"""文案生成器 — 模板模式 + AI 模式双模式。"""
import re
import json
import logging

logger = logging.getLogger(__name__)


class CopyGenerator:
    """文案生成器。"""

    def generate_template_copy(self, template_content: str, product_rules: dict, customer_data: dict) -> dict:
        """模板模式：本地变量替换。

        参数:
            template_content: 含 {{变量}} 占位符的文案模板
            product_rules: 产品规则（manual_parsed_rules）
            customer_data: 客户数据（confirmed_data）

        返回:
            {"headline": "...", "body": "...", "call_to_action": "..."}
        """
        # 构建变量映射
        variables = {}
        # 产品信息
        if product_rules:
            variables["product_name"] = product_rules.get("product_name", "")
            features = product_rules.get("features", [])
            for i, feat in enumerate(features[:3], 1):
                variables[f"feature_{i}_title"] = feat.get("title", "")
                variables[f"feature_{i}_summary"] = feat.get("summary", "")
            variables["currency_options"] = ", ".join(product_rules.get("currency_options", []))

        # 客户数据
        if customer_data:
            variables["age"] = str(customer_data.get("age", ""))
            variables["currency"] = customer_data.get("currency", "")
            variables["sum_assured"] = str(customer_data.get("sum_assured", ""))
            variables["annual_premium"] = str(customer_data.get("annual_premium", ""))
            variables["coverage_period"] = customer_data.get("coverage_period", "")

        # 替换占位符
        result = template_content
        for key, value in variables.items():
            result = result.replace("{{" + key + "}}", value)

        # 尝试按段落拆分为 headline/body/call_to_action
        lines = [l.strip() for l in result.split("\n") if l.strip()]
        return {
            "headline": lines[0] if lines else "",
            "body": "\n".join(lines[1:-1]) if len(lines) > 2 else lines[1] if len(lines) > 1 else "",
            "call_to_action": lines[-1] if len(lines) > 1 else "",
        }

    async def generate_ai_copy(self, product_rules: dict, customer_data: dict, style: str = "专业") -> dict:
        """AI 模式：调用 LLM 生成营销文案。

        返回:
            {"headline": "...", "body": "...", "call_to_action": "..."}
        """
        from insurance.ppt.llm_client import poster_llm_client

        system_prompt = f"""你是一位专业的保险营销文案撰写人。
根据以下产品信息和客户数据，生成一张保险营销海报的文案。

要求：
1. 标题（headline）：简短有力，8字以内
2. 正文（body）：突出产品亮点与客户需求的匹配，50-100字
3. 行动号召（call_to_action）：引导客户咨询，15字以内
4. 风格：{style}
5. 必须基于真实数据，不得虚构收益数字

以 JSON 格式返回（不要包含 markdown 代码块标记）。"""

        user_prompt = f"""
产品信息：{json.dumps(product_rules, ensure_ascii=False)}
客户数据：{json.dumps(customer_data, ensure_ascii=False)}"""

        result, _response = await poster_llm_client.structured_output(
            user_prompt, system_prompt,
            schema={
                "type": "object",
                "properties": {
                    "headline": {"type": "string"},
                    "body": {"type": "string"},
                    "call_to_action": {"type": "string"},
                },
                "required": ["headline", "body", "call_to_action"],
            },
        )
        return result