feat: peer_hint mechanism & history folding compression

agentmain.py

@@ -44,11 +44,11 @@ class GeneraticAgent:
         os.makedirs(os.path.join(script_dir, 'temp'), exist_ok=True)
         self.lock = threading.Lock()
         self.task_dir = None
-        self.history = []
+        self.history = []; self.handler = None; 
         self.task_queue = queue.Queue() 
         self.is_running = False; self.stop_sig = False
-        self.llm_no = 0;  self.inc_out = False
-        self.handler = None; self.verbose = True
+        self.llm_no = 0;  self.inc_out = False; self.verbose = True
+        self.peer_hint = True
         self.load_llm_sessions()
 
     def load_llm_sessions(self):
@@ -136,6 +136,7 @@ class GeneraticAgent:
             self.history.append(f"[USER]: {rquery}")
             
             sys_prompt = get_system_prompt() + getattr(self.llmclient.backend, 'extra_sys_prompt', '')
+            if self.peer_hint: sys_prompt += f"\n[Peer] 用户提及其他会话/后台任务状态时: temp/model_responses/ (只找近期修改的文件尾部)\n"
             handler = GenericAgentHandler(self, self.history, os.path.join(script_dir, 'temp'))
             if self.handler and 'key_info' in self.handler.working: 
                 ki = re.sub(r'\n\[SYSTEM\] 此为.*?工作记忆[。\n]*', '', self.handler.working['key_info'])  # 去旧
@@ -200,6 +201,7 @@ if __name__ == '__main__':
     threading.Thread(target=agent.run, daemon=True).start()
 
     if args.task:
+        agent.peer_hint = False
         agent.task_dir = d = os.path.join(script_dir, f'temp/{args.task}'); nround = ''
         infile = os.path.join(d, 'input.txt')
         if args.input:
@@ -220,6 +222,7 @@ if __name__ == '__main__':
             else: break
             nround = nround + 1 if isinstance(nround, int) else 1
     elif args.reflect:
+        agent.peer_hint = False
         import importlib.util
         spec = importlib.util.spec_from_file_location('reflect_script', args.reflect)
         mod = importlib.util.module_from_spec(spec); spec.loader.exec_module(mod)

ga.py

@@ -508,10 +508,26 @@ class GenericAgentHandler(BaseHandler):
         else: result = "Memory Management SOP not found. Do not update memory."
         return StepOutcome(result, next_prompt=prompt)
 
+    def _fold_earlier(self, lines):
+        FALLBACK = '直接回答了用户问题'
+        parts, cnt, last = [], 0, ''
+        def flush():
+            if cnt:
+                if FALLBACK in last: parts.append(f'[Agent]（{cnt} turns）')
+                else: parts.append(f'{last}（{cnt} turns）')
+        for line in lines:
+            if line.startswith('[USER]'):
+                flush(); parts.append(line); cnt = 0; last = ''
+            else: cnt += 1; last = line
+        flush()
+        return "\n".join(parts[-150:])
+
     def _get_anchor_prompt(self, skip=False):
         if skip: return "\n"
-        h_str = "\n".join(self.history_info[-40:])
-        prompt = f"\n### [WORKING MEMORY]\n<history>\n{h_str}\n</history>"
+        h = self.history_info; W = 30
+        earlier = f'<earlier_context>\n{self._fold_earlier(h[:-W])}\n</earlier_context>\n' if len(h) > W else ""
+        h_str = "\n".join(h[-W:])
+        prompt = f"\n### [WORKING MEMORY]\n{earlier}<history>\n{h_str}\n</history>"
         prompt += f"\nCurrent turn: {self.current_turn}\n"
         if self.working.get('key_info'): prompt += f"\n<key_info>{self.working.get('key_info')}</key_info>"
         if self.working.get('related_sop'): prompt += f"\n有不清晰的地方请再次读取{self.working.get('related_sop')}"
@@ -529,16 +545,17 @@ class GenericAgentHandler(BaseHandler):
             clean_args = {k: v for k, v in args.items() if not k.startswith('_')}
             summary = f"调用工具{tool_name}, args: {clean_args}"
             if tool_name == 'no_tool': summary = "直接回答了用户问题"
-            next_prompt += "\n[DANGER] 你遗漏了<summary>，必须按协议一直在每次回复中用<summary>中输出极简单行摘要！" 
-        summary = smart_format(summary, max_str_len=100)
+            next_prompt += "\n[DANGER] 你遗漏了<summary>，必须按协议在每次回复中用<summary>中输出极简单行摘要" 
+        summary = smart_format(summary.replace('\n', ''), max_str_len=100)
         self.history_info.append(f'[Agent] {summary}')
-        if turn % 65 == 0 and 'plan' not in str(self.working.get('related_sop')):
+        _plan = self._in_plan_mode()
+        if turn % 65 == 0 and (not _plan):
             next_prompt += f"\n\n[DANGER] 已连续执行第 {turn} 轮。你必须总结情况进行ask_user，不允许继续重试。"
         elif turn % 7 == 0:
             next_prompt += f"\n\n[DANGER] 已连续执行第 {turn} 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。如有需要，可调用 update_working_checkpoint 保存关键上下文。"
         elif turn % 10 == 0: next_prompt += get_global_memory()
 
-        if (_plan := self._in_plan_mode()) and turn >= 10 and turn % 5 == 0:
+        if _plan and turn >= 10 and turn % 5 == 0:
             next_prompt = f"[Plan Hint] 你正在计划模式。必须 file_read({_plan}) 确认当前步骤，回复开头引用：📌 当前步骤：...\n\n" + next_prompt
         if _plan and turn >= 90: next_prompt += f"\n\n[DANGER] Plan模式已运行 {turn} 轮，已达上限。必须 ask_user 汇报进度并确认是否继续。"