mirror of
https://github.com/Nezumi-2711/astrbot_plugin_qq_group_daily_analysis.git
synced 2026-09-23 04:09:59 +00:00
fix: 分析器和消息处理
This commit is contained in:
@@ -170,40 +170,34 @@ class GoldenQuoteAnalyzer(BaseAnalyzer):
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def extract_interesting_messages(self, messages: list[dict]) -> list[dict]:
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"""
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提取圣经的文本消息
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根据清理后的消息提取可能有意义的消息片段用于金句分析。
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Args:
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messages: 群聊消息列表
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messages: 已由 MessageCleaner 处理过的 legacy 消息列表
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Returns:
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圣经的文本消息列表
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提取的文本消息列表
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"""
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try:
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interesting_messages = []
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interesting_messages = []
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for msg in messages:
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sender = msg.get("sender", {})
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nickname = InfoUtils.get_user_nickname(self.config_manager, sender)
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msg_time = datetime.fromtimestamp(msg.get("time", 0)).strftime("%H:%M")
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for msg in messages:
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# 获取发送者显示名
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sender = msg.get("sender", {})
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nickname = InfoUtils.get_user_nickname(self.config_manager, sender)
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msg_time = datetime.fromtimestamp(msg.get("time", 0)).strftime("%H:%M")
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for content in msg.get("message", []):
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if content.get("type") == "text":
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text = content.get("data", {}).get("text", "").strip()
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# 过滤长度适中、可能圣经的消息
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if 5 <= len(text) <= 100 and not text.startswith(
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("http", "www", "/")
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):
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interesting_messages.append(
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{
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"sender": nickname,
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"time": msg_time,
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"content": text,
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"user_id": str(sender.get("user_id", "")),
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}
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)
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for content in msg.get("message", []):
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if content.get("type") == "text":
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text = content.get("data", {}).get("text", "").strip()
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# 过滤掉过短或过长的噪音(已经在 cleaner 处理过一遍基本垃圾)
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if 2 <= len(text) <= 500:
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interesting_messages.append(
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{
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"sender": nickname,
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"time": msg_time,
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"content": text,
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"user_id": str(sender.get("user_id", "")),
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}
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)
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return interesting_messages
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except Exception as e:
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logger.error(f"提取圣经消息失败: {e}")
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return []
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return interesting_messages
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@@ -257,79 +257,38 @@ class TopicAnalyzer(BaseAnalyzer):
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def extract_text_messages(self, messages: list[dict]) -> list[dict]:
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"""
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从群聊消息中提取文本消息
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从已清理的消息中提取文本消息用于话题分析。
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Args:
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messages: 群聊消息列表
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messages: 已由 MessageCleaner 处理过的 legacy 消息列表
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Returns:
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提取的文本消息列表
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"""
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logger.debug(
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f"extract_text_messages 开始处理,输入消息数量: {len(messages) if messages else 0}"
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)
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logger.debug(f"extract_text_messages 输入消息类型: {type(messages)}")
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if not messages:
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logger.warning("extract_text_messages 收到空消息列表")
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return []
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text_messages = []
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for i, msg in enumerate(messages):
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logger.debug(f"处理第 {i + 1} 条消息,类型: {type(msg)}")
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# 确保msg是字典类型,避免'str' object has no attribute 'get'错误
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if not isinstance(msg, dict):
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logger.warning(f"跳过非字典类型的消息: {type(msg)} - {msg}")
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continue
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for msg in messages:
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# 获取发送者显示名
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sender = msg.get("sender", {})
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nickname = InfoUtils.get_user_nickname(self.config_manager, sender)
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msg_time = datetime.fromtimestamp(msg.get("time", 0)).strftime("%H:%M")
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try:
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sender = msg.get("sender", {})
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# 确保sender是字典类型,避免'str' object has no attribute 'get'错误
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if not isinstance(sender, dict):
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logger.warning(
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f"extract_text_messages 跳过sender非字典类型的消息: {type(sender)} - {sender}"
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)
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continue
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for content in msg.get("message", []):
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if content.get("type") == "text":
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text = content.get("data", {}).get("text", "").strip()
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# 已经在 MessageCleaner 中处理过基本的垃圾内容
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if text:
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# 简单的额外清理
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cleaned_text = text.replace("\n", " ").replace("\r", " ")
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cleaned_text = re.sub(r"[\x00-\x1f\x7f-\x9f]", "", cleaned_text)
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# 获取发送者ID并过滤机器人消息
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user_id = str(sender.get("user_id", ""))
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bot_self_ids = self.config_manager.get_bot_self_ids()
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# 跳过机器人自己的消息
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if bot_self_ids and user_id in [str(uid) for uid in bot_self_ids]:
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logger.debug(f"extract_text_messages 过滤掉机器人QQ号: {user_id}")
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continue
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nickname = InfoUtils.get_user_nickname(self.config_manager, sender)
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msg_time = datetime.fromtimestamp(msg.get("time", 0)).strftime("%H:%M")
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for content in msg.get("message", []):
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if content.get("type") == "text":
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text = content.get("data", {}).get("text", "").strip()
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if text and len(text) > 2 and not text.startswith("/"):
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# 清理消息内容
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text = text.replace('""', '"').replace('""', '"')
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text = text.replace(""", "'").replace(""", "'")
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text = text.replace("\n", " ").replace("\r", " ")
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text = text.replace("\t", " ")
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text = re.sub(r"[\x00-\x1f\x7f-\x9f]", "", text)
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text_messages.append(
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{
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"sender": nickname,
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"time": msg_time,
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"content": text.strip(),
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}
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)
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except Exception as e:
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logger.error(f"处理第 {i + 1} 条消息时出错: {e}", exc_info=True)
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continue
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logger.debug(
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f"extract_text_messages 完成,提取到 {len(text_messages)} 条文本消息"
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)
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if text_messages:
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logger.debug(f"extract_text_messages 第一条文本消息: {text_messages[0]}")
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text_messages.append(
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{
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"sender": nickname,
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"time": msg_time,
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"content": cleaned_text.strip(),
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}
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)
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return text_messages
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async def analyze_topics(
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@@ -178,16 +178,15 @@ class UserTitleAnalyzer(BaseAnalyzer):
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for user_id, stats in user_analysis.items():
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user_id_str = str(user_id)
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# 过滤机器人自己的消息
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# 过滤机器人由 MessageCleaner 已处理,此处仅作为二级防御
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if bot_self_ids and user_id_str in [str(uid) for uid in bot_self_ids]:
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logger.debug(f"过滤掉机器人ID: {user_id}")
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continue
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# 只处理活跃用户
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# 只处理活跃用户 (top_users 或 消息数>=5)
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if user_id_str not in target_user_ids:
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continue
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# 分析用户特征
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# 分析用户特征 (此处已基于已清理的 stats)
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night_messages = sum(stats["hours"][h] for h in range(6))
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avg_chars = (
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stats["char_count"] / stats["message_count"]
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@@ -198,7 +197,7 @@ class UserTitleAnalyzer(BaseAnalyzer):
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user_summaries.append(
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{
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"name": stats["nickname"],
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"user_id": user_id_str, # 使用 user_id
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"user_id": user_id_str,
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"message_count": stats["message_count"],
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"avg_chars": round(avg_chars, 1),
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"emoji_ratio": round(
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@@ -156,15 +156,21 @@ class LLMAnalyzer:
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user_analysis: dict,
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umo: str = None,
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top_users: list[dict] = None,
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topic_enabled: bool = True,
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user_title_enabled: bool = True,
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golden_quote_enabled: bool = True,
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) -> tuple[list[SummaryTopic], list[UserTitle], list[GoldenQuote], TokenUsage]:
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"""
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并发执行所有分析任务(话题、用户称号、金句)
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并发执行所有分析任务(话题、用户称号、金句),支持按需启用。
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Args:
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messages: 群聊消息列表
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user_analysis: 用户分析统计
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umo: 模型唯一标识符
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top_users: 活跃用户列表(可选)
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topic_enabled: 是否启用话题分析
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user_title_enabled: 是否启用用户称号分析
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golden_quote_enabled: 是否启用金句分析
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Returns:
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(话题列表, 用户称号列表, 金句列表, 总Token使用统计)
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@@ -179,10 +185,13 @@ class LLMAnalyzer:
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else:
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session_id = timestamp
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logger.info(f"开始并发执行所有分析任务,会话ID: {session_id}")
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logger.info(
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f"开始并发执行分析任务 (话题:{topic_enabled}, 称号:{user_title_enabled}, 金句:{golden_quote_enabled}),会话ID: {session_id}"
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)
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# 保存原始消息数据 (Debug Mode)
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if self.config_manager.get_debug_mode():
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# ... (保持原有的调试保存代码)
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try:
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import json
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from pathlib import Path
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@@ -202,44 +211,57 @@ class LLMAnalyzer:
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msg_file_path = debug_dir / f"{session_id}_messages.json"
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with open(msg_file_path, "w", encoding="utf-8") as f:
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json.dump(messages, f, ensure_ascii=False, indent=2)
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logger.info(f"已保存原始消息数据到: {msg_file_path}")
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except Exception as e:
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logger.error(f"保存原始消息数据失败: {e}", exc_info=True)
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except Exception:
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pass
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# 并发执行三个分析任务
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results = await asyncio.gather(
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self.topic_analyzer.analyze_topics(messages, umo, session_id),
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self.user_title_analyzer.analyze_user_titles(
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messages, user_analysis, umo, top_users, session_id
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),
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self.golden_quote_analyzer.analyze_golden_quotes(
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messages, umo, session_id
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),
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return_exceptions=True,
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)
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# 构建并发任务列表
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tasks = []
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task_names = []
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if topic_enabled:
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tasks.append(
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self.topic_analyzer.analyze_topics(messages, umo, session_id)
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)
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task_names.append("topic")
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if user_title_enabled:
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tasks.append(
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self.user_title_analyzer.analyze_user_titles(
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messages, user_analysis, umo, top_users, session_id
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)
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)
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task_names.append("user_title")
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if golden_quote_enabled:
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tasks.append(
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self.golden_quote_analyzer.analyze_golden_quotes(
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messages, umo, session_id
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)
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)
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task_names.append("golden_quote")
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if not tasks:
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return [], [], [], TokenUsage()
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results = await asyncio.gather(*tasks, return_exceptions=True)
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# 处理结果
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topics, topic_usage = [], TokenUsage()
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user_titles, title_usage = [], TokenUsage()
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golden_quotes, quote_usage = [], TokenUsage()
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# 话题分析结果
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if isinstance(results[0], Exception):
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logger.error(f"话题分析失败: {results[0]}")
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else:
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topics, topic_usage = results[0]
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for i, result in enumerate(results):
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name = task_names[i]
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if isinstance(result, Exception):
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logger.error(f"分析任务 {name} 失败: {result}")
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continue
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# 用户称号分析结果
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if isinstance(results[1], Exception):
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logger.error(f"用户称号分析失败: {results[1]}")
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else:
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user_titles, title_usage = results[1]
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# 金句分析结果
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if isinstance(results[2], Exception):
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logger.error(f"金句分析失败: {results[2]}")
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else:
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golden_quotes, quote_usage = results[2]
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if name == "topic":
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topics, topic_usage = result
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elif name == "user_title":
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user_titles, title_usage = result
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elif name == "golden_quote":
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golden_quotes, quote_usage = result
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# 合并Token使用统计
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total_usage = TokenUsage(
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@@ -8,6 +8,14 @@ class InfoUtils:
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"""
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enable_user_card = config_manager.get_enable_user_card()
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if enable_user_card:
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return sender.get("card", "") or sender.get("nickname", "")
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return (
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sender.get("card", "")
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or sender.get("nickname", "")
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or str(sender.get("user_id", ""))
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)
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else:
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return sender.get("nickname", "") or sender.get("card", "")
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return (
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sender.get("nickname", "")
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or sender.get("card", "")
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or str(sender.get("user_id", ""))
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)
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@@ -6,7 +6,7 @@ JSON处理工具模块
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import json
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import re
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from ...utils.logger import logger
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from ....utils.logger import logger
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def fix_json(text: str) -> str:
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@@ -105,9 +105,6 @@ class BotManager:
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def _refresh_from_stored_platforms(self):
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"""尝试从已存储的平台对象中刷新 bot 实例 (Lazy Load)"""
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for platform_id, platform in self._platforms.items():
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if platform_id in self._bot_instances:
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continue
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bot_client = None
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# 优先尝试 get_client()
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if hasattr(platform, "get_client"):
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@@ -121,6 +118,13 @@ class BotManager:
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bot_client = platform.client
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if bot_client:
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# 检查是否已存在且是否发生变化(防止重复创建适配器)
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old_client = self._bot_instances.get(platform_id)
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# 如果 client 对象没变且已经有适配器,跳过
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if bot_client is old_client and platform_id in self._adapters:
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continue
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platform_name = None
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if hasattr(platform, "metadata"):
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# 优先使用 type
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@@ -129,6 +133,16 @@ class BotManager:
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elif hasattr(platform.metadata, "name"):
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platform_name = platform.metadata.name
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# 兼容不同版本的元数据获取
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if not platform_name:
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meta = getattr(platform, "meta", None)
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if callable(meta):
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try:
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metadata = meta()
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platform_name = getattr(metadata, "name", None)
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except Exception:
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pass
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# 后备检测:如果不支持名称
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if not platform_name or not PlatformAdapterFactory.is_supported(
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str(platform_name)
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@@ -138,7 +152,7 @@ class BotManager:
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platform_name = detected
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self.set_bot_instance(bot_client, platform_id, platform_name)
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logger.info(f"懒加载发现平台 {platform_id} 的 bot 实例")
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logger.info(f"已刷新/发现平台 {platform_id} 的 bot 实例 (变动或懒加载)")
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def get_all_bot_instances(self) -> dict:
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"""获取所有已加载的bot实例 {platform_id: bot_instance}"""
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@@ -213,17 +227,29 @@ class BotManager:
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这是 DDD 架构操作的主要方法。
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"""
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if platform_id:
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# 无论是否存在适配器,都尝试检测一次 client 是否有变(如重启后 session 变化)
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if platform_id in self._platforms:
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self._refresh_from_stored_platforms()
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return self._adapters.get(platform_id)
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if self._adapters:
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if len(self._adapters) == 1:
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return list(self._adapters.values())[0]
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logger.error(
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logger.warning(
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f"存在多个适配器 {list(self._adapters.keys())},但未指定 platform_id。"
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)
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return None
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# 如果没有任何适配器,尝试全局刷新一次
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self._refresh_from_stored_platforms()
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if self._adapters:
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if platform_id:
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return self._adapters.get(platform_id)
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if len(self._adapters) == 1:
|
||||
return list(self._adapters.values())[0]
|
||||
|
||||
return None
|
||||
|
||||
def get_all_adapters(self) -> dict:
|
||||
@@ -373,17 +399,22 @@ class BotManager:
|
||||
|
||||
def update_from_event(self, event):
|
||||
"""从事件更新bot实例(用于手动命令)"""
|
||||
if hasattr(event, "bot") and event.bot:
|
||||
# 兼容不同平台的 bot 实例属性名 (OneBot 使用 bot, Discord 使用 client)
|
||||
bot_instance = getattr(event, "bot", None) or getattr(event, "client", None)
|
||||
|
||||
if bot_instance:
|
||||
# 从事件中获取平台ID
|
||||
platform_id = None
|
||||
if hasattr(event, "platform") and isinstance(event.platform, str):
|
||||
if hasattr(event, "get_platform_id"):
|
||||
platform_id = event.get_platform_id()
|
||||
elif hasattr(event, "platform_meta") and hasattr(event.platform_meta, "id"):
|
||||
platform_id = event.platform_meta.id
|
||||
elif hasattr(event, "platform") and isinstance(event.platform, str):
|
||||
platform_id = event.platform
|
||||
elif hasattr(event, "metadata") and hasattr(event.metadata, "id"):
|
||||
platform_id = event.metadata.id
|
||||
|
||||
self.set_bot_instance(event.bot, platform_id)
|
||||
self.set_bot_instance(bot_instance, platform_id)
|
||||
# 每次都尝试从bot实例提取ID
|
||||
bot_self_id = self._extract_bot_self_id(event.bot)
|
||||
bot_self_id = self._extract_bot_self_id(bot_instance)
|
||||
if bot_self_id:
|
||||
# 将单个ID转换为列表,保持统一处理
|
||||
self.set_bot_self_ids([bot_self_id])
|
||||
|
||||
Reference in New Issue
Block a user