Kris
068cf70fe9
新增 iMessage 通道适配器完整实现，包含： 1. 核心适配器与工具工厂导出 2. 运行时存储、反射防护、会话路由等基础组件 3. 消息信封、线程管理、回复上下文格式化 4. Tapback 表情反应处理、自定义异常体系 5. 审批按钮、联系人解析、速率限制功能 6. 文本净化、目标解析、缓存管理模块 7. 配置 schema、多账户支持、安装向导等配置模块 8. 审计日志、媒体AI处理等扩展功能
44 lines
1.2 KiB
Python
44 lines
1.2 KiB
Python
from __future__ import annotations
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def format_reply_context(
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reply_to_message_id: str | None = None,
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reply_to_text: str | None = None,
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reply_to_sender: str | None = None,
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) -> str:
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"""格式化引用回复上下文。
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生成如 "[Replying to +8613800138000 id:msg_001]" 格式的上下文行，
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附加在出站消息文本前。
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"""
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if not reply_to_message_id and not reply_to_text:
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return ""
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parts: list[str] = ["[Replying to"]
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if reply_to_sender:
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parts.append(f" {reply_to_sender}")
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if reply_to_message_id:
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parts.append(f" id:{reply_to_message_id}")
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if reply_to_text:
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preview = reply_to_text[:100].replace("\n", " ")
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parts.append(f' "{preview}"')
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parts.append("]\n")
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return " ".join(parts) if len(parts) > 2 else ""
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def describe_reply_context(data: dict) -> str:
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"""从消息数据中提取并格式化回复上下文。"""
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reply_to_guid = data.get("replyToGuid")
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reply_to_text = data.get("threadOriginatorText")
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reply_to_sender = data.get("threadOriginator")
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return format_reply_context(
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reply_to_message_id=reply_to_guid,
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reply_to_text=reply_to_text,
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reply_to_sender=reply_to_sender,
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)
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