174 lines
7.9 KiB
Python
174 lines
7.9 KiB
Python
"""提示词公共层：与模型家族无关的商品上下文、风格模板、图类型名与文案组件。
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各家族模块（alibaba / doubao / gpt / google）只负责"如何对模型说话"，
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商品信息提炼与风格体系统一在这里维护，避免多处漂移。
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"""
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from __future__ import annotations
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import re
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# ── 风格模板（与插件端 STYLE_SET_OPTIONS 对应；提示词可被用户在插件里改写覆盖）───
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STYLE_SETS: dict[int, dict] = {
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1: {
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"name": "北欧极简",
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"tone": "Nordic minimalism: light gray or warm off-white background, soft diffused light, low-saturation palette, generous negative space, restrained and clean composition",
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"bg": "",
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},
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2: {
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"name": "清新明亮",
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"tone": "Fresh and bright: white-to-pale-blue gradient background, high-key lighting, clear luminous colors, airy and uncluttered composition",
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"bg": "",
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},
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3: {
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"name": "高级感深色",
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"tone": "Premium dark aesthetic: deep gray or charcoal background, dramatic side lighting, emphasize material texture and sheen, refined and restrained mood",
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"bg": "",
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},
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4: {
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"name": "暖调生活",
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"tone": "Warm lifestyle: warm beige background, cozy warm lighting, inviting home-living texture, approachable and natural atmosphere",
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"bg": "",
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},
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5: {
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"name": "纯净棚拍",
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"tone": "Clean e-commerce studio: plain light background, even frontal softbox lighting, no distracting props, product centered and prominent",
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"bg": "",
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},
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}
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# ── 图类型中文名（导出文件名用）───────────────────────────────────────────
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TYPE_NAMES_ZH: dict[str, str] = {
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"white_bg": "白底主图",
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"key_features": "核心卖点图",
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"selling_pt": "卖点图",
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"material": "材质图",
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"lifestyle": "场景展示图",
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"multi_scene": "多场景拼图",
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"ecommerce_detail": "电商详情图",
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"size_chart": "尺寸标注图",
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"sku_collection": "SKU合集图",
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"custom": "创意图",
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}
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# ── 图内营销文案渲染规范（各家族共用；语言由平台决定）──────────────────────
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TEXT_RENDER = {
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"zh": (
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"Render concise Chinese marketing text inside the image: main headline max 8 Chinese characters, "
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"sub-lines max 12 characters each, font is modern clean sans-serif (Source Han Sans style), "
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"high legibility, tasteful typography layout, colors harmonized with the composition. "
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"No spelling errors, no garbled characters."
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),
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"en": (
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"Render concise English marketing text inside the image: headline max 5 words, "
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"sub-lines max 8 words each, Helvetica Neue style sans-serif, high legibility, "
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"tasteful typography layout, colors harmonized with the composition. No spelling errors."
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),
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"ru": (
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"Render concise Russian marketing text inside the image: headline max 4 words, "
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"sub-lines max 6 words each, modern clean sans-serif (Inter / PT Sans style), "
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"proper Cyrillic typography, high legibility, tasteful layout, colors harmonized with the composition. "
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"Translate any Chinese source facts into Russian before rendering. All newly generated visible text "
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"must be Russian Cyrillic only: never render Chinese, Hanzi, CJK characters, or Chinese phrases. "
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"The sole exception is Chinese text physically printed on the reference product itself, which must remain unchanged. "
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"No spelling errors, no mixed latin/cyrillic gibberish."
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),
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}
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def resolve_style(style_set: int, style_prompt: str | None = None) -> dict:
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"""用户改写的风格提示词整体覆盖内置模板（tone/bg 整体替换）。"""
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if style_prompt and style_prompt.strip():
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return {"name": "custom", "tone": style_prompt.strip(), "bg": ""}
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return STYLE_SETS.get(style_set, STYLE_SETS[1])
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def requirements_block(requirements: str | None) -> str:
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"""用户强制要求块：最高优先级、置于提示词最前、覆盖冲突指令（原文保留不翻译）。"""
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if requirements and requirements.strip():
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return (
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"STRICT REQUIREMENTS (highest priority for visual intent; interpret any Chinese source instruction "
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"by meaning only and never copy its Hanzi into newly generated text): "
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+ requirements.strip().rstrip(".")
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+ "."
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)
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return ""
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# ── 商品上下文提炼 ────────────────────────────────────────────────────────
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def _shorten(text: str, n: int) -> str:
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text = re.sub(r"\s+", " ", (text or "")).strip()
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return text[:n]
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def _clean_title(title: str) -> str:
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"""去掉常见堆砌词，让标题更可读。"""
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t = _shorten(title, 60)
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return re.sub(r"[【【】】\\[\\]|/]", " ", t).strip()
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def build_context(raw: dict, fallback_name: str = "", fallback_desc: str = "") -> dict:
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"""从采集数据提炼生图上下文：标题、描述行、卖点列表、参数行。
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raw: {title, desc, price, params: [{key, value}], sellingPoints}
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"""
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# 试算页会同时上传中文采集标题和已回填的俄文标题；后者用于图内可见文案。
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title = _clean_title(raw.get("title_ru") or raw.get("title") or fallback_name or "product")
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desc = _shorten(raw.get("desc") or fallback_desc or "", 200)
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# 卖点：优先显式卖点文本；否则从参数表里挑短而有信息量的键值对
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selling_points: list[dict] = []
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sp_text = raw.get("sellingPoints") or ""
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if sp_text:
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for chunk in re.split(r"[；;\n·]+|(?<!\d)\.(?!\d)", sp_text):
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c = _shorten(chunk, 20)
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if c and len(selling_points) < 5:
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selling_points.append({"zh": c, "en": c})
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if not selling_points:
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for p in (raw.get("params") or [])[:12]:
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k, v = _shorten(p.get("key", ""), 10), _shorten(str(p.get("value", "")), 16)
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if k and v and k.lower() not in {"货号", "sku", "isbn", "上架时间"}:
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selling_points.append({"zh": f"{k} {v}", "en": f"{k} {v}"})
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if len(selling_points) >= 5:
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break
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params_line = "; ".join(
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f"{p.get('key')}: {p.get('value')}" for p in (raw.get("params") or [])[:8]
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)
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return {
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"title": title,
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"title_en": title, # 采集源多为中文标题，英文场景直接用原词避免乱翻译
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"desc": desc,
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"selling_points": selling_points[:3],
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"params_line": params_line,
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# 俄文图片里不能直接渲染中文参数；保留不含汉字的规格（型号、数字、单位）供尺寸图使用。
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"params_line_non_cjk": "; ".join(
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f"{p.get('key')}: {p.get('value')}"
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for p in (raw.get("params") or [])[:8]
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if not re.search(r"[\u3400-\u9fff]", f"{p.get('key')} {p.get('value')}")
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),
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"price": raw.get("price") or "",
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}
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def selling_point_lines(ctx: dict, lang: str, max_n: int = 3) -> str:
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"""卖点列表 → 单行文案（图内 callout/标题用），无卖点返回空串。"""
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sps = ctx["selling_points"][:max_n]
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if not sps:
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return ""
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key = "zh" if lang == "zh" else "en"
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values = [s[key] for s in sps if s.get(key)]
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# 中文卖点是模型理解商品的来源，不应成为俄文图片中的逐字文案。
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if lang == "ru":
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values = [v for v in values if not re.search(r"[\u3400-\u9fff]", v)]
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return "; ".join(values)
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def params_line_for_output(ctx: dict, lang: str) -> str:
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"""返回可进入图内规格文案的参数；俄文模式剔除含汉字的原始采集参数。"""
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return ctx.get("params_line") if lang == "zh" else ctx.get("params_line_non_cjk", "")
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def type_name(type_id: str) -> str:
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return TYPE_NAMES_ZH.get(type_id, type_id)
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