ``cd <workspace> &&``. Rewriting the separator keeps skill scripts
+        executable in that fallback shell.
+        """
+        return command.replace("&&", ";")
+
+    @staticmethod
+    def _find_first_available_shell(candidates: tuple[str, ...]) -> str | None:
+        """Return the first executable shell path or command found from candidates."""
         for shell in candidates:
             if os.path.isabs(shell):
                 if os.path.isfile(shell) and os.access(shell, os.X_OK):
@@ -302,30 +314,39 @@ class LocalSandbox(Sandbox):
         resolved_command = self._resolve_paths_in_command(command)
         shell = self._get_shell()
 
-        if os.name == "nt":
-            if self._is_powershell(shell):
-                args = [shell, "-NoProfile", "-Command", resolved_command]
+        if os.name == "nt":
+            if self._is_powershell(shell):
+                args = [
+                    shell,
+                    "-NoProfile",
+                    "-Command",
+                    self._normalize_powershell_command(resolved_command),
+                ]
             elif self._is_cmd_shell(shell):
                 args = [shell, "/c", resolved_command]
             else:
                 args = [shell, "-c", resolved_command]
 
-            result = subprocess.run(
-                args,
-                shell=False,
-                capture_output=True,
-                text=True,
-                timeout=600,
-            )
-        else:
-            args = [shell, "-c", resolved_command]
-            result = subprocess.run(
-                args,
-                shell=False,
-                capture_output=True,
-                text=True,
-                timeout=600,
-            )
+            result = subprocess.run(
+                args,
+                shell=False,
+                capture_output=True,
+                text=True,
+                encoding="utf-8",
+                errors="replace",
+                timeout=600,
+            )
+        else:
+            args = [shell, "-c", resolved_command]
+            result = subprocess.run(
+                args,
+                shell=False,
+                capture_output=True,
+                text=True,
+                encoding="utf-8",
+                errors="replace",
+                timeout=600,
+            )
         output = result.stdout
         if result.stderr:
             output += f"\nStd Error:\n{result.stderr}" if output else result.stderr