放弃使用system_prompt控制use_report,采用中间件形式在调用工具前控制

src/server/deep_agent/agents/main_agent.py

@@ -1,19 +1,25 @@
-from deepagents import create_deep_agent
+import logging
+from typing import Callable
+
+from deepagents import create_deep_agent, SubAgentMiddleware
 from deepagents.backends import FilesystemBackend
-from langchain.agents.middleware import SummarizationMiddleware, ToolRetryMiddleware
+from langchain.agents.middleware import SummarizationMiddleware, ToolRetryMiddleware, wrap_model_call, ModelRequest, ModelResponse, wrap_tool_call
+from langchain_core.messages import ToolMessage
 from langgraph.checkpoint.mongodb import MongoDBSaver
 from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer
+from langgraph.prebuilt.tool_node import ToolCallRequest
 from langgraph.store.memory import InMemoryStore
+from langgraph.types import Command
 from pymongo import MongoClient
 
 from src.core.config import MONGO_URI
-# from src.server.deep_agent.agents.painter import build_painter_subagent
 from src.server.deep_agent.agents.researcher import build_researcher_subagent
 from src.server.deep_agent.agents.user_profile import user_profile_subagent
 from src.server.deep_agent.init_llm import build_main_llm
 from src.server.deep_agent.init_prompt import build_system_prompt
 from src.server.deep_agent.tools.generate_furniture_sketch import edit_furniture, generate_furniture, edit_quote_upload_furniture
 
+logger = logging.getLogger(__name__)
 client = MongoClient(MONGO_URI)
 checkpointer = MongoDBSaver(
     client=client["furniture_agent_db"],
@@ -23,22 +29,48 @@ checkpointer = MongoDBSaver(
 )
 
 
-class CanvasMiddleware:
+@wrap_tool_call
-    def before_agent(self, state, agent_input, **kwargs):
+async def report_control(
-        canvas = state.get("canvas", {})
+        request: ToolCallRequest,
+        handler: Callable[[ToolCallRequest], ToolMessage | Command],
+) -> ToolMessage | Command:
+    tool_name = request.tool_call.get('name')
+    args = request.tool_call.get('args', {}) or {}
 
-        info = f"""
+    print(f"Executing tool: {tool_name}")
-        当前画布状态：
+    # print(f"Arguments: {args}")   # 可以注释掉，生产环境日志太多
-        - image_path: {canvas.get("image_path")}
-        - 是否已有图片: {bool(canvas.get("image_path"))}
-        """
 
-        agent_input["messages"].append({
+    if tool_name == "task":
-            "role": "system",
+        # 更安全的判断方式（兼容不同字段名）
-            "content": info
+        subagent_name = (
-        })
+                args.get("subagent")
+                or args.get("subagent_type")
+                or args.get("name")
+                or ""
+        ).lower()
 
-        return state, agent_input
+        # use_report按钮检测
+        if "research_subagent" in subagent_name:
+            use_report = request.runtime.config['configurable']['use_report']
+            if not use_report:
+                error_msg = "Reporting is currently not enabled. If you want to use the reporting function, please enable trending report first."
+                logger.info("⚠️ 已拦截 research_subagent 调用")
+                return ToolMessage(
+                    content=error_msg,
+                    tool_call_id=request.tool_call.get("id")
+                )
+            else:
+                logger.info("✅ use_report=True，允许调用 research_subagent")
+    try:
+        result = await handler(request)
+        logger.info(f"Tool {tool_name} completed successfully")
+        return result
+    except Exception as e:
+        logger.info(f"Tool {tool_name} failed: {e}")
+        return ToolMessage(
+            content=f"执行失败: {str(e)}",
+            tool_call_id=request.tool_call.get("id")
+        )
 
 
 def build_main_agent(use_report, workspace_dir, enable_thinking):
@@ -61,6 +93,7 @@ def build_main_agent(use_report, workspace_dir, enable_thinking):
             virtual_mode=True,  # 重要：關掉虛擬模式 → 真的寫硬碟
         ),
         middleware=[
+            report_control,
             SummarizationMiddleware(
                 model=build_main_llm(enable_thinking=enable_thinking),
                 trigger=("tokens", 3000),

src/server/deep_agent/init_prompt.py

@@ -80,8 +80,6 @@
 def build_system_prompt(use_report):
     system_prompt = f"""
     你是主调度 Agent（Supervisor），负责理解用户意图并选择合适的子Agent。
-    当前参数：
-    use_report = {use_report}
     系统中存在两个相关子Agent：
     1. user_profile_subagent
        负责收集和维护用户画像信息，包括但不限于：
@@ -141,14 +139,6 @@ def build_system_prompt(use_report):
     如果用户画像信息已经完整：
     → 调用 research-subagent 生成报告。
     ------------------------
-    【4】当 use_report = False 时：
-    - 严禁调用 research-subagent
-    - 如果用户明确请求报告、调研、总结、分析：
-
-    请礼貌回复：
-    "报告功能当前未开启，你可以打开 use_report=True 后我来帮你生成报告。"
-    - 其他普通问题可以正常回答或调用其他子Agent。
-    ------------------------
     【5】用户画像优先级规则
     只要用户输入包含以下情况：
     - 表达设计需求