3218485270
5ab5cf6586
- 自定义模式：分析模型输出 delta 唯一改动指令，生图模板 custom_image_prompt.md（{delta} 占位符），不再使用负向提示词；generate_design 按 custom_mode 分支，Pinterest 模式保留原创化指令，两模式互不影响
- 多模态分析 response_format 三级回退（json_schema → json_object → none），兼容 DeepSeek
- 模板导出：details 扩展列（细节1/2/3）、target_audience 扩展列（适用人群1）、固定值风格1=休闲/风格2=运动
- 童装特征库更新 + 标题模板外部化 + 图源映射增强
379 lines
15 KiB
Python
379 lines
15 KiB
Python
"""Pinterest 参考模式共享辅助：种子词加载、已用搜索词持久化、搜索词全局过滤、设计图全局 MD5 去重。
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独立于 Google Trends 采集链路，供 pinterest_search / scrape / analyze 节点复用。
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"""
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import hashlib
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import json
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import random
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import re
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import threading
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import time
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from pathlib import Path
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from typing import Any, Dict, List
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from graph.paths import project_root, runtime_root
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# 不适合 T 恤印花的类目关键词（复用 product_batch 的兜底清单）
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_UNSUITABLE = re.compile(
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r"\b(nails?|manicure|pedicure|recipes?|cooking|lottery|jackpot|results?|score|scores?|"
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r"fixtures?|forecast|weather|temperature|map|directions?|parking|opening hours?|"
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r"prices?|price|reviews?|jobs?|salary|mortgage|council tax|election|referendum|"
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r"stock market|exchange rate|gas prices?)\b",
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re.IGNORECASE,
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)
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def pinterest_seed_path(country: str) -> Path:
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for root in (runtime_root(), project_root()):
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p = root / "configs" / "pinterest" / f"{country}.yaml"
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if p.exists():
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return p
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return Path("configs") / "pinterest" / f"{country}.yaml"
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def load_pinterest_seeds(country: str) -> List[str]:
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"""读国家 Pinterest 种子词池（configs/pinterest/<CC>.yaml 的 seeds）。"""
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try:
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import yaml
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p = pinterest_seed_path(country)
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if not p.exists():
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print(f"[pinterest] 未找到种子词配置: {p}")
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return []
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data = yaml.safe_load(p.read_text(encoding="utf-8")) or {}
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seeds = [str(s).strip() for s in (data.get("seeds") or []) if str(s).strip()]
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return seeds
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except Exception as e: # noqa: BLE001
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print(f"[pinterest] 种子词加载失败: {e}")
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return []
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def sample_seeds(country: str, n: int) -> List[str]:
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"""从国家种子池随机抽取 n 个种子词（不足则全取）。"""
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seeds = load_pinterest_seeds(country)
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if not seeds:
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return []
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if len(seeds) <= n:
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return list(seeds)
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return random.sample(seeds, n)
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def used_terms_path(output_dir: str, country: str) -> Path:
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return Path(output_dir) / "pinterest_ref" / country / "used_search_terms.json"
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def load_used_terms(output_dir: str, country: str) -> List[str]:
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"""读已用搜索词（跨多次运行持久化，供动态注入防重复）。"""
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try:
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p = used_terms_path(output_dir, country)
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if p.exists():
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data = json.loads(p.read_text(encoding="utf-8"))
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return [str(t).strip() for t in (data.get("terms") or []) if str(t).strip()]
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except Exception as e: # noqa: BLE001
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print(f"[pinterest] 已用搜索词读取失败: {e}")
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return []
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def save_used_terms(output_dir: str, country: str, terms: List[str]) -> None:
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"""持久化已用搜索词（去重保序）。"""
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try:
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p = used_terms_path(output_dir, country)
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p.parent.mkdir(parents=True, exist_ok=True)
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seen, out = set(), []
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for t in terms:
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k = t.strip().lower()
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if k and k not in seen:
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seen.add(k)
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out.append(t.strip())
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p.write_text(json.dumps({"terms": out}, ensure_ascii=False, indent=2), encoding="utf-8")
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except Exception as e: # noqa: BLE001
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print(f"[pinterest] 已用搜索词保存失败: {e}")
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def filter_search_terms(terms: List[str], used: List[str], blacklist: List[str]) -> List[str]:
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"""全局搜索词过滤：剔除已用、黑名单、不适合 T 恤类目、去重（大小写不敏感）。"""
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used_set = {str(u).strip().lower() for u in used if str(u).strip()}
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black = [str(b).strip().lower() for b in (blacklist or []) if str(b).strip()]
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seen, out = set(), []
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for t in terms:
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s = str(t).strip()
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low = s.lower()
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if not s or low in seen or low in used_set:
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continue
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if any(b and b in low for b in black):
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continue
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if _UNSUITABLE.search(low):
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continue
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seen.add(low)
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out.append(s)
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return out
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def merge_used(existing: List[str], new_terms: List[str]) -> List[str]:
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"""合并已用搜索词（新词追加到末尾，去重保序）。"""
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seen, out = set(), []
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for t in list(existing) + list(new_terms):
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k = str(t).strip().lower()
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if k and k not in seen:
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seen.add(k)
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out.append(str(t).strip())
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return out
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# —— 设计图全局 MD5 去重（跨国家、跨运行；对所有国家生效）——
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_MD5_LOCK = threading.Lock()
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def global_md5_path() -> Path:
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"""全局设计图 MD5 过滤文件（.cache 随打包同步，跨版本保留）。"""
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return runtime_root() / ".cache" / "global_design_md5.json"
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def load_global_md5() -> set:
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"""读全局设计图 MD5 集合。"""
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try:
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p = global_md5_path()
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if p.exists():
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data = json.loads(p.read_text(encoding="utf-8"))
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return {str(m).strip().lower() for m in (data.get("md5s") or []) if str(m).strip()}
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except Exception as e: # noqa: BLE001
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print(f"[pinterest] 全局 MD5 过滤读取失败: {e}")
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return set()
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def add_global_md5(md5: str) -> bool:
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"""把设计图 MD5 加入全局过滤；返回 True=新增可用，False=已存在（全局重复，应跳过）。"""
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md5 = str(md5 or "").strip().lower()
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if not md5:
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return False
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with _MD5_LOCK:
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try:
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p = global_md5_path()
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p.parent.mkdir(parents=True, exist_ok=True)
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md5s = load_global_md5()
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if md5 in md5s:
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return False
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md5s.add(md5)
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p.write_text(json.dumps(
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{"updated_at": time.strftime("%Y-%m-%dT%H:%M:%S"), "md5s": sorted(md5s)},
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ensure_ascii=False, indent=2), encoding="utf-8")
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return True
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except Exception as e: # noqa: BLE001
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print(f"[pinterest] 全局 MD5 过滤写入失败: {e}")
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return True # 写入失败不阻塞：按新增处理，避免误跳过
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def design_md5_ok(image_path: str) -> bool:
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"""计算设计图 MD5 并加入全局过滤；返回 True=新增可用，False=全局重复（应跳过）。"""
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try:
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md5 = hashlib.md5(Path(image_path).read_bytes()).hexdigest()
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return add_global_md5(md5)
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except Exception as e: # noqa: BLE001
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print(f"[pinterest] 设计图 MD5 计算失败: {e}")
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return True
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# —— 图池（Image Pool）：跨轮次/跨运行持久化的爬取图片池 + 已消费图片 MD5 拉黑 ——
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# 图池 = 所有已爬取图片的注册表（path + md5 + term）；已消费（分析过）的图片 MD5 记入
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# used_images，不再复用。分析从图池取未消费图片，池不足时由路由触发新一轮搜索。
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_IMG_EXTS = (".jpg", ".jpeg", ".png", ".webp", ".gif", ".bmp")
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def list_valid_images(folder: Any) -> List[Path]:
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"""返回文件夹内所有有效图片文件（扩展名匹配，含子目录递归），用于自定义模式。
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供图源目录/自定义模式统计「有效图片数量」与注册图池使用；空/不存在返回空列表。
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"""
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d = Path(folder)
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if not d.is_dir():
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return []
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out: List[Path] = []
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for f in sorted(d.rglob("*")):
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# 跳过隐藏/缓存子目录（如 .compressed 压缩缓存），避免把压缩产物当有效图片
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if any(part.startswith(".") for part in f.relative_to(d).parts[:-1]):
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continue
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if f.is_file() and f.suffix.lower() in _IMG_EXTS:
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out.append(f)
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return out
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def validate_custom_images(folder: Any, target: int) -> tuple:
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"""自定义模式数量校验：返回 (ok, valid_n, message)。
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folder 未填/不存在/无有效图片 → 失败；有效图片数 < 选品清单总数 target → 失败
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（「选品清单不得大于有效图片数」硬校验）。供 UI/入口 fail-fast 与节点安全网复用。
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"""
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folder_s = str(folder or "").strip()
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if not folder_s:
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return False, 0, "自定义图片文件夹未填写（pinterest.custom_image_dir / UI 选择上传文件夹）"
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if not Path(folder_s).is_dir():
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return False, 0, f"自定义图片文件夹不存在：{folder_s}"
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imgs = list_valid_images(folder_s)
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n = len(imgs)
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if n == 0:
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return False, 0, f"自定义图片文件夹「{folder_s}」中没有有效图片（jpg/jpeg/png/webp）"
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if target > n:
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return False, n, (f"选品清单数量（{target}）大于自定义图片有效数量（{n}）："
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f"选品清单不得大于有效图片数，请补充图片或减少选品")
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return True, n, f"自定义图片校验通过：有效图片 {n} 张 ≥ 选品清单 {target}"
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def image_pool_path(output_dir: str, country: str) -> Path:
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return Path(output_dir) / "pinterest_ref" / country / "image_pool.json"
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def used_images_path(output_dir: str, country: str) -> Path:
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return Path(output_dir) / "pinterest_ref" / country / "used_images.json"
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def load_image_pool(output_dir: str, country: str) -> Dict[str, Any]:
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"""读图池注册表；无文件时回退扫描文件系统重建。"""
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try:
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p = image_pool_path(output_dir, country)
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if p.exists():
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data = json.loads(p.read_text(encoding="utf-8")) or {}
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imgs = data.get("images") or []
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if imgs:
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return {"updated_at": data.get("updated_at", ""), "images": imgs}
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except Exception as e: # noqa: BLE001
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print(f"[pinterest] 图池读取失败: {e}")
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return {"updated_at": "", "images": scan_scraped_images(output_dir, country)}
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def save_image_pool(output_dir: str, country: str, pool: Dict[str, Any]) -> None:
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"""持久化图池注册表。"""
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try:
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p = image_pool_path(output_dir, country)
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p.parent.mkdir(parents=True, exist_ok=True)
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p.write_text(json.dumps(
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{"updated_at": time.strftime("%Y-%m-%dT%H:%M:%S"), "images": pool.get("images") or []},
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ensure_ascii=False, indent=2), encoding="utf-8")
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except Exception as e: # noqa: BLE001
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print(f"[pinterest] 图池保存失败: {e}")
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def scan_scraped_images(output_dir: str, country: str) -> List[Dict[str, Any]]:
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"""扫描 pinterest_ref/<country>/*/ 下所有图片，重建图池注册表（含 md5）。"""
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base = Path(output_dir) / "pinterest_ref" / country
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out: List[Dict[str, Any]] = []
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if not base.exists():
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return out
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for term_dir in sorted(base.iterdir()):
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if not term_dir.is_dir():
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continue
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term = term_dir.name
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for f in sorted(term_dir.iterdir()):
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if not f.is_file() or f.suffix.lower() not in _IMG_EXTS:
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continue
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out.append({"path": str(f), "md5": image_md5(str(f)), "term": term})
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return out
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def image_md5(path: str) -> str:
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"""计算图片文件 MD5（失败返回空串）。"""
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try:
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return hashlib.md5(Path(path).read_bytes()).hexdigest()
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except Exception as e: # noqa: BLE001
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print(f"[pinterest] 图片 MD5 计算失败 {path}: {e}")
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return ""
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def load_used_images(output_dir: str, country: str) -> set:
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"""读已消费图片 MD5 集合（拉黑，不再复用）。"""
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try:
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p = used_images_path(output_dir, country)
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if p.exists():
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data = json.loads(p.read_text(encoding="utf-8")) or {}
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return {str(m).strip().lower() for m in (data.get("md5s") or []) if str(m).strip()}
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except Exception as e: # noqa: BLE001
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print(f"[pinterest] 已消费图片读取失败: {e}")
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return set()
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def save_used_images(output_dir: str, country: str, md5s: set) -> None:
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"""持久化已消费图片 MD5 集合。"""
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try:
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p = used_images_path(output_dir, country)
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p.parent.mkdir(parents=True, exist_ok=True)
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p.write_text(json.dumps(
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{"updated_at": time.strftime("%Y-%m-%dT%H:%M:%S"), "md5s": sorted(md5s)},
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ensure_ascii=False, indent=2), encoding="utf-8")
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except Exception as e: # noqa: BLE001
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print(f"[pinterest] 已消费图片保存失败: {e}")
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def pool_unused_images(pool: Dict[str, Any], used: set) -> List[Dict[str, Any]]:
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"""从图池取未消费图片（md5 不在 used 集合），保序。"""
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out = []
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for img in pool.get("images") or []:
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if not isinstance(img, dict):
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continue
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m = str(img.get("md5") or "").strip().lower()
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if not m or m in used:
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continue
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if not Path(str(img.get("path") or "")).exists():
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continue
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out.append(img)
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return out
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def compress_image(path: str, max_dim: int = 1024, max_bytes: int = 1_500_000,
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out_dir: str = "") -> str:
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"""压缩大图：超过 max_dim 边长或 max_bytes 体积时缩放/重编码，返回压缩后路径。
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- 内存占用过大（分辨率过高）→ 等比缩放到 max_dim 内；
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- 文件过大 → 转 JPEG 重编码（质量自适应）；
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- 无需压缩 → 返回原路径。压缩产物存 out_dir（默认图片同目录 .compressed/）。
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"""
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try:
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from PIL import Image
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p = Path(path)
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if not p.exists():
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return path
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size = p.stat().st_size
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try:
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with Image.open(p) as im:
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w, h = im.size
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except Exception: # noqa: BLE001 无法解析的图片（损坏/非标准）直接返回原路径
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return path
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if w <= max_dim and h <= max_dim and size <= max_bytes:
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return path
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out_root = Path(out_dir) if out_dir else (p.parent / ".compressed")
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out_root.mkdir(parents=True, exist_ok=True)
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out = out_root / f"{p.stem}_c.jpg"
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with Image.open(p) as im:
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im = im.convert("RGB")
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im.thumbnail((max_dim, max_dim), Image.LANCZOS)
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quality = 85
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while quality >= 40:
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im.save(out, "JPEG", quality=quality, optimize=True)
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if out.stat().st_size <= max_bytes:
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break
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quality -= 15
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print(f"[pinterest] 图片压缩 {p.name} ({w}x{h}, {size // 1024}KB) → "
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f"{out.name} ({out.stat().st_size // 1024}KB)")
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return str(out)
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except Exception as e: # noqa: BLE001
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print(f"[pinterest] 图片压缩失败 {path}: {e}")
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return path
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def is_400_content_image(exc) -> bool:
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"""HTTP 400 且错误信息模糊匹配到「内容」或「图片」才算（用户要求）。
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生图后端抛 RuntimeError("图像 API 400: {body}")，body 在消息里；
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多模态后端抛 requests.HTTPError，响应体在 exc.response.text。
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"""
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msg = str(exc or "")
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resp = getattr(exc, "response", None)
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if resp is not None:
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try:
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body = resp.text or ""
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except Exception: # noqa: BLE001
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body = ""
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if body:
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msg = f"{msg} {body}"
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if "400" not in msg:
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return False
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return ("内容" in msg or "图片" in msg)
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