312 lines
8.4 KiB
Python
312 lines
8.4 KiB
Python
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"""
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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，
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与 max_tokens、max_chars_per_segment 联动；单一 ReplyPlan 供 prompt 与截断共用。
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from enum import Enum
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from typing import TYPE_CHECKING
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from app.agents.chat.background_voice import normalize_background_voice
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if TYPE_CHECKING:
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from app.core.config import Settings
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class ReplyLengthMode(str, Enum):
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"""brief：极短；standard：默认；expanded：值得展开承接时稍长。"""
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brief = "brief"
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standard = "standard"
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expanded = "expanded"
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# 用户本轮字符数分桶（strip 后按 len，中文友好）
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_LEN_BRIEF_MAX = 20
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_LEN_MID_EXPAND_MIN = 40
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_LEN_LONG_MIN = 80
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def heuristic_likely_new_detail(user_message: str) -> bool:
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"""
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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）。
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"""
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m = (user_message or "").strip()
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if len(m) < 2:
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return False
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needles = (
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"叫",
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"名字",
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"名叫",
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"同桌",
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"初恋",
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"现实里",
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"戏里",
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"饰演",
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"演我",
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"第一次",
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"认识",
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"没想到",
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"猜猜",
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)
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return any(n in m for n in needles)
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def heuristic_information_rich(user_message: str) -> bool:
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"""
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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。
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"""
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m = (user_message or "").strip()
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if len(m) < 2:
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return False
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needles = (
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"突然",
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"那年",
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"后来",
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"记得",
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"第一次",
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"没想到",
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"离开",
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"去世",
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"走了",
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"结婚",
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"离婚",
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"生病",
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"辍学",
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"退学",
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"下岗",
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"破产",
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"我爸",
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"我妈",
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"爷爷",
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"奶奶",
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)
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return any(n in m for n in needles)
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def heuristic_likely_emotional(user_message: str) -> bool:
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"""
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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）。
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"""
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m = (user_message or "").strip()
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if len(m) < 4:
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return False
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needles = (
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"想哭",
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"哭了",
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"难过",
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"伤心",
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"心酸",
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"感动",
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"激动",
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"害怕",
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"委屈",
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"后悔",
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"对不起",
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"愧疚",
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"感激",
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"谢谢你",
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"想念",
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"想他",
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"想她",
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"舍不得",
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"不容易",
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"太难了",
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"崩溃",
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"绝望",
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"幸福",
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"骄傲",
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"自豪",
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)
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return any(n in m for n in needles)
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def heuristic_likely_chit_chat(user_message: str) -> bool:
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"""
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轻量启发：本轮是否偏闲聊（放宽长句里纯寒暄/天气类）。
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"""
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m = (user_message or "").strip()
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if len(m) > 200:
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return False
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needles_short = (
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"天气",
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"谢谢",
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"哈哈",
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"呵呵",
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"在吗",
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"吃了吗",
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"早上好",
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"晚安",
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"闲聊",
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"逗你",
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)
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if len(m) > 48:
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head = m[:100]
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if any(n in head for n in needles_short):
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if not heuristic_information_rich(m) and not heuristic_likely_new_detail(m):
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return True
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return False
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if any(n in m for n in needles_short):
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return True
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if len(m) <= 8 and m in ("嗯", "好", "行的", "谢谢", "哈哈", "可以", "没事"):
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return True
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return False
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@dataclass(frozen=True)
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class ReplyPlan:
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"""单一计划：prompt 展示档位与数值上限一致（含背景语气微调）。"""
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mode: ReplyLengthMode
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max_tokens: int
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max_chars_per_segment: int
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max_segments: int
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likely_new_detail: bool
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likely_chit_chat: bool
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information_rich: bool
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def compute_reply_plan(
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user_message: str,
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*,
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background_voice: str | None,
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settings: "Settings",
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) -> ReplyPlan:
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"""
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信息量与情绪优先，字数次之：
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- 短输入且无新信息、无情绪 → brief
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- 短输入但有新细节/高密度/强情绪 → standard
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- 中段（40-79）有实质/情绪 → expanded（给足承接空间）
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- 中段无实质 → standard
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- 长输入：闲聊为主 → standard；有展开价值 → expanded
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"""
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norm = (user_message or "").strip()
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n = max(0, len(norm))
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max_segments = int(settings.chat_interview_max_segments)
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likely_new = heuristic_likely_new_detail(norm)
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likely_chit = heuristic_likely_chit_chat(norm)
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info_rich = heuristic_information_rich(norm)
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emotional = heuristic_likely_emotional(norm)
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substantive = likely_new or info_rich or emotional
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def _mk(m: ReplyLengthMode) -> ReplyPlan:
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return _plan_from_mode(
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m,
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max_segments=max_segments,
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settings=settings,
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background_voice=background_voice,
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likely_new=likely_new,
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likely_chit=likely_chit,
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info_rich=info_rich,
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)
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if likely_chit and not substantive:
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return _mk(
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ReplyLengthMode.brief if n <= _LEN_BRIEF_MAX else ReplyLengthMode.standard
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)
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if n <= _LEN_BRIEF_MAX:
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return _mk(ReplyLengthMode.standard if substantive else ReplyLengthMode.brief)
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if n < _LEN_MID_EXPAND_MIN:
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return _mk(ReplyLengthMode.standard)
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if n < _LEN_LONG_MIN:
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return _mk(
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ReplyLengthMode.expanded if substantive else ReplyLengthMode.standard
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)
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return _mk(ReplyLengthMode.expanded if substantive else ReplyLengthMode.standard)
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def _plan_from_mode(
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mode: ReplyLengthMode,
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*,
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max_segments: int,
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settings: "Settings",
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background_voice: str | None,
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likely_new: bool,
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likely_chit: bool,
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info_rich: bool,
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) -> ReplyPlan:
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if mode == ReplyLengthMode.brief:
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base = ReplyPlan(
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mode=mode,
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max_tokens=int(settings.chat_interview_brief_max_tokens),
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max_chars_per_segment=int(
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settings.chat_interview_brief_max_chars_per_segment
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),
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max_segments=max_segments,
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likely_new_detail=likely_new,
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likely_chit_chat=likely_chit,
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information_rich=info_rich,
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)
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elif mode == ReplyLengthMode.expanded:
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base = ReplyPlan(
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mode=mode,
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max_tokens=int(settings.chat_interview_expanded_max_tokens),
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max_chars_per_segment=int(
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settings.chat_interview_expanded_max_chars_per_segment
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),
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max_segments=max_segments,
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likely_new_detail=likely_new,
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likely_chit_chat=likely_chit,
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information_rich=info_rich,
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)
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else:
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base = ReplyPlan(
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mode=ReplyLengthMode.standard,
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max_tokens=int(settings.chat_interview_max_tokens),
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max_chars_per_segment=int(settings.chat_interview_max_chars_per_segment),
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max_segments=max_segments,
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likely_new_detail=likely_new,
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likely_chit_chat=likely_chit,
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information_rich=info_rich,
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)
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return bump_reply_plan_for_background_voice(
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base, background_voice=background_voice, settings=settings
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)
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def bump_reply_plan_for_background_voice(
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plan: ReplyPlan,
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*,
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background_voice: str | None,
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settings: "Settings",
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) -> ReplyPlan:
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"""
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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）。
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"""
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if normalize_background_voice(background_voice) == "default":
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return plan
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if plan.mode != ReplyLengthMode.standard:
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return plan
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extra_t = int(
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getattr(
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settings,
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"chat_interview_cadre_military_standard_extra_tokens",
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0,
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)
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)
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extra_c = int(
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getattr(
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settings,
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"chat_interview_cadre_military_standard_extra_chars",
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0,
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)
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)
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return ReplyPlan(
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mode=plan.mode,
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max_tokens=plan.max_tokens + extra_t,
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max_chars_per_segment=plan.max_chars_per_segment + extra_c,
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max_segments=plan.max_segments,
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likely_new_detail=plan.likely_new_detail,
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likely_chit_chat=plan.likely_chit_chat,
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information_rich=plan.information_rich,
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)
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