3218485270
f493bde8a9
- 缓存热点批量流程（有采集缓存不触发 Google） - 简报不足直接从采集缓存生成（轻量补齐） - 三图合成（模特/印花/底图）+ 底图压缩 <2MB - 热点去重→风格去重自动切换 + 不适合类目 review 兜底 - 透明背景（background=transparent）+ 提示词清洗（敏感词/背景描述） - 任务前 basemap 校验 + 模板国家校验 + 模特任务级分配
33 lines
1.4 KiB
Python
33 lines
1.4 KiB
Python
# -*- coding: utf-8 -*-
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"""真实 API 全链路验证：JP JPTM001 黑色 × 1（oss 真上传）。"""
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import json
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import sys
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from pathlib import Path
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BASE = Path(__file__).resolve().parent.parent
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sys.path.insert(0, str(BASE))
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import yaml
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from graph.product_batch import run_product_batch
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config = yaml.safe_load(open(BASE / "dist_v2" / "config.yaml", encoding="utf-8"))
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config["seed_provider"] = "openai"
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config["llm_screen"]["provider"] = "openai"
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config["compose"]["backend"] = "openai"
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config["product"]["backend"] = "openai"
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config["oss"]["enabled"] = True
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config["seed_shot"]["count"] = 1
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print("使用配置: llm_model =", config["llm_screen"].get("model"), "| img_model =", config["compose"].get("model"))
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out = run_product_batch("JP", config, BASE, BASE / "dist_v2",
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[{"spu": "JPTM001", "skus": "JPTM001-BL01"}], 1, log_q=None)
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print("\n=== 结果 ===")
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prods = out.get("product") or []
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print("产品数:", len(prods))
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for r in prods:
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print(f" {r.get('spu_code')} | {r.get('sku_code')} | design={bool(r.get('design_path'))} "
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f"| composite={bool(r.get('composite_path'))} | en_title={bool(r.get('en_title'))} "
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f"| ja_title={bool(r.get('ja_title'))} | oss_code={r.get('oss_code')}")
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print(" URLs:", {k: v[:60] for k, v in r.items() if k.endswith("_url")})
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print("errors:", [e.get("message", "")[:100] for e in out.get("errors") or []])
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