- 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。
125 lines
3.8 KiB
Python
125 lines
3.8 KiB
Python
"""
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asset:// 与正文占位符清理。
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从正文移除 {{IMAGE:...}} / {{{{IMAGE:...}}}}(历史正文可能仍含此类标记)。
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"""
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import re
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from typing import Callable
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_PLACEHOLDER_RE = re.compile(
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r"\{\{\{\{IMAGE:(.*?)\}\}\}\}|\{\{IMAGE:(.*?)\}\}",
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re.DOTALL,
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)
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_ASSET_REF_RE = re.compile(r"!\[([^\]]*)\]\(asset://([a-zA-Z0-9_-]+)\)")
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_BLANK_RUN_RE = re.compile(r"\n{3,}")
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def strip_image_placeholders(text: str | None) -> str:
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"""移除正文中的 IMAGE 占位符,保留其余 markdown。"""
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if not text:
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return ""
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return _PLACEHOLDER_RE.sub("", text).strip()
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def parse_asset_refs(markdown: str) -> list[tuple[int, int, str, str]]:
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refs = []
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for m in _ASSET_REF_RE.finditer(markdown or ""):
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refs.append((m.start(), m.end(), m.group(1) or "", m.group(2) or ""))
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return refs
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def collect_asset_ids_from_markdown(markdown: str) -> list[str]:
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return [m.group(2) for m in _ASSET_REF_RE.finditer(markdown or "") if m.group(2)]
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def strip_asset_image_refs_from_markdown(markdown: str | None) -> str:
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"""Remove all `` references; collapse blank lines.
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Used for story single-primary policy: new versions / backfill must not
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accumulate multiple inline asset images.
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"""
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if not markdown or not str(markdown).strip():
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return ""
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text = _ASSET_REF_RE.sub("", markdown or "")
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text = _BLANK_RUN_RE.sub("\n\n", text)
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return text.strip()
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def collect_asset_ids_for_chapter(chapter) -> set[str]:
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"""章节正文 canonical、收录的各 story 正文、cover_asset_id 中的 asset id。"""
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ids: set[str] = set()
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md = getattr(chapter, "canonical_markdown", None) or ""
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ids.update(collect_asset_ids_from_markdown(md))
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cid = getattr(chapter, "cover_asset_id", None)
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if cid:
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ids.add(str(cid))
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for link in getattr(chapter, "story_links", None) or []:
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st = getattr(link, "story", None)
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if st is None:
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continue
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smd = getattr(st, "canonical_markdown", None) or ""
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ids.update(collect_asset_ids_from_markdown(smd))
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for intent in getattr(st, "image_intents", None) or []:
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if getattr(intent, "intent_role", None) == "primary":
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aid = getattr(intent, "asset_id", None)
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if aid:
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ids.add(str(aid))
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return ids
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def collect_asset_ids_for_chapters(chapters: list) -> set[str]:
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combined: set[str] = set()
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for ch in chapters or []:
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combined |= collect_asset_ids_for_chapter(ch)
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return combined
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def split_markdown_by_asset_refs(
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markdown: str,
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resolve_asset: Callable[[str], str | None],
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) -> list[dict]:
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blocks: list[dict] = []
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refs = parse_asset_refs(markdown or "")
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if not refs:
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text = (markdown or "").strip()
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if text:
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blocks.append({"type": "text", "value": text})
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return blocks
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pos = 0
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for start, end, caption, asset_id in refs:
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if start > pos:
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text = markdown[pos:start].strip()
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if text:
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blocks.append({"type": "text", "value": text})
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url = resolve_asset(asset_id) if asset_id else None
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if url:
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blocks.append({"type": "image", "url": url, "caption": caption})
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pos = end
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if pos < len(markdown or ""):
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text = markdown[pos:].strip()
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if text:
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blocks.append({"type": "text", "value": text})
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return blocks
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def resolve_asset_refs_in_markdown(
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markdown: str,
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resolve_asset: Callable[[str], str | None],
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) -> str:
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if not markdown or not resolve_asset:
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return markdown or ""
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def repl(m):
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caption, asset_id = m.group(1) or "", m.group(2) or ""
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url = resolve_asset(asset_id) if asset_id else None
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if url:
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return f""
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return m.group(0)
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return _ASSET_REF_RE.sub(repl, markdown)
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