53e0065e3e
配置 SSOT（TOML + .env） 统一错误契约 Auth 与事务边界 Redis / Celery 可靠性:业务 Redis（DB/0）与 Celery broker/backend（DB/1）显式拆分；连接池、sync client 可观测性（OpenTelemetry + LGTM）
215 lines
6.3 KiB
Python
215 lines
6.3 KiB
Python
"""
|
||
访谈聊天：先检索、后筛选、再限量注入。
|
||
|
||
检索结果不等于注入内容：主 prompt 只收极短「线索」，TurnPlan 挂钩优先用户原话；
|
||
完整 bundle 仅给 reply_planner 做焦点规划（可选）。
|
||
"""
|
||
|
||
from __future__ import annotations
|
||
|
||
from dataclasses import dataclass
|
||
from typing import Any
|
||
|
||
from app.features.conversation.constants import chat
|
||
from app.features.memory.constants import memory
|
||
from app.features.memory.evidence_format import (
|
||
dedupe_evidence_chunk_rows,
|
||
format_evidence_chunks_for_chat_prompt,
|
||
format_evidence_chunks_for_prompt,
|
||
format_user_memory_for_chat_display,
|
||
)
|
||
|
||
|
||
@dataclass(frozen=True)
|
||
class InterviewMemorySlices:
|
||
"""访谈轮次三类 memory 产物。"""
|
||
|
||
# 进主 system Context 的极短片段（可能为空）
|
||
prompt_excerpt: str
|
||
# 供 TurnPlan / extract_anchor_snippet：仅一条短线索或空（不替代用户原话）
|
||
anchor_source: str
|
||
# 供 reply_planner JSON：可较长，仍受 max_chars 截断
|
||
planner_preview: str
|
||
# 检索是否非空（gating 前）
|
||
had_retrieval: bool
|
||
|
||
|
||
_DISMISSIVE_MARKERS: tuple[str, ...] = (
|
||
"哈哈",
|
||
"呵呵",
|
||
"笑死",
|
||
"早就不会",
|
||
"不会了",
|
||
"别提",
|
||
"不想说",
|
||
"算了",
|
||
"没感觉",
|
||
"忘了",
|
||
"不记得",
|
||
"不用了",
|
||
"别问了",
|
||
"别说了",
|
||
"你记错",
|
||
"别扯",
|
||
"打住",
|
||
"翻篇",
|
||
"没那回事",
|
||
"不是那回事",
|
||
"不是那个",
|
||
)
|
||
_REJECTION_MARKERS: tuple[str, ...] = (
|
||
"不是",
|
||
"没有",
|
||
"不对",
|
||
"错了",
|
||
"辟谣",
|
||
"过了",
|
||
)
|
||
_CONTINUATION_MARKERS: tuple[str, ...] = (
|
||
"继续",
|
||
"后来",
|
||
"那次",
|
||
"上次",
|
||
"再说",
|
||
"还有",
|
||
"接着",
|
||
"回到",
|
||
"上回",
|
||
"你刚",
|
||
"刚才",
|
||
)
|
||
|
||
|
||
def _should_suppress_memory_injection(user_message: str) -> bool:
|
||
"""默认不注入：短句敷衍、否定翻篇、或本轮已足够长且未明显接续旧线。"""
|
||
um = (user_message or "").strip()
|
||
if not um:
|
||
return True
|
||
if any(m in um for m in _DISMISSIVE_MARKERS):
|
||
return True
|
||
if any(m in um for m in _REJECTION_MARKERS):
|
||
# 短句里的否定更像翻篇
|
||
if len(um) <= 24:
|
||
return True
|
||
if len(um) <= 18:
|
||
return True
|
||
if len(um) >= 72 and not any(m in um for m in _CONTINUATION_MARKERS):
|
||
# 长段新叙事：优先当前话头，不塞旧记忆块
|
||
return True
|
||
return False
|
||
|
||
|
||
def _first_chunk_line_for_anchor(evidence: dict, *, max_chars: int = 120) -> str:
|
||
chunks = evidence.get("relevant_chunks") or []
|
||
chunks = dedupe_evidence_chunk_rows(chunks[:10])
|
||
for c in chunks:
|
||
content = (
|
||
c.get("content", "") if isinstance(c, dict) else getattr(c, "content", "")
|
||
)
|
||
raw = (content or "").strip()
|
||
if len(raw) < 8:
|
||
continue
|
||
line = raw.splitlines()[0].strip() if raw else ""
|
||
if not line:
|
||
continue
|
||
safe_line = format_user_memory_for_chat_display(line, verbatim=True)
|
||
if len(safe_line) > max_chars:
|
||
return safe_line[: max_chars - 1].rstrip() + "…"
|
||
return safe_line
|
||
summaries = evidence.get("relevant_summaries") or []
|
||
for s in summaries[:1]:
|
||
if isinstance(s, dict):
|
||
st = (s.get("content") or "").strip()
|
||
if st:
|
||
safe_st = format_user_memory_for_chat_display(st)
|
||
return safe_st[:max_chars] if len(safe_st) > max_chars else safe_st
|
||
return ""
|
||
|
||
|
||
def format_minimal_prompt_memory_hint(evidence: dict, *, max_chars: int = 100) -> str:
|
||
"""单条极短线索，供 Context；禁止长段复述。"""
|
||
line = _first_chunk_line_for_anchor(evidence, max_chars=max_chars)
|
||
if not line:
|
||
return ""
|
||
return (
|
||
"## 记忆线索（仅用于追问角度，禁止复述成段正文）\n"
|
||
"以下为检索到的**一条**用户过往口述/系统摘要，**不是**助手自己的经历，"
|
||
"也**不是**用户本轮原话；优先用用户本轮原话承接与追问。\n"
|
||
"若需要轻量勾连，只能用「你之前提过」「你说过」「你刚讲到」这类**归因式**半句，"
|
||
"禁止整段展开，禁止写成助手亲历。\n"
|
||
f"- {line}\n"
|
||
)
|
||
|
||
|
||
def build_planner_preview(
|
||
evidence: dict,
|
||
*,
|
||
use_safe_chat_format: bool,
|
||
) -> str:
|
||
"""reply_planner 专用：保留较完整上下文，仍截断。"""
|
||
if use_safe_chat_format:
|
||
text = format_evidence_chunks_for_chat_prompt(evidence)
|
||
else:
|
||
text = format_evidence_chunks_for_prompt(evidence)
|
||
t = (text or "").strip()
|
||
if not t:
|
||
return ""
|
||
max_c = min(int(chat.memory_evidence_max_chars), 2000)
|
||
if len(t) > max_c:
|
||
return t[: max_c - 3] + "..."
|
||
return t
|
||
|
||
|
||
def slice_interview_memory(
|
||
evidence: dict[str, Any] | None,
|
||
user_message: str,
|
||
) -> InterviewMemorySlices:
|
||
"""
|
||
检索 bundle → 三类切片。gating 关闭时仍可为 planner 提供 preview。
|
||
"""
|
||
if not evidence:
|
||
return InterviewMemorySlices(
|
||
prompt_excerpt="",
|
||
anchor_source="",
|
||
planner_preview="",
|
||
had_retrieval=False,
|
||
)
|
||
|
||
use_safe = chat.memory_safe_evidence_format_enabled
|
||
planner_preview = build_planner_preview(evidence, use_safe_chat_format=use_safe)
|
||
had = bool(planner_preview.strip())
|
||
|
||
if _should_suppress_memory_injection(user_message):
|
||
return InterviewMemorySlices(
|
||
prompt_excerpt="",
|
||
anchor_source="",
|
||
planner_preview=planner_preview,
|
||
had_retrieval=had,
|
||
)
|
||
|
||
if not had:
|
||
return InterviewMemorySlices(
|
||
prompt_excerpt="",
|
||
anchor_source="",
|
||
planner_preview="",
|
||
had_retrieval=False,
|
||
)
|
||
|
||
prompt_excerpt = format_minimal_prompt_memory_hint(evidence)
|
||
anchor = _first_chunk_line_for_anchor(evidence, max_chars=160)
|
||
# anchor 给 TurnPlan：带一条短句即可，不拼整段 M 块
|
||
return InterviewMemorySlices(
|
||
prompt_excerpt=prompt_excerpt,
|
||
anchor_source=anchor,
|
||
planner_preview=planner_preview,
|
||
had_retrieval=True,
|
||
)
|
||
|
||
|
||
__all__ = [
|
||
"InterviewMemorySlices",
|
||
"slice_interview_memory",
|
||
"format_minimal_prompt_memory_hint",
|
||
"build_planner_preview",
|
||
]
|