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fix:并行动作炸裂问题

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This commit is contained in:
SengokuCola
2025-07-26 23:14:47 +08:00
parent 75af87aa5f
commit 0367dae824
5 changed files with 184 additions and 100 deletions
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225
src/chat/chat_loop/heartFC_chat.py
View File

@@ -255,6 +255,53 @@ class HeartFChatting:
person_name = await person_info_manager.get_value(person_id, "person_name")
return f"{person_name}:{message_data.get('processed_plain_text')}"
async def _send_and_store_reply(
self,
response_set,
reply_to_str,
loop_start_time,
action_message,
cycle_timers,
thinking_id,
plan_result):
with Timer("回复发送", cycle_timers):
reply_text = await self._send_response(response_set, reply_to_str, loop_start_time, action_message)
# 存储reply action信息
person_info_manager = get_person_info_manager()
person_id = person_info_manager.get_person_id(
action_message.get("chat_info_platform", ""),
action_message.get("user_id", ""),
)
person_name = await person_info_manager.get_value(person_id, "person_name")
action_prompt_display = f"你对{person_name}进行了回复：{reply_text}"
await database_api.store_action_info(
chat_stream=self.chat_stream,
action_build_into_prompt=False,
action_prompt_display=action_prompt_display,
action_done=True,
thinking_id=thinking_id,
action_data={"reply_text": reply_text, "reply_to": reply_to_str},
action_name="reply",
)
# 构建循环信息
loop_info = {
"loop_plan_info": {
"action_result": plan_result.get("action_result", {}),
},
"loop_action_info": {
"action_taken": True,
"reply_text": reply_text,
"command": "",
"taken_time": time.time(),
},
}
return loop_info, reply_text,cycle_timers
async def _observe(self, message_data: Optional[Dict[str, Any]] = None):
# sourcery skip: hoist-statement-from-if, merge-comparisons, reintroduce-else
if not message_data:
@@ -319,7 +366,11 @@ class HeartFChatting:
# 如果normal模式且不跳过规划器，开始一个回复生成进程，先准备好回复（其实是和planer同时进行的）
if not skip_planner:
reply_to_str = await self.build_reply_to_str(message_data)
gen_task = asyncio.create_task(self._generate_response(message_data, available_actions, reply_to_str, "chat.replyer.normal"))
gen_task = asyncio.create_task(self._generate_response(
message_data=message_data,
available_actions=available_actions,
reply_to=reply_to_str,
request_type="chat.replyer.normal"))
if not skip_planner:
with Timer("规划器", cycle_timers):
@@ -360,11 +411,18 @@ class HeartFChatting:
action_message: Dict[str, Any] = message_data or target_message # type: ignore
if action_type == "reply" or is_parallel:
if action_type == "reply":
# 等待回复生成完毕
if self.loop_mode == ChatMode.NORMAL:
# 只有在gen_task存在时才等待
if gen_task is not None:
if not gen_task:
reply_to_str = await self.build_reply_to_str(message_data)
gen_task = asyncio.create_task(self._generate_response(
message_data=message_data,
available_actions=available_actions,
reply_to=reply_to_str,
request_type="chat.replyer.normal"))
gather_timeout = global_config.chat.thinking_timeout
try:
response_set = await asyncio.wait_for(gen_task, timeout=gather_timeout)
@@ -377,17 +435,6 @@ class HeartFChatting:
logger.warning(f"{self.log_prefix}模型未生成回复内容")
return False
else:
# 如果没有预生成任务，直接生成回复
if not reply_to_str:
reply_to_str = await self.build_reply_to_str(action_message)
with Timer("回复生成", cycle_timers):
response_set = await self._generate_response(action_message, available_actions, reply_to_str, "chat.replyer.normal")
if not response_set:
logger.warning(f"{self.log_prefix}模型未生成回复内容")
return False
else:
logger.info(f"{self.log_prefix}{global_config.bot.nickname} 决定进行回复 (focus模式)")
# 构建reply_to字符串
@@ -395,90 +442,118 @@ class HeartFChatting:
# 生成回复
with Timer("回复生成", cycle_timers):
response_set = await self._generate_response(action_message, available_actions, reply_to_str, request_type="chat.replyer.focus")
response_set = await self._generate_response(
message_data=action_message,
available_actions=available_actions,
reply_to=reply_to_str,
request_type="chat.replyer.focus")
if not response_set:
logger.warning(f"{self.log_prefix}模型未生成回复内容")
return False
# 发送回复
with Timer("回复发送", cycle_timers):
reply_text = await self._send_response(response_set, reply_to_str, loop_start_time, action_message)
# 存储reply action信息
person_info_manager = get_person_info_manager()
person_id = person_info_manager.get_person_id(
action_message.get("chat_info_platform", ""),
action_message.get("user_id", ""),
)
person_name = await person_info_manager.get_value(person_id, "person_name")
action_prompt_display = f"你对{person_name}进行了回复：{reply_text}"
await database_api.store_action_info(
chat_stream=self.chat_stream,
action_build_into_prompt=False,
action_prompt_display=action_prompt_display,
action_done=True,
thinking_id=thinking_id,
action_data={"reply_text": reply_text, "reply_to": reply_to_str},
action_name="reply",
)
# 构建循环信息
loop_info = {
"loop_plan_info": {
"action_result": plan_result.get("action_result", {}),
},
"loop_action_info": {
"action_taken": True,
"reply_text": reply_text,
"command": "",
"taken_time": time.time(),
},
}
success = True
command = ""
loop_info, reply_text,cycle_timers = await self._send_and_store_reply(response_set, reply_to_str, loop_start_time, action_message, cycle_timers, thinking_id, plan_result)
return True
else:
# 如果是并行执行且在normal模式下，需要等待预生成的回复任务完成
# if self.loop_mode == ChatMode.NORMAL and is_parallel and gen_task:
# # 等待预生成的回复任务完成
# gather_timeout = global_config.chat.thinking_timeout
# try:
# response_set = await asyncio.wait_for(gen_task, timeout=gather_timeout)
# if response_set:
# # 发送回复
# with Timer("回复发送", cycle_timers):
# reply_text_parallel = await self._send_response(response_set, reply_to_str, loop_start_time, action_message)
# logger.info(f"{self.log_prefix} 并行执行：已发送回复内容")
# else:
# logger.warning(f"{self.log_prefix} 并行执行：预生成回复内容为空")
# except asyncio.TimeoutError:
# logger.warning(f"{self.log_prefix} 并行执行：回复生成超时>{global_config.chat.thinking_timeout}s，已跳过")
# except asyncio.CancelledError:
# logger.debug(f"{self.log_prefix} 并行执行：回复生成任务已被取消")
# 并行执行：同时进行回复发送和动作执行
tasks = []
# 动作执行计时
# 如果是并行执行且在normal模式下，需要等待预生成的回复任务完成并发送回复
if self.loop_mode == ChatMode.NORMAL and is_parallel and gen_task:
async def handle_reply_task():
# 等待预生成的回复任务完成
gather_timeout = global_config.chat.thinking_timeout
try:
response_set = await asyncio.wait_for(gen_task, timeout=gather_timeout)
except asyncio.TimeoutError:
logger.warning(f"{self.log_prefix} 并行执行：回复生成超时>{global_config.chat.thinking_timeout}s，已跳过")
return None, "", {}
except asyncio.CancelledError:
logger.debug(f"{self.log_prefix} 并行执行：回复生成任务已被取消")
return None, "", {}
if not response_set:
logger.warning(f"{self.log_prefix} 模型超时或生成回复内容为空")
return None, "", {}
reply_to_str = await self.build_reply_to_str(action_message)
loop_info, reply_text, cycle_timers_reply = await self._send_and_store_reply(response_set, reply_to_str, loop_start_time, action_message, cycle_timers, thinking_id, plan_result)
return loop_info, reply_text, cycle_timers_reply
# 添加回复任务到并行任务列表
tasks.append(asyncio.create_task(handle_reply_task()))
# 动作执行任务
async def handle_action_task():
with Timer("动作执行", cycle_timers):
success, reply_text, command = await self._handle_action(
action_type, reasoning, action_data, cycle_timers, thinking_id, action_message
)
return success, reply_text, command
# 添加动作执行任务到并行任务列表
tasks.append(asyncio.create_task(handle_action_task()))
# 并行执行所有任务
results = await asyncio.gather(*tasks, return_exceptions=True)
# 处理结果
reply_loop_info = None
reply_text_from_reply = ""
action_success = False
action_reply_text = ""
action_command = ""
if len(tasks) == 2: # 有回复任务和动作任务
# 处理回复任务结果
reply_result = results[0]
if isinstance(reply_result, Exception):
logger.error(f"{self.log_prefix} 回复任务执行异常: {reply_result}")
elif reply_result and reply_result[0] is not None:
reply_loop_info, reply_text_from_reply, _ = reply_result
# 处理动作任务结果
action_result = results[1]
if isinstance(action_result, Exception):
logger.error(f"{self.log_prefix} 动作任务执行异常: {action_result}")
else:
action_success, action_reply_text, action_command = action_result
else: # 只有动作任务
action_result = results[0]
if isinstance(action_result, Exception):
logger.error(f"{self.log_prefix} 动作任务执行异常: {action_result}")
else:
action_success, action_reply_text, action_command = action_result
# 构建最终的循环信息
if reply_loop_info:
# 如果有回复信息，使用回复的loop_info作为基础
loop_info = reply_loop_info
# 更新动作执行信息
loop_info["loop_action_info"].update({
"action_taken": action_success,
"command": action_command,
"taken_time": time.time(),
})
reply_text = reply_text_from_reply
else:
# 没有回复信息，构建纯动作的loop_info
loop_info = {
"loop_plan_info": {
"action_result": plan_result.get("action_result", {}),
},
"loop_action_info": {
"action_taken": success,
"reply_text": reply_text,
"command": command,
"action_taken": action_success,
"reply_text": action_reply_text,
"command": action_command,
"taken_time": time.time(),
},
}
reply_text = action_reply_text
if ENABLE_S4U:

2
src/chat/express/expression_learner.py
View File

@@ -524,7 +524,7 @@ class ExpressionLearner:
chat_str=random_msg_str,
)
logger.debug(f"学习{type_str}的prompt: {prompt}")
logger.info(f"学习{type_str}的prompt: {prompt}")
try:
response, _ = await self.express_learn_model.generate_response_async(prompt)

1
src/chat/express/expression_selector.py
View File

@@ -279,6 +279,7 @@ class ExpressionSelector:
if not isinstance(result, dict) or "selected_situations" not in result:
logger.error("LLM返回格式错误")
logger.info(f"LLM返回结果: \n{content}")
return []
selected_indices = result["selected_situations"]

1
src/plugin_system/apis/generator_api.py
View File

@@ -140,6 +140,7 @@ async def generate_reply(
except Exception as e:
logger.error(f"[GeneratorAPI] 生成回复时出错: {e}")
logger.error(traceback.format_exc())
return False, [], None

11
template/template.env
View File

@@ -1,11 +1,17 @@
HOST=127.0.0.1
PORT=8000
#key and url
# 密钥和url
# 硅基流动
SILICONFLOW_BASE_URL=https://api.siliconflow.cn/v1/
# DeepSeek官方
DEEP_SEEK_BASE_URL=https://api.deepseek.com/v1
CHAT_ANY_WHERE_BASE_URL=https://api.chatanywhere.tech/v1
# 阿里百炼
BAILIAN_BASE_URL = https://dashscope.aliyuncs.com/compatible-mode/v1
# 火山引擎
HUOSHAN_BASE_URL =
# xxxxx平台
xxxxxxx_BASE_URL=https://xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
# 定义你要用的api的key(需要去对应网站申请哦)
@@ -13,4 +19,5 @@ DEEP_SEEK_KEY=
CHAT_ANY_WHERE_KEY=
SILICONFLOW_KEY=
BAILIAN_KEY =
HUOSHAN_KEY =
xxxxxxx_KEY=