mirror of
https://github.com/hansjone/oclaw.git
synced 2026-10-09 07:03:15 +08:00
694 lines
23 KiB
Python
694 lines
23 KiB
Python
from __future__ import annotations
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import os
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import re
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from dataclasses import dataclass
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from typing import Any
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GROUP_SESSION_USER_SENTINEL = "__group__"
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_NONSEND_REPLY_TEXTS = frozenset(
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{
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"(silent)",
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"[silent]",
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"no_reply",
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"no reply",
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"静默",
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}
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)
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def normalize_jid(jid: str) -> str:
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s = str(jid or "").strip().lower()
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if not s:
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return ""
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if "@" in s:
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user, domain = s.split("@", 1)
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user = user.split(":")[0]
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return f"{user}@{domain}"
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return s.split(":")[0]
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def jid_phone(jid: str) -> str:
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head = str(jid or "").strip().split("@", 1)[0]
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head = head.split(":", 1)[0]
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return re.sub(r"\D", "", head)
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def jid_base_local(jid: str) -> str:
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s = str(jid or "").strip().lower()
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if not s:
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return ""
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return s.split("@", 1)[0].split(":", 1)[0]
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def jids_same_user(a: str, b: str) -> bool:
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na = normalize_jid(a)
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nb = normalize_jid(b)
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if na and nb and na == nb:
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return True
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la = jid_base_local(a)
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lb = jid_base_local(b)
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if la and lb and la == lb:
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digits = re.sub(r"\D", "", la)
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if len(digits) >= 6:
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return True
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pa = jid_phone(a)
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pb = jid_phone(b)
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return len(pa) >= 6 and pa == pb
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def _bot_identity_jids(*, bot_jid: str | None, metadata: dict[str, Any] | None) -> list[str]:
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out: list[str] = []
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seen: set[str] = set()
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for candidate in [bot_jid]:
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s = str(candidate or "").strip()
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if s and s not in seen:
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seen.add(s)
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out.append(s)
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if isinstance(metadata, dict):
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for key in ("bot_lid", "botLid"):
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s = str(metadata.get(key) or "").strip()
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if s and s not in seen:
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seen.add(s)
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out.append(s)
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raw = _metadata_raw(metadata)
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for key in ("botLid", "bot_lid"):
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s = str(raw.get(key) or "").strip()
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if s and s not in seen:
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seen.add(s)
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out.append(s)
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return out
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def _metadata_raw(metadata: dict[str, Any] | None) -> dict[str, Any]:
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if not isinstance(metadata, dict):
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return {}
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raw = metadata.get("raw")
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return raw if isinstance(raw, dict) else {}
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def metadata_mentions_bot(metadata: dict[str, Any] | None) -> bool:
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"""Sidecar hint when WhatsApp omits mentionedJid (display-name @)."""
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if not isinstance(metadata, dict):
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return False
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if metadata.get("mentions_bot") is True or metadata.get("mentionsBot") is True:
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return True
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raw = _metadata_raw(metadata)
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return raw.get("mentionsBot") is True or raw.get("mentions_bot") is True
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def mentions_include_bot(
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*,
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mentions: list[str],
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bot_jid: str | None,
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metadata: dict[str, Any] | None = None,
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) -> bool:
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identities = _bot_identity_jids(bot_jid=bot_jid, metadata=metadata)
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if not identities:
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return False
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for raw in mentions or []:
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mention = str(raw or "").strip()
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if not mention:
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continue
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for identity in identities:
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if jids_same_user(mention, identity):
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return True
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return False
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def text_mentions_bot(*, text: str, bot_jid: str | None) -> bool:
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"""Fallback when WhatsApp omits mentionedJid but user visibly @-mentions the bot."""
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bot = str(bot_jid or "").strip()
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if not bot:
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return False
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phone = jid_phone(bot)
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if len(phone) < 6:
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return False
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body = str(text or "")
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if "@" not in body:
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return False
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digits_in_text = re.sub(r"\D", "", body)
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return phone in digits_in_text
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def is_reply_to_bot(*, metadata: dict[str, Any] | None, bot_jid: str | None) -> bool:
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raw = _metadata_raw(metadata)
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if raw.get("isReplyToBot") is True or raw.get("is_reply_to_bot") is True:
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return True
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quoted = ""
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if isinstance(metadata, dict):
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quoted = str(metadata.get("quoted_participant") or "").strip()
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if not quoted:
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quoted = str(raw.get("quotedParticipant") or raw.get("quoted_participant") or "").strip()
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bot = str(bot_jid or "").strip()
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if quoted and bot and jids_same_user(quoted, bot):
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return True
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return False
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def extract_quoted_ume_alert_text(*, metadata: dict[str, Any] | None) -> str:
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raw = _metadata_raw(metadata)
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quoted_text = str(raw.get("quotedText") or raw.get("quoted_text") or "").strip()
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if quoted_text and (quoted_text.startswith("[UME") or "[UME Alarm" in quoted_text[:120]):
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return quoted_text
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return ""
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def extract_group_quoted_message(*, metadata: dict[str, Any] | None) -> dict[str, str]:
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raw = _metadata_raw(metadata)
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quoted_text = str(raw.get("quotedText") or raw.get("quoted_text") or "").strip()
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quoted_participant = str(raw.get("quotedParticipant") or raw.get("quoted_participant") or "").strip()
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push_name = str(raw.get("quotedPushName") or raw.get("quoted_push_name") or "").strip()
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stanza_id = str(raw.get("quotedStanzaId") or raw.get("quoted_stanza_id") or "").strip()
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return {
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"quoted_text": quoted_text,
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"quoted_participant": quoted_participant,
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"quoted_push_name": push_name,
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"quoted_stanza_id": stanza_id,
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}
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def _normalize_quoted_compare_text(text: str) -> str:
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"""Normalize quote/history text for dedupe.
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WhatsApp reply-to often prefixes the bot body with ``@<lid|phone>``; session
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assistant rows usually do not. Strip those so same-session quotes match.
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"""
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s = str(text or "").strip()
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if not s:
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return ""
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# Drop leading @tokens (jid / phone / display-name mentions).
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s = re.sub(r"^(?:@\S+\s+)+", "", s)
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# Drop common group-ingest wrappers if somehow present.
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s = re.sub(r"^\[被引用消息\]\s*", "", s)
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s = re.sub(r"^\[Quoted message\]\s*", "", s, flags=re.IGNORECASE)
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s = re.sub(r"\s+", " ", s).strip()
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return s[:400]
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def _quoted_texts_overlap(quoted: str, history: str) -> bool:
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"""True when quote body is essentially the same as a history row."""
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q = _normalize_quoted_compare_text(quoted)
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h = _normalize_quoted_compare_text(history)
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if not q or not h:
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return False
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if q == h:
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return True
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q_fp = q[:160]
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h_fp = h[:160]
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if q_fp == h_fp:
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return True
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# Substantial containment only — avoid short-string false positives.
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min_len = 48
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if len(q_fp) >= min_len and q_fp in h:
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return True
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if len(h_fp) >= min_len and h_fp in q:
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return True
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if len(q) >= min_len and len(h) >= min_len:
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n = 0
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for a, b in zip(q_fp, h_fp):
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if a != b:
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break
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n += 1
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if n >= min_len:
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return True
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return False
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def should_inject_quoted_context(*, quoted_text: str, recent_messages: list[Any]) -> bool:
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"""Return False when quoted body already appears in recent session history.
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Prefer assistant rows (same-session bot replies). Also scan other roles as a
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fallback so previously injected ``[被引用消息]`` user rows still dedupe.
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"""
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token = _normalize_quoted_compare_text(quoted_text)
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if not token:
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return False
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assistants: list[Any] = []
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others: list[Any] = []
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for row in recent_messages or []:
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role = str(getattr(row, "role", "") or "").strip().lower()
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if role == "assistant":
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assistants.append(row)
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else:
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others.append(row)
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for row in assistants:
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if _quoted_texts_overlap(token, str(getattr(row, "content", "") or "")):
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return False
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for row in others:
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if _quoted_texts_overlap(token, str(getattr(row, "content", "") or "")):
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return False
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return True
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def build_group_quoted_context_block(*, metadata: dict[str, Any] | None, lang: str = "en") -> str:
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info = extract_group_quoted_message(metadata=metadata)
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quoted_text = str(info.get("quoted_text") or "").strip()
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if not quoted_text:
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return ""
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quoted_participant = str(info.get("quoted_participant") or "").strip()
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quoted_push_name = str(info.get("quoted_push_name") or "").strip()
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speaker = quoted_push_name or quoted_participant or "unknown"
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if str(lang or "").strip().lower().startswith("zh"):
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return f"[被引用消息]\n{speaker}: {quoted_text}"
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return f"[Quoted message]\n{speaker}: {quoted_text}"
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def enrich_alert_group_question(*, user_text: str, quoted_alert: str) -> str:
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body = str(user_text or "").strip()
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quote = str(quoted_alert or "").strip()
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if not quote:
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return body
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if not body:
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return f"[Quoted UME alarm]\n{quote}"
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return f"[Quoted UME alarm]\n{quote}\n\n[User question]\n{body}"
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def normalize_jids(jids: list[str]) -> set[str]:
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out: set[str] = set()
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for raw in jids or []:
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n = normalize_jid(raw)
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if n:
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out.add(n)
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return out
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def normalize_group_session_scope(raw: Any) -> str:
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scope = str(raw or "").strip().lower()
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if scope in {"chat", "shared", "shared_chat"}:
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return "chat"
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if scope in {"user", "user_in_chat", "per_user", "member"}:
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return "user_in_chat"
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return "user_in_chat"
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def session_user_key(*, is_group: bool, external_user_id: str, session_scope: str = "user_in_chat") -> str:
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if not is_group:
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return str(external_user_id or "").strip()
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if normalize_group_session_scope(session_scope) == "chat":
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return GROUP_SESSION_USER_SENTINEL
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return str(external_user_id or "").strip()
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def infer_is_group_from_chat_id(chat_id: str) -> bool:
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c = str(chat_id or "").strip().lower()
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return c.endswith("@g.us")
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def resolve_is_group(*, payload_is_group: bool, chat_id: str) -> bool:
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if payload_is_group:
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return True
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return infer_is_group_from_chat_id(chat_id)
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def is_nonsend_channel_reply_text(text: str) -> bool:
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t = str(text or "").strip()
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if not t:
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return True
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normalized = t.lower().replace("（", "(").replace("）", ")")
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if normalized in _NONSEND_REPLY_TEXTS:
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return True
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return bool(re.fullmatch(r"no_reply", normalized, flags=re.IGNORECASE))
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def should_send_channel_reply_text(text: str) -> bool:
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return not is_nonsend_channel_reply_text(text)
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@dataclass(frozen=True)
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class GroupPolicyConfig:
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require_mention: bool = True
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triggers: tuple[str, ...] = ("/oclaw",)
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session_scope: str = "user_in_chat"
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def _parse_bool_env(name: str, default: bool) -> bool:
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raw = str(os.environ.get(name) or "").strip().lower()
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if not raw:
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return default
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return raw not in {"0", "false", "no", "off"}
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def _parse_triggers_env(name: str, default: tuple[str, ...]) -> tuple[str, ...]:
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raw = str(os.environ.get(name) or "").strip()
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if not raw:
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return default
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parts = [p.strip() for p in raw.split(",") if p.strip()]
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return tuple(parts) if parts else default
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def _parse_group_policy_dict(raw: Any) -> GroupPolicyConfig | None:
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if not isinstance(raw, dict):
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return None
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require_mention = raw.get("require_mention")
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triggers_raw = raw.get("triggers")
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session_scope = raw.get("session_scope")
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triggers: tuple[str, ...] | None = None
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if isinstance(triggers_raw, list):
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triggers = tuple(str(x).strip() for x in triggers_raw if str(x).strip())
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return GroupPolicyConfig(
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require_mention=bool(require_mention) if require_mention is not None else True,
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triggers=triggers if triggers is not None else ("/oclaw",),
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session_scope=normalize_group_session_scope(session_scope),
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)
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def resolve_group_policy(*, account: dict[str, Any] | None = None) -> GroupPolicyConfig:
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"""Resolve group mention/session policy.
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Default ``session_scope`` is ``user_in_chat`` (per speaker in a group). Override via
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account ``group_policy.session_scope`` or env ``AIA_WHATSAPP_GROUP_SESSION_SCOPE=chat``
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when a shared group transcript is intentionally desired.
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"""
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cfg = (account or {}).get("config")
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if isinstance(cfg, dict):
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gp = _parse_group_policy_dict(cfg.get("group_policy"))
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if gp is not None:
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return gp
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gp = _parse_group_policy_dict(cfg.get("group"))
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if gp is not None:
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return gp
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return GroupPolicyConfig(
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require_mention=_parse_bool_env("AIA_WHATSAPP_GROUP_REQUIRE_MENTION", True),
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triggers=_parse_triggers_env("AIA_WHATSAPP_GROUP_TRIGGERS", ("/oclaw", "|oclaw")),
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session_scope=normalize_group_session_scope(os.environ.get("AIA_WHATSAPP_GROUP_SESSION_SCOPE")),
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)
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def should_process_group_inbound(
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*,
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is_group: bool,
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text: str,
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mentions: list[str],
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bot_jid: str | None,
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require_mention: bool = True,
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triggers: list[str] | tuple[str, ...] | None = None,
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metadata: dict[str, Any] | None = None,
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) -> bool:
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if not is_group:
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return True
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mentions_list = [str(m).strip() for m in (mentions or []) if str(m).strip()]
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trigger_list = [str(t) for t in (triggers or []) if str(t)]
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body = str(text or "")
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has_trigger = bool(trigger_list and any(t in body for t in trigger_list))
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bot_mentioned = mentions_include_bot(
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mentions=mentions_list,
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bot_jid=bot_jid,
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metadata=metadata,
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) or text_mentions_bot(text=text, bot_jid=bot_jid)
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# Multi-@: reply only when the bot is among mentionedJid; @ others alone stays silent.
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if mentions_list:
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if bot_mentioned:
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return True
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return has_trigger
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# Quote/reply-to-bot alone is not enough — require explicit @ or a trigger.
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if metadata_mentions_bot(metadata):
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return True
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if bot_mentioned:
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return True
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if has_trigger:
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return True
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return not require_mention
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def build_group_sender_context(
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*,
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metadata: dict[str, Any] | None,
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external_user_id: str,
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lang: str = "en",
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) -> str:
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meta = metadata if isinstance(metadata, dict) else {}
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raw = meta.get("raw") if isinstance(meta.get("raw"), dict) else {}
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push_name = str(raw.get("pushName") or meta.get("push_name") or meta.get("display_name") or "").strip()
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sender = str(external_user_id or "").strip()
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label = push_name or sender or "unknown"
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if str(lang or "").strip().lower().startswith("zh"):
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return f"[发言: {label}]"
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return f"[Sender: {label}]"
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def _mention_tokens_for_jids(jids: list[str]) -> list[str]:
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tokens: list[str] = []
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seen: set[str] = set()
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for jid in jids or []:
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local = jid_base_local(jid)
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if local:
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tok = f"@{local}"
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if tok.lower() not in seen:
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seen.add(tok.lower())
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tokens.append(tok)
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phone = jid_phone(jid)
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if phone and len(phone) >= 6:
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tok = f"@{phone}"
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if tok.lower() not in seen:
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seen.add(tok.lower())
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tokens.append(tok)
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return tokens
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def strip_bot_mentions_from_text(
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*,
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text: str,
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bot_jid: str | None,
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metadata: dict[str, Any] | None = None,
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) -> str:
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body = str(text or "")
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identities = _bot_identity_jids(bot_jid=bot_jid, metadata=metadata)
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tokens = _mention_tokens_for_jids(identities)
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extra_names: set[str] = set()
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if isinstance(metadata, dict):
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for name in (metadata.get("bot_push_name"), "oliver"):
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n = str(name or "").strip()
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if n:
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extra_names.add(n.lower())
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for token in sorted(tokens, key=len, reverse=True):
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body = re.sub(
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re.escape(token) + r"(?=\s|$|[，。！？!?,.])",
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"",
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body,
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flags=re.IGNORECASE,
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)
|
||
for name in sorted(extra_names, key=len, reverse=True):
|
||
body = re.sub(
|
||
rf"@{re.escape(name)}(?=\s|$|[，。！？!?,.])",
|
||
"",
|
||
body,
|
||
flags=re.IGNORECASE,
|
||
)
|
||
body = re.sub(r"\s{2,}", " ", body).strip()
|
||
return body
|
||
|
||
|
||
def _filter_non_bot_mention_jids(
|
||
mention_jids: list[str],
|
||
*,
|
||
bot_jid: str | None,
|
||
metadata: dict[str, Any] | None = None,
|
||
) -> list[str]:
|
||
identities = _bot_identity_jids(bot_jid=bot_jid, metadata=metadata)
|
||
out: list[str] = []
|
||
seen: set[str] = set()
|
||
for raw in mention_jids or []:
|
||
jid = str(raw or "").strip()
|
||
if not jid:
|
||
continue
|
||
if any(jids_same_user(jid, identity) for identity in identities):
|
||
continue
|
||
key = jid_base_local(jid) or jid.lower()
|
||
if key in seen:
|
||
continue
|
||
seen.add(key)
|
||
out.append(jid)
|
||
return out
|
||
|
||
|
||
def normalize_mentioned_users_in_text(
|
||
*,
|
||
text: str,
|
||
mention_jids: list[str],
|
||
mention_names: list[str] | None = None,
|
||
store: Any = None,
|
||
tenant_id: str = "",
|
||
account_id: str = "",
|
||
) -> str:
|
||
body = str(text or "")
|
||
names = [str(x or "").strip() for x in (mention_names or [])]
|
||
for idx, jid in enumerate(mention_jids or []):
|
||
jid_s = str(jid or "").strip()
|
||
if not jid_s:
|
||
continue
|
||
name = names[idx] if idx < len(names) and names[idx] else ""
|
||
if not name and store is not None:
|
||
from runtime.scheduler.whatsapp_mentions import _lookup_push_name
|
||
|
||
name = _lookup_push_name(
|
||
store,
|
||
tenant_id=str(tenant_id or ""),
|
||
account_id=str(account_id or ""),
|
||
jid=jid_s,
|
||
)
|
||
if not name:
|
||
local = jid_base_local(jid_s)
|
||
if local:
|
||
body = re.sub(
|
||
rf"@{re.escape(local)}(?=\s|$|[，。！？!?,.])",
|
||
"",
|
||
body,
|
||
)
|
||
continue
|
||
local = jid_base_local(jid_s)
|
||
if local:
|
||
body = re.sub(
|
||
rf"@{re.escape(local)}(?=\s|$|[，。！？!?,.])",
|
||
f"@{name}",
|
||
body,
|
||
)
|
||
phone = jid_phone(jid_s)
|
||
if phone and len(phone) >= 6:
|
||
body = re.sub(
|
||
rf"@{re.escape(phone)}(?=\s|$|[，。！？!?,.])",
|
||
f"@{name}",
|
||
body,
|
||
)
|
||
body = re.sub(r"\s{2,}", " ", body).strip()
|
||
return body
|
||
|
||
|
||
def prepare_group_user_text_for_model(
|
||
*,
|
||
text: str,
|
||
metadata: dict[str, Any] | None,
|
||
mentions: list[str],
|
||
bot_jid: str | None,
|
||
session_scope: str,
|
||
external_user_id: str,
|
||
filtered_mention_jids: list[str] | None = None,
|
||
mention_names: list[str] | None = None,
|
||
store: Any = None,
|
||
tenant_id: str = "",
|
||
account_id: str = "",
|
||
quoted_ctx: str = "",
|
||
lang: str = "en",
|
||
) -> str:
|
||
body = str(text or "").strip()
|
||
body = strip_bot_mentions_from_text(text=body, bot_jid=bot_jid, metadata=metadata)
|
||
target_jids = (
|
||
filtered_mention_jids
|
||
if filtered_mention_jids is not None
|
||
else _filter_non_bot_mention_jids(list(mentions or []), bot_jid=bot_jid, metadata=metadata)
|
||
)
|
||
body = normalize_mentioned_users_in_text(
|
||
text=body,
|
||
mention_jids=target_jids,
|
||
mention_names=mention_names,
|
||
store=store,
|
||
tenant_id=tenant_id,
|
||
account_id=account_id,
|
||
)
|
||
prefix_parts: list[str] = []
|
||
# Shared group transcript only: tag speaker so multi-member history cannot 串话.
|
||
# Per-user group sessions (user_in_chat) already isolate by session — skip the prefix.
|
||
if normalize_group_session_scope(session_scope) == "chat":
|
||
prefix_parts.append(
|
||
build_group_sender_context(metadata=metadata, external_user_id=external_user_id, lang=lang)
|
||
)
|
||
quote = str(quoted_ctx or "").strip()
|
||
if quote:
|
||
prefix_parts.append(quote)
|
||
prefix = "\n".join(part for part in prefix_parts if str(part).strip())
|
||
if prefix and body:
|
||
return f"{prefix}\n{body}"
|
||
return prefix or body
|
||
|
||
|
||
def build_group_focus_instruction(*, lang: str = "en") -> str:
|
||
"""Isolation hint for *shared* group transcripts (session_scope=chat)."""
|
||
if str(lang or "").strip().lower().startswith("zh"):
|
||
return (
|
||
"[群聊规则（共享会话）：只回答当前发言人（见 [发言: …]）的问题；"
|
||
"除非本条消息明确引用或承接前文，否则不要默认继承其他群成员的上下文；"
|
||
"若排队合并了多条跟进，按条分别回应并 @ 对应发言人。]"
|
||
)
|
||
return (
|
||
"[Shared group-chat rule: answer only the current sender (see [Sender: …]). "
|
||
"Do not assume context from other members unless this message explicitly quotes or references it. "
|
||
"If several follow-ups were merged while busy, answer each item and @ the matching sender.]"
|
||
)
|
||
|
||
|
||
def build_channel_file_delivery_instruction(*, lang: str = "en") -> str:
|
||
if str(lang or "").strip().lower().startswith("zh"):
|
||
return (
|
||
"[渠道规则：若要把生成的附件发回用户（WhatsApp/微信，含文档/图片/视频），"
|
||
"必须调用 save_deliverable_attachment（path 或 attachment_id）；"
|
||
"write_file、run_command、生图工具 alone 不会随消息发送附件。]"
|
||
)
|
||
return (
|
||
"[Channel rule: to send any generated attachment back to the user on WhatsApp/WeChat "
|
||
"(documents, images, videos), call save_deliverable_attachment with path or attachment_id. "
|
||
"write_file, run_command, and image generation alone do not attach files to the outbound message.]"
|
||
)
|
||
|
||
|
||
def build_whatsapp_group_reply_metadata(
|
||
*,
|
||
inbound: Any,
|
||
) -> dict[str, Any]:
|
||
"""Outbound hints for WhatsApp sidecar: @ sender + quote original message."""
|
||
meta = inbound.metadata if isinstance(getattr(inbound, "metadata", None), dict) else {}
|
||
raw = meta.get("raw") if isinstance(meta.get("raw"), dict) else {}
|
||
sender_jid = str(getattr(inbound, "external_user_id", "") or "").strip()
|
||
chat_id = str(getattr(inbound, "external_chat_id", "") or "").strip()
|
||
participant_raw = str(raw.get("participant") or sender_jid or "").strip()
|
||
stanza_id = str(raw.get("id") or meta.get("message_id") or "").strip()
|
||
quote_text = str(getattr(inbound, "text", "") or "").strip()
|
||
push_name = str(raw.get("pushName") or meta.get("push_name") or "").strip()
|
||
out: dict[str, Any] = {
|
||
"is_group": True,
|
||
"reply_to_user_id": participant_raw or normalize_jid(sender_jid),
|
||
"mention_jids": [participant_raw] if participant_raw else ([normalize_jid(sender_jid)] if sender_jid else []),
|
||
"quote_remote_jid": chat_id,
|
||
"quote_stanza_id": stanza_id,
|
||
"quote_participant": participant_raw or normalize_jid(str(raw.get("participant") or sender_jid or "")),
|
||
"quote_text": quote_text,
|
||
}
|
||
if push_name:
|
||
out["quote_push_name"] = push_name
|
||
out["mention_names"] = [push_name]
|
||
return out
|
||
|
||
|
||
__all__ = [
|
||
"GROUP_SESSION_USER_SENTINEL",
|
||
"GroupPolicyConfig",
|
||
"build_channel_file_delivery_instruction",
|
||
"build_group_sender_context",
|
||
"build_group_focus_instruction",
|
||
"build_group_quoted_context_block",
|
||
"build_whatsapp_group_reply_metadata",
|
||
"enrich_alert_group_question",
|
||
"extract_group_quoted_message",
|
||
"extract_quoted_ume_alert_text",
|
||
"mentions_include_bot",
|
||
"metadata_mentions_bot",
|
||
"normalize_mentioned_users_in_text",
|
||
"normalize_jid",
|
||
"normalize_group_session_scope",
|
||
"normalize_jids",
|
||
"prepare_group_user_text_for_model",
|
||
"strip_bot_mentions_from_text",
|
||
"infer_is_group_from_chat_id",
|
||
"is_nonsend_channel_reply_text",
|
||
"resolve_is_group",
|
||
"resolve_group_policy",
|
||
"session_user_key",
|
||
"should_inject_quoted_context",
|
||
"should_process_group_inbound",
|
||
"should_send_channel_reply_text",
|
||
"text_mentions_bot",
|
||
]
|