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WIP: memory system improvements (in progress)

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Interview/chat prompt layers, reply planner, style profiles, memory
injection, interview meta store, and related tests. Work not finished.

Made-with: Cursor
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Kevin
2026-04-22 16:56:28 +08:00
parent e848f26354
commit 3121d1384d
28 changed files with 2790 additions and 452 deletions
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161
api/app/agents/state_schema.py
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@@ -1,5 +1,13 @@
"""
共享状态 Schema（对话 Agent 与后台 Agent 共用）
共享状态 Schema（对话 Agent 与后台 Agent 共用）。
Option B 的 schema 分层：
- `NarrativeCoverageState`：叙述覆盖视图 —— 阶段推进、叙述槽、每阶段的完成情况；**不掺控制元信息**。
- `InterviewControlState`：访谈控制视图 —— 已确认事实、人物主线、最近已问；用于访谈控场，**不参与成稿槽位**。
- `MemoirStateSchema`：以 facade 形式聚合两个视图，保留旧字段以兼容已持久化数据。
消费方**应**通过 `state.narrative()` / `state.control()` 视图取值；顶层字段会逐步按阶段迁出。
"""
from __future__ import annotations
@@ -48,51 +56,39 @@ class PersonaThread(BaseModel):
return self.trait
class MemoirStateSchema(BaseModel):
"""回忆录状态"""
# =============================================================================
# Narrative 视图：叙述覆盖、阶段推进、叙述槽
# =============================================================================
class NarrativeCoverageState(BaseModel):
"""叙述覆盖视图。
只承载「人生叙事覆盖」相关信息：阶段顺序、当前阶段、覆盖过的阶段、每阶段的叙述槽。
**禁止**在此视图承载访谈控场数据（已确认事实、人物主线、最近已问），那些数据属于
`InterviewControlState`。
"""
stage_order: List[str]
current_stage: str
covered_stages: List[str]
slots: Dict[str, Dict[str, SlotData]]
known_facts: List[KnownFact] = Field(default_factory=list)
persona_threads: List[PersonaThread] = Field(default_factory=list)
recent_questions: List[str] = Field(default_factory=list)
def empty_slots_for_current_stage(self) -> List[str]:
stage_slots = self.slots.get(self.current_stage, {})
empty_keys: List[str] = []
for key, value in stage_slots.items():
if not value.snippet:
empty_keys.append(key)
return empty_keys
def prompt_empty_slots_for_stage(self, stage: str) -> List[str]:
"""生成 prompt 时可追问的槽位，排除已被 known_facts 覆盖的方向。"""
blocked = {
fact.slot_name
for fact in self.known_facts
if fact.slot_name and (not fact.stage or fact.stage == stage)
}
return [key for key in self.empty_slots_for_stage(stage) if key not in blocked]
def prompt_empty_slots_for_current_stage(self) -> List[str]:
return self.prompt_empty_slots_for_stage(self.current_stage)
return [key for key, value in stage_slots.items() if not value.snippet]
def empty_slots_for_stage(self, stage: str) -> List[str]:
"""获取指定阶段的空槽位"""
stage_slots = self.slots.get(stage, {})
return [key for key, value in stage_slots.items() if not value.snippet]
def filled_slots_for_stage(self, stage: str) -> Dict[str, str]:
"""获取指定阶段已填充的槽位及其内容"""
stage_slots = self.slots.get(stage, {})
return {
key: value.snippet for key, value in stage_slots.items() if value.snippet
}
def all_stages_coverage(self) -> Dict[str, Dict]:
"""获取所有阶段的覆盖情况摘要"""
coverage: Dict[str, Dict] = {}
for stage in self.stage_order:
stage_slots = self.slots.get(stage, {})
@@ -106,6 +102,23 @@ class MemoirStateSchema(BaseModel):
}
return coverage
# =============================================================================
# Interview Control 视图：访谈控场（已知事实 / 人物主线 / 最近已问）
# =============================================================================
class InterviewControlState(BaseModel):
"""访谈控制视图。
承载仅与「控场 / 去重问 / 人物呼应」相关的信息。这些字段**不应**出现在叙述覆盖计算里，也
**不应**写入 `slots`。
"""
known_facts: List[KnownFact] = Field(default_factory=list)
persona_threads: List[PersonaThread] = Field(default_factory=list)
recent_questions: List[str] = Field(default_factory=list)
def prompt_known_fact_lines(self, *, limit: int = 10) -> List[str]:
xs: List[str] = []
for fact in self.known_facts[-limit:]:
@@ -133,8 +146,89 @@ class MemoirStateSchema(BaseModel):
out.append(s)
return out
def blocked_slot_names_for_stage(self, stage: str) -> set[str]:
"""已被 known_facts 覆盖的槽位名：追问时应避开。"""
return {
fact.slot_name
for fact in self.known_facts
if fact.slot_name and (not fact.stage or fact.stage == stage)
}
# =============================================================================
# Facade：MemoirStateSchema 兼容旧字段形态，方法委托到两个视图
# =============================================================================
class MemoirStateSchema(BaseModel):
"""回忆录状态（Facade）。
为兼容既有持久化与旧调用方，顶层字段保持不变；内部将其投影成
`NarrativeCoverageState` 与 `InterviewControlState` 两个视图，后续新代码应直接使用
`state.narrative()` / `state.control()` 表达意图。
"""
stage_order: List[str]
current_stage: str
covered_stages: List[str]
slots: Dict[str, Dict[str, SlotData]]
known_facts: List[KnownFact] = Field(default_factory=list)
persona_threads: List[PersonaThread] = Field(default_factory=list)
recent_questions: List[str] = Field(default_factory=list)
# ---- 视图投影 ----
def narrative(self) -> NarrativeCoverageState:
return NarrativeCoverageState(
stage_order=self.stage_order,
current_stage=self.current_stage,
covered_stages=self.covered_stages,
slots=self.slots,
)
def control(self) -> InterviewControlState:
return InterviewControlState(
known_facts=self.known_facts,
persona_threads=self.persona_threads,
recent_questions=self.recent_questions,
)
# ---- 兼容层：委托到 narrative / control 视图 ----
def empty_slots_for_current_stage(self) -> List[str]:
return self.narrative().empty_slots_for_current_stage()
def empty_slots_for_stage(self, stage: str) -> List[str]:
return self.narrative().empty_slots_for_stage(stage)
def filled_slots_for_stage(self, stage: str) -> Dict[str, str]:
return self.narrative().filled_slots_for_stage(stage)
def all_stages_coverage(self) -> Dict[str, Dict]:
return self.narrative().all_stages_coverage()
def prompt_empty_slots_for_stage(self, stage: str) -> List[str]:
"""生成 prompt 时可追问的槽位，排除已被 known_facts 覆盖的方向。"""
blocked = self.control().blocked_slot_names_for_stage(stage)
return [
key
for key in self.narrative().empty_slots_for_stage(stage)
if key not in blocked
]
def prompt_empty_slots_for_current_stage(self) -> List[str]:
return self.prompt_empty_slots_for_stage(self.current_stage)
def prompt_known_fact_lines(self, *, limit: int = 10) -> List[str]:
return self.control().prompt_known_fact_lines(limit=limit)
def prompt_persona_thread_lines(self, *, limit: int = 6) -> List[str]:
return self.control().prompt_persona_thread_lines(limit=limit)
def prompt_recent_question_lines(self, *, limit: int = 4) -> List[str]:
return self.control().prompt_recent_question_lines(limit=limit)
# 与 stage_constants.CHAT_STAGES 同一顺序；list() 避免与元组共享可变别名
DEFAULT_STAGE_ORDER: list[str] = list(CHAT_STAGES)
@@ -184,3 +278,16 @@ def default_state() -> MemoirStateSchema:
covered_stages=[],
slots=default_slots(),
)
__all__ = [
"DEFAULT_STAGE_ORDER",
"InterviewControlState",
"KnownFact",
"MemoirStateSchema",
"NarrativeCoverageState",
"PersonaThread",
"SlotData",
"default_slots",
"default_state",
]