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移除mai4u：s4u_watching_manager.py, screen_manager.py, super_chat_manager.py, yes_or_no.py, openai_client.py, and s4u_config.py. These changes streamline the codebase by eliminating unused components and improving maintainability.

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Windpicker-owo
2025-10-31 15:52:42 +08:00
parent c045895754
commit 155b6e9d04
22 changed files with 1 additions and 4897 deletions
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200
src/chat/message_receive/message.py
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@@ -309,206 +309,6 @@ class MessageRecv(Message):
return f"[处理失败的{segment.type}消息]"
@dataclass
class MessageRecvS4U(MessageRecv):
def __init__(self, message_dict: dict[str, Any]):
super().__init__(message_dict)
self.is_gift = False
self.is_fake_gift = False
self.is_superchat = False
self.gift_info = None
self.gift_name = None
self.gift_count: int | None = None
self.superchat_info = None
self.superchat_price = None
self.superchat_message_text = None
self.is_screen = False
self.is_internal = False
self.voice_done = None
self.chat_info = None
async def process(self) -> None:
self.processed_plain_text = await self._process_message_segments(self.message_segment)
async def _process_single_segment(self, segment: Seg) -> str:
"""处理单个消息段
Args:
segment: 消息段
Returns:
str: 处理后的文本
"""
try:
if segment.type == "text":
self.is_voice = False
self.is_picid = False
self.is_emoji = False
return segment.data # type: ignore
elif segment.type == "image":
self.is_voice = False
# 如果是base64图片数据
if isinstance(segment.data, str):
self.has_picid = True
self.is_picid = True
self.is_emoji = False
image_manager = get_image_manager()
# print(f"segment.data: {segment.data}")
_, processed_text = await image_manager.process_image(segment.data)
return processed_text
return "[发了一张图片，网卡了加载不出来]"
elif segment.type == "emoji":
self.has_emoji = True
self.is_emoji = True
self.is_picid = False
if isinstance(segment.data, str):
return await get_image_manager().get_emoji_description(segment.data)
return "[发了一个表情包，网卡了加载不出来]"
elif segment.type == "voice":
self.has_picid = False
self.is_picid = False
self.is_emoji = False
self.is_voice = True
# 检查消息是否由机器人自己发送
# 检查消息是否由机器人自己发送
if self.message_info and self.message_info.user_info and str(self.message_info.user_info.user_id) == str(global_config.bot.qq_account):
logger.info(f"检测到机器人自身发送的语音消息 (User ID: {self.message_info.user_info.user_id})，尝试从缓存获取文本。")
if isinstance(segment.data, str):
cached_text = consume_self_voice_text(segment.data)
if cached_text:
logger.info(f"成功从缓存中获取语音文本: '{cached_text[:70]}...'")
return f"[语音：{cached_text}]"
else:
logger.warning("机器人自身语音消息缓存未命中，将回退到标准语音识别。")
# 标准语音识别流程 (也作为缓存未命中的后备方案)
if isinstance(segment.data, str):
return await get_voice_text(segment.data)
return "[发了一段语音，网卡了加载不出来]"
elif segment.type == "mention_bot":
self.is_voice = False
self.is_picid = False
self.is_emoji = False
self.is_mentioned = float(segment.data) # type: ignore
return ""
elif segment.type == "priority_info":
self.is_voice = False
self.is_picid = False
self.is_emoji = False
if isinstance(segment.data, dict):
# 处理优先级信息
self.priority_mode = "priority"
self.priority_info = segment.data
"""
{
'message_type': 'vip', # vip or normal
'message_priority': 1.0, # 优先级，大为优先，float
}
"""
return ""
elif segment.type == "gift":
self.is_voice = False
self.is_gift = True
# 解析gift_info，格式为"名称:数量"
name, count = segment.data.split(":", 1) # type: ignore
self.gift_info = segment.data
self.gift_name = name.strip()
self.gift_count = int(count.strip())
return ""
elif segment.type == "voice_done":
msg_id = segment.data
logger.info(f"voice_done: {msg_id}")
self.voice_done = msg_id
return ""
elif segment.type == "superchat":
self.is_superchat = True
self.superchat_info = segment.data
price, message_text = segment.data.split(":", 1) # type: ignore
self.superchat_price = price.strip()
self.superchat_message_text = message_text.strip()
self.processed_plain_text = str(self.superchat_message_text)
self.processed_plain_text += (
f"（注意：这是一条超级弹幕信息，价值{self.superchat_price}元，请你认真回复）"
)
return self.processed_plain_text
elif segment.type == "screen":
self.is_screen = True
self.screen_info = segment.data
return "屏幕信息"
elif segment.type == "file":
if isinstance(segment.data, dict):
file_name = segment.data.get('name', '未知文件')
file_size = segment.data.get('size', '未知大小')
return f"[文件：{file_name} ({file_size}字节)]"
return "[收到一个文件]"
elif segment.type == "video":
self.is_voice = False
self.is_picid = False
self.is_emoji = False
logger.info(f"接收到视频消息，数据类型: {type(segment.data)}")
# 检查视频分析功能是否可用
if not is_video_analysis_available():
logger.warning("⚠️ Rust视频处理模块不可用，跳过视频分析")
return "[视频]"
if global_config.video_analysis.enable:
logger.info("已启用视频识别,开始识别")
if isinstance(segment.data, dict):
try:
# 从Adapter接收的视频数据
video_base64 = segment.data.get("base64")
filename = segment.data.get("filename", "video.mp4")
logger.info(f"视频文件名: {filename}")
logger.info(f"Base64数据长度: {len(video_base64) if video_base64 else 0}")
if video_base64:
# 解码base64视频数据
video_bytes = base64.b64decode(video_base64)
logger.info(f"解码后视频大小: {len(video_bytes)} 字节")
# 使用video analyzer分析视频
video_analyzer = get_video_analyzer()
result = await video_analyzer.analyze_video_from_bytes(
video_bytes, filename
)
logger.info(f"视频分析结果: {result}")
# 返回视频分析结果
summary = result.get("summary", "")
if summary:
return f"[视频内容] {summary}"
else:
return "[已收到视频，但分析失败]"
else:
logger.warning("视频消息中没有base64数据")
return "[收到视频消息，但数据异常]"
except Exception as e:
logger.error(f"视频处理失败: {e!s}")
import traceback
logger.error(f"错误详情: {traceback.format_exc()}")
return "[收到视频，但处理时出现错误]"
else:
logger.warning(f"视频消息数据不是字典格式: {type(segment.data)}")
return "[发了一个视频，但格式不支持]"
else:
return ""
else:
logger.warning(f"未知的消息段类型: {segment.type}")
return f"[{segment.type} 消息]"
except Exception as e:
logger.error(f"处理消息段失败: {e!s}, 类型: {segment.type}, 数据: {segment.data}")
return f"[处理失败的{segment.type}消息]"
@dataclass
class MessageProcessBase(Message):
"""消息处理基类，用于处理中和发送中的消息"""