baseline: Clover 独立仓库首次基线提交
将 Clover 从上层产品包旧仓库中独立出来,建立专属版本控制。 当前状态=纵切片端到端已打通(登录→选品→出文出图→审核→下载包), M1文案质量去套路化已验收。此提交作为后续按核销清单逐条修复的基线。 Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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yangqianqian
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backend/app/api/v1/tasks.py
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backend/app/api/v1/tasks.py
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"""
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app/api/v1/tasks.py — 任务路由（查询层）
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发起任务 / 任务列表 / 任务详情
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操作类端点（选文案/选图/导入/重生成/提审/偏好上下文）在 task_actions.py。
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"""
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import logging
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from typing import Annotated
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from fastapi import APIRouter, Depends, Query
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from pydantic import BaseModel, field_validator
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from sqlalchemy.orm import Session
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from app.core.database import get_db
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from app.core.response import ok, paginate, raise_not_found
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from app.middleware.workspace_guard import CurrentUser, require_write_permission
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from app.models.task import GenerationTask, ImageCandidate, TextCandidate
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/tasks", tags=["tasks"])
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# ── DTO ────────────────────────────────────────────────────
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class CreateTaskRequest(BaseModel):
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product_id: int
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benchmark_ids: list[int] = []
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theme: str | None = None
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text_count: int = 5 # 不写死（基石A），用户设定
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image_count: int = 3 # 不写死（基石A），用户设定
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track: str = "ai" # ai | import
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need_product_image: bool = True # 本次产品是否入镜：True=无图禁生成不降级
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@field_validator("text_count", "image_count")
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@classmethod
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def positive(cls, v: int) -> int:
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if v < 1 or v > 20:
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raise ValueError("数量范围 1-20")
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return v
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@field_validator("track")
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@classmethod
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def valid_track(cls, v: str) -> str:
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if v not in ("ai", "import"):
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raise ValueError("track 必须是 ai 或 import")
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return v
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class SelectCandidateRequest(BaseModel):
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candidate_id: int
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class ImportTextRequest(BaseModel):
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content: str
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angle_label: str | None = None
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# ── 格式化辅助 ──────────────────────────────────────────────
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def _fmt_task(t: GenerationTask) -> dict:
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return {
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"id": t.id, "product_id": t.product_id, "theme": t.theme,
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"status": t.status, "text_count": t.text_count, "image_count": t.image_count,
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"track": t.track, "need_product_image": t.need_product_image,
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"created_at": t.created_at.isoformat(),
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}
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def _score_array_to_obj(arr) -> dict:
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"""score_json 是评分明细数组 [{item,score,max,note}]。
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AI评委7维(2026-06-15新版：痛点18/情绪18/买点18/钩子15/标题13/真实感13+合规5)
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或旧机械5维均可处理。
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total 直接对明细求和(不依赖固定key)，透传 dims 给前端 ScoreDimBars 数据驱动渲染。
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同时填旧5维key保持兼容(能映射的填，映射不上的为0)。"""
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# 旧5维 + 新7维维度名 → 旧key 的映射表（兼容新旧两套维度名）
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legacy = {
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# 旧机械维度
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"标题吸引力": "title", "标题点击力": "title",
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"情绪共鸣": "emotion", "情绪张力": "emotion",
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"买点表达": "selling", "买点转化": "selling",
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"关键词覆盖": "keyword", "合规性": "compliance",
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# 新AI评委维度（2026-06-15）→ 最近似旧key
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"痛点人群精准": "keyword", # 痛点人群精准语义最接近旧关键词(均为"内容精准度")
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"开头钩子": "emotion", # 钩子即情绪抓点，归入 emotion
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"真实感": "selling", # 真实感/买点转化同属"用户感知"维度
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# "产品聚焦一件事" 已被"真实感"替换，保留映射避免旧存量数据报 KeyError
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"产品聚焦一件事": "selling",
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}
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obj = {"title": 0, "emotion": 0, "selling": 0, "keyword": 0, "compliance": 0,
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"total": 0, "dims": []}
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if isinstance(arr, list):
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total = 0
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for d in arr:
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if not isinstance(d, dict):
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continue
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item = d.get("item", "")
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sc = d.get("score", 0) or 0
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total += sc
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obj["dims"].append({"item": item, "score": sc,
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"max": d.get("max", 0), "note": d.get("note", "")})
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key = legacy.get(item)
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if key:
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obj[key] = sc
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obj["total"] = max(0, min(100, total))
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return obj
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def _fmt_text(tc: TextCandidate) -> dict:
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import json
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# content 列存整条 JSON dict（含 title/content/tags/angle 等），解包后分字段返回
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parsed: dict = {}
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if tc.content:
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try:
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parsed = json.loads(tc.content)
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except (json.JSONDecodeError, ValueError):
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# 兼容旧数据：如果 content 已经是纯正文则原样返回
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parsed = {"content": tc.content}
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score_raw = json.loads(tc.score_json) if tc.score_json else None
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return {
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"candidate_id": tc.id,
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"angle_label": tc.angle_label,
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"title": parsed.get("title", ""),
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"content": parsed.get("content", ""), # 纯正文，前端直接展示
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"tags": parsed.get("tags", []),
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"cover_title": parsed.get("coverTitle", ""),
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"image_brief": parsed.get("imageBrief", ""),
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"source": tc.source,
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"score": _score_array_to_obj(score_raw), # 转成 {title,emotion,...,total,dims} 对象
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"banned_word_status": tc.banned_word_status,
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"is_selected": tc.is_selected,
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# AI 评委总评（verdict/summary 存在 content 列，新数据有，旧数据为空字符串降级）
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"verdict": parsed.get("verdict", ""), # "优秀"|"合格"|"不合格"
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"summary": parsed.get("summary", ""), # 一句话总评含改进点
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}
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def _fmt_image(ic: ImageCandidate) -> dict:
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return {
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"candidate_id": ic.id, "role": ic.role, "url": ic.url,
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"strategy": ic.strategy, "seq": ic.seq, "is_selected": ic.is_selected,
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}
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def _check_task_ownership(task: GenerationTask | None, workspace_id: int) -> GenerationTask:
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if not task or task.workspace_id != workspace_id:
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raise_not_found("任务不存在")
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return task
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# ── 路由 ───────────────────────────────────────────────────
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@router.post("")
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def create_task(
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body: CreateTaskRequest,
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current_user: Annotated[CurrentUser, Depends(require_write_permission)],
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db: Session = Depends(get_db),
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):
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"""发起任务：校验有无 key → 只推 task_id 入队，绝不传 key。"""
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from app.services.task_service import create_generation_task
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task = create_generation_task(db, current_user, body)
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return ok(_fmt_task(task))
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@router.get("")
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def list_tasks(
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page: int = 1, page_size: int = 20,
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status: list[str] | None = Query(default=None),
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current_user: Annotated[CurrentUser, Depends(require_write_permission)] = None,
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db: Session = Depends(get_db),
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):
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q = db.query(GenerationTask).filter(GenerationTask.workspace_id == current_user.workspace_id)
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if status:
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# 支持多状态(?status=approved&status=rejected)，单值也兼容
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q = q.filter(GenerationTask.status.in_(status))
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total = q.count()
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items = q.order_by(GenerationTask.created_at.desc()).offset((page - 1) * page_size).limit(page_size).all()
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return ok(paginate([_fmt_task(t) for t in items], total, page, page_size))
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@router.get("/{task_id}")
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def get_task(
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task_id: int,
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current_user: Annotated[CurrentUser, Depends(require_write_permission)] = None,
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db: Session = Depends(get_db),
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):
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task = db.query(GenerationTask).filter(GenerationTask.id == task_id).first()
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task = _check_task_ownership(task, current_user.workspace_id)
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texts = db.query(TextCandidate).filter(TextCandidate.task_id == task_id).all()
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images = db.query(ImageCandidate).filter(ImageCandidate.task_id == task_id).all()
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return ok({
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**_fmt_task(task),
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"text_candidates": [_fmt_text(tc) for tc in texts],
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"image_candidates": [_fmt_image(ic) for ic in images],
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})
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