v0.2.2
优化了CQ码获取逻辑和图片下载逻辑 去除硬编码的“麦麦”()
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SengokuCola
@@ -8,8 +8,9 @@ from ...common.database import Database
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from PIL import Image
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from .config import BotConfig, global_config
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import urllib3
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from .cq_code import CQCode
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from .utils_user import get_user_nickname
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from .utils_cq import parse_cq_code
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from .cq_code import cq_code_tool,CQCode
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Message = ForwardRef('Message') # 添加这行
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@@ -63,12 +64,10 @@ class Message:
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self.group_name = self.get_groupname(self.group_id)
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if not self.processed_plain_text:
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# 解析消息片段
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if self.raw_message:
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# print(f"\033[1;34m[调试信息]\033[0m 原始消息: {self.raw_message}")
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self.message_segments = self.parse_message_segments(str(self.raw_message))
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self.processed_plain_text = ' '.join(
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seg['translated_text']
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seg.translated_plain_text
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for seg in self.message_segments
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)
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@@ -87,96 +86,80 @@ class Message:
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else:
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return f"群{group_id}"
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def parse_message_segments(self, message: str) -> List[Dict]:
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def parse_message_segments(self, message: str) -> List[CQCode]:
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"""
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将消息解析为片段列表，包括纯文本和CQ码
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返回的列表中每个元素都是字典，包含：
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- type: 'text' 或 CQ码类型
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- data: 对于text类型是文本内容，对于CQ码是参数字典
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- translated_text: 经过处理后的文本
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- cq_code_list:分割出的聊天对象，包括文本和CQ码
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- trans_list:翻译后的对象列表
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"""
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segments = []
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start = 0
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cq_code_dict_list = []
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trans_list = []
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start = 0
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print(f"\033[1;34m[调试信息]\033[0m 原始消息: {message}")
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while True:
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# 查找下一个CQ码的开始位置
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cq_start = message.find('[CQ:', start)
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#如果没有cq码，直接返回文本内容
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if cq_start == -1:
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# 如果没有找到更多CQ码，添加剩余文本
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if start < len(message):
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text = message[start:].strip()
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if text: # 只添加非空文本
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segments.append({
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'type': 'text',
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'data': {'text': text},
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'translated_text': text
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})
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cq_code_dict_list.append(parse_cq_code(text))
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break
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# 添加CQ码前的文本
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if cq_start > start:
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text = message[start:cq_start].strip()
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if text: # 只添加非空文本
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segments.append({
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'type': 'text',
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'data': {'text': text},
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'translated_text': text
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})
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cq_code_dict_list.append(parse_cq_code(text))
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# 查找CQ码的结束位置
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cq_end = message.find(']', cq_start)
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if cq_end == -1:
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# CQ码未闭合，作为普通文本处理
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text = message[cq_start:].strip()
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if text:
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segments.append({
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'type': 'text',
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'data': {'text': text},
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'translated_text': text
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})
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cq_code_dict_list.append(parse_cq_code(text))
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break
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# 提取完整的CQ码并创建CQCode对象
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cq_code = message[cq_start:cq_end + 1]
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try:
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cq_obj = CQCode.from_cq_code(cq_code,reply = self.reply_message)
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# 设置必要的属性
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segments.append({
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'type': cq_obj.type,
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'data': cq_obj.params,
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'translated_text': cq_obj.translated_plain_text
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})
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except Exception as e:
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import traceback
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print(f"\033[1;31m[错误]\033[0m 处理CQ码失败: {str(e)}")
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print(f"CQ码内容: {cq_code}")
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print(f"当前消息属性:")
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print(f"- group_id: {self.group_id}")
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print(f"- user_id: {self.user_id}")
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print(f"- user_nickname: {self.user_nickname}")
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print(f"- group_name: {self.group_name}")
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print("详细错误信息:")
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print(traceback.format_exc())
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# 处理失败时，将CQ码作为普通文本处理
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segments.append({
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'type': 'text',
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'data': {'text': cq_code},
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'translated_text': cq_code
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})
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#将cq_code解析成字典
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cq_code_dict_list.append(parse_cq_code(cq_code))
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# 更新start位置到当前CQ码之后
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start = cq_end + 1
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print(f"\033[1;34m[调试信息]\033[0m 提取的消息对象：列表: {cq_code_dict_list}")
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if len(segments) == 1 and segments[0]['type'] == 'image':
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#判定是否是表情包消息，以及是否含有表情包
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if len(cq_code_dict_list) == 1 and cq_code_dict_list[0]['type'] == 'image':
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self.is_emoji = True
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self.has_emoji_emoji = True
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else:
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for segment in segments:
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for segment in cq_code_dict_list:
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if segment['type'] == 'image' and segment['data'].get('sub_type') == '1':
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self.has_emoji_emoji = True
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break
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#翻译作为字典的CQ码
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for _code_item in cq_code_dict_list:
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#一个一个CQ码处理
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message_obj = cq_code_tool.cq_from_dict_to_class(_code_item,reply = self.reply_message)
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trans_list.append(message_obj)
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# except Exception as e:
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# import traceback
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# print(f"\033[1;31m[错误]\033[0m 处理CQ码失败: {str(e)}")
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# print(f"CQ码内容: {cq_code}")
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# print(f"当前消息属性:")
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# print(f"- group_id: {self.group_id}")
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# print(f"- user_id: {self.user_id}")
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# print(f"- user_nickname: {self.user_nickname}")
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# print(f"- group_name: {self.group_name}")
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# print("详细错误信息:")
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# print(traceback.format_exc())
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return segments
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return trans_list
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class Message_Thinking:
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"""消息思考类"""
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