786ebf8ae6
- 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。
528 lines
18 KiB
Python
528 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=%s status=%s", 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 _select_placeholders_for_effective_max(
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placeholders: list[dict],
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existing_images: list[dict] | None,
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effective_max: int,
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) -> list[dict]:
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existing_placeholders = {
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item.get("placeholder")
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for item in normalize_image_assets(existing_images)
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if item.get("placeholder")
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}
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existing_count_in_content = sum(
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1 for item in placeholders if item.get("placeholder") in existing_placeholders
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)
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remaining_new_slots = max(0, effective_max - existing_count_in_content)
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selected: list[dict] = []
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for item in placeholders:
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if item.get("placeholder") in existing_placeholders:
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selected.append(item)
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continue
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if remaining_new_slots <= 0:
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continue
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selected.append(item)
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remaining_new_slots -= 1
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return [{**item, "index": index} for index, item in enumerate(selected)]
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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 = state.current_stage or 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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chapters_to_enqueue: set[str] = set()
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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: transcript -> memory_sources, chunks, FTS
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conv_id = getattr(segments[0], "conversation_id", None) or ""
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transcript = "\n\n".join(seg.transcript_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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ingest_transcript_sync(db, user_id, conv_id, transcript)
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except Exception as e:
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logger.warning("Memory ingest 跳过: %s", e)
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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=%s, 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: %s", 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: %s", 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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logger.info(f"回忆录处理完成: user_id={user_id}, task_id={task_id}")
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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, task_id, "success", {"processed": len(segments)}
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)
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return {"status": "success", "processed": len(segments)}
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|
||
except Exception as e:
|
||
logger.error(f"回忆录处理失败: {e}")
|
||
|
||
# 更新任务状态为失败
|
||
_update_task_status_sync(user_id, task_id, "failure", {"error": str(e)})
|
||
|
||
# 重试
|
||
raise self.retry(exc=e) from e
|
||
|
||
|
||
@shared_task(bind=True, max_retries=3, default_retry_delay=30)
|
||
def generate_chapter_content(self, user_id: str, stage: str, new_content: str):
|
||
"""
|
||
单独生成章节内容的任务（用于实时更新）
|
||
|
||
Args:
|
||
user_id: 用户 ID
|
||
stage: 阶段
|
||
new_content: 新内容
|
||
"""
|
||
logger.info(f"生成章节内容: user_id={user_id}, stage={stage}")
|
||
|
||
try:
|
||
with get_sync_db() as db:
|
||
llm = _get_llm()
|
||
user_obj = db.get(User, user_id)
|
||
user_profile = ""
|
||
user_birth_year = None
|
||
if user_obj:
|
||
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.transcript_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: %s", exc)
|
||
try:
|
||
recompose_chapters_for_story.delay(sid)
|
||
except Exception as exc:
|
||
logger.warning("recompose_chapters_for_story delay: %s", 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
|