🤖 自动格式化代码 [skip ci]
This commit is contained in:
github-actions[bot]
@@ -38,9 +38,7 @@ class ReplyAction(BaseAction):
|
||||
action_description = "参与聊天回复，发送文本进行表达"
|
||||
|
||||
# 动作参数定义
|
||||
action_parameters = {
|
||||
"reply_to": "你要回复的对方的发言内容，格式：（用户名:发言内容），可以为none"
|
||||
}
|
||||
action_parameters = {"reply_to": "你要回复的对方的发言内容，格式：（用户名:发言内容），可以为none"}
|
||||
|
||||
# 动作使用场景
|
||||
action_require = ["你想要闲聊或者随便附和", "有人提到你", "如果你刚刚进行了回复，不要对同一个话题重复回应"]
|
||||
@@ -53,45 +51,40 @@ class ReplyAction(BaseAction):
|
||||
logger.info(f"{self.log_prefix} 决定回复: {self.reasoning}")
|
||||
|
||||
start_time = self.action_data.get("loop_start_time", time.time())
|
||||
|
||||
|
||||
try:
|
||||
|
||||
success, reply_set = await generator_api.generate_reply(
|
||||
chat_stream=self.chat_stream,
|
||||
action_data=self.action_data,
|
||||
platform=self.platform,
|
||||
chat_id=self.chat_id,
|
||||
is_group=self.is_group
|
||||
is_group=self.is_group,
|
||||
)
|
||||
|
||||
# 检查从start_time以来的新消息数量
|
||||
# 获取动作触发时间或使用默认值
|
||||
current_time = time.time()
|
||||
new_message_count = message_api.count_new_messages(
|
||||
chat_id=self.chat_id,
|
||||
start_time=start_time,
|
||||
end_time=current_time
|
||||
chat_id=self.chat_id, start_time=start_time, end_time=current_time
|
||||
)
|
||||
|
||||
|
||||
# 根据新消息数量决定是否使用reply_to
|
||||
need_reply = new_message_count >= 4
|
||||
logger.info(f"{self.log_prefix} 从{start_time}到{current_time}共有{new_message_count}条新消息，{'使用' if need_reply else '不使用'}reply_to")
|
||||
logger.info(
|
||||
f"{self.log_prefix} 从{start_time}到{current_time}共有{new_message_count}条新消息，{'使用' if need_reply else '不使用'}reply_to"
|
||||
)
|
||||
|
||||
# 构建回复文本
|
||||
reply_text = ""
|
||||
reply_text = ""
|
||||
first_reply = False
|
||||
for reply_seg in reply_set:
|
||||
data = reply_seg[1]
|
||||
if not first_reply and need_reply:
|
||||
await self.send_text(
|
||||
content=data,
|
||||
reply_to=self.action_data.get("reply_to", "")
|
||||
)
|
||||
await self.send_text(content=data, reply_to=self.action_data.get("reply_to", ""))
|
||||
else:
|
||||
await self.send_text(content=data)
|
||||
first_reply = True
|
||||
reply_text += data
|
||||
|
||||
|
||||
# 存储动作记录
|
||||
await self.store_action_info(
|
||||
@@ -110,7 +103,6 @@ class ReplyAction(BaseAction):
|
||||
return False, f"回复失败: {str(e)}"
|
||||
|
||||
|
||||
|
||||
class NoReplyAction(BaseAction):
|
||||
"""不回复动作，继承时会等待新消息或超时"""
|
||||
|
||||
@@ -168,7 +160,7 @@ class NoReplyAction(BaseAction):
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"{self.log_prefix} 不回复动作执行失败: {e}")
|
||||
return False, f"不回复动作执行失败: {e}"
|
||||
return False, f"不回复动作执行失败: {e}"
|
||||
|
||||
@classmethod
|
||||
def reset_consecutive_count(cls):
|
||||
@@ -218,17 +210,17 @@ class EmojiAction(BaseAction):
|
||||
# 1. 根据描述选择表情包
|
||||
description = self.action_data.get("description", "")
|
||||
emoji_result = await emoji_api.get_by_description(description)
|
||||
|
||||
|
||||
if not emoji_result:
|
||||
logger.warning(f"{self.log_prefix} 未找到匹配描述 '{description}' 的表情包")
|
||||
return False, f"未找到匹配 '{description}' 的表情包"
|
||||
|
||||
|
||||
emoji_base64, emoji_description, matched_emotion = emoji_result
|
||||
logger.info(f"{self.log_prefix} 找到表情包: {emoji_description}, 匹配情感: {matched_emotion}")
|
||||
|
||||
|
||||
# 使用BaseAction的便捷方法发送表情包
|
||||
success = await self.send_emoji(emoji_base64)
|
||||
|
||||
|
||||
if not success:
|
||||
logger.error(f"{self.log_prefix} 表情包发送失败")
|
||||
return False, "表情包发送失败"
|
||||
@@ -430,10 +422,6 @@ class CoreActionsPlugin(BasePlugin):
|
||||
return components
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
# class DeepReplyAction(BaseAction):
|
||||
# """回复动作 - 参与聊天回复"""
|
||||
|
||||
@@ -467,42 +455,39 @@ class CoreActionsPlugin(BasePlugin):
|
||||
# chatting_observation = self._get_chatting_observation()
|
||||
# if not chatting_observation:
|
||||
# return False, "未找到聊天观察"
|
||||
|
||||
|
||||
# talking_message_str = chatting_observation.talking_message_str
|
||||
|
||||
# # 处理回复目标
|
||||
# chat_stream = self.api.get_service("chat_stream")
|
||||
# anchor_message = await create_empty_anchor_message(chat_stream.platform, chat_stream.group_info, chat_stream)
|
||||
|
||||
|
||||
|
||||
|
||||
# llm_model = self.api.get_available_models().replyer_1
|
||||
|
||||
|
||||
# prompt = f"""
|
||||
# {talking_message_str}
|
||||
|
||||
# 在上面的聊天中，你对{self.action_data.get("topic", "")}感兴趣，形成深刻观点，请你思考,总结成一份学术论文,APA标准格式
|
||||
# """
|
||||
|
||||
|
||||
# success, response, reasoning, model_name = await self.api.generate_with_model(prompt, llm_model)
|
||||
|
||||
|
||||
# print(prompt)
|
||||
# print(f"DeepReplyAction: {response}")
|
||||
|
||||
|
||||
# # prompt = f"""
|
||||
# # {talking_message_str}
|
||||
|
||||
# # 在上面的聊天中，你对{self.action_data.get("topic", "")}感兴趣，请你思考
|
||||
# # """
|
||||
|
||||
|
||||
# extra_info_block = self.action_data.get("extra_info_block", "")
|
||||
# extra_info_block += response
|
||||
# # extra_info_block += f"\n--------------------------------\n注意，这是最重要的内容！！！！！你现在可以用比较长的篇幅来表达你的观点，不要只回复一个字或者几个字\n由于你进入了深度思考模式，所以下方聊天记录的回复要求不再适用，请你自由的表达，不论字数长短限制\n\n--------------------------------\n注意，你现在可以用比较长的篇幅来表达你的观点，不要只回复一个字或者几个字\n由于你进入了深度思考模式，所以下方聊天记录的回复要求不再适用，请你自由的表达，不论字数长短限制\n"
|
||||
# # extra_info_block += f"\n--------------------------------\n注意，优先关注这句！！！！你现在可以用比较长的篇幅来表达你的观点，不要只回复一个字或者几个字\n由于你进入了深度思考模式，所以下方聊天记录的回复要求不再适用，请你自由的表达，不论字数长短限制\n\n--------------------------------\n注意，你现在可以用比较长的篇幅来表达你的观点，不要只回复一个字或者几个字\n由于你进入了深度思考模式，所以其他的回复要求不再适用，请你自由的表达，不论字数长短限制\n"
|
||||
# self.action_data["extra_info_block"] = extra_info_block
|
||||
|
||||
|
||||
|
||||
|
||||
# # 获取回复器服务
|
||||
# # replyer = self.api.get_service("replyer")
|
||||
@@ -558,4 +543,4 @@ class CoreActionsPlugin(BasePlugin):
|
||||
# for reply in reply_set:
|
||||
# data = reply[1]
|
||||
# reply_text += data
|
||||
# return reply_text
|
||||
# return reply_text
|
||||
|
||||
Reference in New Issue
Block a user