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feat(chat): 低信息短答主动续话；修复本地 dev 环境与迁移链

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- interview_turn_plan: 识别低信息短回复，引导 AI 承接后主动追问新话题
- development.sh / docker-compose.dev: Postgres/Redis 端口与 .env 对齐，补充宿主机端口监听检查
- Alembic: 补回 0016 memory pipeline status、0017 segment narrative defer
- app-expo: api/ws URL 去掉末尾斜杠，避免 WS 双斜杠；更新 .env.staging

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
Kevin
2026-05-11 12:06:17 +08:00
parent 55cfbc7f80
commit 705fe951b3
8 changed files with 427 additions and 15 deletions
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121
api/app/agents/chat/interview_turn_plan.py
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@@ -14,7 +14,7 @@ from dataclasses import dataclass
from typing import Literal
from app.agents.chat.prompts_conversation import SLOT_NAME_MAP
from app.agents.stage_constants import STAGE_SLOT_KEYS
from app.agents.stage_constants import STAGE_KEYWORD_WEIGHTS, STAGE_SLOT_KEYS
InterviewTurnMode = Literal[
"emotion_first",
@@ -66,6 +66,7 @@ class InterviewTurnPlan:
secondary_focus: FocusPrimary | None = None
focus_summary: str = ""
focus_source: FocusSource = "rule"
low_information_reply: bool = False
# ---- 语义属性：供 prompt_layers / interview_agent 等调用方消费，禁止重复立法 ----
@@ -323,6 +324,17 @@ _ASSISTANT_IDENTITY_QUESTION_MARKERS: tuple[str, ...] = (
"你也是",
)
_LOW_INFORMATION_REPLY_MAX_CHARS = 8
_LOW_INFORMATION_REPLY_CHARS: frozenset[str] = frozenset(
# 这不是短语白名单，而是一组低信息的应声/确认/语气字符。
# 只要短回复里出现不在此集合中的字，就会被视为有潜在叙事信号。
"嗯唔呃哦噢喔啊呀呢嘛吧哈"
"对是的了好行可允许以"
"没错确实不否无有还太很挺就"
"什么这样那样当当然"
)
_ACK_STRIP_CHARS = " \t\r\n，。！？!?、,.；;：:~～…"
def _is_emotion_heavy(text: str) -> bool:
t = (text or "").strip()
@@ -351,6 +363,32 @@ def _is_ambiguous_or_needs_slow_pace(text: str) -> bool:
return False
def _normalized_short_reply(text: str) -> str:
return "".join(ch for ch in (text or "").strip() if ch not in _ACK_STRIP_CHARS)
def _has_substantive_short_reply_signal(compact: str) -> bool:
"""短回复里的叙事实质信号：地点/人事词、阶段关键词、年份数字等。"""
if any(ch.isdigit() for ch in compact):
return True
if any(("a" <= ch.lower() <= "z") for ch in compact):
return True
for weighted_keywords in STAGE_KEYWORD_WEIGHTS.values():
if any(keyword and keyword in compact for keyword, _ in weighted_keywords):
return True
return any(ch not in _LOW_INFORMATION_REPLY_CHARS for ch in compact)
def _is_low_information_reply(text: str) -> bool:
"""识别短、低信息、没有新增叙事素材的确认/应声回复。"""
compact = _normalized_short_reply(text)
if not compact:
return False
if len(compact) > _LOW_INFORMATION_REPLY_MAX_CHARS:
return False
return not _has_substantive_short_reply_signal(compact)
def _is_too_vague_for_memoir_push(text: str) -> bool:
"""过短或仍含糊时，不进入 memoir_push。"""
t = (text or "").strip()
@@ -396,6 +434,7 @@ def plan_interview_turn(
)
um = (normalized_user_message or "").strip()
asks_assistant_identity = _is_asking_assistant_identity_or_life(um)
low_information_reply = _is_low_information_reply(um)
reply_shape: ReplyShape = "flexible"
if any(
k in um
@@ -403,6 +442,45 @@ def plan_interview_turn(
):
reply_shape = "ack_then_question"
if low_information_reply:
slot = primary_empty_slot(current_stage, empty_slots)
if slot:
readable = SLOT_NAME_MAP.get(slot, slot)
return InterviewTurnPlan(
mode="memoir_push",
anchor_slot_key=slot,
anchor_slot_readable=readable,
anchor_snippet=snippet,
anchor_source_kind=anchor_source_kind,
assistant_identity_question=asks_assistant_identity,
memory_usage=mem_use,
reply_shape="ack_then_question",
primary_focus=_focus_primary_for_mode("memoir_push"),
focus_summary=(
f"用户只做了简短确认；短接一句后，不澄清“{um}”，"
f"主动从「{readable}」打开一个具体、好回答的新回忆话题"
),
focus_source="rule",
low_information_reply=True,
)
return InterviewTurnPlan(
mode="follow_user_only",
anchor_slot_key=None,
anchor_slot_readable="（本阶段主要叙述槽已有素材）请回到上文最近的人/事/地方或情绪线，主动打开一个纵深问题",
anchor_snippet=snippet,
anchor_source_kind=anchor_source_kind,
assistant_identity_question=asks_assistant_identity,
memory_usage=mem_use,
reply_shape="ack_then_question",
primary_focus=_focus_primary_for_mode("follow_user_only"),
focus_summary=(
f"用户只做了简短确认；短接一句后，不澄清“{um}”，"
"回到上文最近的具体线索，主动递一个新的回忆追问"
),
focus_source="rule",
low_information_reply=True,
)
if _is_emotion_heavy(normalized_user_message):
slot = primary_empty_slot(current_stage, empty_slots)
readable = (
@@ -534,6 +612,17 @@ def format_interview_turn_directive_block(plan: InterviewTurnPlan) -> str:
else:
shape_block = ""
ack_block = ""
if plan.low_information_reply:
ack_block = (
"- **低信息短回复处理**：用户本轮只是简短确认、应声或泛泛回应，没有新增叙事素材。"
"不要把这个短答本身当成需要澄清的内容，不要反复追问「你是说……吗」，"
"也不要停在原地等用户继续补充。\n"
"- 先用半句自然接住，再主动从「主追问方向」、上文最近的具体人/事/地方，"
"或过往记忆线索里挑一个**具体、好回答**的新回忆话题；若挂钩线索为空，"
"允许直接借当前阶段未聊方向起问，但禁止编造用户没说过的细节。\n"
)
if plan.mode == "emotion_first":
mode_rules = (
"- **情绪优先**：本轮以承接、并肩与安全感为主，**不要**为推进「叙述槽大纲」而追加信息搜集型追问。\n"
@@ -557,13 +646,29 @@ def format_interview_turn_directive_block(plan: InterviewTurnPlan) -> str:
"- **跟话头**：本轮禁止问卷式首开、禁止重启式盘点；顺着用户刚展开的画面、人物或情绪自然往下。\n"
"- 若带问句，最多**一个**，且必须**从用户原词或下面摘录**长出来，禁止空泛「还有吗」。"
)
if plan.low_information_reply:
mode_rules = (
"- **跟话头 + 主动续话**：用户本轮只是简短确认，没有新素材；"
"不要围着短答本身澄清，也不要重复上一问等对方补充。\n"
"- 若带问句，最多**一个**，优先从上文最近的具体人/事/地方或下面摘录长出来；"
"若无可用摘录，就从当前阶段已聊内容的纵深处打开一个新回忆话题。"
)
else:
mode_rules = (
"- **回忆推进（memoir_push）**：对用户可见回复中须有**恰好一个**开放式回忆追问，\n"
" 且意图明显在补足下面「主追问方向」；问句必须挂住**用户本轮原词**或**挂钩摘录**（二者至少其一，且**优先原词**）。\n"
"- **禁止**把用户仍含糊的表达改写成确定事实或关系；禁止用日常寒暄替代该追问；"
"仍遵守全篇「最多一个问句」「禁止晚会硬切」。"
)
if plan.low_information_reply:
mode_rules = (
"- **回忆推进（memoir_push）**：用户本轮只是简短确认，"
"对用户可见回复中须有**恰好一个**开放式回忆追问，主动把话头往下递。\n"
" 追问可挂住**上文最近具体细节**、**主追问方向**或**挂钩摘录**；"
"不要要求从低信息短答里抽词。\n"
"- 禁止用日常寒暄替代该追问；仍遵守全篇「最多一个问句」「禁止晚会硬切」。"
)
else:
mode_rules = (
"- **回忆推进（memoir_push）**：对用户可见回复中须有**恰好一个**开放式回忆追问，\n"
" 且意图明显在补足下面「主追问方向」；问句必须挂住**用户本轮原词**或**挂钩摘录**（二者至少其一，且**优先原词**）。\n"
"- **禁止**把用户仍含糊的表达改写成确定事实或关系；禁止用日常寒暄替代该追问；"
"仍遵守全篇「最多一个问句」「禁止晚会硬切」。"
)
focus_block = _focus_directive_lines(plan)
@@ -576,7 +681,7 @@ def format_interview_turn_directive_block(plan: InterviewTurnPlan) -> str:
return f"""## 本轮编排指令（硬规则，优先于后文一般性建议）
{mode_rules}
{focus_block}{mem_block}{perspective_block}{shape_block}- **主追问方向（叙述槽）**：{plan.anchor_slot_readable}
{focus_block}{ack_block}{mem_block}{perspective_block}{shape_block}- **主追问方向（叙述槽）**：{plan.anchor_slot_readable}
- **挂钩线索**{anchor_label}：{snippet_line}
"""