Files
life-echo/api/app/features/memoir/cover_eligibility.py
Kevin 786ebf8ae6 refactor(api,expo): 多智能体与会话收敛、回忆录兼容层移除、后端测试集大幅删减
- 对齐「多智能体收敛」与「回忆录 stories-first / markdown-first」方向:收紧运行时契约、
  删除过渡兼容路径与双轨逻辑,并同步更新客户端与文档。

- Chat:以 ChatOrchestrator 为实时编排入口;删除独立 conversation_agent,精简 prompts。
- Memoir:删除 memory_agent;MemoirOrchestrator、classification / story_route 与 prompts 收敛到
  prepare_batches + run_story_pipeline_for_category_batch 主链路。
- 将 agents 侧 processor 迁入 feature 层为 background_runner,并移除 features 下重复/过时
  processor 封装。

- 新增 history_store,强化「conversation_messages 为 DB 真源、Redis 为缓存」模型。
- 调整 models、repo、service、session_history;精简 WS message_types,重构 pipeline 与 router。

- 移除章节占位、整章再生等旧路径;章节列表与封面逻辑要求 story 关联;收紧 cover 资格与
  enqueue。
- helpers、repo、service、router、reading_segment_materialize、story_pipeline_sync、pdf_service
  等按 canonical markdown / cover_asset_id 收缩;删除 memoir_images/provider 等冗余。
- tasks:memoir_tasks、chapter_cover_tasks 等大幅瘦身;story_image_tasks 等与当前图片任务对齐。

- core:config、logging、redis、task_tracker 小幅调整。
- auth / user / payment / quota:路由或服务侧删减过时接口或逻辑(如 payment router 行数减少)。

- pyproject.toml、development.sh、.env.example / .env.production、README 等同步说明或变量。

- Alembic 0001_initial_schema 微调(与当前 schema 叙事一致的小改动)。

- 回忆录:types / mappers / api、章节页与 memoir 页与后端契约对齐;markdown-renderer 调整。
- 语音:删除 voice/player,voice-segment-store 相应精简。

- api/tests:删除 conftest 及绝大部分既有测试文件(websocket_baseline、conversation、memoir
  图片、PDF、SMS 等),属有意收缩/待按 backend-test-system 重建的信号。
- docs:新增多智能体收敛与移除兼容层计划摘要;更新 story-first 设计、backend-test-system、
  multi-agent-refactor-plan、实施总结等。

BREAKING CHANGE: 后端对外契约、回忆录章节字段与若干路由/任务行为已变更;大量 API 测试被移除,
  CI 若依赖这些用例需按新策略补测或调整流水线。
2026-03-22 18:10:28 +08:00

81 lines
2.8 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
"""章节封面是否可入队(与 Celery 任务共享,避免循环 import"""
from __future__ import annotations
from typing import Any
from app.features.memoir.asset_resolver import parse_asset_refs
from app.features.memoir.memoir_images.schema import (
IMAGE_STATUS_FAILED,
IMAGE_STATUS_PENDING,
)
# 正文内 ![...](asset://...) 数量需 **大于** 此值才生成/展示章节封面(与故事头图、正文配图任务独立)
MIN_INLINE_BODY_IMAGES_FOR_CHAPTER_COVER = 3
def chapter_has_story_links(chapter: Any) -> bool:
return any(
getattr(link, "story", None)
for link in getattr(chapter, "story_links", None) or []
)
def count_chapter_inline_body_images(chapter: Any) -> int:
"""统计章节 canonical_markdown 中正文插图asset:// 图片引用)次数。"""
md = getattr(chapter, "canonical_markdown", None) or ""
return len(parse_asset_refs(md))
def chapter_eligible_for_cover_by_inline_body_image_count(chapter: Any) -> bool:
"""仅当正文内插图数量 > MIN_INLINE_BODY_IMAGES_FOR_CHAPTER_COVER 时才生成/展示章节封面。"""
return (
count_chapter_inline_body_images(chapter)
> MIN_INLINE_BODY_IMAGES_FOR_CHAPTER_COVER
)
def primary_chapter_memoir_image(chapter: Any) -> Any | None:
"""章节级 MemoirImage封面槽位按 order_index 最小取第一条。"""
imgs = sorted(
getattr(chapter, "images", None) or [],
key=lambda m: getattr(m, "order_index", 0),
)
return imgs[0] if imgs else None
def chapter_needs_cover_enqueue(chapter) -> bool:
"""尚无 cover_asset、有正文、且正文内 asset 插图多于阈值时,可派发 generate_chapter_cover。"""
if not chapter:
return False
if not chapter_has_story_links(chapter):
return False
if getattr(chapter, "cover_asset_id", None):
return False
md = (getattr(chapter, "canonical_markdown", None) or "").strip()
if not md:
return False
return chapter_eligible_for_cover_by_inline_body_image_count(chapter)
def chapter_has_cover_to_generate(chapter) -> bool:
"""章节是否有待生成的封面图(任一条 chapter 级 MemoirImage 为 pending/failed"""
for m in getattr(chapter, "images", None) or []:
status = (m.status or "").strip()
if status in (IMAGE_STATUS_PENDING, IMAGE_STATUS_FAILED):
return True
return False
def cover_memoir_image_pending_or_failed(chapter: Any) -> Any | None:
"""用于补图任务:按 order_index 找到第一条 pending/failed 的章节配图行。"""
images = sorted(
getattr(chapter, "images", None) or [],
key=lambda m: getattr(m, "order_index", 0),
)
for m in images:
st = (m.status or "").strip()
if st in (IMAGE_STATUS_PENDING, IMAGE_STATUS_FAILED):
return m
return None