#!/usr/bin/env python3
"""
平台适配文章撰写
根据大纲和平台配置（字数/格式/配图要求），为知乎/公众号/小红书各平台生成适配内容
"""
import json, datetime, logging, sys, re
from pathlib import Path
from typing import Dict, List

PROJECT_ROOT = Path(__file__).parent.parent
sys.path.insert(0, str(PROJECT_ROOT))
sys.path.insert(0, str(PROJECT_ROOT / 'platform' / 'backend'))

from db_helper import get_topic_by_id, update_topic_status, save_article
from content_cleaner import strip_thinking, strip_ai_preface, clean_markdown_content, clean_html_content
from prompt_loader import get_prompt, get_prompt_params
try:
    from app.core.nvidia_client import call_llm
    HAVE_LLM = True
except ImportError:
    HAVE_LLM = False

import mistune

DATA_DIR = PROJECT_ROOT / "automation" / "data"
OUTLINE_DIR = DATA_DIR / "outlines"
TEMPLATES_DIR = PROJECT_ROOT / "automation" / "templates"
LOGS_DIR = PROJECT_ROOT / "automation" / "logs"
TODAY = datetime.datetime.now().strftime("%Y-%m-%d")
GEN_TIME = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")

logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(message)s',
    handlers=[
        logging.FileHandler(LOGS_DIR / f"writer_{TODAY}.log"),
        logging.StreamHandler()
    ]
)
logger = logging.getLogger(__name__)

_md_parser = mistune.create_markdown()

_FALLBACK_PLATFORM_CONFIG = {
    "zhihu": {"max_chars": 3000, "style": "深度长文分析", "min_chars": 1500},
    "wechat": {"max_chars": 1500, "style": "亲切口语化", "min_chars": 800},
    "xiaohongshu": {"max_chars": 800, "style": "图文笔记，emoji+标签", "min_chars": 300},
}

def _load_platform_config() -> dict:
    try:
        from app.database import SessionLocal
        from app.models import PlatformConfig
        db = SessionLocal()
        configs = db.query(PlatformConfig).all()
        db.close()
        result = {}
        for c in configs:
            result[c.platform] = {
                "max_chars": c.max_words or _FALLBACK_PLATFORM_CONFIG.get(c.platform, {}).get("max_chars", 3000),
                "style": c.default_format or _FALLBACK_PLATFORM_CONFIG.get(c.platform, {}).get("style", "深度内容"),
                "min_chars": c.min_words or _FALLBACK_PLATFORM_CONFIG.get(c.platform, {}).get("min_chars", 300),
            }
        return result
    except Exception:
        pass
    return dict(_FALLBACK_PLATFORM_CONFIG)

PLATFORM_CONFIG = _load_platform_config()

class Writer:
    def __init__(self, topic_id: str):
        self.topic_id = topic_id
        self.topic = self._load_topic()
        outline_file = OUTLINE_DIR / TODAY / f"{topic_id}_outline.md"
        if not outline_file.exists():
            raise FileNotFoundError(f"Outline not found: {outline_file}")
        self.outline_content = outline_file.read_text(encoding='utf-8')
        research_file = DATA_DIR / "research" / TODAY / f"{topic_id}_research.md"
        self.research_notes = research_file.read_text(encoding='utf-8') if research_file.exists() else ""

    def _load_topic(self) -> Dict:
        topic = get_topic_by_id(self.topic_id)
        if not topic:
            raise ValueError(f"Topic {self.topic_id} not found")
        return topic

    def _clean_title(self, title: str) -> str:
        title = re.sub(r'[（(]约\s*\d+字[）)]', '', title)
        title = re.sub(r'[（(]MVP[）)]', '', title)
        title = re.sub(r'[（(][^）)]*?[）)]', '', title)
        return title.strip()

    def _parse_outline_sections(self) -> List[Dict]:
        sections = []
        current = None
        for line in self.outline_content.splitlines():
            if line.startswith("# "):
                if current:
                    sections.append(current)
                current = {"level": 1, "title": line[2:].strip(), "content": "", "section_type": "normal"}
            elif line.startswith("## "):
                if current:
                    sections.append(current)
                title = line[3:].strip()
                stype = "noise" if title in ("文章大纲", "大纲", "文章结构", "结构") else "normal"
                current = {"level": 2, "title": title, "content": "", "section_type": stype}
            elif line.startswith("### "):
                if current:
                    sections.append(current)
                current = {"level": 3, "title": line[4:].strip(), "content": "", "section_type": "normal"}
            else:
                if current and line.strip():
                    current['content'] = current.get('content', '') + line + "\n"
        if current:
            sections.append(current)
        return sections

    @staticmethod
    def _clean_markdown(text: str) -> str:
        return clean_markdown_content(text)

    @staticmethod
    def _is_outline_noise(line: str) -> bool:
        stripped = line.strip()
        if not stripped:
            return True
        if stripped.startswith('---'):
            return True
        if '大纲生成时间' in stripped:
            return True
        if stripped.startswith('*大纲'):
            return True
        if re.match(r'^\*{0,3}【[^】]*】\*{0,3}\s*$', stripped):
            return True
        return False

    def _is_bullet_only(self, text: str) -> bool:
        """检查内容是否主要是要点列表（大纲格式），需要 LLM 展开"""
        lines = [l.strip() for l in text.split('\n') if l.strip()]
        if not lines:
            return False
        bullet_count = sum(1 for l in lines if l.startswith(('- ', '* ', '**', '+ ')))
        return bullet_count / len(lines) > 0.4

    def _expand_section(self, section: Dict) -> str:
        content = section.get('content', '').strip()
        # 大纲要点格式（>40% 行以 -/*/** 开头）应始终由 LLM 展开为连贯段落
        if HAVE_LLM and self._is_bullet_only(content):
            logger.info(f"使用 LLM 扩写章节(要点→段落): {section['title']}")
            prompt = get_prompt("section_expansion",
                topic_title=self.topic['title'],
                section_title=section['title'],
                date=datetime.datetime.now().strftime('%Y年%m月%d日'),
                content=content,
            )
            try:
                params = get_prompt_params("section_expansion")
                expanded = call_llm(prompt, temperature=params.get("temperature", 0.75), max_tokens=params.get("max_tokens", 3000))
                if expanded:
                    cleaned = self._clean_markdown(expanded.strip())
                    if cleaned:
                        return cleaned
            except Exception as e:
                logger.warning(f"LLM 扩写失败: {e}")

        # Fallback: 将 bullet points 展开为段落（过滤噪音行）
        lines = [l.strip() for l in content.split('\n') if not self._is_outline_noise(l)]
        if lines:
            sentences = []
            for line in lines:
                text = line
                for prefix in ['- ', '* ', '1. ', '2. ', '3. ', '4. ', '5. ']:
                    if line.startswith(prefix):
                        text = line[len(prefix):]
                        break
                text = text.strip()
                if text:
                    if text[-1] not in '。！？；':
                        text += '。'
                    sentences.append(text)
            if sentences:
                result = ' '.join(sentences)
                return self._clean_markdown(result)
        return ''

    def generate_full_markdown(self) -> str:
        sections = self._parse_outline_sections()
        parts = []
        for sec in sections:
            if sec['level'] == 1:
                if sec.get('content'):
                    expanded = self._expand_section(sec)
                    if expanded:
                        parts.append(expanded + "\n")
                continue
            # 跳过大纲结构噪音节点
            title_stripped = sec['title'].strip()
            if title_stripped in ('文章大纲', '大纲', '文章结构', '结构'):
                continue
            if sec.get('section_type') == 'noise':
                continue
            heading = f"{'#' * sec['level']} {sec['title']}"
            parts.append(heading)
            if sec.get('content'):
                expanded = self._expand_section(sec)
                parts.append(expanded + "\n")
        full_md = "\n".join(parts).strip()
        return full_md

    def _adapt_for_platform(self, markdown: str, platform: str) -> str:
        cfg = PLATFORM_CONFIG[platform]
        max_c = cfg['max_chars']
        lines = markdown.split('\n')

        if platform == "xiaohongshu":
            result = []
            char_count = 0
            for line in lines:
                if char_count >= max_c:
                    break
                if line.startswith('## '):
                    line = f"## ✨ {line[3:]}"
                elif line.startswith('### '):
                    line = f"### 💡 {line[4:]}"
                result.append(line)
                char_count += len(line)
            adapted = '\n'.join(result)
            if adapted.count('#') == 0:
                adapted = f"# {self.topic['title']}\n\n{adapted}"
            return adapted

        if platform == "wechat":
            result = []
            for line in lines:
                line = line.replace('我', '你')
                if line.startswith('### '):
                    result.append(f"\n**{line[4:]}**\n")
                elif line.startswith('## '):
                    result.append(f"\n**{line[3:]}**\n")
                elif line.strip() and len(line) > 80:
                    sentences = [s.strip() for s in line.replace('。', '。\n').split('\n') if s.strip()]
                    for s in sentences:
                        if s:
                            result.append(s)
                else:
                    result.append(line)
            adapted = '\n'.join(result)
            return adapted

        return markdown

    def _get_platform_tags(self, platform: str) -> str:
        field = self.topic.get('field', '')
        title = self.topic.get('title', '')
        core = self.topic.get('core_concept', '')

        tag_prompts = {
            "zhihu": get_prompt("tags_generation", platform="知乎", title=title, field=field, core=core),
            "wechat": get_prompt("tags_generation", platform="公众号", title=title, field=field, core=core),
            "xiaohongshu": get_prompt("tags_generation", platform="小红书", title=title, field=field, core=core),
        }

        if HAVE_LLM:
            prompt = tag_prompts.get(platform, get_prompt("tags_generation", platform=platform, title=title, field=field, core=core))
            try:
                params = get_prompt_params("tags_generation")
                tags_text = call_llm(prompt, temperature=params.get("temperature", 0.3), max_tokens=params.get("max_tokens", 500))
                tags_text = strip_thinking(tags_text)
                if tags_text:
                    tags = [t.strip('#') for t in tags_text.strip().split() if t.strip('#')]
                    if tags:
                        return " ".join(f'<span class="tag">{t}</span>' for t in tags[:5])
            except Exception:
                pass

        tags = []
        if field:
            import re
            parts = re.split(r'[/、与和及]', field)
            for p in parts:
                p = p.strip()
                if len(p) >= 2:
                    tags.append(p)
            if len(parts) == 1 and len(parts[0]) > 4:
                for i in range(0, len(parts[0]), 2):
                    chunk = parts[0][i:i+2]
                    if len(chunk) == 2:
                        tags.append(chunk)
                tags.pop(0)

        platform_extra = {"zhihu": ["职场"], "xiaohongshu": ["生活"]}
        for t in platform_extra.get(platform, []):
            if t not in tags:
                tags.append(t)

        if not tags:
            tags = ["科技"]

        seen = set()
        return " ".join(f'<span class="tag">{t}</span>' for t in tags if t not in seen and not seen.add(t))

    def _optimize_title(self, platform: str) -> str:
        original = self.topic['title']
        if not HAVE_LLM:
            return original

        if platform == "zhihu":
            prompt = get_prompt("title_optimize_zhihu",
                title=original,
                core=self.topic.get('core_concept', ''),
                pain=self.topic.get('audience_pain', ''),
                field=self.topic.get('field', ''),
            )
        elif platform == "wechat":
            prompt = get_prompt("title_optimize_wechat",
                title=original,
                core=self.topic.get('core_concept', ''),
            )
        elif platform == "xiaohongshu":
            prompt = get_prompt("title_optimize_xhs",
                title=original,
                core=self.topic.get('core_concept', ''),
            )
        else:
            prompt = f"给以下文章改个吸引人的{platform}标题：{original}"

        try:
            if platform in ("zhihu", "wechat", "xiaohongshu"):
                params = get_prompt_params(f"title_optimize_{platform}")
                resp = call_llm(prompt, temperature=params.get("temperature", 0.8), max_tokens=params.get("max_tokens", 1500))
            else:
                resp = call_llm(prompt, temperature=0.7)
            resp = strip_thinking(resp)
            titles = []
            for line in resp.strip().split('\n'):
                line = line.strip()
                if not line:
                    continue
                line = re.sub(r'^\d+[.、)\s]+', '', line)
                line = line.strip('*#- \t')
                if line:
                    titles.append(line)
            if titles:
                logger.info(f"标题优化 [{platform}]: {titles[0][:50]}...")
                return titles[0]
        except Exception as e:
            logger.warning(f"标题优化失败: {e}")
        return original

    def generate_platform_html(self, markdown: str, platform: str) -> str:
        title = self._optimize_title(platform)
        adapted = self._adapt_for_platform(markdown, platform)
        tpl_path = TEMPLATES_DIR / f"{platform}.html"
        if tpl_path.exists():
            template = tpl_path.read_text(encoding='utf-8')
        else:
            template = "<!DOCTYPE html><html><head><meta charset='UTF-8'><title>{{TITLE}}</title><meta name='viewport' content='width=device-width'><style>body{max-width:800px;margin:0 auto;padding:20px;font-family:-apple-system,sans-serif;line-height:1.8}</style></head><body><h1>{{TITLE}}</h1><!-- CONTENT --></body></html>"

        adapted = strip_ai_preface(adapted)
        html = template.replace("{{TITLE}}", title).replace("{{DATE}}", TODAY).replace("{{GEN_TIME}}", GEN_TIME)
        html_content = _md_parser(adapted)

        # WeChat: insert topic-relevant image at start of body
        if platform == "wechat":
            import base64
            topic_title = self.topic.get('title', title)
            topic_field = self.topic.get('field', '')
            safe_title = topic_title.replace('&', '&amp;').replace('<', '&lt;').replace('>', '&gt;').replace('"', '&quot;').replace("'", '&apos;')
            safe_field = topic_field.replace('&', '&amp;').replace('<', '&lt;').replace('>', '&gt;')
            lines = []
            chars_per_line = 24
            for i in range(0, len(safe_title), chars_per_line):
                lines.append(safe_title[i:i+chars_per_line])
            if not lines:
                lines = ['配图']
            line_y = 220 - (len(lines) - 1) * 20
            title_texts = ''.join(f'<text x="540" y="{line_y + i*55}" font-size="36" fill="#1a1a1a" font-weight="bold">{l}</text>' for i, l in enumerate(lines))
            field_text = f'<text x="540" y="{line_y + len(lines)*55 + 30}" font-size="20" fill="#98a2b3">{safe_field}</text>' if safe_field else ''
            img_svg = f'''<svg xmlns="http://www.w3.org/2000/svg" width="1080" height="600" viewBox="0 0 1080 600" style="width:100%;max-width:1080px;border-radius:8px;background:linear-gradient(135deg,#f0f4ff,#e8f0fe)">
<rect width="1080" height="600" fill="url(#bg)"/>
<defs><linearGradient id="bg" x1="0%" y1="0%" x2="100%" y2="100%"><stop offset="0%" style="stop-color:#f0f4ff"/><stop offset="100%" style="stop-color:#e8f0fe"/></linearGradient></defs>
<g transform="translate(540,300)" text-anchor="middle" font-family="-apple-system,BlinkMacSystemFont,Helvetica Neue,PingFang SC,Microsoft YaHei,sans-serif">
<rect x="-60" y="-100" width="120" height="4" rx="2" fill="#409eff"/>
{title_texts}
{field_text}
<text y="100" font-size="14" fill="#c0c4cc">宇之然 · 配图（可替换）</text>
</g></svg>'''
            img_b64 = 'data:image/svg+xml;base64,' + base64.b64encode(img_svg.encode('utf-8')).decode('ascii')
            img_tag = f'<p><img src="{img_b64}" alt="{safe_title}" style="width:100%;max-width:1080px;border-radius:8px;"></p>\n'
            h1_end = html_content.find('</h1>')
            if h1_end != -1:
                html_content = html_content[:h1_end + 5] + '\n' + img_tag + html_content[h1_end + 5:]
            else:
                html_content = img_tag + html_content

        html = html.replace("<!-- CONTENT -->", html_content)

        # 防御：清理可能在 LLM 输出中混入的 markdown 代码围栏和文件头
        html = re.sub(r'^```+\w*\s*\n?', '', html)
        html = html.strip()

        tags_html = self._get_platform_tags(platform)
        if tags_html:
            html = html.replace("<!-- TAGS -->", tags_html)
        else:
            html = html.replace("<!-- TAGS -->", "")

        return html

    def save_html(self, html: str, platform: str) -> str:
        try:
            save_article(self.topic_id, platform, html)
            logger.info(f"文章写入数据库: {platform}_{self.topic_id}")
            return f"db:{platform}_{self.topic_id}"
        except Exception as e:
            logger.warning(f"数据库保存失败: {e}")
            return ""

    def mark_draft(self):
        update_topic_status(self.topic_id, 'review')
        logger.info(f"选题 {self.topic_id} 状态已更新为待审查（数据库）")

    def run(self):
        logger.info("开始撰写阶段")
        markdown = self.generate_full_markdown()
        results = {}
        for platform in ["zhihu", "wechat", "xiaohongshu"]:
            html = self.generate_platform_html(markdown, platform)
            results[platform] = str(self.save_html(html, platform))
        self.mark_draft()
        logger.info(f"撰写完成，状态已更新为待审查")
        return {"ok": True, "files": results}

def main():
    import argparse
    parser = argparse.ArgumentParser()
    parser.add_argument('--topic-id', required=True, help='选题ID')
    args = parser.parse_args()

    w = Writer(args.topic_id)
    result = w.run()
    print(json.dumps(result, ensure_ascii=False))
    sys.exit(0 if result['ok'] else 1)

if __name__ == "__main__":
    main()