refactor: 智能体重命名并添加格式检查

src/agents/common/toolagent.py

@@ -84,4 +84,4 @@ class ToolAgent(BaseAgent):
         # Execute the tool node
         result = await tool_node.ainvoke(state)
 
-        return cast(dict[str, list[ToolMessage]], result)
+        return cast(dict[str, list[ToolMessage]], result)

src/agents/common/tools.py

@@ -31,7 +31,7 @@ def get_approved_user_goal(
     """
     # 构建详细的中断信息
     interrupt_info = {
-        "question": f"是否批准以下操作？",
+        "question": "是否批准以下操作？",
         "operation": operation_description,
     }
 

src/agents/mini_agent/__init__.py

@@ -0,0 +1,3 @@
+from .graph import MiniAgent
+
+__all__ = ["MiniAgent"]

src/agents/mini_agent/graph.py

@@ -0,0 +1,49 @@
+
+from langchain.agents import create_agent
+from langchain.agents.middleware import ModelRequest, ModelResponse, dynamic_prompt, wrap_model_call
+
+from src.agents.common.base import BaseAgent
+from src.agents.common.models import load_chat_model
+from src.agents.common.tools import get_buildin_tools
+
+
+@dynamic_prompt
+def context_aware_prompt(request: ModelRequest) -> str:
+    runtime = request.runtime
+    return runtime.context.system_prompt
+
+
+@wrap_model_call
+async def context_based_model(request: ModelRequest, handler) -> ModelResponse:
+    # 从 runtime context 读取配置
+    model_spec = request.runtime.context.model
+    model = load_chat_model(model_spec)
+
+    request = request.override(model=model)
+    return await handler(request)
+
+
+class MiniAgent(BaseAgent):
+    name = "智能体 Demo"
+    description = "一个基于内置工具的智能体示例"
+
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    def get_tools(self):
+        return get_buildin_tools()
+
+    async def get_graph(self, **kwargs):
+        if self.graph:
+            return self.graph
+
+        # 创建 MiniAgent
+        graph = create_agent(
+            model=load_chat_model("siliconflow/Qwen/Qwen3-235B-A22B-Instruct-2507"),  # 实际会被覆盖
+            tools=self.get_tools(),
+            middleware=[context_aware_prompt, context_based_model],
+            checkpointer=await self._get_checkpointer(),
+        )
+
+        self.graph = graph
+        return graph

src/agents/multi_agent/tools.py

@@ -1,11 +1,9 @@
-import os
 from typing import Any
 
 from langchain.tools import tool
 from langchain_core.runnables import RunnableConfig
 
 from src.agents import agent_manager
-from src.agents.common.toolkits.mysql import get_mysql_tools
 from src.agents.common.tools import get_buildin_tools
 from src.utils import logger
 

src/agents/react/graph.py

@@ -1,4 +1,4 @@
-from langgraph.constants import START, END
+from langgraph.constants import END
 from langgraph.graph import StateGraph
 
 from src.agents.common.toolagent import ToolAgent
@@ -18,10 +18,9 @@ def tools_branch_continue(state: State):
 
 
 class ReActAgent(ToolAgent):
-    name = "智能体 Demo"
-    description = "A react agent that can answer questions and help with tasks."
+    name = "ReActAgent"
+    description = "符合 ReAct 范式的智能体，可以通过调用工具来完成复杂任务。"
 
-    # TODO:[已完成] React智能体
     '''
     提示词示例：
     你是一个智能体助手

src/agents/react/tools.py

@@ -1,12 +1,9 @@
-import os
 from typing import Any
 
-import requests
 from langchain.tools import tool
 
 from src.agents.common.toolkits.mysql import get_mysql_tools
 from src.agents.common.tools import get_buildin_tools
-from src.storage.minio import upload_image_to_minio
 from src.utils import logger
 
 @tool(name_or_callable="加密计算器", description="可以对给定的2个数字选择进行加减乘除四种加密计算")

src/agents/reporter/graph.py

@@ -1,5 +1,4 @@
 import textwrap
-from pathlib import Path
 
 from langchain.agents import create_agent
 from langchain.agents.middleware import ModelRequest, ModelResponse, dynamic_prompt, wrap_model_call
@@ -64,4 +63,4 @@ class SqlReporterAgent(BaseAgent):
 
         self.graph = graph
         logger.info("SqlReporterAgent 构建成功")
-        return graph
+        return graph

src/knowledge/base.py

@@ -136,7 +136,6 @@ class KnowledgeBase(ABC):
         """
         from src.utils import hashstr
 
-        from src.utils import hashstr
 
         # 从 kwargs 中获取 is_private 配置
         is_private = kwargs.get('is_private', False)