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