subagent历史带工具调用信息

Author: elecvoid243

astrbot/core/astr_agent_tool_exec.py

@@ -373,7 +373,7 @@ async def _execute_handoff(
             except Exception:
                 pass
 
-        llm_resp = await ctx.tool_loop_agent(
+        llm_resp, runner_messages = await ctx.tool_loop_agent(
             event=event,
             chat_provider_id=prov_id,
             prompt=input_,
@@ -384,25 +384,16 @@ async def _execute_handoff(
             max_steps=agent_max_step,
             tool_call_timeout=run_context.tool_call_timeout,
             stream=stream,
+            return_runner_messages=True
         )
 
         # 保存历史上下文
-        if agent_name:
+        if agent_name and runner_messages:
             try:
                 from astrbot.core.dynamic_subagent_manager import DynamicSubAgentManager
-
-                # 构建当前对话的历史消息
-                current_messages = []
-                # 添加本轮用户输入
-                current_messages.append({"role": "user", "content": input_})
-                # 添加助手回复
-                current_messages.append(
-                    {"role": "assistant", "content": llm_resp.completion_text}
+                DynamicSubAgentManager.update_subagent_history(
+                    umo, agent_name, runner_messages
                 )
-                if current_messages:
-                    DynamicSubAgentManager.save_subagent_history(
-                        umo, agent_name, current_messages
-                    )
             except Exception:
                 pass  # 不影响主流程
 

astrbot/core/dynamic_subagent_manager.py

@@ -70,8 +70,8 @@ class DynamicSubAgentManager:
     _max_subagent_count: int = 3
     _auto_cleanup_per_turn: bool = True
     _shared_context_enabled: bool = False
-    _shared_context_maxlen: int = 200
-
+    _shared_context_maxlen: int = 200   # 公共上下文保留的历史消息条数
+    _max_subagent_history: int = 500   # 每个subagent最多保留的历史消息条数
     _tools_blacklist: set[str] = {
         "send_shared_context_for_main_agentcreate_dynamic_subagent",
         "protect_subagent",
@@ -251,20 +251,32 @@ def protect_subagent(cls, session_id: str, agent_name: str) -> None:
         )
 
     @classmethod
-    def save_subagent_history(
+    def update_subagent_history(
         cls, session_id: str, agent_name: str, current_messages: list
     ) -> None:
-        """Save conversation history for a subagent"""
+        """Update conversation history for a subagent"""
         session = cls.get_session(session_id)
         if not session or agent_name not in session.protected_agents:
             return
 
         if agent_name not in session.subagent_histories:
             session.subagent_histories[agent_name] = []
 
-        # 追加新消息
         if isinstance(current_messages, list):
-            session.subagent_histories[agent_name].extend(current_messages)
+            _MAX_TOOL_RESULT_LEN = 2000
+            for msg in current_messages:
+                if isinstance(msg, dict) and msg.get("role") == "system": # 移除system消息
+                    current_messages.remove(msg)
+                # 对过长的 tool 结果做截断，避免单条消息占用过多空间
+                if (isinstance(msg, dict) and msg.get("role") == "tool" and isinstance(msg.get("content"), str) and len(msg["content"]) > _MAX_TOOL_RESULT_LEN
+                ):
+                    msg["content"] = (
+                            msg["content"][:_MAX_TOOL_RESULT_LEN] + "\n...[truncated]"
+                    )
+
+        session.subagent_histories[agent_name].extend(current_messages)
+        if cls._max_subagent_history < len(session.subagent_histories[agent_name]):
+            session.subagent_histories[agent_name] = session.subagent_histories[agent_name][-cls._max_subagent_history:]
 
         logger.debug(
             "[EnhancedSubAgent:History] Saved messages for %s, current len=%d",

astrbot/core/star/context.py

@@ -159,7 +159,7 @@ async def tool_loop_agent(
         max_steps: int = 30,
         tool_call_timeout: int = 120,
         **kwargs: Any,
-    ) -> LLMResponse:
+    ) -> LLMResponse | tuple[LLMResponse, list[Any]]:
         """Run an agent loop that allows the LLM to call tools iteratively until a final answer is produced.
         If you do not pass the agent_context parameter, the method will recreate a new agent context.
 
@@ -250,6 +250,11 @@ async def tool_loop_agent(
         llm_resp = agent_runner.get_final_llm_resp()
         if not llm_resp:
             raise Exception("Agent did not produce a final LLM response")
+        if kwargs.get("return_runner_messages", False):
+            runner_messages = []
+            for msg in agent_runner.run_context.messages:
+                runner_messages.append(msg.model_dump())
+            return llm_resp, runner_messages
         return llm_resp
 
     async def get_current_chat_provider_id(self, umo: str) -> str: