7fe0b70d5c
- 在 api/agents/conversation_agent.py 中添加 _detect_user_stage 方法，以通过关键词检测用户谈论的人生阶段。 - 在 api/agents/memory_agent.py 中更新章节排序逻辑，使用 STAGE_TO_ORDER 替代 CHAPTER_ORDER。 - 在 api/agents/state_schema.py 中添加方法以获取各阶段的填充情况。 - 在 api/agents/prompts/conversation_prompts.py 中更新对话提示，包含用户阶段检测和整体进度信息。 - 在 api/migrations/fix_chapter_order_index.sql 中添加 SQL 脚本以修复章节 order_index 的问题。 - 更新相关文档和提示以反映新功能。
111 lines
3.3 KiB
Python
111 lines
3.3 KiB
Python
"""
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共享状态 Schema（对话 Agent 与后台 Agent 共用）
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"""
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from __future__ import annotations
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from typing import Dict, List, Optional
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from pydantic import BaseModel, Field
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class SlotData(BaseModel):
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"""Slot 数据结构"""
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snippet: Optional[str] = None
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segment_ids: List[str] = Field(default_factory=list)
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class MemoirStateSchema(BaseModel):
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"""回忆录状态"""
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stage_order: List[str]
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current_stage: str
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covered_stages: List[str]
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slots: Dict[str, Dict[str, SlotData]]
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def empty_slots_for_current_stage(self) -> List[str]:
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stage_slots = self.slots.get(self.current_stage, {})
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empty_keys: List[str] = []
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for key, value in stage_slots.items():
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if not value.snippet:
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empty_keys.append(key)
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return empty_keys
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def empty_slots_for_stage(self, stage: str) -> List[str]:
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"""获取指定阶段的空槽位"""
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stage_slots = self.slots.get(stage, {})
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return [key for key, value in stage_slots.items() if not value.snippet]
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def filled_slots_for_stage(self, stage: str) -> Dict[str, str]:
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"""获取指定阶段已填充的槽位及其内容"""
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stage_slots = self.slots.get(stage, {})
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return {
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key: value.snippet
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for key, value in stage_slots.items()
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if value.snippet
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}
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def all_stages_coverage(self) -> Dict[str, Dict]:
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"""获取所有阶段的覆盖情况摘要"""
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coverage: Dict[str, Dict] = {}
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for stage in self.stage_order:
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stage_slots = self.slots.get(stage, {})
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total = len(stage_slots)
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filled = sum(1 for v in stage_slots.values() if v.snippet)
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coverage[stage] = {
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"total": total,
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"filled": filled,
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"empty": total - filled,
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"ratio": filled / total if total > 0 else 0,
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}
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return coverage
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DEFAULT_STAGE_ORDER = ["childhood", "education", "career", "family", "belief"]
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def default_slots() -> Dict[str, Dict[str, SlotData]]:
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return {
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"childhood": {
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"place": SlotData(),
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"people": SlotData(),
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"daily_life": SlotData(),
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"emotion": SlotData(),
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"turning_event": SlotData(),
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},
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"education": {
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"school": SlotData(),
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"city": SlotData(),
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"motivation": SlotData(),
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"challenge": SlotData(),
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"change": SlotData(),
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},
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"career": {
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"job": SlotData(),
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"environment": SlotData(),
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"decision": SlotData(),
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"pressure": SlotData(),
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"growth": SlotData(),
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},
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"family": {
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"relationship": SlotData(),
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"conflict": SlotData(),
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"support": SlotData(),
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"responsibility": SlotData(),
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"change": SlotData(),
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},
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"belief": {
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"value": SlotData(),
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"regret": SlotData(),
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"pride": SlotData(),
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"lesson": SlotData(),
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},
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}
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def default_state() -> MemoirStateSchema:
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return MemoirStateSchema(
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stage_order=DEFAULT_STAGE_ORDER,
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current_stage=DEFAULT_STAGE_ORDER[0],
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covered_stages=[],
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slots=default_slots(),
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)
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