feat: 更新对话内容处理逻辑及新增用户回忆整理脚本
- 修改 get_narrative_prompt 函数，优化对话内容的叙述生成逻辑，确保新内容与已有内容自然衔接。 - 在 api/scripts 中新增 reprocess_user_memoir.py 脚本，用于整理用户历史对话为回忆录章节，支持远程预览和确认写入。 - 更新 .gitignore，添加对 certs/ 和 scripts/output/ 目录的忽略规则，确保不必要的文件不被跟踪。 - 在 memoir_tasks.py 中添加章节锁机制，防止并发写入同一章节，提升数据一致性和安全性。
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penghanyuan
@@ -27,6 +27,20 @@ from agents.prompts.memory_prompts import (
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logger = logging.getLogger(__name__)
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def _acquire_chapter_lock(user_id: str, stage: str, timeout: int = 120) -> bool:
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"""获取章节分布式锁，防止并发写入同一章节"""
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r = redis.from_url(os.getenv("REDIS_URL", "redis://localhost:6379/0"))
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lock_key = f"lock:chapter:{user_id}:{stage}"
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return r.set(lock_key, "1", nx=True, ex=timeout)
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def _release_chapter_lock(user_id: str, stage: str):
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"""释放章节分布式锁"""
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r = redis.from_url(os.getenv("REDIS_URL", "redis://localhost:6379/0"))
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lock_key = f"lock:chapter:{user_id}:{stage}"
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r.delete(lock_key)
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def _update_task_status_sync(user_id: str, task_id: str, status: str, result: Dict = None):
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"""同步更新任务状态（在 Celery 任务中使用）"""
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try:
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@@ -208,96 +222,116 @@ def process_memoir_segments(self, user_id: str, segment_ids: List[str]):
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# 生成章节内容
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for stage, stage_segments in stage_to_segments.items():
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segment_texts = [seg.transcript_text for seg in stage_segments]
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combined_text = "\n\n".join(segment_texts)
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source_ids = [seg.id for seg in stage_segments]
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# 查找 active 章节（被清除的章节不继续更新，而是创建新的）
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stmt_chapter = select(Chapter).where(
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Chapter.user_id == user_id,
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Chapter.category == stage,
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Chapter.is_active == True,
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)
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result_chapter = db.execute(stmt_chapter)
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chapter = result_chapter.scalar_one_or_none()
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# 获取 slot snippets
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slot_snippets = {
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key: value.snippet
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for key, value in (state.slots.get(stage, {}) or {}).items()
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if value.snippet
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}
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# 生成标题和内容
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title = chapter.title if chapter else f"{stage} 回忆"
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existing_content = chapter.content if chapter else ""
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narrative = combined_text
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if llm:
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try:
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if not chapter:
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title_prompt = get_creative_title_prompt(
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stage=stage,
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emotion="neutral",
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slots=slot_snippets
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if not _acquire_chapter_lock(user_id, stage):
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logger.warning(f"章节锁竞争: user={user_id}, stage={stage}, 延迟重试")
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raise self.retry(countdown=10)
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try:
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segment_texts = [seg.transcript_text for seg in stage_segments]
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combined_text = "\n\n".join(segment_texts)
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source_ids = [seg.id for seg in stage_segments]
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# 查找 active 章节（被清除的章节不继续更新，而是创建新的）
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stmt_chapter = select(Chapter).where(
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Chapter.user_id == user_id,
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Chapter.category == stage,
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Chapter.is_active == True,
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)
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result_chapter = db.execute(stmt_chapter)
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chapter = result_chapter.scalar_one_or_none()
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# 获取 slot snippets
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slot_snippets = {
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key: value.snippet
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for key, value in (state.slots.get(stage, {}) or {}).items()
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if value.snippet
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}
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# 生成标题和内容
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title = chapter.title if chapter else f"{stage} 回忆"
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existing_content = chapter.content if chapter else ""
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narrative = combined_text
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if llm:
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try:
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if not chapter:
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title_prompt = get_creative_title_prompt(
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stage=stage,
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emotion="neutral",
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slots=slot_snippets
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)
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title_response = llm.invoke(title_prompt)
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title = title_response.content.strip().strip('"')
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narrative_prompt = get_narrative_prompt(
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stage=stage,
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slots=slot_snippets,
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new_content=combined_text,
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existing_content=existing_content,
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)
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title_response = llm.invoke(title_prompt)
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title = title_response.content.strip().strip('"')
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narrative_prompt = get_narrative_prompt(
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stage=stage,
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slots=slot_snippets,
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new_content=combined_text,
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existing_content=existing_content,
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narrative_response = llm.invoke(narrative_prompt)
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new_narrative = narrative_response.content.strip()
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# 追加而非替换
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if existing_content:
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narrative = f"{existing_content}\n\n{new_narrative}"
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else:
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narrative = new_narrative
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except Exception as e:
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logger.warning(f"LLM 生成失败: {e}")
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if existing_content:
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narrative = f"{existing_content}\n\n{combined_text}"
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# 安全检查：新内容不应比旧内容短
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if existing_content and len(narrative) < len(existing_content) * 0.8:
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logger.warning(
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f"内容长度异常: existing={len(existing_content)}, "
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f"new={len(narrative)}, stage={stage}. 回退为追加模式"
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)
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narrative_response = llm.invoke(narrative_prompt)
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narrative = narrative_response.content.strip()
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except Exception as e:
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logger.warning(f"LLM 生成失败: {e}")
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if existing_content:
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narrative = f"{existing_content}\n\n{combined_text}"
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# 更新或创建章节
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if chapter:
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chapter.content = narrative
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chapter.title = title
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chapter.is_new = True
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chapter.source_segments = list({*(chapter.source_segments or []), *source_ids})
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else:
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# 根据 stage 计算正确的排序索引
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calculated_order_index = STAGE_TO_ORDER.get(stage, 999)
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chapter = Chapter(
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id=str(uuid.uuid4()),
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user_id=user_id,
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title=title,
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content=narrative,
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order_index=calculated_order_index,
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status="completed",
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category=stage,
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images=[],
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is_new=True,
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source_segments=source_ids,
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)
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db.add(chapter)
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db.flush()
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# 更新 Book
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stmt_book = select(Book).where(Book.user_id == user_id).order_by(Book.updated_at.desc())
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result_book = db.execute(stmt_book)
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book = result_book.scalar_one_or_none()
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if not book:
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book = Book(
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id=str(uuid.uuid4()),
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user_id=user_id,
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title="我的回忆录",
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total_pages=0,
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total_words=0,
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cover_image_url=None,
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)
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db.add(book)
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book.has_update = True
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book.last_update_chapter_id = chapter.id
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narrative = f"{existing_content}\n\n{combined_text}"
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# 更新或创建章节
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if chapter:
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chapter.content = narrative
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chapter.title = title
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chapter.is_new = True
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chapter.source_segments = list({*(chapter.source_segments or []), *source_ids})
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else:
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# 根据 stage 计算正确的排序索引
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calculated_order_index = STAGE_TO_ORDER.get(stage, 999)
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chapter = Chapter(
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id=str(uuid.uuid4()),
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user_id=user_id,
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title=title,
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content=narrative,
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order_index=calculated_order_index,
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status="completed",
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category=stage,
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images=[],
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is_new=True,
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source_segments=source_ids,
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)
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db.add(chapter)
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db.flush()
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# 更新 Book
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stmt_book = select(Book).where(Book.user_id == user_id).order_by(Book.updated_at.desc())
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result_book = db.execute(stmt_book)
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book = result_book.scalar_one_or_none()
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if not book:
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book = Book(
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id=str(uuid.uuid4()),
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user_id=user_id,
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title="我的回忆录",
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total_pages=0,
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total_words=0,
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cover_image_url=None,
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)
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db.add(book)
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book.has_update = True
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book.last_update_chapter_id = chapter.id
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finally:
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_release_chapter_lock(user_id, stage)
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# 标记段落为已处理
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for seg in segments:
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@@ -360,10 +394,23 @@ def generate_chapter_content(self, user_id: str, stage: str, new_content: str):
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existing_content=existing_content,
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)
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response = llm.invoke(prompt)
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narrative = response.content.strip()
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new_narrative = response.content.strip()
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# 追加而非替换
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if existing_content:
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narrative = f"{existing_content}\n\n{new_narrative}"
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else:
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narrative = new_narrative
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else:
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narrative = f"{existing_content}\n\n{new_content}" if existing_content else new_content
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# 安全检查：新内容不应比旧内容短
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if existing_content and len(narrative) < len(existing_content) * 0.8:
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logger.warning(
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f"内容长度异常: existing={len(existing_content)}, "
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f"new={len(narrative)}, stage={stage}. 回退为追加模式"
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)
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narrative = f"{existing_content}\n\n{new_content}"
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if chapter:
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chapter.content = narrative
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chapter.is_new = True
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