fix: 修复 setup_agent 创建专家流程的多个问题

后端 (setup_agent_approval_middleware.py)：
- 拦截策略从 wrap_tool_call + Command(goto=END) 改为
  after_model + jump_to="end"。在 tool_node 执行前直接终止图，
  避免模型并行调多个 tool_call 时 Command 输出被稀释、graph
  路由不稳定的问题（症状：审批 ToolMessage 发出后流不结束）。
- 用 @hook_config(can_jump_to=["end"]) 装饰器声明跳转能力，
  否则 LangChain 不会为该 hook 构造 conditional edge。

前端 (NewAgentPage.tsx)：
- 聊天阶段不再调 ensureAgent / POST /api/agents，placeholder
  agent 不再落库；agent 仅在用户点右上角“保存”时创建。
- 自动生成的占位名 "未命名专家-xxx" 不再回写到输入框，保持空白
  直到用户输入或 setup_agent 审批回填。
- handleApproveSetupAgent 仅把模型 propose 的 payload 填入表单，
  不再 PUT /api/agents/{id}；落库交给手动保存按钮。
- onToolEnd 不再 getAgentWithRetry —— 工具被 middleware 拦截、
  根本不会执行，没有 agent 状态可拉。清理对应死代码（getAgent
  import、wait()、AGENT_READ_RETRY_DELAYS_MS、getAgentWithRetry）。
- 路由跳转补齐 /page 前缀：返回按钮、“开始对话”按钮。
- 右侧表单：SOUL.md textarea 加 max-h-[400px]，技能列表外框加
  max-h-[240px]，各自 overflow-y-auto，避免长内容撑高整列。

前端 (agent-card.tsx)：
- 列表卡片“聊天”按钮的跳转路径补齐 /page 前缀，避免点击后 404。

无新依赖。

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

frontend-web/src/components/workspace/agents/agent-card.tsx

@@ -91,7 +91,7 @@ export function AgentCard({ agent }: AgentCardProps) {
   ]);
 
   function handleChat() {
-    router.push(`/workspace/agents/${agent.id}/chats/new`);
+    router.push(`/page/workspace/agents/${agent.id}/chats/new`);
   }
 
   async function handleDelete() {

frontend-web/src/pages/NewAgentPage.tsx

@@ -30,7 +30,6 @@ import {
   AgentNameCheckError,
   checkAgentName,
   createAgent,
-  getAgent,
   updateAgent,
 } from "@/core/agents/api";
 import { useI18n } from "@/core/i18n/hooks";
@@ -40,27 +39,8 @@ import { useThreadStream } from "@/core/threads/hooks";
 import { uuid } from "@/core/utils/uuid";
 import { cn } from "@/lib/utils";
 
-const AGENT_READ_RETRY_DELAYS_MS = [200, 500, 1_000, 2_000];
 const DEFAULT_SELECTED_SKILL_COUNT = 3;
 
-function wait(ms: number) {
-  return new Promise((resolve) => window.setTimeout(resolve, ms));
-}
-
-async function getAgentWithRetry(agentId: string) {
-  for (const delay of [0, ...AGENT_READ_RETRY_DELAYS_MS]) {
-    if (delay > 0) {
-      await wait(delay);
-    }
-    try {
-      return await getAgent(agentId);
-    } catch {
-      // Retry until the file/database write settles.
-    }
-  }
-  return null;
-}
-
 function getCreateAgentErrorMessage(
   error: unknown,
   networkErrorMessage: string,
@@ -116,19 +96,11 @@ export default function NewAgentPage() {
       mode: "flash",
       is_bootstrap: true,
     },
-    onToolEnd({ name }) {
-      if (name !== "setup_agent" || !agentId) {
-        return;
-      }
-      void getAgentWithRetry(agentId).then((fetched) => {
-        if (fetched) {
-          setAgent(fetched);
-          setDescriptionInput(fetched.description ?? "");
-          setSoulInput(fetched.soul ?? "");
-          setSelectedSkills(fetched.skills ?? []);
-          toast.success("专家配置已创建");
-        }
-      });
+    onToolEnd() {
+      // setup_agent never actually executes in this flow — it gets
+      // intercepted by SetupAgentApprovalMiddleware and the form is filled
+      // from the approval ToolMessage payload (handleApproveSetupAgent).
+      // No agent record is fetched/refreshed during chat.
     },
   });
 
@@ -159,10 +131,13 @@ export default function NewAgentPage() {
     }
     let name = provided;
     if (!name) {
-      // Names are display-only and may collide, so a timestamped placeholder is
-      // safe. Reflect it in the form so the user sees what got created.
+      // Names are display-only and may collide, so a timestamped placeholder
+      // is safe to send to the backend just to satisfy the required-field
+      // validation. Intentionally NOT written back into the visible input —
+      // the user wants the name box to stay blank while they chat, and we
+      // refill it later (with the model's proposed name) on setup_agent
+      // approval.
       name = `未命名专家-${Date.now().toString(36)}`;
-      setNameInput(name);
     }
 
     if (agentId) {
@@ -239,63 +214,37 @@ export default function NewAgentPage() {
       if (!trimmed || thread.isLoading) {
         return;
       }
-      // Lazily create the agent on first message so the user can just start
-      // typing — ensureAgent generates a placeholder name when none is provided.
-      let activeAgentId = agentId;
-      if (!activeAgentId) {
-        const created = await ensureAgent();
-        if (!created) {
-          return;
-        }
-        activeAgentId = created.id;
-      }
+      // Chat is purely a discussion channel. The agent record is only
+      // created when the user explicitly clicks Save (top-right). If the
+      // model proposes a config via setup_agent, our approval handler
+      // prefills the form locally — it does NOT persist anything.
       await ensureThreadExists();
-      await sendMessage(
-        threadId,
-        { text: trimmed, files: [] },
-        { agent_id: activeAgentId },
-      );
+      await sendMessage(threadId, { text: trimmed, files: [] });
     },
-    [agentId, ensureAgent, ensureThreadExists, sendMessage, thread.isLoading, threadId],
+    [ensureThreadExists, sendMessage, thread.isLoading, threadId],
   );
 
   const handleApproveSetupAgent = useCallback(
     async (payload: SetupAgentApprovalPayload) => {
-      if (!agentId) {
-        return;
-      }
-      // Approval persists directly to the backend — no LLM round-trip. The
-      // backend's PUT /api/agents/{id} writes both the DB record and SOUL.md /
-      // config.yaml on disk, which is exactly what setup_agent_tool would have
-      // done if we'd let the model re-invoke it.
+      // Approving the model's setup_agent proposal **does not** persist
+      // anything — it only mirrors the proposal into the form so the user
+      // can review it. Creation/update happens later when the user clicks
+      // the top-right Save button.
       const proposedName = payload.name?.trim() ?? "";
       const newDescription = payload.description ?? "";
       const newSoul = payload.soul ?? "";
       const newSkills = payload.skills ?? [];
 
-      // Prefer the model's proposed name when present; fall back to whatever
-      // the user already typed, or the existing agent record.
-      const resolvedName = proposedName || nameInput.trim() || agent?.name || agentId;
-      setNameInput(resolvedName);
+      if (proposedName) {
+        setNameInput(proposedName);
+      }
       setDescriptionInput(newDescription);
       setSoulInput(newSoul);
       setSelectedSkills(newSkills);
       setIsSkillSelectionTouched(true);
-
-      try {
-        const updated = await updateAgent(agentId, {
-          name: resolvedName,
-          description: newDescription,
-          soul: newSoul,
-          skills: newSkills,
-        });
-        setAgent(updated);
-        toast.success("专家配置已保存");
-      } catch (error) {
-        toast.error(error instanceof Error ? error.message : "保存失败");
-      }
+      toast.success("已套用模型建议，可继续编辑或点保存");
     },
-    [agent, agentId, nameInput],
+    [],
   );
 
   const handleRejectSetupAgent = useCallback(
@@ -326,7 +275,7 @@ export default function NewAgentPage() {
               <Button
                 variant="ghost"
                 size="icon-sm"
-                onClick={() => router.push("/workspace/agents")}
+                onClick={() => router.push("/page/workspace/agents")}
               >
                 <ArrowLeftIcon className="h-4 w-4" />
               </Button>
@@ -336,7 +285,7 @@ export default function NewAgentPage() {
               <Button
                 variant="outline"
                 size="sm"
-                onClick={() => router.push(`/workspace/agents/${agent.id}/chats/new`)}
+                onClick={() => router.push(`/page/workspace/agents/${agent.id}/chats/new`)}
               >
                 <CheckCircleIcon className="h-4 w-4" />
                 开始对话
@@ -411,7 +360,7 @@ export default function NewAgentPage() {
                     placeholder="写下专家的人设、边界、工作方式和输出要求"
                     value={soulInput}
                     onChange={(event) => setSoulInput(event.currentTarget.value)}
-                    className="min-h-48 resize-y font-mono text-xs"
+                    className="min-h-48 max-h-[400px] resize-y overflow-y-auto font-mono text-xs"
                   />
                 </div>
 
@@ -422,7 +371,7 @@ export default function NewAgentPage() {
                       已选 {selectedSkills.length} 个
                     </span>
                   </div>
-                  <div className="rounded-md border p-2">
+                  <div className="max-h-[240px] overflow-y-auto rounded-md border p-2">
                     {isSkillsLoading ? (
                       <p className="text-muted-foreground text-sm">技能加载中...</p>
                     ) : enabledSkills.length === 0 ? (

offline-backend-20260512/backend/packages/harness/deerflow/agents/middlewares/setup_agent_approval_middleware.py

@@ -3,16 +3,13 @@
 from __future__ import annotations
 
 import logging
-from collections.abc import Callable
 from hashlib import sha256
 from typing import Any, override
 
 from langchain.agents import AgentState
-from langchain.agents.middleware import AgentMiddleware
-from langchain_core.messages import ToolMessage
-from langgraph.graph import END
-from langgraph.prebuilt.tool_node import ToolCallRequest
-from langgraph.types import Command
+from langchain.agents.middleware import AgentMiddleware, hook_config
+from langchain_core.messages import AIMessage, ToolMessage
+from langgraph.runtime import Runtime
 
 logger = logging.getLogger(__name__)
 
@@ -26,15 +23,22 @@ class SetupAgentApprovalMiddlewareState(AgentState):
 class SetupAgentApprovalMiddleware(AgentMiddleware[SetupAgentApprovalMiddlewareState]):
     """Stop before ``setup_agent`` writes files and ask the user to approve.
 
-    The first ``setup_agent`` call is converted into a structured tool message
-    and the run ends. A subsequent request can set ``setup_agent_approved`` in
-    runtime context to allow the tool to execute.
+    The interception runs in ``after_model``: as soon as the model emits an
+    AIMessage that contains a ``setup_agent`` tool call (and the run has not
+    been pre-approved via ``setup_agent_approved=True`` in runtime context),
+    we append a structured approval ``ToolMessage`` and return
+    ``jump_to="end"`` to terminate the LangGraph run *before* the tool node
+    executes. This is the LangChain-recommended way to short-circuit after
+    the model; using ``wrap_tool_call`` + ``Command(goto=END)`` proved
+    unreliable when the AIMessage contained multiple parallel tool calls
+    (the ``Command`` got mixed with normal tool outputs and the graph
+    looped back to the model instead of terminating).
     """
 
     state_schema = SetupAgentApprovalMiddlewareState
 
-    def _is_approved(self, request: ToolCallRequest) -> bool:
-        context = getattr(request.runtime, "context", None) or {}
+    def _is_approved(self, runtime: Runtime) -> bool:
+        context = getattr(runtime, "context", None) or {}
         if not isinstance(context, dict):
             return False
         return context.get("setup_agent_approved") is True
@@ -54,37 +58,57 @@ class SetupAgentApprovalMiddleware(AgentMiddleware[SetupAgentApprovalMiddlewareS
             "skills": skills if isinstance(skills, list) else [],
         }
 
-    def _handle_setup_agent(self, request: ToolCallRequest) -> Command:
-        args = request.tool_call.get("args", {}) or {}
-        tool_call_id = request.tool_call.get("id", "")
+    def _intercept(self, last: AIMessage) -> dict[str, Any] | None:
+        """Return a state update if setup_agent must be gated; None to passthrough."""
+        tool_calls = list(last.tool_calls or [])
+        setup_call = next((tc for tc in tool_calls if tc.get("name") == "setup_agent"), None)
+        if setup_call is None:
+            return None
+
+        args = setup_call.get("args") or {}
+        tool_call_id = setup_call.get("id") or ""
         payload = self._build_payload(args)
         logger.info("Setup agent approval requested before writing agent files")
 
-        message = ToolMessage(
+        approval_msg = ToolMessage(
             id=self._stable_message_id(tool_call_id, args),
             content="请确认是否创建/更新这个专家配置。",
             tool_call_id=tool_call_id,
             name="setup_agent",
             additional_kwargs={"setup_agent_approval": payload},
         )
-        return Command(update={"messages": [message]}, goto=END)
 
-    @override
-    def wrap_tool_call(
-        self,
-        request: ToolCallRequest,
-        handler: Callable[[ToolCallRequest], ToolMessage | Command],
-    ) -> ToolMessage | Command:
-        if request.tool_call.get("name") != "setup_agent" or self._is_approved(request):
-            return handler(request)
-        return self._handle_setup_agent(request)
+        # Any other tool_calls on the same AIMessage are left dangling; the
+        # existing DanglingToolCallMiddleware will inject placeholder
+        # ToolMessages on the next model invocation, which matches the
+        # desired semantics: every action pauses until the user approves.
+        return {
+            "messages": [approval_msg],
+            "jump_to": "end",
+        }
 
+    @hook_config(can_jump_to=["end"])
     @override
-    async def awrap_tool_call(
+    def after_model(
         self,
-        request: ToolCallRequest,
-        handler: Callable[[ToolCallRequest], ToolMessage | Command],
-    ) -> ToolMessage | Command:
-        if request.tool_call.get("name") != "setup_agent" or self._is_approved(request):
-            return await handler(request)
-        return self._handle_setup_agent(request)
+        state: SetupAgentApprovalMiddlewareState,
+        runtime: Runtime,
+    ) -> dict[str, Any] | None:
+        if self._is_approved(runtime):
+            return None
+        messages = state.get("messages") or []
+        if not messages:
+            return None
+        last = messages[-1]
+        if not isinstance(last, AIMessage):
+            return None
+        return self._intercept(last)
+
+    @hook_config(can_jump_to=["end"])
+    @override
+    async def aafter_model(
+        self,
+        state: SetupAgentApprovalMiddlewareState,
+        runtime: Runtime,
+    ) -> dict[str, Any] | None:
+        return self.after_model(state, runtime)