Files
life-echo/api/app/tasks/memoir_tasks.py
Kevin aac484463d feat(api): 拆分章节物化与 Story 后处理,并加固 Redis 锁与腾讯 ASR
回忆录 Story 流水线(同步)
- 同步路径仅写入 Story 与章节关联,改为 mark_chapter_dirty_sync,不再内联 compose
- 物化由 Celery recompose_chapter 异步完成;compose 不变量与异常时保留 dirty 的语义在 repo 中补充说明
- Evidence:大批次时降低 top_k;路由候选 story 携带 char_count/version_count;append 超长/版本过多时强制新开 story
- 叙事 prompt:relevant_chunks 去重,减少重复证据噪声
- 叙事回退与忠实度 gate:返回 fallback 类型并记录结构化日志(含耗时、JSON 有效性等)

Post-commit 与任务编排
- 新增 post_commit.enqueue_story_post_commit_effects:统一派发 generate_story_image(Redis 去重)、延迟 recompose_chapter、可选 memory compaction
- memoir_tasks / story_service / story_image_tasks 改为调用 post-commit 入口;主图回填后按关联章节重算并调度物化与 compacs(锁委托、Redis 单例、ASR to_thread)
- 更新 test_narrative_pipeline 以适配 _apply_narrative_fallbacks 返回值
2026-03-30 11:53:04 +08:00

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"""
回忆录处理 Celery 任务
"""
import json
import uuid
from datetime import datetime, timezone
from typing import Dict, List, Set
import redis
from celery import shared_task
from sqlalchemy import select
from sqlalchemy.orm import Session
from app.agents.chat.prompts_profile import format_user_profile_context
from app.agents.memoir import MemoirOrchestrator
from app.agents.state_schema import MemoirStateSchema, SlotData, default_state
from app.core.chapter_pipeline_lock import (
acquire_chapter_pipeline_lock as _acquire_chapter_lock,
)
from app.core.chapter_pipeline_lock import (
release_chapter_pipeline_lock as _release_chapter_lock,
)
from app.core.config import settings
from app.core.db import get_sync_db
from app.core.dependencies import get_llm_provider
from app.core.logging import get_logger
from app.features.conversation.models import Segment
from app.features.memoir.cover_eligibility import (
chapter_needs_cover_enqueue,
)
from app.features.memoir.memoir_images.parser import (
build_initial_image_assets,
)
from app.features.memoir.memoir_images.schema import (
IMAGE_STATUS_COMPLETED,
IMAGE_STATUS_FAILED,
IMAGE_STATUS_PENDING,
normalize_image_assets,
)
from app.features.memoir.memoir_images.serializers import (
image_dict_to_row_kwargs,
)
from app.features.memoir.memoir_images.settings import MemoirImageSettings
from app.features.memoir.models import (
Book,
MemoirImage,
MemoirState,
)
from app.features.memoir.story_pipeline_sync import (
run_story_pipeline_for_category_batch,
)
from app.features.user.models import User
logger = get_logger(__name__)
_REDIS_CLIENTS: dict[bool, redis.Redis] = {}
def _get_llm():
"""Celery 任务内获取 LangChain LLM通过 port"""
try:
return getattr(get_llm_provider(), "langchain_llm", None)
except Exception:
return None
def _get_redis_client(*, decode_responses: bool = False) -> redis.Redis:
from app.core.config import settings
client = _REDIS_CLIENTS.get(decode_responses)
if client is None:
client = redis.from_url(
settings.redis_url,
decode_responses=decode_responses,
)
_REDIS_CLIENTS[decode_responses] = client
return client
def _chapter_lock_ttl() -> int:
return int(settings.chapter_pipeline_lock_ttl_seconds)
def _update_task_status_sync(
user_id: str, task_id: str, status: str, result: Dict = None
):
"""同步更新任务状态(在 Celery 任务中使用)"""
try:
r = _get_redis_client(decode_responses=True)
key = f"task:user:{user_id}:tasks"
# 获取现有任务信息
data = r.hget(key, task_id)
if data:
task_info = json.loads(data)
else:
task_info = {"task_id": task_id}
task_info["status"] = status
task_info["updated_at"] = datetime.now(timezone.utc).isoformat()
if result is not None:
task_info["result"] = result
r.hset(key, task_id, json.dumps(task_info))
r.expire(key, 3600) # 1小时过期
logger.debug("任务状态已更新: task_id={} status={}", task_id, status)
except Exception as e:
logger.error(f"更新任务状态失败: {e}")
def _merge_chapter_image_assets(
existing_images: list[dict] | None,
placeholders: list[dict],
provider: str,
style: str,
size: str,
now_iso: str,
) -> list[dict]:
normalized_existing_images = normalize_image_assets(existing_images)
existing_by_placeholder = {
item.get("placeholder"): dict(item)
for item in normalized_existing_images
if item.get("placeholder")
}
merged_assets: list[dict] = []
for item in placeholders:
existing = existing_by_placeholder.get(item["placeholder"])
if existing:
merged_item = dict(existing)
merged_item["index"] = item["index"]
merged_item["placeholder"] = item["placeholder"]
merged_item["description"] = item["description"]
merged_item["provider"] = merged_item.get("provider") or provider
merged_item["style"] = merged_item.get("style") or style
merged_item["size"] = merged_item.get("size") or size
merged_item["created_at"] = merged_item.get("created_at") or now_iso
merged_item["updated_at"] = merged_item.get("updated_at") or now_iso
if merged_item.get("status") == IMAGE_STATUS_COMPLETED and not (
merged_item.get("storage_key") or merged_item.get("url")
):
merged_item["status"] = IMAGE_STATUS_FAILED
merged_item["error"] = merged_item.get("error") or "missing image url"
else:
merged_item = build_initial_image_assets(
placeholders=[item],
provider=provider,
style=style,
size=size,
now_iso=now_iso,
)[0]
merged_assets.append(merged_item)
return merged_assets
def chapter_has_images_to_generate(images: list[dict] | None) -> bool:
return any(
item.get("status") in {IMAGE_STATUS_PENDING, IMAGE_STATUS_FAILED}
for item in normalize_image_assets(images)
)
def _memoir_image_from_asset(
chapter_id: str,
order_index: int,
image_asset: dict,
) -> MemoirImage:
"""从单条图片 dict 构建 MemoirImage 行(用于写入 memoir_images 表)。"""
kwargs = image_dict_to_row_kwargs(image_asset)
return MemoirImage(
id=str(uuid.uuid4()).replace("-", "")[:32],
chapter_id=chapter_id,
order_index=order_index,
**kwargs,
)
def _coerce_state(model: MemoirState) -> MemoirStateSchema:
"""将数据库模型转换为 Schema"""
return MemoirStateSchema.model_validate(
{
"stage_order": model.stage_order or default_state().stage_order,
"current_stage": model.current_stage,
"covered_stages": model.covered_stages or [],
"slots": model.slots
if isinstance(model.slots, dict)
else default_state().slots,
}
)
def _get_or_create_state_sync(user_id: str, db: Session) -> MemoirStateSchema:
"""同步获取或创建状态"""
stmt = select(MemoirState).where(MemoirState.user_id == user_id)
result = db.execute(stmt)
state = result.scalar_one_or_none()
if state:
return _coerce_state(state)
default = default_state()
state = MemoirState(
id=str(uuid.uuid4()),
user_id=user_id,
stage_order=default.stage_order,
current_stage=default.current_stage,
covered_stages=default.covered_stages,
slots={
k: {sk: sv.model_dump() for sk, sv in v.items()}
for k, v in default.slots.items()
},
)
db.add(state)
db.commit()
db.refresh(state)
return _coerce_state(state)
def _update_slot_sync(
user_id: str,
stage: str,
slot_name: str,
snippet: str,
segment_ids: List[str],
db: Session,
) -> MemoirStateSchema:
"""同步更新 slot"""
stmt = select(MemoirState).where(MemoirState.user_id == user_id)
result = db.execute(stmt)
state = result.scalar_one_or_none()
if not state:
_get_or_create_state_sync(user_id, db)
result = db.execute(stmt)
state = result.scalar_one()
slots: Dict[str, Dict] = state.slots or {}
stage_slots = slots.get(stage, {})
existing = stage_slots.get(slot_name, {})
merged_segment_ids = list({*(existing.get("segment_ids") or []), *segment_ids})
stage_slots[slot_name] = SlotData(
snippet=snippet, segment_ids=merged_segment_ids
).model_dump()
slots[stage] = stage_slots
state.slots = slots
state.current_stage = stage
db.commit()
db.refresh(state)
return _coerce_state(state)
@shared_task(bind=True, max_retries=3, default_retry_delay=60)
def process_memoir_segments(self, user_id: str, segment_ids: List[str]):
"""
处理回忆录段落的 Celery 任务
Args:
user_id: 用户 ID
segment_ids: 段落 ID 列表
"""
task_id = self.request.id
logger.info(
f"开始处理回忆录段落: user_id={user_id}, task_id={task_id}, segments={len(segment_ids)}"
)
# 更新任务状态为 running
_update_task_status_sync(user_id, task_id, "running")
try:
with get_sync_db() as db:
# 获取段落
stmt = select(Segment).where(Segment.id.in_(segment_ids))
result = db.execute(stmt)
segments = result.scalars().all()
if not segments:
logger.warning(f"未找到段落: {segment_ids}")
return {"status": "no_segments"}
# Memory ingest 先于回忆录流水线 commit保证后续 retrieve_evidence_sync 可见本批 chunk
# (见 api/docs/memory-retrieval.md
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()
image_settings = MemoirImageSettings.from_env()
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,
)
story_dispatch_ids: Set[str] = set()
memoir_orchestrator = MemoirOrchestrator()
prepared = memoir_orchestrator.prepare_batches(
segments=list(segments),
llm=llm,
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)
),
)
chapters_to_enqueue: Set[str] = set()
affected_chapter_ids: Set[str] = set()
for (
chapter_category,
category_segments,
) in prepared.category_to_segments.items():
lock_handle = _acquire_chapter_lock(
user_id, chapter_category, ttl_seconds=_chapter_lock_ttl()
)
if lock_handle is None:
logger.warning(
"章节锁竞争: category={}, 延迟重试",
chapter_category,
)
raise self.retry(countdown=10)
try:
chapter, needs_cover, disp = run_story_pipeline_for_category_batch(
db,
user_id=user_id,
chapter_category=chapter_category,
category_segments=category_segments,
state=prepared.state,
user_profile=user_profile,
user_birth_year=user_birth_year,
llm=llm,
)
story_dispatch_ids |= disp
db.flush()
db.refresh(chapter)
affected_chapter_ids.add(chapter.id)
needs_cover_enqueue = (
image_settings.enabled and chapter_needs_cover_enqueue(chapter)
)
stmt_book = (
select(Book)
.where(Book.user_id == user_id)
.order_by(Book.updated_at.desc())
)
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 chapter and needs_cover_enqueue:
chapters_to_enqueue.add(chapter.id)
finally:
_release_chapter_lock(lock_handle)
# 标记段落为已处理
for seg in segments:
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",
need_compaction=True,
compaction_extra={
"pipeline_run_id": str(task_id),
"story_dispatch_ids": sorted(story_dispatch_ids),
"chapters_to_enqueue": sorted(chapters_to_enqueue),
},
)
logger.info(
"event=story_post_commit user_id={} trigger=pipeline "
"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"):
logger.info(f"派发章节封面任务: chapter={chapter_id}")
categories_processed = sorted(prepared.category_to_segments.keys())
logger.info(
"回忆录处理完成: user_id={} task_id={} segment_count={} "
"categories_processed={}",
user_id,
task_id,
len(segments),
categories_processed,
)
# 更新任务状态为成功
_update_task_status_sync(
user_id,
task_id,
"success",
{
"processed": len(segments),
"categories_processed": categories_processed,
},
)
return {
"status": "success",
"processed": len(segments),
"categories_processed": categories_processed,
}
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.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.features.story.post_commit import enqueue_story_post_commit_effects
ch_ids: set[str] = set()
if chapter is not None:
ch_ids.add(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 Exception as e:
logger.error(f"章节生成失败: {e}")
raise self.retry(exc=e) from e