""" 访谈回复长度：由用户本轮文本 + 启发式（新细节 / 闲聊 / 信息密度）决定档位， 与 max_tokens、max_chars_per_segment 联动；单一 ReplyPlan 供 prompt 与截断共用。 """ from __future__ import annotations from dataclasses import dataclass from enum import Enum from typing import TYPE_CHECKING from app.agents.chat.background_voice import normalize_background_voice if TYPE_CHECKING: from app.core.config import Settings class ReplyLengthMode(str, Enum): """brief：极短；standard：默认；expanded：值得展开承接时稍长。""" brief = "brief" standard = "standard" expanded = "expanded" # 用户本轮字符数分桶（strip 后按 len，中文友好） _LEN_BRIEF_MAX = 20 _LEN_MID_EXPAND_MIN = 40 _LEN_LONG_MIN = 80 def heuristic_likely_new_detail(user_message: str) -> bool: """ 轻量启发：本轮是否很可能补充了新人名、新关系或新情节（追问触发与长度共用）。 """ m = (user_message or "").strip() if len(m) < 2: return False needles = ( "叫", "名字", "名叫", "同桌", "初恋", "现实里", "戏里", "饰演", "演我", "第一次", "认识", "没想到", "猜猜", ) return any(n in m for n in needles) def heuristic_information_rich(user_message: str) -> bool: """ 轻量启发：短句也可能信息密度高（新转折、重大事件、时间锚点），用于避免误压成 brief。 """ m = (user_message or "").strip() if len(m) < 2: return False needles = ( "突然", "那年", "后来", "记得", "第一次", "没想到", "离开", "去世", "走了", "结婚", "离婚", "生病", "辍学", "退学", "下岗", "破产", "我爸", "我妈", "爷爷", "奶奶", ) return any(n in m for n in needles) def heuristic_likely_emotional(user_message: str) -> bool: """ 轻量启发：用户本轮是否在表达较强情绪（需要更多承接空间、不应被压成 brief）。 """ m = (user_message or "").strip() if len(m) < 4: return False needles = ( "想哭", "哭了", "难过", "伤心", "心酸", "感动", "激动", "害怕", "委屈", "后悔", "对不起", "愧疚", "感激", "谢谢你", "想念", "想他", "想她", "舍不得", "不容易", "太难了", "崩溃", "绝望", "幸福", "骄傲", "自豪", ) return any(n in m for n in needles) def heuristic_likely_chit_chat(user_message: str) -> bool: """ 轻量启发：本轮是否偏闲聊（放宽长句里纯寒暄/天气类）。 """ m = (user_message or "").strip() if len(m) > 200: return False needles_short = ( "天气", "谢谢", "哈哈", "呵呵", "在吗", "吃了吗", "早上好", "晚安", "闲聊", "逗你", ) if len(m) > 48: head = m[:100] if any(n in head for n in needles_short): if not heuristic_information_rich(m) and not heuristic_likely_new_detail(m): return True return False if any(n in m for n in needles_short): return True if len(m) <= 8 and m in ("嗯", "好", "行的", "谢谢", "哈哈", "可以", "没事"): return True return False @dataclass(frozen=True) class ReplyPlan: """单一计划：prompt 展示档位与数值上限一致（含背景语气微调）。""" mode: ReplyLengthMode max_tokens: int max_chars_per_segment: int max_segments: int likely_new_detail: bool likely_chit_chat: bool information_rich: bool def compute_reply_plan( user_message: str, *, background_voice: str | None, settings: "Settings", ) -> ReplyPlan: """ 信息量与情绪优先，字数次之： - 短输入且无新信息、无情绪 → brief - 短输入但有新细节/高密度/强情绪 → standard - 中段（40-79）有实质/情绪 → expanded（给足承接空间） - 中段无实质 → standard - 长输入：闲聊为主 → standard；有展开价值 → expanded """ norm = (user_message or "").strip() n = max(0, len(norm)) max_segments = int(settings.chat_interview_max_segments) likely_new = heuristic_likely_new_detail(norm) likely_chit = heuristic_likely_chit_chat(norm) info_rich = heuristic_information_rich(norm) emotional = heuristic_likely_emotional(norm) substantive = likely_new or info_rich or emotional def _mk(m: ReplyLengthMode) -> ReplyPlan: return _plan_from_mode( m, max_segments=max_segments, settings=settings, background_voice=background_voice, likely_new=likely_new, likely_chit=likely_chit, info_rich=info_rich, ) if likely_chit and not substantive: return _mk( ReplyLengthMode.brief if n <= _LEN_BRIEF_MAX else ReplyLengthMode.standard ) if n <= _LEN_BRIEF_MAX: return _mk(ReplyLengthMode.standard if substantive else ReplyLengthMode.brief) if n < _LEN_MID_EXPAND_MIN: return _mk(ReplyLengthMode.standard) if n < _LEN_LONG_MIN: return _mk( ReplyLengthMode.expanded if substantive else ReplyLengthMode.standard ) return _mk(ReplyLengthMode.expanded if substantive else ReplyLengthMode.standard) def _plan_from_mode( mode: ReplyLengthMode, *, max_segments: int, settings: "Settings", background_voice: str | None, likely_new: bool, likely_chit: bool, info_rich: bool, ) -> ReplyPlan: if mode == ReplyLengthMode.brief: base = ReplyPlan( mode=mode, max_tokens=int(settings.chat_interview_brief_max_tokens), max_chars_per_segment=int( settings.chat_interview_brief_max_chars_per_segment ), max_segments=max_segments, likely_new_detail=likely_new, likely_chit_chat=likely_chit, information_rich=info_rich, ) elif mode == ReplyLengthMode.expanded: base = ReplyPlan( mode=mode, max_tokens=int(settings.chat_interview_expanded_max_tokens), max_chars_per_segment=int( settings.chat_interview_expanded_max_chars_per_segment ), max_segments=max_segments, likely_new_detail=likely_new, likely_chit_chat=likely_chit, information_rich=info_rich, ) else: base = ReplyPlan( mode=ReplyLengthMode.standard, max_tokens=int(settings.chat_interview_max_tokens), max_chars_per_segment=int(settings.chat_interview_max_chars_per_segment), max_segments=max_segments, likely_new_detail=likely_new, likely_chit_chat=likely_chit, information_rich=info_rich, ) return bump_reply_plan_for_background_voice( base, background_voice=background_voice, settings=settings ) def bump_reply_plan_for_background_voice( plan: ReplyPlan, *, background_voice: str | None, settings: "Settings", ) -> ReplyPlan: """ 干部/军队背景时，仅对 standard 档小幅提高 token 与单段字数；**展示档位不变**（仍为 standard）。 """ if normalize_background_voice(background_voice) == "default": return plan if plan.mode != ReplyLengthMode.standard: return plan extra_t = int( getattr( settings, "chat_interview_cadre_military_standard_extra_tokens", 0, ) ) extra_c = int( getattr( settings, "chat_interview_cadre_military_standard_extra_chars", 0, ) ) return ReplyPlan( mode=plan.mode, max_tokens=plan.max_tokens + extra_t, max_chars_per_segment=plan.max_chars_per_segment + extra_c, max_segments=plan.max_segments, likely_new_detail=plan.likely_new_detail, likely_chit_chat=plan.likely_chit_chat, information_rich=plan.information_rich, )