refine agent loop and working memory tools

agent_loop.py

@@ -73,5 +73,9 @@ def agent_runner_loop(client, system_prompt, user_input, handler, tools_schema,
             datastr = json.dumps(outcome.data, ensure_ascii=False, default=json_default) if type(outcome.data) in [dict, list] else str(outcome.data) 
             next_prompt += f"<tool_result>\n{datastr}\n</tool_result>\n\n"
         next_prompt += outcome.next_prompt
+        if (turn+1) % 5 == 0:
+            next_prompt += f"\n\n[DANGER] 已连续执行第 {turn+1} 轮。禁止无效重试。若无有效进展，必须切换策略：1. 探测物理边界 2. 请求用户协助。"
+        if turn == 23:
+            next_prompt += f"\n\n[DANGER] 已连续执行第 {turn+1} 轮。你必须总结情况进行ask_user，不允许继续重试。"
         messages = [{"role": "user", "content": next_prompt}]
     return {'result': 'MAX_TURNS_EXCEEDED'}

assets/tools_schema.json

@@ -47,11 +47,11 @@
       "save_to_file": {"type": "string", "description": "可选。将 JS 执行结果（js_return）保存到的文件路径。注意：该功能不支持 await 等异步结果。"}}, "required": ["script"]}
   }},
   {"type": "function", "function": {
-    "name": "update_sop_plan",
+    "name": "update_working_mem",
-    "description": "【在读取SOP后需要调用】准备开始执行此SOP。提取容易遗忘但关键的内容，生成极简检查清单，100tokens以内，后续每轮自动注入context。特别是靠后的内容。",
+    "description": "更新当前任务的工作记忆。当任务目标细化、阶段切换或发现关键物理约束（坑）时调用，内容将作为物理锚点在后续每轮自动注入，强行锁定推理方向，防止长程任务逻辑漂移。",
     "parameters": {"type": "object", "properties": {
-      "keys": {"type": "string", "description": "每轮自动注入的必须注意的文本，可以是约束规则/执行步骤/需要注意的坑"},
+      "key_info": {"type": "string", "description": "替换掉当前的极简关键信息（200tokens以内），包含当前进度和目标、已获取的关键信息及下一步必须绕过的坑，已经解决或完成的步骤可以去掉"},
-      "sop_path": {"type": "string", "description": "sop路径，必要时可以再读"}}}
+      "related_sop": {"type": "string", "description": "相关sop名称，可以多个，必要时需要再读"}}}
   }},
   {"type": "function", "function": {
     "name": "ask_user",
@@ -62,7 +62,7 @@
   }},
   {"type": "function", "function": {
     "name": "trigger_memory_update",
-    "description": "用户的任务完成后，若发现值得长期记忆的信息（环境事实/用户偏好/避坑经验），调用此工具触发记忆提炼。不允许在记忆更新或自主流程内调用。",
+    "description": "若发现值得长期记忆的信息（环境事实/用户偏好/避坑经验），调用此工具触发记忆提炼。一次用户对话只允许调用一次，严禁在记忆更新或自主流程内调用。",
     "parameters": {"type": "object", "properties": {}}}
   }
 ]

ga.py

@@ -241,8 +241,8 @@ class GenericAgentHandler(BaseHandler):
     '''
     def __init__(self, parent, last_history=None, cwd='./'):
         self.parent = parent
-        self.sop_keys = ""
+        self.key_info = ""
-        self.sop_path = ""
+        self.related_sop = ""
         self.cwd = cwd
         self.history_info = last_history if last_history else []
         self.code_stop_signal = []
@@ -382,19 +382,19 @@ class GenericAgentHandler(BaseHandler):
             result = tips + result 
         next_prompt = self._get_anchor_prompt()
         if 'memory' in path or 'sop' in path: 
-            next_prompt += "\nPROTOCOL: 你正在读取记忆或SOP文件，若决定按sop执行请先调用准备执行相关工具，提取sop中的重点内容（特别是靠后的）进入工作记忆。"
+            next_prompt += "\nPROTOCOL: 你正在读取记忆或SOP文件，若决定按sop执行请先调用相关工具提取sop中的关键点（特别是靠后的）进入工作记忆。"
         return StepOutcome(result, next_prompt=next_prompt)
     
-    def do_update_sop_plan(self, args, response):
+    def do_update_working_mem(self, args, response):
         '''读取完sop后，为整个任务设定后续需要临时记忆的重点。
         '''
-        sop_keys = args.get("keys", "")
+        key_info = args.get("key_info", "")
-        sop_path = args.get("sop_path", "")
+        related_sop = args.get("related_sop", "")
-        if sop_keys: self.sop_keys = sop_keys
+        if key_info: self.key_info = key_info
-        if sop_path: self.sop_path = sop_path
+        if related_sop: self.related_sop = related_sop
-        yield f"[Info] Updated sop_keys and sop_path.\n"
+        yield f"[Info] Updated key_info and related_sop.\n"
-        yield f"sop_keys:\n{self.sop_keys}\n\n"
+        yield f"key_info:\n{self.key_info}\n\n"
-        yield f"sop_path:\n{self.sop_path}\n\n"
+        yield f"related_sop:\n{self.related_sop}\n\n"
         next_prompt = self._get_anchor_prompt()
         return StepOutcome({"status": "success"}, next_prompt=next_prompt)
 
@@ -458,8 +458,8 @@ class GenericAgentHandler(BaseHandler):
     def _get_anchor_prompt(self):
         h_str = "\n".join(self.history_info[-20:])
         prompt = f"\n### [WORKING MEMORY]\n<history>\n{h_str}\n</history>"
-        if self.sop_keys: prompt += f"\n<sop_essentials>{self.sop_keys}</sop_essentials>"
+        if self.key_info: prompt += f"\n<sop_essentials>{self.key_info}</sop_essentials>"
-        if self.sop_path: prompt += f"\n有不清晰的地方请再次读取{self.sop_path}"
+        if self.related_sop: prompt += f"\n有不清晰的地方请再次读取{self.related_sop}"
         print(prompt)
         return prompt