增长策略与激活：淘宝AI工具

# 智能作图：白底图 → 多场景素材scenes = ["白底图", "街拍场景", "家居实景"]for scene in scenes:    prompt = f"{product}置于{scene}，{style}风格"    generate_image(prompt)  # 一键生成多场景图

# AI客服：关键词匹配商品知识库for key, answer in knowledge_base.items():    if all(w in question for w in key):        return answer  # 命中则自动回复return transfer_to_human()  # 未命中转人工

# AI文案：模板填充生成营销文案template = "【{name}】{feature}，{benefit}。{appeal}"copy = template.format(name=name, feature=feature, benefit=benefit, appeal=appeal)

import randomfrom typing import List, Dict, Optional  class ProductImageGenerator:    """淘宝AI作图工具：根据白底商品图生成多场景素材"""    SCENES = ["白底图", "街拍场景", "家居实景", "节日主题", "使用场景"]    STYLES = ["清新自然", "高端商务", "活力运动", "简约文艺"]     def __init__(self, product_name: str, base_image: str):        self.product_name = product_name        self.base_image = base_image     def generate(self, scene: str, style: str) -> Dict:        prompt = f"{self.product_name}置于{scene}，{style}风格"        seed = hash(prompt) % 10000        return {"scene": scene, "style": style, "prompt": prompt, "image_id": f"IMG_{seed}", "status": "generated"}     def batch_generate(self, scene: Optional[str] = None) -> List[Dict]:        results = []        targets = [scene] if scene else self.SCENES        for sc in targets:            for st in self.STYLES:                results.append(self.generate(sc, st))        return results  class AICustomerService:    """淘宝AI客服：基于商品知识库的智能问答匹配"""    def __init__(self, knowledge_base: Dict[str, str]):        self.kb = knowledge_base     def match_intent(self, question: str) -> Optional[str]:        best_key, best_score = None, 0        for key in self.kb:            score = sum(1 for w in key if w in question)            if score > best_score:                best_key, best_score = key, score        return best_key     def answer(self, question: str) -> Dict:        matched = self.match_intent(question)        if matched and self.kb.get(matched):            return {"question": question, "answer": self.kb[matched], "handler": "ai", "confidence": 0.9}        return {"question": question, "answer": "该问题较复杂，已为您转接人工客服", "handler": "human", "confidence": 0.3}  class AIMarketingCopywriter:    """淘宝AI文案工具：根据商品特征生成营销文案"""    TEMPLATES = {        "detail": "【{name}】{feature}，{benefit}。{appeal}让每一分钱都花在刀刃上。",        "main": "{name} | {feature} | {benefit}",        "promo": "限时特惠！{name}{feature}，{appeal}",    }     def __init__(self, name: str, features: List[str], audience: str):        self.name = name        self.features = features        self.audience = audience     def generate_copy(self, copy_type: str = "detail") -> str:        feature = random.choice(self.features)        benefits = {"保暖": "告别寒冬", "透气": "清爽一夏", "耐磨": "经久耐用"}        benefit = benefits.get(feature, "品质之选")        appeal = f"专为{self.audience}打造"        return self.TEMPLATES[copy_type].format(name=self.name, feature=feature, benefit=benefit, appeal=appeal)  def demo_taobao_ai_toolkit():    generator = ProductImageGenerator("纯棉卫衣", "white_bg_001.jpg")    images = generator.batch_generate(scene="街拍场景")    print("[AI作图] 生成", len(images), "张素材，示例：", images[0]["image_id"], "-", images[0]["prompt"])     kb = {"尺码": "本款偏大一码，建议拍小一码", "物流": "江浙沪次日达，全国3-5天", "退换货": "支持7天无理由退换"}    service = AICustomerService(kb)    reply = service.answer("请问这件衣服尺码怎么选")    print("[AI客服]", reply["question"], "->", reply["answer"], "（处理方：" + reply["handler"] + "）")     copywriter = AIMarketingCopywriter("纯棉卫衣", ["保暖", "透气", "耐磨"], "年轻人")    copy = copywriter.generate_copy("detail")    print("[AI文案]", copy)  if __name__ == "__main__":    demo_taobao_ai_toolkit()