feat(actions): 支持同时进行回复与其他动作
重构了动作执行流程,以支持更丰富的多动作组合,例如在发送文本回复的同时发送一个表情。 主要变更: - **执行流程**: 在 `CycleProcessor` 中,将动作分为“回复”和“其他”两类。系统会先串行执行回复动作,再并行执行所有其他动作,确保了核心回复的优先性。 - **规划逻辑**: 在 `Planner` 中优化了提示词,并增加后处理步骤,以鼓励并确保在回复时触发补充性动作(如100%概率的emoji)。 - **emoji动作**: 重构了表情选择逻辑,现在会评估所有可用的表情,而不仅仅是随机抽样,提高了选择的准确性。 - **修复**: 修复了 `ActionModifier` 中随机激活概率为100%的动作可能不触发的bug。
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@@ -299,63 +299,67 @@ class CycleProcessor:
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"error": str(e),
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}
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# 创建所有动作的后台任务
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action_tasks = [asyncio.create_task(execute_action(action)) for action in actions]
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# 并行执行所有任务
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results = await asyncio.gather(*action_tasks, return_exceptions=True)
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# 处理执行结果
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# 分离 reply 动作和其他动作
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reply_actions = [a for a in actions if a.get("action_type") == "reply"]
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other_actions = [a for a in actions if a.get("action_type") != "reply"]
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reply_loop_info = None
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reply_text_from_reply = ""
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action_success = False
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action_reply_text = ""
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action_command = ""
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other_actions_results = []
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for i, result in enumerate(results):
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if isinstance(result, BaseException):
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logger.error(f"{self.log_prefix} 动作执行异常: {result}")
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continue
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action_info = actions[i]
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if result["action_type"] != "reply":
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action_success = result["success"]
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action_reply_text = result["reply_text"]
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action_command = result.get("command", "")
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elif result["action_type"] == "reply":
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if result["success"]:
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reply_loop_info = result["loop_info"]
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reply_text_from_reply = result["reply_text"]
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# 1. 首先串行执行所有 reply 动作(通常只有一个)
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if reply_actions:
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logger.info(f"{self.log_prefix} 正在执行文本回复...")
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for action in reply_actions:
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result = await execute_action(action)
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if isinstance(result, Exception):
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logger.error(f"{self.log_prefix} 回复动作执行异常: {result}")
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continue
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if result.get("success"):
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reply_loop_info = result.get("loop_info")
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reply_text_from_reply = result.get("reply_text", "")
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else:
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logger.warning(f"{self.log_prefix} 回复动作执行失败")
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# 2. 然后并行执行所有其他动作
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if other_actions:
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logger.info(f"{self.log_prefix} 正在执行附加动作: {[a.get('action_type') for a in other_actions]}")
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other_action_tasks = [asyncio.create_task(execute_action(action)) for action in other_actions]
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results = await asyncio.gather(*other_action_tasks, return_exceptions=True)
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for i, result in enumerate(results):
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if isinstance(result, BaseException):
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logger.error(f"{self.log_prefix} 附加动作执行异常: {result}")
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continue
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other_actions_results.append(result)
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# 构建最终的循环信息
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if reply_loop_info:
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# 如果有回复信息,使用回复的loop_info作为基础
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loop_info = reply_loop_info
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# 更新动作执行信息
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loop_info["loop_action_info"].update(
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{
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"action_taken": action_success,
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"command": action_command,
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"taken_time": time.time(),
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}
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)
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# 将其他动作的结果合并到loop_info中
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if "other_actions" not in loop_info["loop_action_info"]:
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loop_info["loop_action_info"]["other_actions"] = []
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loop_info["loop_action_info"]["other_actions"].extend(other_actions_results)
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reply_text = reply_text_from_reply
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else:
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# 没有回复信息,构建纯动作的loop_info
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# 即使没有回复,也要正确处理其他动作
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final_action_taken = any(res.get("success", False) for res in other_actions_results)
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final_reply_text = " ".join(res.get("reply_text", "") for res in other_actions_results if res.get("reply_text"))
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final_command = " ".join(res.get("command", "") for res in other_actions_results if res.get("command"))
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loop_info = {
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"loop_plan_info": {
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"action_result": actions,
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},
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"loop_action_info": {
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"action_taken": action_success,
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"reply_text": action_reply_text,
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"command": action_command,
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"action_taken": final_action_taken,
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"reply_text": final_reply_text,
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"command": final_command,
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"taken_time": time.time(),
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"other_actions": other_actions_results,
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},
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}
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reply_text = action_reply_text
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reply_text = final_reply_text
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# 停止正在输入状态
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if ENABLE_S4U:
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@@ -421,7 +425,7 @@ class CycleProcessor:
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if fallback_action and fallback_action != action:
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logger.info(f"{self.context.log_prefix} 使用回退动作: {fallback_action}")
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action_handler = self.context.action_manager.create_action(
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action_name=fallback_action if isinstance(fallback_action, list) else fallback_action,
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action_name=fallback_action,
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action_data=action_data,
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reasoning=f"原动作'{action}'不可用,自动回退。{reasoning}",
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cycle_timers=cycle_timers,
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@@ -205,7 +205,9 @@ class ActionModifier:
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elif activation_type == ActionActivationType.RANDOM:
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probability = action_info.random_activation_probability
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if random.random() >= probability:
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if probability >= 1.0:
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continue # 概率为100%或更高,直接激活
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if random.random() > probability:
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reason = f"RANDOM类型未触发(概率{probability})"
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deactivated_actions.append((action_name, reason))
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logger.debug(f"{self.log_prefix}未激活动作: {action_name},原因: {reason}")
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@@ -76,6 +76,8 @@ def init_prompt():
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{action_options_text}
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- 如果用户明确要求使用某个动作,请优先选择该动作。
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- 当一个动作可以作为另一个动作的补充时,你应该同时选择它们。例如,在回复的同时可以发送表情包(emoji)。
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你必须从上面列出的可用action中选择一个或多个,并说明触发action的消息id(不是消息原文)和选择该action的原因。消息id格式:m+数字
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请根据动作示例,以严格的 JSON 格式输出,返回一个包含所有选定动作的JSON列表。如果只选择一个动作,也请将其包含在列表中。如果没有任何合适的动作,返回一个空列表[]。不要输出markdown格式```json等内容,直接输出且仅包含 JSON 列表内容:
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@@ -407,6 +409,23 @@ class ActionPlanner:
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# --- 3. 后处理 ---
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final_actions = self._filter_no_actions(final_actions)
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# === 强制后处理:确保100%概率的动作在回复时被附带 ===
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has_reply_action = any(a.get("action_type") == "reply" for a in final_actions)
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if has_reply_action:
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for action_name, action_info in available_actions.items():
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if action_info.activation_type == ActionActivationType.RANDOM and action_info.random_activation_probability >= 1.0:
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# 检查此动作是否已被选择
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is_already_chosen = any(a.get("action_type") == action_name for a in final_actions)
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if not is_already_chosen:
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logger.info(f"{self.log_prefix}强制添加100%概率动作: {action_name}")
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final_actions.append({
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"action_type": action_name,
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"reasoning": "根据100%概率设置强制添加",
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"action_data": {},
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"action_message": self.get_latest_message(used_message_id_list),
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"available_actions": available_actions,
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})
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if not final_actions:
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final_actions = [
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{
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@@ -531,9 +550,13 @@ class ActionPlanner:
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if mode == ChatMode.FOCUS:
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no_action_block = """
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- 'no_reply' 表示不进行回复,等待合适的回复时机
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- 当你刚刚发送了消息,没有人回复时,选择no_reply
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- 当你一次发送了太多消息,为了避免打扰聊天节奏,选择no_reply
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动作:no_action
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动作描述:不选择任何动作
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{{
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"action": "no_action",
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"reason":"不动作的原因"
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}}
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动作:no_reply
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动作描述:不进行回复,等待合适的回复时机
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- 当你刚刚发送了消息,没有人回复时,选择no_reply
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