#!/usr/bin/env python3
"""
合规审查与优化任务
每天 05:45 运行，处理当天所有 draft 文章：
1. 执行合规检查（compliance_checker）
2. 自动修复已知问题（标题、标签）
3. 重写合规版本
4. 更新选题状态为「审查通过待发布」
5. 生成优化报告通知
"""

import json, datetime, logging, sys, re
from pathlib import Path
from typing import Dict, List
from dataclasses import dataclass, asdict

PROJECT_ROOT = Path('/root/.openclaw/workspaces/yzr-yxl/projects/yu-zhi-ran')
sys.path.insert(0, str(PROJECT_ROOT))
from scripts.compliance_checker import check_article

# 导入 LLM 客户端（合规优化使用 NVIDIA）
sys.path.insert(0, str(PROJECT_ROOT / "platform" / "backend"))
try:
    from app.core.nvidia_client import call_llm
    HAVE_LLM = True
except ImportError:
    HAVE_LLM = False

DATA_DIR = PROJECT_ROOT / "automation" / "data"
RELEASES_DIR = DATA_DIR / "releases"
DRAFTS_DIR = DATA_DIR / "drafts"
TOPICS_FILE = DATA_DIR / "sustainability_topics.json"
LOGS_DIR = PROJECT_ROOT / "automation" / "logs"
TODAY = datetime.datetime.now().strftime("%Y-%m-%d")

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

# 平台白名单标签
PLATFORM_TAGS = {
    "zhihu": ["科技", "职场"],
    "xiaohongshu": ["AI", "可持续", "生活方式"]
}

@dataclass
class OptimizationResult:
    file: str
    platform: str
    topic_id: str
    title: str
    original_issues: int
    fixed_issues: int
    final_score: int
    status: str

def load_topic_map():
    with open(TOPICS_FILE, 'r', encoding='utf-8') as f:
        topics = json.load(f)
    return {t['id']: t for t in topics}


def update_topic_status(topic_id: str, status: str):
    """更新选题状态（JSON + 数据库）"""
    # 更新 JSON
    with open(TOPICS_FILE, 'r', encoding='utf-8') as f:
        topics = json.load(f)
    updated = False
    for t in topics:
        if t.get('id') == topic_id:
            t['status'] = status
            updated = True
            break
    if updated:
        with open(TOPICS_FILE, 'w', encoding='utf-8') as f:
            json.dump(topics, f, ensure_ascii=False, indent=2)
    # 更新数据库
    try:
        from app.database import SessionLocal
        from app.models import Topic
        db = SessionLocal()
        topic_db = db.query(Topic).filter(Topic.id == topic_id).first()
        if topic_db:
            topic_db.status = status
            db.commit()
        db.close()
    except Exception as e:
        logger.error(f"更新数据库失败: {e}")

def fix_wechat_title(html: str, title: str) -> str:
    """微信标题优化：<title>和<h1>都控制长度（考虑后缀）"""
    suffix = f" - {TODAY} - 微信公众号"
    max_base_len = 32 - len(suffix)  # <title> 中 base 部分允许的最大长度

    # 处理 <title>...</title>
    title_tag = re.search(r'<title>([^<]+)</title>', html)
    if title_tag:
        full_title = title_tag.group(1)
        # 提取 base（去掉后缀）
        if full_title.endswith(suffix):
            base = full_title[:-len(suffix)]
        else:
            base = full_title.split(" - ")[0]
        if len(base) > max_base_len:
            base = base[:max_base_len-3] + "..."
        new_full = base + suffix
        html = html.replace(full_title, new_full)

    # 处理 <h1>...</h1>（不含后缀，但要截断）
    h1_match = re.search(r'<h1[^>]*>([^<]+)</h1>', html)
    if h1_match:
        current_h1 = h1_match.group(1)
        # 如果 h1 包含后缀（不应该），去掉
        base_h1 = current_h1.split(" - ")[0] if " - " in current_h1 else current_h1
        if len(base_h1) > 32:
            base_h1 = base_h1[:29] + "..."
        html = html.replace(current_h1, base_h1)

    return html

def fix_tags(html: str, platform: str) -> str:
    """强制替换标签为平台白名单"""
    if platform == "zhihu":
        tags_str = " ".join(f"#{t}" for t in PLATFORM_TAGS["zhihu"])
        # 替换 <div class="tags">...</div>
        if '<div class="tags">' in html:
            old = html.split('<div class="tags">')[1].split('</div>')[0]
            html = html.replace(f'<div class="tags">{old}</div>', f'<div class="tags">{tags_str}</div>')
    elif platform == "xiaohongshu":
        tags_str = " ".join(f"#{t}" for t in PLATFORM_TAGS["xiaohongshu"])
        if '<div class="hashtags">' in html:
            old = html.split('<div class="hashtags">')[1].split('</div>')[0]
            html = html.replace(f'<div class="hashtags">{old}</div>', f'<div class="hashtags">{tags_str}</div>')
    return html

def optimize_article(html: str, platform: str, topic_data: Dict) -> (str, List[str]):
    logs = []
    # 1. 标题优化（微信）
    if platform == "wechat":
        html = fix_wechat_title(html, topic_data.get("title", ""))
        logs.append("标题截断（含后缀）")
    # 2. 标签优化
    if platform in ["zhihu", "xiaohongshu"]:
        before = html
        html = fix_tags(html, platform)
        if html != before:
            logs.append(f"标签标准化为{PLATFORM_TAGS[platform]}")
        # 3. 图片内联检查
        # 提取所有 img 标签
        img_tags = re.findall(r'<img[^>]*>', html, re.IGNORECASE)
        for tag in img_tags:
            m = re.search(r'src=["\']([^"\']+)["\']', tag, re.IGNORECASE)
            if m:
                src = m.group(1)
                if not src.startswith('data:image/'):
                    logs.append(f"图片未内联: {src[:50]}... 需手动修复")

        # 4. LLM 内容优化（使用 NVIDIA step-3.5-flash）
        if HAVE_LLM:
            try:
                polish_prompt = f"""你是一个专业的内容润色助手。请优化以下文章内容，提升表达的专业性和可读性，保持原文事实、数据、章节结构不变，输出相同的HTML格式（保留<h2>, <h3>, <p>标签）。

原文：
{html}

优化后："""
                polished = call_llm(polish_prompt, temperature=0.5, max_tokens=4000)
                if '<h2' in polished or '<p>' in polished:
                    html = polished
                    logs.append("LLM 内容优化（NVIDIA）")
            except Exception as e:
                logger.warning(f"LLM 优化失败: {e}")
    return html, logs

def main(topic_ids: List[str] = None):
    logger.info("=== 合规审查与优化开始 ===")
    release_dir = RELEASES_DIR / TODAY
    if not release_dir.exists():
        logger.warning(f"今日发布目录不存在: {release_dir}")
        return

    topic_map = load_topic_map()
    results = []
    all_passed = True

    for platform_dir in ["zhihu", "wechat", "xiaohongshu"]:
        platform_path = release_dir / platform_dir
        if not platform_path.exists():
            continue
        for html_file in platform_path.glob("*.html"):
            stem = html_file.stem
            parts = stem.split('_')
            if len(parts) < 2:
                continue
            topic_id = parts[1]
            # 如果指定了 topic_ids，则只处理匹配的
            if topic_ids is not None and topic_id not in topic_ids:
                continue
            topic_data = topic_map.get(topic_id)
            if not topic_data:
                logger.warning(f"未找到选题: {topic_id}")
                continue

            html = html_file.read_text(encoding='utf-8')
            check_result = check_article(html, platform_dir, topic_data)
            issues = check_result['issues']
            score = check_result['score']

            if any(issue['type'] == '平台规则' for issue in issues):
                optimized_html, opt_logs = optimize_article(html, platform_dir, topic_data)
                recheck = check_article(optimized_html, platform_dir, topic_data)
                if recheck['passed']:
                    html_file.write_text(optimized_html, encoding='utf-8')
                    logger.info(f"✅ {html_file.name} 已优化并通过合规检查")
                    results.append(OptimizationResult(
                        file=str(html_file.relative_to(PROJECT_ROOT)),
                        platform=platform_dir,
                        topic_id=topic_id,
                        title=topic_data.get('title',''),
                        original_issues=len(issues),
                        fixed_issues=len(issues) - len(recheck['issues']),
                        final_score=recheck['score'],
                        status="passed"
                    ))
                    update_topic_status(topic_id, '待发布')
                else:
                    logger.warning(f"⚠️ {html_file.name} 优化后仍有问题，需人工审核")
                    results.append(OptimizationResult(
                        file=str(html_file.relative_to(PROJECT_ROOT)),
                        platform=platform_dir,
                        topic_id=topic_id,
                        title=topic_data.get('title',''),
                        original_issues=len(issues),
                        fixed_issues=len(issues) - len(recheck['issues']),
                        final_score=recheck['score'],
                        status="manual_review"
                    ))
                    all_passed = False
            else:
                results.append(OptimizationResult(
                    file=str(html_file.relative_to(PROJECT_ROOT)),
                    platform=platform_dir,
                    topic_id=topic_id,
                    title=topic_data.get('title',''),
                    original_issues=0,
                    fixed_issues=0,
                    final_score=score,
                    status="passed" if check_result['passed'] else "manual_review"
                ))
                if not check_result['passed']:
                    all_passed = False

    # 更新选题状态
    for res in results:
        if res.status == "passed":
            tid = res.topic_id
            with open(TOPICS_FILE, 'r', encoding='utf-8') as f:
                topics = json.load(f)
            for t in topics:
                if t.get('id') == tid:
                    t['status'] = '待发布'
                    t['ready_at'] = TODAY
                    t['compliance_score'] = res.final_score
                    break
            with open(TOPICS_FILE, 'w', encoding='utf-8') as f:
                json.dump(topics, f, ensure_ascii=False, indent=2)

    # 生成报告
    report_file = DRAFTS_DIR / TODAY / "optimization_report.json"
    report_file.parent.mkdir(parents=True, exist_ok=True)
    report = {
        "date": TODAY,
        "summary": {
            "total_articles": len(results),
            "passed_auto": sum(1 for r in results if r.status == "passed"),
            "need_manual": sum(1 for r in results if r.status == "manual_review"),
            "average_score": sum(r.final_score for r in results) / len(results) if results else 0
        },
        "details": [asdict(r) for r in results],
        "all_passed": all_passed
    }
    with open(report_file, 'w', encoding='utf-8') as f:
        json.dump(report, f, ensure_ascii=False, indent=2)

    logger.info(f"✅ 合规优化完成: {len(results)} 篇文章, {sum(1 for r in results if r.status=='passed')} 篇自动通过")
    print(f"OPTIMIZATION_COMPLETE: {len(results)} articles, {sum(1 for r in results if r.status=='passed')} passed, {sum(1 for r in results if r.status=='manual_review')} need manual review")
    sys.exit(0)

if __name__ == "__main__":
    import argparse
    parser = argparse.ArgumentParser(description='合规审查与优化任务')
    parser.add_argument('--topic-ids', help='逗号分隔的选题ID列表，例如: A01,B02')
    args = parser.parse_args()
    topic_ids = args.topic_ids.split(',') if args.topic_ids else None
    main(topic_ids)