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>
This commit is contained in:
yangqianqian
308
backend/app/api/v1/products.py
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308
backend/app/api/v1/products.py
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"""
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app/api/v1/products.py — 品牌库路由（管理员）
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products / benchmark_notes / banned_words
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category 是纯数据字段，不在代码里做枚举（基石A）。
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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, UploadFile, File
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from pydantic import BaseModel
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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_admin, require_write_permission
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from app.models.product import BannedWord, BenchmarkNote, Product
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logger = logging.getLogger(__name__)
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router = APIRouter(tags=["products"])
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# ── DTO ────────────────────────────────────────────────────
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class ProductCreate(BaseModel):
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name: str
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category: str | None = None # 纯数据字段，不做枚举（基石A）
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source: str = "custom" # preset | custom
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selling_points: list[str] = []
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style_tone: str | None = None
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text_angles: list[str] = [] # 用户设定，不写死（基石A）
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custom_prompt: str | None = None # 等北哥方案注入
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banned_word_ids: list[int] = []
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image_path: str | None = None # 产品参考图(可建档即带；通常走 upload-image 接口)
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brand_keyword: str | None = None # 品牌词，客户录入，012:套2字段暴露
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target_audience: str | None = None # 目标人群，客户录入，012:套2字段暴露
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class BenchmarkCreate(BaseModel):
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screenshot_url: str | None = None
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highlights: str | None = None
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link_url: str | None = None
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class BannedWordCreate(BaseModel):
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word: str
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level: str # auto_fix | soft_warn | hard_block
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replacement: str | None = None
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updatable: bool = True
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def _fmt_product(p: Product) -> dict:
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import json
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return {
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"id": p.id, "name": p.name, "category": p.category,
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"source": p.source, "is_active": p.is_active,
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"selling_points": json.loads(p.selling_points) if p.selling_points else [],
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"style_tone": p.style_tone,
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"text_angles": json.loads(p.text_angles) if p.text_angles else [],
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"custom_prompt": p.custom_prompt,
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"image_path": p.image_path,
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"brand_keyword": p.brand_keyword, # 012: 套2字段暴露
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"target_audience": p.target_audience, # 012: 套2字段暴露
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"created_at": p.created_at.isoformat(),
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}
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# ── 产品档案 ────────────────────────────────────────────────
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@router.get("/products")
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def list_products(
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page: int = 1, page_size: int = 20, source: str | None = 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(Product).filter(Product.workspace_id == current_user.workspace_id, Product.is_active == True)
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if source in ("preset", "custom"):
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q = q.filter(Product.source == source)
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total = q.count()
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items = q.offset((page - 1) * page_size).limit(page_size).all()
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return ok(paginate([_fmt_product(p) for p in items], total, page, page_size))
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@router.post("/products")
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def create_product(
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body: ProductCreate,
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current_user: Annotated[CurrentUser, Depends(require_admin)] = None,
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db: Session = Depends(get_db),
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):
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import json
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p = Product(
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workspace_id=current_user.workspace_id,
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name=body.name, category=body.category, source=body.source,
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selling_points=json.dumps(body.selling_points, ensure_ascii=False),
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style_tone=body.style_tone,
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text_angles=json.dumps(body.text_angles, ensure_ascii=False),
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custom_prompt=body.custom_prompt,
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image_path=body.image_path or None,
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brand_keyword=body.brand_keyword or None, # 012: 套2字段
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target_audience=body.target_audience or None, # 012: 套2字段
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)
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db.add(p)
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db.commit()
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db.refresh(p)
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return ok(_fmt_product(p))
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@router.get("/products/{product_id}")
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def get_product(
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product_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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p = db.query(Product).filter(Product.id == product_id, Product.workspace_id == current_user.workspace_id).first()
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if not p:
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raise_not_found("产品不存在")
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return ok(_fmt_product(p))
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@router.put("/products/{product_id}")
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def update_product(
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product_id: int, body: ProductCreate,
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current_user: Annotated[CurrentUser, Depends(require_admin)] = None,
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db: Session = Depends(get_db),
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):
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import json
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p = db.query(Product).filter(Product.id == product_id, Product.workspace_id == current_user.workspace_id).first()
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if not p:
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raise_not_found("产品不存在")
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p.name = body.name; p.category = body.category; p.source = body.source
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p.selling_points = json.dumps(body.selling_points, ensure_ascii=False)
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p.style_tone = body.style_tone
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p.text_angles = json.dumps(body.text_angles, ensure_ascii=False)
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p.custom_prompt = body.custom_prompt
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p.brand_keyword = body.brand_keyword or None # 012: 套2字段
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p.target_audience = body.target_audience or None # 012: 套2字段
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db.commit(); db.refresh(p)
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return ok(_fmt_product(p))
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@router.delete("/products/{product_id}")
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def delete_product(
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product_id: int,
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current_user: Annotated[CurrentUser, Depends(require_admin)] = None,
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db: Session = Depends(get_db),
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):
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p = db.query(Product).filter(Product.id == product_id, Product.workspace_id == current_user.workspace_id).first()
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if not p:
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raise_not_found("产品不存在")
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p.is_active = False # 软删
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db.commit()
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return ok({"deleted": product_id})
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# ── 产品参考图上传 ──────────────────────────────────────────
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_ALLOWED_CONTENT_TYPES = {"image/jpeg", "image/png", "image/webp"}
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_MAX_SIZE_BYTES = 10 * 1024 * 1024 # 10 MB
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@router.post("/products/{product_id}/upload-image")
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async def upload_product_image(
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product_id: int,
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file: UploadFile = File(...),
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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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"""
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上传产品参考图（铁律：生图必须带产品图）。
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文件类型：JPEG/PNG/WebP；大小上限 10 MB。
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存储路径：uploads/products/{workspace_id}/{product_id}/{filename}
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写回 product.image_path，生图管道读此字段构建 reference_images。
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"""
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from app.core.response import raise_business
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from app.core.config import get_settings
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import os, uuid
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p = db.query(Product).filter(
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Product.id == product_id,
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Product.workspace_id == current_user.workspace_id,
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).first()
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if not p:
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raise_not_found("产品不存在")
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if file.content_type not in _ALLOWED_CONTENT_TYPES:
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raise_business(f"不支持的文件类型 {file.content_type}，仅支持 JPEG/PNG/WebP")
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data = await file.read()
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if len(data) > _MAX_SIZE_BYTES:
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raise_business("文件超过 10 MB 限制")
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settings = get_settings()
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ext = os.path.splitext(file.filename or "img.jpg")[1] or ".jpg"
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# 存绝对路径：锚定 StaticFiles 根 /app/uploads，避免 worker(cwd=/) 读不到。
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abs_dir = os.path.join(settings.UPLOAD_ABS_ROOT, "products",
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str(current_user.workspace_id), str(product_id))
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os.makedirs(abs_dir, exist_ok=True)
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filename = f"{uuid.uuid4().hex}{ext}"
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save_path = os.path.join(abs_dir, filename)
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with open(save_path, "wb") as f:
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f.write(data)
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p.image_path = save_path # 绝对路径，worker 直接 open 可读
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db.commit()
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db.refresh(p)
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logger.info("product image uploaded: product_id=%s path=%s", product_id, save_path)
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return ok(_fmt_product(p))
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# ── 套1 产品图视觉分析 ────────────────────────────────────────
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_VISION_PROMPT = """你是小红书产品种草策划。请根据产品图分析卖点与人群。
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硬性规则：只分析本次上传图片，不沿用历史案例，不默认护肤品。
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返回JSON（仅JSON，无其他文字）：
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{
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"productName": "从包装识别，识别不到填空",
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"category": "美妆护肤/个护护理/食品饮品/营养健康/家居生活/服饰穿搭/电商产品之一",
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"sellingPoints": ["转成用户买点，不要品牌空话，3-6个"],
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"targetAudience": "一句话描述核心人群",
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"scenarios": ["使用场景，2-4个"],
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"keywords": ["小红书搜索关键词，3-5个"],
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"bannedWords": ["合规禁用词"],
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"imageDirection": "这组图如何拍/排版，一句话",
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"confidence": 0.9,
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"source": "vision"
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}"""
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def _parse_vision_json(raw: str) -> dict:
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"""从模型返回文本中提取JSON（容错 markdown ```json 代码块）"""
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import json, re
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# 去掉 markdown 代码块包裹
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cleaned = re.sub(r"```json\s*", "", raw)
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cleaned = re.sub(r"```\s*", "", cleaned)
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# 提取第一个 {...} 块
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m = re.search(r"\{[\s\S]*\}", cleaned)
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if not m:
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raise ValueError("vision 返回内容中未找到 JSON")
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return json.loads(m.group())
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def _fallback_analysis(product_name: str = "") -> dict:
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"""vision 失败时的文字兜底，保证接口不空手返回"""
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return {
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"productName": product_name or "产品",
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"category": "电商产品",
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"sellingPoints": ["使用方便", "适合日常场景"],
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"targetAudience": "有明确使用场景和效率诉求的人群",
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"scenarios": ["日常使用", "通勤出门"],
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"keywords": [product_name or "好物", "真实测评", "种草分享"],
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"bannedWords": ["美白", "祛斑", "速效", "医用", "药妆"],
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"imageDirection": "产品白底图保证准确，真实场景图突出使用体验",
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"confidence": 0.45,
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"source": "fallback",
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}
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@router.post("/products/{product_id}/analyze-image")
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async def analyze_product_image(
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product_id: int,
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file: UploadFile = File(...),
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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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"""
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套1：上传产品图 → GPT vision 读图 → 返回结构化卖点/人群分析。
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key 链路：从当前用户 API key 解密（基石B）；plain_key 只活在局部变量。
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"""
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from app.core.response import raise_business
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from app.models.workspace import UserApiKey
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from app.utils.fernet_utils import decrypt_key
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from app.services.ai_engine.gemini_factory import build_ai_clients
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# 文件校验（复用 upload_product_image 同款规则）
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if file.content_type not in _ALLOWED_CONTENT_TYPES:
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raise_business(f"不支持的文件类型 {file.content_type}，仅支持 JPEG/PNG/WebP")
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data = await file.read()
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if len(data) > _MAX_SIZE_BYTES:
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raise_business("文件超过 10 MB 限制")
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# key 解密（照抄 pipeline_steps.decrypt_user_key，基石B）
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api_key_row = db.query(UserApiKey).filter(
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UserApiKey.user_id == current_user.user_id,
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UserApiKey.workspace_id == current_user.workspace_id,
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UserApiKey.provider.in_(["openai", "apiports"]),
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).first()
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if not api_key_row:
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raise_business("未配置 API Key，请先在设置中录入")
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plain_key = decrypt_key(api_key_row.encrypted_key)
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clients = build_ai_clients(plain_key)
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plain_key = None # 立即清零，不传出（基石B）
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try:
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raw = await clients.gpt_vision_analyze(_VISION_PROMPT, [data])
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try:
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result = _parse_vision_json(raw)
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result["source"] = "vision"
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except Exception as parse_err:
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logger.warning("vision JSON parse failed, fallback: %s", parse_err)
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result = _fallback_analysis()
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result["warning"] = f"视觉分析解析失败，已使用文字兜底：{parse_err}"
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except Exception as e:
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logger.warning("vision_analyze failed, fallback: %s", e)
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result = _fallback_analysis()
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result["warning"] = f"视觉分析失败，已使用文字兜底：{e}"
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finally:
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await clients.aclose()
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logger.info("analyze_product_image done: product_id=%s source=%s conf=%.2f",
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product_id, result.get("source"), result.get("confidence", 0))
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return ok(result)
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Reference in New Issue
Block a user