Files
beige/backend/app/services/fission_service.py
yangqianqian d85dcd401b 第11环裂变重写:对齐上线版 split.js 一次LLM出N套完整笔记包
架构从"扇出N个GenerationTask各跑完整管道"改为"一次LLM调用直接出N套
完整笔记包(N=1~5)",落 FissionNote 表 + 独立展示页。

后端:
- 018迁移:fission_notes 表(文案JSON+score+passed+imagePlan+images+status)
- fission_prompt:FISSION_SYSTEM+三档参考度(low/mid/high)+normalize_tags+品类兜底
- fission_pipeline:一次LLM出N套→各评分(@80合格线)→排序→落库,不达标标
  needs_optimization 非丢弃;apiports 503 回落 codeproxy gpt-5.5 强档兜底
- fission_images:每套串行调现有生图接口(零改动image_gen/storyboard)
- tasks.py:run_fission_pipeline Celery task,删旧扇出注入
- api/v1/fission:进度聚合FissionNote + GET /fission/{id}/notes(剥内部字段)

前端:FissionProgress对齐状态机 + N套独立展示页 + FissionNoteCard

测试:test_fission_engine(19)+test_fission_pipeline(5) 全过;104 全量回归绿

实测task5(fanout=2,mid)端到端跑通:一次出2套→seq0=85过/seq1=79标优化→
生图codeproxy/edits→1024×1536去AI化→task completed→notes端点返完整数据

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-18 11:17:37 +08:00

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"""
app/services/fission_service.py — 第11环裂变 service 入口(对齐上线版 split.js
裂变 = 1爆款 → 一次 LLM 出 N 套完整笔记包N=1~5
本文件只留 API 入口:
- create_fission建 FissionTask 后丢 run_fission_pipeline.delay不再扇出 GenerationTask
编排层(解析/评分/落库/生图)在 app/services/fission_pipeline.py红线≤200行已拆
"""
import json
import logging
from sqlalchemy.orm import Session
from app.core.response import raise_business
from app.middleware.workspace_guard import CurrentUser
from app.models.fission import FissionTask
from app.models.task import GenerationTask
from app.services.ai_engine.fission_prompt import valid_level
from app.services.task_service import _check_user_has_key
logger = logging.getLogger(__name__)
MAX_FANOUT = 5 # 每用户并发上限5(红线);裂变 N 套直出受同等约束
def create_fission(
db: Session, current_user: CurrentUser,
source_task_id: int, reference_level: str, fanout_count: int,
) -> tuple[int, list[int]]:
"""
从一个源任务建裂变任务,丢 Celery 一次出 N 套笔记包。
返回 (fission_id, [])。子笔记落 FissionNote不再扇出 GenerationTask
故第二个返回值恒为空列表(保留签名兼容旧调用方)。
"""
_check_user_has_key(db, current_user.user_id, current_user.workspace_id)
level = valid_level(reference_level)
n = max(1, min(fanout_count or 3, MAX_FANOUT))
# 读源任务(取产品+主题+已选文案作为爆款源)
src = db.query(GenerationTask).filter(
GenerationTask.id == source_task_id,
GenerationTask.workspace_id == current_user.workspace_id,
).first()
if not src:
raise_business("裂变源任务不存在")
source_note = {"title": src.theme or "", "content": _extract_source_copy(db, src)}
# 建 fission_task 记录(带 source_task_id 供 pipeline 取产品/张数)
ft = FissionTask(
workspace_id=current_user.workspace_id,
source_note=json.dumps(source_note, ensure_ascii=False),
reference_level=level, fanout_count=n, status="generating",
)
db.add(ft); db.commit(); db.refresh(ft)
# 丢 Celery一次 LLM 出 N 套(不扇出 GenerationTask
from app.workers.tasks import run_fission_pipeline
run_fission_pipeline.delay(ft.id, source_task_id)
logger.info("fission created id=%s level=%s n=%s src_task=%s",
ft.id, level, n, source_task_id)
return ft.id, []
def _extract_source_copy(db: Session, src: GenerationTask) -> str:
"""取源任务已选/最高分文案当爆款正文;无则用主题兜底。"""
from app.models.task import TextCandidate
c = (db.query(TextCandidate)
.filter(TextCandidate.task_id == src.id)
.order_by(TextCandidate.is_selected.desc(), TextCandidate.id.asc())
.first())
if c and c.content:
return c.content
return src.theme or ""