#!/usr/bin/env python3 """ 合规审查与优化任务(数据库版) 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「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-workspace/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.modelscope_client import call_llm HAVE_LLM = True except ImportError: HAVE_LLM = False # 导入数据库辅助模块 from db_helper import get_topic_by_id, update_topic_status DATA_DIR = PROJECT_ROOT / "automation" / "data" RELEASES_DIR = DATA_DIR / "releases" DRAFTS_DIR = DATA_DIR / "drafts" 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(): """从数据库加载所有选题数据""" from db_helper import export_topics_to_json topics = export_topics_to_json() return {t['id']: t for t in topics} def update_topic_status_db_only(topic_id: str, status: str): """仅更新数据库状态(不更新JSON)""" from db_helper import update_topic_status update_topic_status(topic_id, status) def fix_wechat_title(html: str, title: str) -> str: """微信标题优化: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_tag = re.search(r'([^<]+)', html) if title_tag: full_title = title_tag.group(1) 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_match = re.search(r']*>([^<]+)', html) if h1_match: current_h1 = h1_match.group(1) 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"]) if '
' in html: old = html.split('
')[1].split('
')[0] html = html.replace(f'
{old}
', f'
{tags_str}
') elif platform == "xiaohongshu": tags_str = " ".join(f"#{t}" for t in PLATFORM_TAGS["xiaohongshu"]) if '
' in html: old = html.split('
')[1].split('
')[0] html = html.replace(f'
{old}
', f'
{tags_str}
') return html def optimize_article(html: str, platform: str, topic_data: Dict) -> (str, List[str]): logs = [] if platform == "wechat": html = fix_wechat_title(html, topic_data.get("title", "")) logs.append("标题截断(含后缀)") 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]}") img_tags = re.findall(r']*>', 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") 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

,

,

标签)。 原文: {html} 优化后:""" polished = call_llm(polish_prompt, temperature=0.5, max_tokens=4000) if '' 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] 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_db_only(topic_id, 'pending') 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 (JSON + 数据库) for res in results: if res.status == "passed": tid = res.topic_id # 更新数据库状态为 'pending'(待发布) update_topic_status(tid, 'ready') # 可选:同时更新 JSON 以保持兼容 # (已废弃,但保留更新,避免其他组件出错) try: json_path = DATA_DIR / "sustainability_topics.json" with open(json_path, 'r', encoding='utf-8') as f: topics = json.load(f) for t in topics: if t.get('id') == tid: t['status'] = 'ready' t['ready_at'] = TODAY t['compliance_score'] = res.final_score break with open(json_path, 'w', encoding='utf-8') as f: json.dump(topics, f, ensure_ascii=False, indent=2) except Exception as e: logger.warning(f"更新 JSON 失败: {e}") # 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)