07c6478742
- 新增 utterance_substance：短时/应答/元话语可跳过记忆检索、阶段 LLM 与资料抽取 LLM；可配置 - 输入归一化：LLM 模式默认仅语音/ASR；配置项写入 .env.example - Memoir Phase1：可选 batch LLM 一次性抽取+分类（失败回退逐段）；Extraction 空槽位时阶段与 current_stage 对齐，prompt 约束收紧 - 叙事与忠实度：narrative_safety、证据重叠/场合锚点、标题 slots 与履历短语 grounded；fidelity 解析失败 fail-open 可配置 - 章节管线：锁 TTL 上调、锁竞争 Celery 重试、Phase2 immediate singleflight 等；story_pipeline_sync / chapter_compose / memoir_tasks 联动 - Memory：compaction / repo / summarizer / evidence 小修；事实 FTS 未命中是否回退最近事实可配置 - 新增 memoir_pipeline_trace；补充 memoir_reliability 文档与多项回归/门控测试
852 lines
30 KiB
Python
852 lines
30 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 celery.exceptions import Retry
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from celery.result import AsyncResult
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from sqlalchemy import func, select
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from sqlalchemy.orm import Session
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from app.agents.chat.background_voice import infer_background_voice
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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.stage_constants import normalize_chapter_category
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from app.agents.state_schema import MemoirStateSchema, default_state
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from app.core.chapter_pipeline_lock import (
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acquire_chapter_pipeline_lock as _acquire_chapter_lock,
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)
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from app.core.chapter_pipeline_lock import (
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release_chapter_pipeline_lock as _release_chapter_lock,
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)
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from app.core.config import settings
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from app.core.db import get_sync_db
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from app.core.dependencies import get_llm_provider, get_llm_provider_fast
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from app.core.logging import get_logger
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from app.core.memoir_pipeline_trace import (
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effective_correlation_id,
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new_memoir_correlation_id,
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)
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from app.features.conversation.models import Conversation, Segment
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from app.tasks.celery_app import celery_app
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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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)
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from app.features.memoir.state_service import (
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get_or_create_state_sync,
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update_slot_sync,
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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_llm_fast():
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"""分类 / 抽取等快档位任务（与叙事、路由默认模型可分离）。"""
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try:
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return getattr(get_llm_provider_fast(), "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 _chapter_lock_ttl() -> int:
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return int(settings.chapter_pipeline_lock_ttl_seconds)
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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 _phase2_timeout_task_id(user_id: str, chapter_category: str) -> str:
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return f"phase2-timeout-{user_id}-{chapter_category}"
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def _revoke_phase2_timeout(user_id: str, chapter_category: str) -> None:
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tid = _phase2_timeout_task_id(user_id, chapter_category)
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try:
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AsyncResult(tid, app=celery_app).revoke(terminate=False)
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except Exception as e:
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logger.debug(
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"event=phase2_timeout_revoke_skipped task_id={} exc={}",
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tid,
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e,
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)
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def _should_trigger_phase2(
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db: Session,
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user_id: str,
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chapter_category: str,
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current_segment_chars: int,
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) -> bool:
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if current_segment_chars >= int(settings.memoir_narrative_immediate_char_threshold):
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return True
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user_convs = select(Conversation.id).where(
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Conversation.user_id == user_id,
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Conversation.deleted_at.is_(None),
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)
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stmt = select(
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func.count(Segment.id),
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func.coalesce(func.sum(func.length(Segment.user_input_text)), 0),
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).where(
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Segment.conversation_id.in_(user_convs),
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Segment.topic_category == chapter_category,
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Segment.narrated.is_(False),
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Segment.skip_narrative.is_(False),
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)
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row = db.execute(stmt).one()
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count, total_chars = int(row[0] or 0), int(row[1] or 0)
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if count >= int(settings.memoir_narrative_batch_min_segments):
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return True
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if total_chars >= int(settings.memoir_narrative_batch_min_chars):
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return True
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return False
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def _phase2_immediate_task_id(user_id: str, chapter_category: str) -> str:
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return f"phase2-immediate-{user_id}-{chapter_category}"
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def _schedule_phase2_timeout(
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user_id: str, chapter_category: str, memoir_correlation_id: str | None = None
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) -> None:
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"""Reset countdown for Phase 2 narrative for one category."""
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_revoke_phase2_timeout(user_id, chapter_category)
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countdown = float(max(1.0, settings.memoir_narrative_batch_max_wait_seconds))
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p2_kwargs: dict = {}
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if memoir_correlation_id:
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p2_kwargs["memoir_correlation_id"] = memoir_correlation_id
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celery_app.send_task(
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"app.tasks.memoir_tasks.process_memoir_phase2",
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args=[user_id, chapter_category],
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kwargs=p2_kwargs,
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countdown=countdown,
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task_id=_phase2_timeout_task_id(user_id, chapter_category),
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)
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logger.info(
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"event=phase2_timeout_scheduled user_id={} chapter_category={} countdown={} "
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"memoir_correlation_id={}",
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user_id,
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chapter_category,
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countdown,
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memoir_correlation_id or "",
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)
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def _dispatch_phase2_immediate(
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user_id: str, chapter_category: str, memoir_correlation_id: str | None = None
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) -> None:
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_revoke_phase2_timeout(user_id, chapter_category)
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p2_kwargs: dict = {}
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if memoir_correlation_id:
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p2_kwargs["memoir_correlation_id"] = memoir_correlation_id
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send_kw: dict = {
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"args": [user_id, chapter_category],
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"kwargs": p2_kwargs,
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}
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if settings.memoir_phase2_singleflight_immediate:
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send_kw["task_id"] = _phase2_immediate_task_id(user_id, chapter_category)
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celery_app.send_task("app.tasks.memoir_tasks.process_memoir_phase2", **send_kw)
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logger.info(
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"event=phase2_dispatched_immediate user_id={} chapter_category={} "
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"memoir_correlation_id={} task_id_mode={}",
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user_id,
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chapter_category,
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memoir_correlation_id or "",
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"singleflight" if settings.memoir_phase2_singleflight_immediate else "unique",
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)
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def dispatch_pending_memoir_phase2_for_user(user_id: str) -> None:
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"""会话结束等场景：为该用户所有待叙事类目各发一条 Phase2（幂等）。"""
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try:
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with get_sync_db() as db:
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user_convs = select(Conversation.id).where(
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Conversation.user_id == user_id,
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Conversation.deleted_at.is_(None),
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)
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stmt = (
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select(Segment.topic_category)
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.where(
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Segment.conversation_id.in_(user_convs),
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Segment.narrated.is_(False),
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Segment.skip_narrative.is_(False),
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Segment.topic_category.isnot(None),
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)
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.distinct()
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)
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cats = [r[0] for r in db.execute(stmt).all() if r[0]]
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for chapter_category in cats:
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_revoke_phase2_timeout(user_id, chapter_category)
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flush_cid = new_memoir_correlation_id()
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celery_app.send_task(
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"app.tasks.memoir_tasks.process_memoir_phase2",
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args=[user_id, chapter_category],
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kwargs={"memoir_correlation_id": flush_cid},
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)
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logger.info(
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"event=phase2_dispatched_flush user_id={} chapter_category={} "
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"memoir_correlation_id={}",
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user_id,
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chapter_category,
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flush_cid,
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)
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except Exception as e:
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logger.error(
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"event=phase2_flush_failed user_id={} exc_type={} exc={}",
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user_id,
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type(e).__name__,
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e,
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)
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@shared_task(bind=True, max_retries=3, default_retry_delay=30)
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def process_memoir_phase2(
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self,
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user_id: str,
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chapter_category: str,
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memoir_correlation_id: str | None = None,
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):
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"""Phase 2：叙事 / 路由 / 忠实度 / 标题；按类目加锁，消费未叙事且非 skip 的 segments。"""
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task_id = self.request.id
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cid = effective_correlation_id(
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explicit=memoir_correlation_id, celery_task_id=str(task_id)
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)
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logger.info(
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"event=memoir_phase2_start user_id={} task_id={} chapter_category={} "
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"memoir_correlation_id={}",
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user_id,
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task_id,
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chapter_category,
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cid,
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)
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try:
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with get_sync_db() as db:
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user_convs = select(Conversation.id).where(
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Conversation.user_id == user_id,
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Conversation.deleted_at.is_(None),
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)
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stmt = (
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select(Segment)
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.where(
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Segment.conversation_id.in_(user_convs),
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Segment.topic_category == chapter_category,
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Segment.narrated.is_(False),
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Segment.skip_narrative.is_(False),
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)
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.order_by(Segment.created_at)
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)
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category_segments = list(db.execute(stmt).scalars().all())
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if not category_segments:
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logger.info(
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"event=memoir_phase2_noop user_id={} chapter_category={}",
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user_id,
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chapter_category,
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)
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return {"status": "noop"}
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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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background_voice = "default"
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user_occupation = ""
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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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background_voice = infer_background_voice(user_obj.occupation)
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user_occupation = user_obj.occupation or ""
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image_settings = MemoirImageSettings.from_env()
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story_dispatch_ids: Set[str] = set()
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chapters_to_enqueue: Set[str] = set()
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affected_chapter_ids: Set[str] = set()
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lock_handle = _acquire_chapter_lock(
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user_id, chapter_category, ttl_seconds=_chapter_lock_ttl()
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)
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if lock_handle is None:
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logger.warning(
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"event=memoir_phase2_lock_busy user_id={} chapter_category={}",
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user_id,
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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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# 锁内再查一次，避免等待锁期间状态已变
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category_segments = list(db.execute(stmt).scalars().all())
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if not category_segments:
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return {"status": "noop"}
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state = get_or_create_state_sync(user_id, db)
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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=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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background_voice=background_voice,
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occupation=user_occupation,
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memoir_correlation_id=cid,
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)
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story_dispatch_ids |= disp
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db.flush()
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if chapter is None:
|
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logger.error(
|
||
"event=memoir_phase2_no_chapter user_id={} chapter_category={}",
|
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user_id,
|
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chapter_category,
|
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)
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db.rollback()
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raise self.retry(
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exc=RuntimeError("story_pipeline returned no chapter"),
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countdown=30,
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)
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db.refresh(chapter)
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affected_chapter_ids.add(chapter.id)
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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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)
|
||
result_book = db.execute(stmt_book)
|
||
book = result_book.scalar_one_or_none()
|
||
if not book:
|
||
book = Book(
|
||
id=str(uuid.uuid4()),
|
||
user_id=user_id,
|
||
title="我的回忆录",
|
||
total_pages=0,
|
||
total_words=0,
|
||
cover_image_url=None,
|
||
)
|
||
db.add(book)
|
||
book.has_update = True
|
||
book.last_update_chapter_id = chapter.id
|
||
|
||
if needs_cover_enqueue:
|
||
chapters_to_enqueue.add(chapter.id)
|
||
|
||
for seg in category_segments:
|
||
seg.narrated = True
|
||
seg.processed = True
|
||
|
||
db.commit()
|
||
|
||
from app.features.story.post_commit import (
|
||
enqueue_story_post_commit_effects,
|
||
)
|
||
|
||
pc = enqueue_story_post_commit_effects(
|
||
user_id=user_id,
|
||
story_ids=set(story_dispatch_ids),
|
||
chapter_ids=affected_chapter_ids,
|
||
trigger_source="pipeline_phase2",
|
||
need_compaction=True,
|
||
compaction_extra={
|
||
"pipeline_run_id": str(task_id),
|
||
"memoir_correlation_id": cid,
|
||
"story_dispatch_ids": sorted(story_dispatch_ids),
|
||
"chapters_to_enqueue": sorted(chapters_to_enqueue),
|
||
"chapter_category": chapter_category,
|
||
},
|
||
)
|
||
logger.info(
|
||
"event=story_post_commit user_id={} trigger=pipeline_phase2 "
|
||
"enqueued_story_image_count={} enqueued_chapter_recompose_count={} "
|
||
"compaction_scheduled={} errors={}",
|
||
user_id,
|
||
pc.enqueued_story_image_count,
|
||
pc.enqueued_chapter_recompose_count,
|
||
pc.compaction_scheduled,
|
||
pc.errors,
|
||
)
|
||
|
||
from app.tasks.chapter_cover_enqueue import (
|
||
try_enqueue_generate_chapter_cover,
|
||
)
|
||
|
||
for chapter_id in sorted(chapters_to_enqueue):
|
||
if try_enqueue_generate_chapter_cover(
|
||
chapter_id, source="pipeline_phase2"
|
||
):
|
||
logger.info(f"派发章节封面任务: chapter={chapter_id}")
|
||
|
||
logger.info(
|
||
"event=memoir_phase2_done user_id={} task_id={} chapter_category={} "
|
||
"segment_count={} memoir_correlation_id={}",
|
||
user_id,
|
||
task_id,
|
||
chapter_category,
|
||
len(category_segments),
|
||
cid,
|
||
)
|
||
return {
|
||
"status": "success",
|
||
"chapter_category": chapter_category,
|
||
"segments": len(category_segments),
|
||
}
|
||
finally:
|
||
_release_chapter_lock(lock_handle)
|
||
|
||
except Retry:
|
||
raise
|
||
except Exception as e:
|
||
logger.error(
|
||
"event=memoir_phase2_failed user_id={} chapter_category={} exc={}",
|
||
user_id,
|
||
chapter_category,
|
||
e,
|
||
)
|
||
raise self.retry(exc=e) from e
|
||
|
||
|
||
@shared_task(bind=True, max_retries=3, default_retry_delay=60)
|
||
def process_memoir_phase1(self, user_id: str, segment_ids: List[str]):
|
||
"""
|
||
Phase 1：记忆 ingest + 抽取/分类；持久化 topic_category / skip_narrative；
|
||
按需派发 Phase 2（阈值或延迟兜底）。
|
||
"""
|
||
task_id = self.request.id
|
||
memoir_correlation_id = new_memoir_correlation_id()
|
||
logger.info(
|
||
"event=memoir_phase1_start user_id={} task_id={} segments={} "
|
||
"memoir_correlation_id={}",
|
||
user_id,
|
||
task_id,
|
||
len(segment_ids),
|
||
memoir_correlation_id,
|
||
)
|
||
_update_task_status_sync(user_id, task_id, "running")
|
||
|
||
try:
|
||
with get_sync_db() as db:
|
||
stmt = (
|
||
select(Segment)
|
||
.where(Segment.id.in_(segment_ids))
|
||
.order_by(Segment.created_at.asc(), Segment.id.asc())
|
||
)
|
||
rows = db.execute(stmt).scalars().all()
|
||
segments = [s for s in rows if not s.narrated]
|
||
|
||
if not segments:
|
||
logger.warning("event=memoir_phase1_no_segments ids={}", segment_ids)
|
||
_update_task_status_sync(
|
||
user_id,
|
||
task_id,
|
||
"success",
|
||
{"processed": 0, "categories": []},
|
||
)
|
||
return {"status": "no_segments"}
|
||
|
||
conv_id = getattr(segments[0], "conversation_id", None) or ""
|
||
transcript = "\n\n".join(seg.user_input_text or "" for seg in segments)
|
||
if transcript.strip():
|
||
try:
|
||
from app.features.memory.service import ingest_transcript_sync
|
||
|
||
source_id = ingest_transcript_sync(db, user_id, conv_id, transcript)
|
||
logger.info(
|
||
"event=memory_transcript_ingested user_id={} task_id={} "
|
||
"source_id={} conversation_id={} transcript_chars={} "
|
||
"segment_count={}",
|
||
user_id,
|
||
task_id,
|
||
source_id,
|
||
conv_id,
|
||
len(transcript),
|
||
len(segments),
|
||
)
|
||
except Exception as e:
|
||
logger.warning(
|
||
"Memory ingest 跳过: {} exc_type={}",
|
||
e,
|
||
type(e).__name__,
|
||
)
|
||
|
||
llm = _get_llm()
|
||
llm_fast = _get_llm_fast()
|
||
if (settings.llm_fast_model or "").strip():
|
||
logger.info(
|
||
"event=llm_fast_tier_used pipeline=memoir_prepare_batches model={}",
|
||
settings.llm_fast_model,
|
||
)
|
||
|
||
memoir_orchestrator = MemoirOrchestrator()
|
||
prepared = memoir_orchestrator.prepare_batches(
|
||
segments=list(segments),
|
||
llm=llm,
|
||
llm_fast=llm_fast,
|
||
get_or_create_state=lambda: get_or_create_state_sync(user_id, db),
|
||
update_slot=lambda stage, slot_name, snippet, seg_ids: update_slot_sync(
|
||
user_id,
|
||
stage,
|
||
slot_name,
|
||
snippet,
|
||
seg_ids,
|
||
db,
|
||
memoir_batch=True,
|
||
),
|
||
)
|
||
|
||
skip_ids = prepared.segment_skip_story_ids
|
||
missing_cat = [
|
||
seg.id
|
||
for seg in segments
|
||
if not prepared.segment_chapter_category.get(str(seg.id))
|
||
]
|
||
if missing_cat:
|
||
logger.error(
|
||
"event=memoir_phase1_missing_category abort segment_ids={}",
|
||
missing_cat,
|
||
)
|
||
raise RuntimeError(
|
||
f"memoir_phase1_missing_category: {len(missing_cat)} segments"
|
||
)
|
||
|
||
for seg in segments:
|
||
cat = prepared.segment_chapter_category[str(seg.id)]
|
||
seg.topic_category = cat
|
||
is_skip = str(seg.id) in skip_ids
|
||
seg.skip_narrative = is_skip
|
||
seg.narrated = False
|
||
if is_skip:
|
||
seg.processed = True
|
||
|
||
db.flush()
|
||
|
||
categories_for_phase2: Set[str] = set()
|
||
phase2_immediate: list[str] = []
|
||
phase2_timeout: list[str] = []
|
||
for chapter_category, cat_segments in prepared.category_to_segments.items():
|
||
batch_non_skip = [
|
||
s
|
||
for s in cat_segments
|
||
if str(s.id) not in prepared.segment_skip_story_ids
|
||
]
|
||
if not batch_non_skip:
|
||
continue
|
||
max_chars = max(
|
||
len((s.user_input_text or "").strip()) for s in batch_non_skip
|
||
)
|
||
categories_for_phase2.add(chapter_category)
|
||
if _should_trigger_phase2(db, user_id, chapter_category, max_chars):
|
||
phase2_immediate.append(chapter_category)
|
||
else:
|
||
phase2_timeout.append(chapter_category)
|
||
|
||
db.commit()
|
||
|
||
for cc in phase2_immediate:
|
||
_dispatch_phase2_immediate(user_id, cc, memoir_correlation_id)
|
||
for cc in phase2_timeout:
|
||
_schedule_phase2_timeout(user_id, cc, memoir_correlation_id)
|
||
|
||
categories_processed = sorted(prepared.category_to_segments.keys())
|
||
_update_task_status_sync(
|
||
user_id,
|
||
task_id,
|
||
"success",
|
||
{
|
||
"processed": len(segments),
|
||
"categories_processed": categories_processed,
|
||
"phase2_watch_categories": sorted(categories_for_phase2),
|
||
},
|
||
)
|
||
logger.info(
|
||
"event=memoir_phase1_done user_id={} task_id={} segment_count={} "
|
||
"categories={} memoir_correlation_id={}",
|
||
user_id,
|
||
task_id,
|
||
len(segments),
|
||
categories_processed,
|
||
memoir_correlation_id,
|
||
)
|
||
return {
|
||
"status": "success",
|
||
"processed": len(segments),
|
||
"categories_processed": categories_processed,
|
||
}
|
||
|
||
except Retry:
|
||
raise
|
||
except Exception as e:
|
||
logger.error("event=memoir_phase1_failed user_id={} exc={}", user_id, e)
|
||
_update_task_status_sync(user_id, task_id, "failure", {"error": str(e)})
|
||
raise self.retry(exc=e) from e
|
||
|
||
|
||
# 兼容旧 Celery/文档入口名
|
||
process_memoir_segments = process_memoir_phase1
|
||
|
||
|
||
@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
|
||
"""
|
||
stage = normalize_chapter_category(stage, fallback="summary")
|
||
cid = effective_correlation_id(explicit=None, celery_task_id=str(self.request.id))
|
||
logger.info(
|
||
"event=generate_chapter_content_start user_id={} stage={} memoir_correlation_id={}",
|
||
user_id,
|
||
stage,
|
||
cid,
|
||
)
|
||
|
||
try:
|
||
with get_sync_db() as db:
|
||
llm = _get_llm()
|
||
user_obj = db.get(User, user_id)
|
||
user_profile = ""
|
||
user_birth_year = None
|
||
background_voice = "default"
|
||
user_occupation = ""
|
||
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,
|
||
)
|
||
background_voice = infer_background_voice(user_obj.occupation)
|
||
user_occupation = user_obj.occupation or ""
|
||
|
||
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,
|
||
background_voice=background_voice,
|
||
occupation=user_occupation,
|
||
memoir_correlation_id=cid,
|
||
)
|
||
db.flush()
|
||
if chapter is None:
|
||
logger.error(
|
||
"event=generate_chapter_content_no_chapter user_id={} stage={}",
|
||
user_id,
|
||
stage,
|
||
)
|
||
db.rollback()
|
||
raise self.retry(
|
||
exc=RuntimeError("story_pipeline returned no chapter"),
|
||
countdown=30,
|
||
)
|
||
db.commit()
|
||
db.refresh(chapter)
|
||
|
||
from app.features.story.post_commit import enqueue_story_post_commit_effects
|
||
|
||
ch_ids: set[str] = {str(chapter.id)}
|
||
pc = enqueue_story_post_commit_effects(
|
||
user_id=user_id,
|
||
story_ids=set(dispatch_ids),
|
||
chapter_ids=ch_ids,
|
||
trigger_source="pipeline",
|
||
need_compaction=False,
|
||
)
|
||
logger.info(
|
||
"event=story_post_commit user_id={} trigger=pipeline_generate_chapter "
|
||
"enqueued_story_image_count={} enqueued_chapter_recompose_count={} "
|
||
"compaction_scheduled={} errors={}",
|
||
user_id,
|
||
pc.enqueued_story_image_count,
|
||
pc.enqueued_chapter_recompose_count,
|
||
pc.compaction_scheduled,
|
||
pc.errors,
|
||
)
|
||
|
||
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 Retry:
|
||
raise
|
||
except Exception as e:
|
||
logger.error(f"章节生成失败: {e}")
|
||
raise self.retry(exc=e) from e
|