feat: 优化智能体的提示逻辑，简化代码

backend/package/yuxi/agents/buildin/chatbot/graph.py

@@ -19,12 +19,49 @@ from yuxi.services.subagent_service import get_subagents_from_names
 from .prompt import PROMPT
 
 
-def _create_fs_backend(rt):
+async def _build_middlewares(context):
-    """创建文件存储后端（支持沙盒执行）
+    """构建中间件列表"""
+    all_mcp_tools = (
+        await get_tools_from_all_servers()
+    )  # 因为异步加载，无法放在 RuntimeConfigMiddleware 的 __init__ 中
 
-    由 composite backend 从 runtime 中自动解析 thread_id 并路由到沙盒后端。
+
-    """
+    # summary middleware
-    return create_agent_composite_backend(rt)
+    # 主 Agent 上下文优化：90k tokens 触发压缩（128k context window 的 70%）
+    summary_middleware = SummaryOffloadMiddleware(
+        model=load_chat_model(fully_specified_name=context.model),
+        trigger=("tokens", getattr(context, "summary_threshold", 100) * 1024),
+        trim_tokens_to_summarize=4000,
+        summary_offload_threshold=500,
+        max_retention_ratio=0.5,
+    )
+
+    # subagents
+    subagents = await get_subagents_from_names(context.subagents)
+    subagents_middleware = SubAgentMiddleware(
+        default_model=load_chat_model(fully_specified_name=context.subagents_model),
+        subagents=subagents,
+        general_purpose_agent=True,
+        default_middleware=[
+            FilesystemMiddleware(backend=create_agent_composite_backend),  # 文件系统后端
+            PatchToolCallsMiddleware(),
+            summary_middleware,
+        ],
+    )
+    # all middlewares
+    middlewares = [
+        save_attachments_to_fs,  # 附件注入提示词
+        FilesystemMiddleware(backend=create_agent_composite_backend),  # 文件系统后端
+        KnowledgeBaseMiddleware(),  # 知识库工具
+        RuntimeConfigMiddleware(extra_tools=all_mcp_tools),  # 运行时配置应用（模型/工具/MCP/提示词）
+        SkillsMiddleware(),  # Skills 中间件（提示词注入、依赖展开、动态激活）
+        subagents_middleware,
+        summary_middleware,
+        ModelRetryMiddleware(),  # 模型重试中间件
+        PatchToolCallsMiddleware(),
+    ]
+
+    return middlewares
 
 
 class ChatbotAgent(BaseAgent):
@@ -43,61 +80,18 @@ class ChatbotAgent(BaseAgent):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
 
-    async def _build_middlewares(self, context):
-        """构建中间件列表"""
-        all_mcp_tools = (
-            await get_tools_from_all_servers()
-        )  # 因为异步加载，无法放在 RuntimeConfigMiddleware 的 __init__ 中
-
-        # subagents
-        subagents = await get_subagents_from_names(context.subagents)
-        subagents_middleware = SubAgentMiddleware(
-            default_model=load_chat_model(context.subagents_model),
-            subagents=subagents,
-            general_purpose_agent=True,
-            default_middleware=[
-                FilesystemMiddleware(backend=_create_fs_backend),  # 文件系统后端
-                PatchToolCallsMiddleware(),
-            ],
-        )
-
-        # summary middleware
-        # 主 Agent 上下文优化：90k tokens 触发压缩（128k context window 的 70%）
-        summary_middleware = SummaryOffloadMiddleware(
-            model=load_chat_model(fully_specified_name=context.model),
-            trigger=("tokens", getattr(context, "summary_threshold", 100) * 1024),
-            trim_tokens_to_summarize=4000,
-            summary_offload_threshold=500,
-            max_retention_ratio=0.5,
-        )
-
-        # all middlewares
-        middlewares = [
-            save_attachments_to_fs,  # 附件注入提示词
-            FilesystemMiddleware(backend=_create_fs_backend),  # 文件系统后端
-            KnowledgeBaseMiddleware(),  # 知识库工具
-            RuntimeConfigMiddleware(extra_tools=all_mcp_tools),  # 运行时配置应用（模型/工具/MCP/提示词）
-            SkillsMiddleware(),  # Skills 中间件（提示词注入、依赖展开、动态激活）
-            subagents_middleware,
-            summary_middleware,
-            ModelRetryMiddleware(),  # 模型重试中间件
-            PatchToolCallsMiddleware(),
-        ]
-
-        return middlewares
 
     async def get_graph(self, context=None, **kwargs):
 
         context = context or self.context_schema()  # 获取上下文配置
 
-        system_prompt = PROMPT.strip() + "\n\n" + (context.system_prompt or "")
+        system_prompt = f"{PROMPT.strip()}\n\n{context.system_prompt or ''}"
 
         # 使用 create_agent 创建智能体
-        # 注意：tools 参数由 RuntimeConfigMiddleware 在 wrap_model_call 中动态设置
         graph = create_agent(
             model=load_chat_model(fully_specified_name=context.model),
             system_prompt=system_prompt.strip(),
-            middleware=await self._build_middlewares(context),
+            middleware=await _build_middlewares(context),
             checkpointer=await self._get_checkpointer(),
         )
 

backend/package/yuxi/agents/buildin/chatbot/prompt.py

@@ -8,4 +8,7 @@ PROMPT = """
 - /home/gem/user-data/outputs/：用于存放最终输出结果
 - /home/gem/user-data/uploads/：用于存放用户上传的文件
 
+如果启用了知识库，除了使用知识库工具之外，
+当需要精准获取信息的时候，还可以直接访问知识库文件系统 （路径为 /home/gem/kbs/）来获取信息。
+源文件可能无法解析，可以在 /home/gem/kbs/<db_name>/parsed/ 中找到解析后的 markdown 文件。
 """

backend/package/yuxi/agents/buildin/deep_agent/graph.py

@@ -1,5 +1,3 @@
-"""Deep Agent - 基于create_deep_agent的深度分析智能体"""
-
 from deepagents.middleware.filesystem import FilesystemMiddleware
 from deepagents.middleware.patch_tool_calls import PatchToolCallsMiddleware
 from deepagents.middleware.subagents import SubAgentMiddleware
@@ -23,18 +21,12 @@ from yuxi.services.mcp_service import get_tools_from_all_servers
 from yuxi.services.subagent_service import get_subagents_from_names
 from yuxi.utils import logger
 
-from .context import DeepContext
+from .prompt import DEEP_PROMPT
-
-
-def _create_fs_backend(rt):
-    """创建文件存储后端"""
-    return create_agent_composite_backend(rt)
 
 
 class DeepAgent(BaseAgent):
     name = "深度分析"
     description = "具备规划、深度分析和子智能体协作能力的智能体，可以处理复杂的多步骤任务"
-    context_schema = DeepContext
     capabilities = ["file_upload", "files", "todo"]  # 支持文件上传功能
     metadata = {"examples": ["调研一下多模态 GraphRAG 的相关论文"]}
 
@@ -60,6 +52,7 @@ class DeepAgent(BaseAgent):
     async def get_graph(self, context=None, **kwargs):
 
         context = context or self.context_schema()  # 获取上下文配置
+        system_prompt = f"{DEEP_PROMPT.strip()}\n\n{context.system_prompt or ''}"
 
         model = load_chat_model(context.model)
         sub_model = load_chat_model(context.subagents_model)
@@ -79,28 +72,14 @@ class DeepAgent(BaseAgent):
             max_retention_ratio=0.5,
         )
 
-        # 子 Agent 独立的上下文优化：更激进的压缩策略
-        sub_summary_middleware = SummaryOffloadMiddleware(
-            model=sub_model,
-            trigger=("tokens", 50000),
-            trim_tokens_to_summarize=2000,
-            summary_offload_threshold=300,
-            max_retention_ratio=0.4,
-        )
-
         subagents_middleware = SubAgentMiddleware(
             default_model=sub_model,
             default_tools=search_tools,
             subagents=user_subagents,
             default_middleware=[
-                RuntimeConfigMiddleware(
+                FilesystemMiddleware(backend=create_agent_composite_backend),  # 文件系统后端
-                    model_context_name="subagents_model",
-                    enable_model_override=True,
-                    enable_system_prompt_override=False,
-                    enable_tools_override=False,
-                ),
                 PatchToolCallsMiddleware(),
-                sub_summary_middleware,
+                summary_middleware,
                 # 子 Agent 搜索工具限制：tavily_search 最多 8 次
                 ToolCallLimitMiddleware(
                     tool_name="tavily_search",
@@ -114,9 +93,9 @@ class DeepAgent(BaseAgent):
         # 使用 create_deep_agent 创建深度智能体
         graph = create_agent(
             model=model,
-            system_prompt=context.system_prompt,
+            system_prompt=system_prompt,
             middleware=[
-                FilesystemMiddleware(backend=_create_fs_backend),  # 文件系统后端
+                FilesystemMiddleware(backend=create_agent_composite_backend),  # 文件系统后端
                 RuntimeConfigMiddleware(extra_tools=all_mcp_tools),
                 SkillsMiddleware(),  # Skills 中间件（提示词注入、依赖展开、动态激活）
                 save_attachments_to_fs,  # 附件注入提示词