- 新增韩国(KR)适配:countries/pinterest 种子词、K-pop 提示词、UI 国家列表 - 爬虫跨运行持久化已采集 URL(.collected_urls.json),同关键词重复搜索采新图 - 模板导出增强:SPU 商品属性列名前缀剥离匹配、尺码下拉框 INDIRECT 动态引用、 SPU 字段映射(袖长/门襟/胸垫等)、季节/印花图案女装映射、建议售价统一必填、 SKU 分类/数量/单位直接填默认值 - 自定义模式:多模态提示词独立(custom_analyze_*)、生图提示词模板可配置 - Pinterest:空选品守卫、连续空分析保护(max_empty_analyze)、flat_prompt 配置覆盖 - 生图可靠性:开始/完成进度日志、异步任务轮询超时 60s→300s
165 lines
9.5 KiB
Python
165 lines
9.5 KiB
Python
"""节点 5/6:提示词构造(prompt_build)。
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读取 prompts/<country>/ 的 extra 风格规则,用固定模板装配四种最终提示词
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(image_prompt / wearable_prompt / composite_prompt / composite_negative)。
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四要素缺失时用 derive_style_palette 动态兜底,保证每条提示词结构一致、有规则。
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"""
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from typing import Any, Dict, List
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import random
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from graph.style_rules import derive_style_palette, derive_composition
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from graph.templates import assemble_prompts
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from graph.validate import validate_brief, with_fallback
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# —— Pinterest 图生图生最终设计稿时统一追加的「小印花 + 纯白底」约束段 ——
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# (从热点搜集的文字生图模板里提炼:尺寸缩小、禁止自带背景/满幅)
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PINTEREST_PRINT_SUFFIX = (
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" standalone pure print design on a pure white background, "
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"the print artwork is SMALL and CENTERED with clearly larger white margins around it, "
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"print area between about 15x18 cm and 26x32 cm, "
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"do NOT fill the entire canvas, do NOT force full-bleed, "
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"do NOT add any gradient, texture or background color behind the artwork, "
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"no garment, no shirt, no model, no mannequin, no watermark"
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)
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# Pinterest 生图提示词 3 段结构中第 2 段(仅当设计含文字时追加):
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# 要求模型把引号内的文字按原文逐字正确拼写,避免乱码/拼错
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SPELLING_RULE = (
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"Render every phrase shown in quotes exactly as written, "
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"correctly spelled."
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)
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# review(疑似商标/受保护主题)简报统一追加的「原创化魔改」引导段:
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# 只做风格参考,禁复刻品牌/商标/角色,换名换细节,生成通用非侵权致敬式设计。
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# 两个模式(热点采集 / Pinterest 参考)共用同一文本,避免不一致。
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REVIEW_REBRAND_HINT = (
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"IMPORTANT: this theme is ONLY a loose stylistic reference. "
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"Do NOT reproduce any brand logo, trademark, character, mascot, copyrighted artwork or real person. "
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"Create a fully ORIGINAL design with a different name and distinct visual details and colors — "
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"a generic, non-infringing homage in the same mood, clearly distinct from the original."
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)
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# —— 自定义模式(custom)生图模板:固定前缀 + 分析模型 image_prompt + 固定负向 ——
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# 自定义模式分析模型产出的是「新设计描述」,生图时套用这套固定模板(含防复制/防服装约束),
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# 负向用固定文本(写入 composite_negative,compose 生图时作为负向参数传给图像后端)。
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CUSTOM_IMAGE_PROMPT_TEMPLATE = (
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"Use the attached bestseller product photo only as loose inspiration for "
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"overall mood, theme, era and style genre — do NOT reproduce, trace, "
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"rearrange, recolor or closely imitate its printed artwork, characters, "
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"layout or text, and do NOT render a shirt, garment, model, hanger, photo "
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"scene, product mockup or background of any kind. First, carefully examine "
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"the printed artwork on the garment in the attached photo: zoom in mentally "
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"on the print area, identify its subject, technique, palette and layout, and "
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"base the new design on THOSE observed traits. Ignore the model, background "
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"and photo quality. Then: {image_prompt}"
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)
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CUSTOM_NEGATIVE_PROMPT = (
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"copy of reference artwork, lookalike of the bestseller print, characters, "
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"mascots, likenesses, logos, trademarks, watermark, photorealistic shirt, "
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"apparel, product mockup, model, garment, hanger, busy background"
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)
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# 图像生成策略敏感词 → 安全等效描述(生成设计稿前清洗 motif,
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# 避免 gpt-image 等内容策略频繁拦截导致"生图限制多")
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_IMG_RISKY_SWAP = {
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"skull": "smiley mascot", "skeleton": "cute mascot", "blood": "red accents",
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"gore": "bold shapes", "gun": "star", "weapon": "tool", "bomb": "firework",
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"drug": "confetti", "demon": "cute monster", "devil": "mischievous imp",
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"occult": "mystic pattern", "satanic": "dark pattern", "nazi": "retro emblem",
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"hitler": "retro emblem", "zombie": "friendly ghoul", "horror": "spooky-cute",
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"vampire": "night owl", "politics": "abstract shapes", "political": "abstract",
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"president": "captain", "army": "team", "police": "officer",
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}
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def _safe_motif(motif: str) -> str:
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"""清洗 motif 中的图像策略敏感词(替换为安全等效描述),降低生图内容政策拦截率。"""
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low = motif.lower()
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for k, v in _IMG_RISKY_SWAP.items():
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if k in low:
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# 按词边界替换(避免误伤 "letterhead" 等)
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import re
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motif = re.sub(rf"\b{re.escape(k)}\b", v, motif, flags=re.IGNORECASE)
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low = motif.lower()
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return motif
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@with_fallback("prompt_build")
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def prompt_node(state: Dict[str, Any]) -> Dict[str, Any]:
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screened: List[Dict[str, Any]] = state.get("screened") or []
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config = state["config"]
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country = state["country"]
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cc = state["country_config"]
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extra_rules = cc.get("extra_style_rules") or []
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tpls = config.get("prompt_templates") or {}
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# Pinterest 生图提示词固定段:可配置(config.pinterest.prompt_pieces),留空/缺失回退内置常量。
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# 自定义模式(custom_mode)用独立的一套固定段(config.custom.prompt_pieces),默认与 Pinterest 相同、可单独编辑。
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if bool(state.get("custom_mode")):
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pp = (config.get("custom") or {}).get("prompt_pieces") or {}
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else:
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pp = (config.get("pinterest") or {}).get("prompt_pieces") or {}
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print_suffix = (pp.get("print_suffix") or "").strip() or PINTEREST_PRINT_SUFFIX
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spelling_rule = (pp.get("spelling_rule") or "").strip() or SPELLING_RULE
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review_rebrand_hint = (pp.get("review_rebrand_hint") or "").strip() or REVIEW_REBRAND_HINT
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custom_ip_tpl = (pp.get("image_prompt_template") or "").strip() or CUSTOM_IMAGE_PROMPT_TEMPLATE
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custom_neg = (pp.get("negative_prompt") or "").strip() or CUSTOM_NEGATIVE_PROMPT
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briefs: List[Dict[str, Any]] = []
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for r in screened:
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r = validate_brief(r)
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art, pal = derive_style_palette(
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r["topic"], country, extra_rules=extra_rules, category=r.get("design_category")
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)
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motif = (r.get("motif") or "").strip() or r.get("topic", "")
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cleaned = _safe_motif(motif)
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if cleaned != motif:
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print(f"[prompt] motif 敏感词清洗: 「{motif}」→「{cleaned}」(降低生图内容政策拦截)")
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r["motif"] = cleaned
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motif = cleaned
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art_style = (r.get("art_style") or art).strip()
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palette = (r.get("color_palette") or pal).strip()
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composition = (r.get("composition") or derive_composition(r["topic"], r.get("design_category"))).strip()
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prompts = assemble_prompts(motif, art_style, palette, composition, tpls, country)
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llm_ip = (r.get("image_prompt") or "").strip()
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if r.get("source") == "pinterest" and llm_ip:
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if bool(state.get("custom_mode")):
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# —— 自定义模式:固定模板(前缀 + 分析 image_prompt),负向用固定文本 ——
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# 模板含防复制/防服装约束,不再追加 print_suffix;负向写入 composite_negative,
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# compose 生图时作为负向参数传给图像后端。
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prompts["image_prompt"] = custom_ip_tpl.replace("{image_prompt}", llm_ip)
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prompts["composite_negative"] = custom_neg
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print(f"[prompt] 自定义模式按固定模板拼 image_prompt(含固定负向): 「{r['topic']}」")
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else:
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# —— Pinterest 参考模式:跳过四要素模板,按 3 段结构拼 image_prompt ——
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# ① image_prompt(分析模型产出) + 固定输出形态后缀 PINTEREST_PRINT_SUFFIX
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# ② 拼写锁定句 SPELLING_RULE(仅当 LLM image_prompt 已含引号文字段时)
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# 是否含文字、拼写与否均由分析模型产出决定,本模式不注入 slogan。
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seg: List[str] = [llm_ip, print_suffix]
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if '"' in llm_ip:
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seg.append(spelling_rule)
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prompts["image_prompt"] = ", ".join(seg)
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print(f"[prompt] Pinterest 简报按 3 段结构拼 image_prompt(跳过四要素模板): 「{r['topic']}」")
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else:
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# —— 热点采集模式:四要素模板装配 + 文字印花(约 30% 概率注入 slogan)——
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slogan = (r.get("slogan") or "").strip()
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if slogan and random.random() < float(config.get("prompt_templates", {}).get("text_ratio", 0.3)):
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text_seg = (f', with the text "{slogan}" rendered as bold retro typography, '
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f'lettering clean and correctly spelled, high contrast, as the focal text of the print')
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prompts["image_prompt"] = prompts["image_prompt"] + text_seg
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r["used_slogan"] = slogan
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# review(疑似商标/受保护主题)→ 追加「原创化魔改」引导(两个模式通用)
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if str(r.get("risk_level", "")).strip().lower() == "review":
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prompts["image_prompt"] = prompts["image_prompt"] + " " + review_rebrand_hint
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print(f"[prompt] review 简报注入原创化魔改引导: 「{r['topic']}」")
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r.update(prompts)
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r["motif"] = motif
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r["art_style"] = art_style
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r["color_palette"] = palette
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r["composition"] = composition
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briefs.append(r)
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stats = dict(state.get("stats") or {})
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stats["prompt"] = {"briefs": len(briefs)}
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return {"briefs": briefs, "stats": stats}
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