e4bf0710c7
数据库 - 新增迁移 0003：timeline_events.memory_source_id 外键 → memory_sources，便于按 ingest 源做时间线幂等 后端 - 记忆 - 新增 ingest 后 LLM 富化（摘要/事实/时间线），可配置开关与最大字符数 - 新增证据包组装：合并 chunk、摘要、事实、时间线、故事等检索结果；支持空 query 时是否仍带 rolling 等开关 - repo/retriever/service/router/schemas/summarizer/timeline/extractor 等扩展；文档 memory-retrieval.md 更新 后端 - 对话 WS - 增加 PING/PONG；分段 ASR 日志与空音频处理；转写失败与「无助手回复」错误提示更明确 - 助手多段回复持久化使用统一分隔符，与分段逻辑一致 后端 - Agent - reply_limits：按 [SPLIT] 与段落拆段，并保证非空 fallback，供 WS 与 TTS 多段下发 后端 - 回忆录任务 - transcript ingest 记录 source_id；任务成功结?
533 lines
18 KiB
Python
533 lines
18 KiB
Python
"""
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回忆录处理 Celery 任务
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"""
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import json
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import uuid
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from datetime import datetime, timezone
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from typing import Dict, List, Set
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import redis
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from celery import shared_task
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from sqlalchemy import select
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from sqlalchemy.orm import Session
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from app.agents.chat.prompts_profile import format_user_profile_context
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from app.agents.memoir import MemoirOrchestrator
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from app.agents.state_schema import MemoirStateSchema, SlotData, default_state
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from app.core.db import get_sync_db
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from app.core.dependencies import get_llm_provider
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from app.core.logging import get_logger
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from app.features.conversation.models import Segment
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from app.features.memoir.cover_eligibility import (
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chapter_needs_cover_enqueue,
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)
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from app.features.memoir.memoir_images.parser import (
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build_initial_image_assets,
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)
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from app.features.memoir.memoir_images.schema import (
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IMAGE_STATUS_COMPLETED,
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IMAGE_STATUS_FAILED,
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IMAGE_STATUS_PENDING,
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normalize_image_assets,
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)
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from app.features.memoir.memoir_images.serializers import (
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image_dict_to_row_kwargs,
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)
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from app.features.memoir.memoir_images.settings import MemoirImageSettings
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from app.features.memoir.models import (
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Book,
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MemoirImage,
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MemoirState,
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)
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from app.features.memoir.story_pipeline_sync import (
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run_story_pipeline_for_category_batch,
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)
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from app.features.user.models import User
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logger = get_logger(__name__)
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_REDIS_CLIENTS: dict[bool, redis.Redis] = {}
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def _get_llm():
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"""Celery 任务内获取 LangChain LLM（通过 port）"""
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try:
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return getattr(get_llm_provider(), "langchain_llm", None)
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except Exception:
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return None
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def _get_redis_client(*, decode_responses: bool = False) -> redis.Redis:
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from app.core.config import settings
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client = _REDIS_CLIENTS.get(decode_responses)
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if client is None:
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client = redis.from_url(
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settings.redis_url,
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decode_responses=decode_responses,
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)
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_REDIS_CLIENTS[decode_responses] = client
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return client
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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 = _get_redis_client()
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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 = _get_redis_client()
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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(
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user_id: str, task_id: str, status: str, result: Dict = None
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):
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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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r = _get_redis_client(decode_responses=True)
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key = f"task:user:{user_id}:tasks"
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# 获取现有任务信息
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data = r.hget(key, task_id)
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if data:
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task_info = json.loads(data)
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else:
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task_info = {"task_id": task_id}
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task_info["status"] = status
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task_info["updated_at"] = datetime.now(timezone.utc).isoformat()
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if result is not None:
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task_info["result"] = result
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r.hset(key, task_id, json.dumps(task_info))
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r.expire(key, 3600) # 1小时过期
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logger.debug("任务状态已更新: task_id={} status={}", task_id, status)
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except Exception as e:
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logger.error(f"更新任务状态失败: {e}")
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def _merge_chapter_image_assets(
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existing_images: list[dict] | None,
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placeholders: list[dict],
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provider: str,
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style: str,
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size: str,
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now_iso: str,
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) -> list[dict]:
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normalized_existing_images = normalize_image_assets(existing_images)
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existing_by_placeholder = {
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item.get("placeholder"): dict(item)
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for item in normalized_existing_images
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if item.get("placeholder")
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}
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merged_assets: list[dict] = []
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for item in placeholders:
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existing = existing_by_placeholder.get(item["placeholder"])
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if existing:
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merged_item = dict(existing)
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merged_item["index"] = item["index"]
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merged_item["placeholder"] = item["placeholder"]
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merged_item["description"] = item["description"]
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merged_item["provider"] = merged_item.get("provider") or provider
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merged_item["style"] = merged_item.get("style") or style
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merged_item["size"] = merged_item.get("size") or size
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merged_item["created_at"] = merged_item.get("created_at") or now_iso
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merged_item["updated_at"] = merged_item.get("updated_at") or now_iso
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if merged_item.get("status") == IMAGE_STATUS_COMPLETED and not (
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merged_item.get("storage_key") or merged_item.get("url")
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):
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merged_item["status"] = IMAGE_STATUS_FAILED
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merged_item["error"] = merged_item.get("error") or "missing image url"
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else:
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merged_item = build_initial_image_assets(
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placeholders=[item],
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provider=provider,
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style=style,
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size=size,
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now_iso=now_iso,
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)[0]
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merged_assets.append(merged_item)
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return merged_assets
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def chapter_has_images_to_generate(images: list[dict] | None) -> bool:
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return any(
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item.get("status") in {IMAGE_STATUS_PENDING, IMAGE_STATUS_FAILED}
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for item in normalize_image_assets(images)
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)
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def _memoir_image_from_asset(
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chapter_id: str,
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order_index: int,
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image_asset: dict,
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) -> MemoirImage:
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"""从单条图片 dict 构建 MemoirImage 行（用于写入 memoir_images 表）。"""
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kwargs = image_dict_to_row_kwargs(image_asset)
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return MemoirImage(
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id=str(uuid.uuid4()).replace("-", "")[:32],
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chapter_id=chapter_id,
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order_index=order_index,
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**kwargs,
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)
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def _coerce_state(model: MemoirState) -> MemoirStateSchema:
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"""将数据库模型转换为 Schema"""
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return MemoirStateSchema.model_validate(
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{
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"stage_order": model.stage_order or default_state().stage_order,
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"current_stage": model.current_stage,
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"covered_stages": model.covered_stages or [],
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"slots": model.slots
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if isinstance(model.slots, dict)
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else default_state().slots,
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}
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)
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def _get_or_create_state_sync(user_id: str, db: Session) -> MemoirStateSchema:
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"""同步获取或创建状态"""
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stmt = select(MemoirState).where(MemoirState.user_id == user_id)
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result = db.execute(stmt)
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state = result.scalar_one_or_none()
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if state:
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return _coerce_state(state)
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default = default_state()
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state = MemoirState(
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id=str(uuid.uuid4()),
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user_id=user_id,
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stage_order=default.stage_order,
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current_stage=default.current_stage,
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covered_stages=default.covered_stages,
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slots={
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k: {sk: sv.model_dump() for sk, sv in v.items()}
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for k, v in default.slots.items()
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},
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)
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db.add(state)
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db.commit()
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db.refresh(state)
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return _coerce_state(state)
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def _update_slot_sync(
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user_id: str,
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stage: str,
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slot_name: str,
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snippet: str,
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segment_ids: List[str],
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db: Session,
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) -> MemoirStateSchema:
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"""同步更新 slot"""
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stmt = select(MemoirState).where(MemoirState.user_id == user_id)
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result = db.execute(stmt)
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state = result.scalar_one_or_none()
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if not state:
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_get_or_create_state_sync(user_id, db)
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result = db.execute(stmt)
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state = result.scalar_one()
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slots: Dict[str, Dict] = state.slots or {}
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stage_slots = slots.get(stage, {})
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existing = stage_slots.get(slot_name, {})
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merged_segment_ids = list({*(existing.get("segment_ids") or []), *segment_ids})
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stage_slots[slot_name] = SlotData(
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snippet=snippet, segment_ids=merged_segment_ids
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).model_dump()
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slots[stage] = stage_slots
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state.slots = slots
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state.current_stage = stage
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db.commit()
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db.refresh(state)
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return _coerce_state(state)
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@shared_task(bind=True, max_retries=3, default_retry_delay=60)
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def process_memoir_segments(self, user_id: str, segment_ids: List[str]):
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"""
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处理回忆录段落的 Celery 任务
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Args:
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user_id: 用户 ID
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segment_ids: 段落 ID 列表
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"""
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task_id = self.request.id
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logger.info(
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f"开始处理回忆录段落: user_id={user_id}, task_id={task_id}, segments={len(segment_ids)}"
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)
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# 更新任务状态为 running
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_update_task_status_sync(user_id, task_id, "running")
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try:
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with get_sync_db() as db:
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# 获取段落
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stmt = select(Segment).where(Segment.id.in_(segment_ids))
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result = db.execute(stmt)
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segments = result.scalars().all()
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if not segments:
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logger.warning(f"未找到段落: {segment_ids}")
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return {"status": "no_segments"}
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# Memory ingest 先于回忆录流水线 commit，保证后续 retrieve_evidence_sync 可见本批 chunk
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# （见 api/docs/memory-retrieval.md）
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conv_id = getattr(segments[0], "conversation_id", None) or ""
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transcript = "\n\n".join(seg.user_input_text or "" for seg in segments)
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if transcript.strip():
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try:
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from app.features.memory.service import ingest_transcript_sync
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source_id = ingest_transcript_sync(db, user_id, conv_id, transcript)
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logger.info(
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"event=memory_transcript_ingested user_id={} task_id={} "
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"source_id={} conversation_id={} transcript_chars={} "
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"segment_count={}",
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user_id,
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task_id,
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source_id,
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conv_id,
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len(transcript),
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len(segments),
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)
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except Exception as e:
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logger.warning(
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"Memory ingest 跳过: {} exc_type={}",
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e,
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type(e).__name__,
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)
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llm = _get_llm()
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image_settings = MemoirImageSettings.from_env()
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user_obj = db.get(User, user_id)
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user_profile = ""
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user_birth_year = None
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if user_obj:
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user_birth_year = user_obj.birth_year
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user_profile = format_user_profile_context(
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birth_year=user_obj.birth_year,
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birth_place=user_obj.birth_place,
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grew_up_place=user_obj.grew_up_place,
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occupation=user_obj.occupation,
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)
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story_dispatch_ids: Set[str] = set()
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memoir_orchestrator = MemoirOrchestrator()
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prepared = memoir_orchestrator.prepare_batches(
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segments=list(segments),
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llm=llm,
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get_or_create_state=lambda: _get_or_create_state_sync(user_id, db),
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update_slot=lambda stage, slot_name, snippet, seg_ids: (
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_update_slot_sync(user_id, stage, slot_name, snippet, seg_ids, db)
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),
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)
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chapters_to_enqueue: Set[str] = set()
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for (
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chapter_category,
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category_segments,
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) in prepared.category_to_segments.items():
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if not _acquire_chapter_lock(user_id, chapter_category):
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logger.warning(
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"章节锁竞争: category={}, 延迟重试",
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chapter_category,
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)
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raise self.retry(countdown=10)
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try:
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chapter, needs_cover, disp = run_story_pipeline_for_category_batch(
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db,
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user_id=user_id,
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chapter_category=chapter_category,
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category_segments=category_segments,
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state=prepared.state,
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user_profile=user_profile,
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user_birth_year=user_birth_year,
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llm=llm,
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)
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story_dispatch_ids |= disp
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db.flush()
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db.refresh(chapter)
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needs_cover_enqueue = (
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image_settings.enabled and chapter_needs_cover_enqueue(chapter)
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)
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stmt_book = (
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select(Book)
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.where(Book.user_id == user_id)
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.order_by(Book.updated_at.desc())
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)
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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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if chapter and needs_cover_enqueue:
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chapters_to_enqueue.add(chapter.id)
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finally:
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_release_chapter_lock(user_id, chapter_category)
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# 标记段落为已处理
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for seg in segments:
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seg.processed = True
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db.commit()
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from app.tasks.chapter_compose_tasks import recompose_chapters_for_story
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from app.tasks.story_image_tasks import generate_story_image
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for sid in story_dispatch_ids:
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try:
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generate_story_image.delay(sid)
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except Exception as exc:
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logger.warning("generate_story_image delay: {}", exc)
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try:
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recompose_chapters_for_story.delay(sid)
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except Exception as exc:
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logger.warning("recompose_chapters_for_story delay: {}", exc)
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from app.tasks.chapter_cover_enqueue import (
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try_enqueue_generate_chapter_cover,
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)
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for chapter_id in sorted(chapters_to_enqueue):
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if try_enqueue_generate_chapter_cover(chapter_id, source="pipeline"):
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logger.info(f"派发章节封面任务: chapter={chapter_id}")
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categories_processed = sorted(prepared.category_to_segments.keys())
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logger.info(
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"回忆录处理完成: user_id={} task_id={} segment_count={} "
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"categories_processed={}",
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user_id,
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task_id,
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len(segments),
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categories_processed,
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)
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# 更新任务状态为成功
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_update_task_status_sync(
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user_id,
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task_id,
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"success",
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{
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"processed": len(segments),
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"categories_processed": categories_processed,
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},
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)
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return {
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"status": "success",
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"processed": len(segments),
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"categories_processed": categories_processed,
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}
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except Exception as e:
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logger.error(f"回忆录处理失败: {e}")
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# 更新任务状态为失败
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_update_task_status_sync(user_id, task_id, "failure", {"error": str(e)})
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# 重试
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raise self.retry(exc=e) from e
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@shared_task(bind=True, max_retries=3, default_retry_delay=30)
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def generate_chapter_content(self, user_id: str, stage: str, new_content: str):
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"""
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单独生成章节内容的任务（用于实时更新）
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Args:
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user_id: 用户 ID
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stage: 阶段
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new_content: 新内容
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"""
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logger.info(f"生成章节内容: user_id={user_id}, stage={stage}")
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try:
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with get_sync_db() as db:
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llm = _get_llm()
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user_obj = db.get(User, user_id)
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user_profile = ""
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user_birth_year = None
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if user_obj:
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||
user_birth_year = user_obj.birth_year
|
||
user_profile = format_user_profile_context(
|
||
birth_year=user_obj.birth_year,
|
||
birth_place=user_obj.birth_place,
|
||
grew_up_place=user_obj.grew_up_place,
|
||
occupation=user_obj.occupation,
|
||
)
|
||
|
||
class _Seg:
|
||
def __init__(self, text: str):
|
||
self.id = str(uuid.uuid4())
|
||
self.user_input_text = text
|
||
|
||
state = _get_or_create_state_sync(user_id, db)
|
||
chapter, _, dispatch_ids = run_story_pipeline_for_category_batch(
|
||
db,
|
||
user_id=user_id,
|
||
chapter_category=stage,
|
||
category_segments=[_Seg(new_content)],
|
||
state=state,
|
||
user_profile=user_profile,
|
||
user_birth_year=user_birth_year,
|
||
llm=llm,
|
||
)
|
||
db.commit()
|
||
db.refresh(chapter)
|
||
|
||
from app.tasks.chapter_compose_tasks import recompose_chapters_for_story
|
||
from app.tasks.story_image_tasks import generate_story_image
|
||
|
||
for sid in dispatch_ids:
|
||
try:
|
||
generate_story_image.delay(sid)
|
||
except Exception as exc:
|
||
logger.warning("generate_story_image delay: {}", exc)
|
||
try:
|
||
recompose_chapters_for_story.delay(sid)
|
||
except Exception as exc:
|
||
logger.warning("recompose_chapters_for_story delay: {}", exc)
|
||
|
||
image_settings = MemoirImageSettings.from_env()
|
||
if (
|
||
image_settings.enabled
|
||
and chapter
|
||
and chapter_needs_cover_enqueue(chapter)
|
||
):
|
||
from app.tasks.chapter_cover_enqueue import (
|
||
try_enqueue_generate_chapter_cover,
|
||
)
|
||
|
||
try_enqueue_generate_chapter_cover(chapter.id, source="pipeline")
|
||
return {"status": "success"}
|
||
|
||
except Exception as e:
|
||
logger.error(f"章节生成失败: {e}")
|
||
raise self.retry(exc=e) from e
|