"""节点 5/6：提示词构造（prompt_build）。

读取 prompts/<country>/ 的 extra 风格规则，用固定模板装配四种最终提示词
（image_prompt / wearable_prompt / composite_prompt / composite_negative）。
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。
"""
from typing import Any, Dict, List
import random

from graph.style_rules import derive_style_palette, derive_composition
from graph.templates import assemble_prompts
from graph.validate import validate_brief, with_fallback

# 图像生成策略敏感词 → 安全等效描述（生成设计稿前清洗 motif，
# 避免 gpt-image 等内容策略频繁拦截导致"生图限制多"）
_IMG_RISKY_SWAP = {
    "skull": "smiley mascot", "skeleton": "cute mascot", "blood": "red accents",
    "gore": "bold shapes", "gun": "star", "weapon": "tool", "bomb": "firework",
    "drug": "confetti", "demon": "cute monster", "devil": "mischievous imp",
    "occult": "mystic pattern", "satanic": "dark pattern", "nazi": "retro emblem",
    "hitler": "retro emblem", "zombie": "friendly ghoul", "horror": "spooky-cute",
    "vampire": "night owl", "politics": "abstract shapes", "political": "abstract",
    "president": "captain", "army": "team", "police": "officer",
}


def _safe_motif(motif: str) -> str:
    """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。"""
    low = motif.lower()
    for k, v in _IMG_RISKY_SWAP.items():
        if k in low:
            # 按词边界替换（避免误伤 "letterhead" 等）
            import re
            motif = re.sub(rf"\b{re.escape(k)}\b", v, motif, flags=re.IGNORECASE)
            low = motif.lower()
    return motif


@with_fallback("prompt_build")
def prompt_node(state: Dict[str, Any]) -> Dict[str, Any]:
    screened: List[Dict[str, Any]] = state.get("screened") or []
    config = state["config"]
    country = state["country"]
    cc = state["country_config"]
    extra_rules = cc.get("extra_style_rules") or []
    tpls = config.get("prompt_templates") or {}

    briefs: List[Dict[str, Any]] = []
    for r in screened:
        r = validate_brief(r)
        art, pal = derive_style_palette(
            r["topic"], country, extra_rules=extra_rules, category=r.get("design_category")
        )
        motif = (r.get("motif") or "").strip() or r.get("topic", "")
        cleaned = _safe_motif(motif)
        if cleaned != motif:
            print(f"[prompt] motif 敏感词清洗: 「{motif}」→「{cleaned}」（降低生图内容政策拦截）")
            r["motif"] = cleaned
            motif = cleaned
        art_style = (r.get("art_style") or art).strip()
        palette = (r.get("color_palette") or pal).strip()
        composition = (r.get("composition") or derive_composition(r["topic"], r.get("design_category"))).strip()

        prompts = assemble_prompts(motif, art_style, palette, composition, tpls, country)
        # 文字印花（约 30% 概率）：简报有 slogan 时，随机注入文字段到设计稿提示词
        slogan = (r.get("slogan") or "").strip()
        if slogan and random.random() < float(config.get("prompt_templates", {}).get("text_ratio", 0.3)):
            text_seg = (f', with the text "{slogan}" rendered as bold retro typography, '
                        f'lettering clean and correctly spelled, high contrast, as the focal text of the print')
            prompts["image_prompt"] = prompts["image_prompt"] + text_seg
            r["used_slogan"] = slogan
        # review（疑似商标/受保护主题）→ 动态注入「原创化魔改」引导：只做风格参考，禁止复刻品牌/商标/角色，
        # 换名换细节，生成通用非侵权的致敬式设计
        if str(r.get("risk_level", "")).strip().lower() == "review":
            prompts["image_prompt"] = (prompts["image_prompt"]
                + " IMPORTANT: this theme is ONLY a loose stylistic reference. "
                  "Do NOT reproduce any brand logo, trademark, character, mascot, copyrighted artwork or real person. "
                  "Create a fully ORIGINAL design with a different name and distinct visual details and colors — "
                  "a generic, non-infringing homage in the same mood, clearly distinct from the original.")
            print(f"[prompt] review 简报注入原创化魔改引导: 「{r['topic']}」")
        r.update(prompts)
        r["motif"] = motif
        r["art_style"] = art_style
        r["color_palette"] = palette
        r["composition"] = composition
        briefs.append(r)

    stats = dict(state.get("stats") or {})
    stats["prompt"] = {"briefs": len(briefs)}
    return {"briefs": briefs, "stats": stats}
