Kris
043e75d787
新增 RocketChat 渠道扩展，支持在 Yuxi 平台中集成 RocketChat 团队协作平台。 包含以下功能模块： - client: RocketChat API 客户端封装 - config: 渠道配置管理 - gateway: SSE/WebSocket 网关接入 - websocket: WebSocket 实时连接 - webhook: Webhook 事件处理 - outbound: 外发消息管理 - streaming: 流式消息处理 - pairing: 用户配对与绑定 - security: 安全校验 - dedup: 消息去重 - monitor: 渠道状态监控 - status: 会话状态管理 - session: 会话管理 - gating: 门控管理 - threading: 线程管理 - reactions: 表情反应 - types: 类型定义
78 lines
2.2 KiB
Python
78 lines
2.2 KiB
Python
from __future__ import annotations
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ROCKETCHAT_TEXT_LIMIT = 4000
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def markdown_to_rocketchat(md_text: str) -> str:
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return md_text.strip()
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def strip_markdown_to_plain(md_text: str, max_chars: int = ROCKETCHAT_TEXT_LIMIT) -> str:
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text = md_text.strip()
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if len(text) > max_chars:
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text = text[: max_chars - 3] + "..."
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return text
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def safe_split_markdown(text: str, chunk_limit: int = ROCKETCHAT_TEXT_LIMIT) -> list[str]:
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if len(text) <= chunk_limit:
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return [text]
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chunks: list[str] = []
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remaining = text
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while len(remaining) > chunk_limit:
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split_at = _find_paragraph_break(remaining, chunk_limit)
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chunks.append(remaining[:split_at].strip())
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remaining = remaining[split_at:].strip()
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if remaining:
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chunks.append(remaining)
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return chunks
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def _find_paragraph_break(text: str, limit: int) -> int:
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search_text = text[:limit]
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for sep in ["\n\n", "\n"]:
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idx = search_text.rfind(sep)
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if idx > limit * 0.3:
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return idx + len(sep)
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last_space = search_text.rfind(" ")
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if last_space > limit * 0.7:
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return last_space + 1
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return limit
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def truncate_markdown(text: str, max_chars: int = ROCKETCHAT_TEXT_LIMIT) -> str:
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if len(text) <= max_chars:
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return text
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return text[: max_chars - 3] + "..."
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def chunk_text(text: str, chunk_limit: int = ROCKETCHAT_TEXT_LIMIT) -> list[str]:
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return safe_split_markdown(text, chunk_limit)
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def normalize_message(text: str, bot_username: str | None = None) -> str:
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result = text.strip()
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if bot_username:
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patterns = [f"@{bot_username}", f"@{bot_username.lower()}"]
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for pattern in patterns:
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result = _strip_mention(result, pattern)
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return result
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def _strip_mention(text: str, mention: str) -> str:
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result = text.replace(mention, "").strip()
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for part in mention.split():
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result = result.replace(part, "").strip()
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return result.strip()
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def extract_onchar_content(text: str, prefixes: list[str]) -> str | None:
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stripped = text.strip()
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for prefix in prefixes:
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if stripped.startswith(prefix):
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return stripped[len(prefix) :].strip()
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return None
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