feat: 智能体创建流程优化与管理员记忆页面

- 创建智能体页面：保存后自动跳转列表页、技能列表增加搜索过滤框
- Bootstrap 模式：开放全部技能可见性，注入专属提示词（skill_list 匹配意图、禁止 skill_manage）
- 管理员记忆页面：新增 AdminMemoryPage 及路由，支持查看/编辑用户记忆条目
- 内存配置与管理员用户接口同步更新

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

offline-backend-20260512/backend/app/gateway/routers/admin_users.py

@@ -19,12 +19,12 @@ from fastapi import APIRouter, HTTPException, Query, Request
 from pydantic import BaseModel, Field
 
 from app.gateway.deps import (
+    get_agent_store,
     get_checkpointer,
     get_current_user_from_request,
     get_thread_store,
 )
 from deerflow.agents.memory import BuiltinFileProvider
-from deerflow.config.agents_config import AGENT_NAME_PATTERN
 from deerflow.config.paths import get_paths
 from deerflow.runtime import serialize_channel_values
 
@@ -127,10 +127,22 @@ async def list_user_thread_messages(
 
 
 class AdminMemoryBucket(BaseModel):
-    name: str = Field(..., description="Bucket name: 'global' or a custom-agent name")
+    name: str = Field(..., description="Bucket name: 'global' or the agent id (used for CRUD)")
+    display_name: str = Field("", description="Human-readable name shown in the UI")
     data: dict = Field(default_factory=dict, description="Raw memory data for the bucket")
 
 
+class AdminMemoryEntryAddRequest(BaseModel):
+    content: str = Field(..., min_length=1, description="Entry content to add")
+    agent: str | None = Field(None, description="Agent name; None = global USER.md bucket")
+
+
+class AdminMemoryEntryReplaceRequest(BaseModel):
+    old_text: str = Field(..., min_length=1, description="Short unique substring to locate the entry")
+    content: str = Field(..., min_length=1, description="New content to replace with")
+    agent: str | None = Field(None, description="Agent name; None = global USER.md bucket")
+
+
 class AdminMemoryResponse(BaseModel):
     user_id: str
     buckets: list[AdminMemoryBucket] = Field(default_factory=list)
@@ -154,25 +166,103 @@ async def get_user_memory(user_id: str, request: Request) -> AdminMemoryResponse
 
     Memory V2 layout: the ``global`` bucket is ``USER.md`` (user profile);
     each per-agent bucket is that agent's ``MEMORY.md`` working notes.
+    Agent list is sourced from the database (all agents owned by this user)
+    so agents without any existing MEMORY.md still appear.
     """
     await _require_admin(request)
 
     buckets: list[AdminMemoryBucket] = [
-        AdminMemoryBucket(name="global", data=_read_memory_bucket(user_id, None))
+        AdminMemoryBucket(name="global", display_name="用户画像", data=_read_memory_bucket(user_id, None))
     ]
 
-    agents_root = get_paths().user_dir(user_id) / "agents"
-    if agents_root.is_dir():
-        for entry in sorted(agents_root.iterdir(), key=lambda p: p.name.lower()):
-            if not entry.is_dir() or not (entry / "MEMORY.md").exists():
-                continue
-            if not AGENT_NAME_PATTERN.match(entry.name):
-                continue
-            try:
-                data = _read_memory_bucket(user_id, entry.name)
-            except Exception:
-                logger.warning("Failed to read memory bucket %s for user", entry.name)
-                continue
-            buckets.append(AdminMemoryBucket(name=entry.name, data=data))
+    # Source agents from the database: only agents owned by this specific user.
+    agent_store = get_agent_store(request)
+    all_agents = await agent_store.list_visible(user_id)
+    owned_agents = sorted(
+        [a for a in all_agents if a.get("user_id") == user_id],
+        key=lambda a: (a.get("name") or a["id"]).lower(),
+    )
+
+    for agent in owned_agents:
+        agent_id: str = agent["id"]
+        display_name: str = agent.get("name") or agent_id
+        try:
+            data = _read_memory_bucket(user_id, agent_id)
+        except Exception:
+            data = {"entries": []}
+        buckets.append(AdminMemoryBucket(name=agent_id, display_name=display_name, data=data))
 
     return AdminMemoryResponse(user_id=user_id, buckets=buckets)
+
+
+@router.post("/{user_id}/memory/entries", response_model=AdminMemoryBucket)
+async def admin_add_memory_entry(
+    user_id: str,
+    body: AdminMemoryEntryAddRequest,
+    request: Request,
+) -> AdminMemoryBucket:
+    """Add a memory entry for a user (admin only)."""
+    await _require_admin(request)
+    target = "user" if body.agent is None else "memory"
+    provider = BuiltinFileProvider()
+    provider.initialize(user_id=user_id, agent_id=body.agent)
+    try:
+        result = provider.add(target, body.content)
+        if result is False:
+            raise HTTPException(status_code=400, detail="Failed to add entry (quota exceeded or write error)")
+    except HTTPException:
+        raise
+    except Exception as exc:
+        logger.error("admin_add_memory_entry failed for user %s: %s", user_id, exc, exc_info=True)
+        raise HTTPException(status_code=500, detail="Failed to write memory entry") from exc
+    bucket_name = "global" if body.agent is None else body.agent
+    return AdminMemoryBucket(name=bucket_name, data=_read_memory_bucket(user_id, body.agent))
+
+
+@router.put("/{user_id}/memory/entries", response_model=AdminMemoryBucket)
+async def admin_replace_memory_entry(
+    user_id: str,
+    body: AdminMemoryEntryReplaceRequest,
+    request: Request,
+) -> AdminMemoryBucket:
+    """Replace a memory entry for a user (admin only)."""
+    await _require_admin(request)
+    target = "user" if body.agent is None else "memory"
+    provider = BuiltinFileProvider()
+    provider.initialize(user_id=user_id, agent_id=body.agent)
+    try:
+        result = provider.replace(target, body.old_text, body.content)
+        if result is False:
+            raise HTTPException(status_code=404, detail="Entry not found or write failed")
+    except HTTPException:
+        raise
+    except Exception as exc:
+        logger.error("admin_replace_memory_entry failed for user %s: %s", user_id, exc, exc_info=True)
+        raise HTTPException(status_code=500, detail="Failed to replace memory entry") from exc
+    bucket_name = "global" if body.agent is None else body.agent
+    return AdminMemoryBucket(name=bucket_name, data=_read_memory_bucket(user_id, body.agent))
+
+
+@router.delete("/{user_id}/memory/entries", response_model=AdminMemoryBucket)
+async def admin_delete_memory_entry(
+    user_id: str,
+    request: Request,
+    old_text: str = Query(..., min_length=1, description="Short unique substring to locate the entry"),
+    agent: str | None = Query(None, description="Agent name; None = global USER.md bucket"),
+) -> AdminMemoryBucket:
+    """Delete a memory entry for a user (admin only)."""
+    await _require_admin(request)
+    target = "user" if agent is None else "memory"
+    provider = BuiltinFileProvider()
+    provider.initialize(user_id=user_id, agent_id=agent)
+    try:
+        result = provider.remove(target, old_text)
+        if result is False:
+            raise HTTPException(status_code=404, detail="Entry not found")
+    except HTTPException:
+        raise
+    except Exception as exc:
+        logger.error("admin_delete_memory_entry failed for user %s: %s", user_id, exc, exc_info=True)
+        raise HTTPException(status_code=500, detail="Failed to delete memory entry") from exc
+    bucket_name = "global" if agent is None else agent
+    return AdminMemoryBucket(name=bucket_name, data=_read_memory_bucket(user_id, agent))

offline-backend-20260512/backend/packages/harness/deerflow/agents/lead_agent/agent.py

@@ -375,7 +375,7 @@ def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
         config["metadata"] = {}
 
     if is_bootstrap:
-        runtime_available_skills: list[str] | None = ["bootstrap"]
+        runtime_available_skills: list[str] | None = None  # all enabled skills visible in bootstrap
     elif agent_config:
         # Custom agents must use an explicit allowlist. If omitted, default to none.
         runtime_available_skills = list(agent_config.skills or [])
@@ -416,7 +416,8 @@ def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
                 max_concurrent_subagents=max_concurrent_subagents,
                 writing_mode=writing_mode,
                 writing_artifact_path=writing_artifact_path,
-                available_skills=set(["bootstrap"]),
+                available_skills=None,
+                is_bootstrap=True,
                 app_config=resolved_app_config,
             ),
             state_schema=ThreadState,

offline-backend-20260512/backend/packages/harness/deerflow/agents/lead_agent/prompt.py

@@ -496,6 +496,8 @@ You: "Deploying to staging..." [proceed]
 
 {skills_section}
 
+{bootstrap_section}
+
 {deferred_tools_section}
 
 {writing_mode_section}
@@ -819,6 +821,27 @@ def _build_custom_mounts_section(*, app_config: AppConfig | None = None) -> str:
     return f"\n**Custom Mounted Directories:**\n{mounts_list}\n- If the user needs files outside `/mnt/user-data`, use these absolute container paths directly when they match the requested directory"
 
 
+def _build_bootstrap_section() -> str:
+    return """<bootstrap_agent_creation>
+你正在帮助用户创建一个自定义智能体。
+
+**技能匹配规则（必须遵守）：**
+1. 先调用 `skill_list` 查看用户当前所有可用技能及其描述。
+2. 根据用户对新智能体的描述/意图，从已有技能中选出最相关的 1-5 个技能名称（skill name，使用 hyphen-case）。
+3. 将选出的技能名称填入 `setup_agent` 的 `skills` 参数。
+4. **严禁在本次创建流程中调用 `skill_manage`（创建、编辑或删除技能）**。如用户提出需要新技能，请告知他们创建完智能体后再单独创建。
+5. 如果没有任何技能与用户意图相关，可将 `skills` 设为空列表，并向用户说明原因。
+
+**工作流程：**
+1. 与用户充分沟通，明确新智能体的用途、专长和边界。
+2. 调用 `skill_list` 列出现有技能。
+3. 在思考中匹配技能，选出最合适的。
+4. 草拟 SOUL.md（定义智能体的人设、工作方式、输出要求）。
+5. 向用户确认配置后，调用 `setup_agent` 提交。
+</bootstrap_agent_creation>
+"""
+
+
 def apply_prompt_template(
     subagent_enabled: bool = False,
     max_concurrent_subagents: int = 3,
@@ -828,6 +851,7 @@ def apply_prompt_template(
     writing_mode: bool = False,
     writing_artifact_path: str | None = None,
     available_skills: set[str] | None = None,
+    is_bootstrap: bool = False,
     app_config: AppConfig | None = None,
 ) -> str:
     storage_agent_id = agent_id if agent_id is not None else agent_name
@@ -857,6 +881,9 @@ def apply_prompt_template(
         else ""
     )
 
+    # Bootstrap section: skill-matching guidance (only in agent creation flow)
+    bootstrap_section = _build_bootstrap_section() if is_bootstrap else ""
+
     # Get skills section
     skills_section = get_skills_prompt_section(available_skills, app_config=app_config)
 
@@ -902,6 +929,7 @@ Writing mode is enabled for this run.
         agent_name=agent_name or storage_agent_id or "CM 助手",
         soul=get_agent_soul(storage_agent_id),
         skills_section=skills_section,
+        bootstrap_section=bootstrap_section,
         deferred_tools_section=deferred_tools_section,
         writing_mode_section=writing_mode_section,
         memory_context=memory_context,

offline-backend-20260512/backend/packages/harness/deerflow/config/memory_config.py

@@ -73,7 +73,7 @@ class HindsightMemoryConfig(BaseModel):
         description="agent 私有工作 bank 命名模板",
     )
     memory_mode: str = Field(
-        default="context",
+        default="hybrid",
         description="工具暴露策略:context(仅自动) / tools(仅工具) / hybrid(两者)",
     )
     bank_mission: str = Field(default="", description="reflect 推理的身份/框架描述")
@@ -136,13 +136,15 @@ class MemoryConfig(BaseModel):
 # 不在此表中的字段必须改 config.yaml 并重启 (例如 provider / api_key / 字符配额)。
 USER_WRITABLE_FIELDS: frozenset[str] = frozenset(
     {
-        "injection.enabled",
+        # injection.enabled and injection.include_builtin are always ON;
+        # removing them from the whitelist makes _filter_to_whitelist drop
+        # any per-user override for these fields, so stored "false" values
+        # in existing memory_config.json files are silently ignored.
         "injection.max_tokens",
-        "injection.include_builtin",
         "injection.include_hindsight",
-        "hindsight.memory_mode",
+        # hindsight.memory_mode is fixed to "hybrid"; not user-writable.
+        # hindsight.bank_mission is fixed; not user-writable.
         "hindsight.recall_budget",
-        "hindsight.bank_mission",
     }
 )