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1c7abd81d1
- 310 registry:skill items, 1528 files, 7 categories (hub tags) - registry.json generated by @kortix/registry buildRegistry - nested SKILL.md in sn-da-* renamed SUBSKILL.md (no phantom skills) - provenance + licenses: SOURCES.md
252 lines
7.4 KiB
Python
252 lines
7.4 KiB
Python
#!/usr/bin/env python3
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"""
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分析字幕并生成章节
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解析 VTT 字幕文件，准备数据供 Claude AI 分析
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"""
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import sys
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import re
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import json
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from pathlib import Path
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from typing import List, Dict
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from utils import (
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time_to_seconds,
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seconds_to_time,
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get_video_duration_display
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)
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def parse_vtt(vtt_path: str) -> List[Dict]:
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"""
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解析 VTT 字幕文件
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Args:
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vtt_path: VTT 文件路径
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Returns:
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List[Dict]: 字幕列表，每项包含 {start, end, text}
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Example:
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[
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{'start': 0.0, 'end': 3.5, 'text': 'Hello world'},
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{'start': 3.5, 'end': 7.2, 'text': 'This is a test'},
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...
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]
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"""
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vtt_path = Path(vtt_path)
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if not vtt_path.exists():
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raise FileNotFoundError(f"Subtitle file not found: {vtt_path}")
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print(f"📊 解析字幕文件: {vtt_path.name}")
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subtitles = []
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with open(vtt_path, 'r', encoding='utf-8') as f:
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content = f.read()
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# 移除 WEBVTT 头部和样式信息
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content = re.sub(r'^WEBVTT.*?\n\n', '', content, flags=re.DOTALL)
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content = re.sub(r'STYLE.*?-->', '', content, flags=re.DOTALL)
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# 分割字幕块
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blocks = content.strip().split('\n\n')
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for block in blocks:
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lines = block.strip().split('\n')
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if len(lines) < 2:
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continue
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# 查找时间戳行
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timestamp_line = None
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text_lines = []
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for line in lines:
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# 匹配时间戳格式: 00:00:00.000 --> 00:00:03.000
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if '-->' in line:
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timestamp_line = line
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elif line and not line.isdigit(): # 跳过序号
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text_lines.append(line)
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if not timestamp_line or not text_lines:
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continue
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# 解析时间戳
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try:
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# 移除可能的位置信息（如 align:start position:0%）
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timestamp_line = re.sub(r'align:.*|position:.*', '', timestamp_line).strip()
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times = timestamp_line.split('-->')
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start_str = times[0].strip()
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end_str = times[1].strip()
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start = time_to_seconds(start_str)
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end = time_to_seconds(end_str)
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# 合并文本行
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text = ' '.join(text_lines)
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# 清理 HTML 标签（如果有）
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text = re.sub(r'<[^>]+>', '', text)
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# 清理特殊字符
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text = text.strip()
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if text:
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subtitles.append({
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'start': start,
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'end': end,
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'text': text
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})
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except Exception as e:
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# 跳过无法解析的字幕块
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continue
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print(f" 找到 {len(subtitles)} 条字幕")
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if subtitles:
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total_duration = subtitles[-1]['end']
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print(f" 总时长: {get_video_duration_display(total_duration)}")
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return subtitles
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def prepare_analysis_data(subtitles: List[Dict], target_chapter_duration: int = 180) -> Dict:
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"""
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准备数据供 Claude AI 分析
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Args:
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subtitles: 字幕列表
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target_chapter_duration: 目标章节时长（秒），默认 180 秒（3 分钟）
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Returns:
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Dict: {
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'subtitle_text': 带时间戳的完整字幕文本,
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'total_duration': 总时长,
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'subtitle_count': 字幕条数,
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'target_chapter_duration': 目标章节时长,
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'estimated_chapters': 预估章节数
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}
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"""
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if not subtitles:
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raise ValueError("No subtitles to analyze")
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print(f"\n📝 准备分析数据...")
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# 将字幕合并为带时间戳的完整文本
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full_text_lines = []
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for sub in subtitles:
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time_str = seconds_to_time(sub['start'], include_hours=True, use_comma=False)
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full_text_lines.append(f"[{time_str}] {sub['text']}")
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full_text = '\n'.join(full_text_lines)
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total_duration = subtitles[-1]['end']
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estimated_chapters = max(1, int(total_duration / target_chapter_duration))
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print(f" 总时长: {get_video_duration_display(total_duration)}")
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print(f" 字幕条数: {len(subtitles)}")
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print(f" 目标章节时长: {target_chapter_duration} 秒 ({target_chapter_duration // 60} 分钟)")
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print(f" 预估章节数: {estimated_chapters}")
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return {
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'subtitle_text': full_text,
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'total_duration': total_duration,
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'subtitle_count': len(subtitles),
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'target_chapter_duration': target_chapter_duration,
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'estimated_chapters': estimated_chapters,
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'subtitles_raw': subtitles # 保留原始数据供后续使用
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}
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def save_analysis_data(data: Dict, output_path: str):
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"""
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保存分析数据到 JSON 文件
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Args:
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data: 分析数据
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output_path: 输出文件路径
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"""
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output_path = Path(output_path)
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# 创建输出目录
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output_path.parent.mkdir(parents=True, exist_ok=True)
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# 保存为 JSON
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with open(output_path, 'w', encoding='utf-8') as f:
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json.dump(data, f, indent=2, ensure_ascii=False)
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print(f"✅ 分析数据已保存: {output_path}")
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def main():
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"""命令行入口"""
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if len(sys.argv) < 2:
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print("Usage: python analyze_subtitles.py <vtt_file> [target_duration] [output_json]")
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print("\nArguments:")
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print(" vtt_file - VTT 字幕文件路径")
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print(" target_duration - 目标章节时长（秒），默认 180")
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print(" output_json - 输出 JSON 文件路径（可选）")
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print("\nExample:")
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print(" python analyze_subtitles.py video.en.vtt")
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print(" python analyze_subtitles.py video.en.vtt 240")
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print(" python analyze_subtitles.py video.en.vtt 240 analysis.json")
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sys.exit(1)
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vtt_file = sys.argv[1]
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target_duration = int(sys.argv[2]) if len(sys.argv) > 2 else 180
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output_json = sys.argv[3] if len(sys.argv) > 3 else None
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try:
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# 解析字幕
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subtitles = parse_vtt(vtt_file)
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if not subtitles:
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print("❌ 未找到有效字幕")
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sys.exit(1)
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# 准备分析数据
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analysis_data = prepare_analysis_data(subtitles, target_duration)
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# 输出字幕文本（供 Claude 分析）
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print("\n" + "="*60)
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print("字幕文本（前 50 行预览）:")
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print("="*60)
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lines = analysis_data['subtitle_text'].split('\n')
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preview_lines = lines[:50]
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print('\n'.join(preview_lines))
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if len(lines) > 50:
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print(f"\n... （还有 {len(lines) - 50} 行）")
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# 保存到文件（如果指定）
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if output_json:
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save_analysis_data(analysis_data, output_json)
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# 输出摘要信息
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print("\n" + "="*60)
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print("分析摘要:")
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print("="*60)
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print(json.dumps({
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'total_duration': analysis_data['total_duration'],
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'total_duration_display': get_video_duration_display(analysis_data['total_duration']),
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'subtitle_count': analysis_data['subtitle_count'],
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'target_chapter_duration': analysis_data['target_chapter_duration'],
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'estimated_chapters': analysis_data['estimated_chapters']
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}, indent=2, ensure_ascii=False))
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print("\n💡 提示：现在可以使用 Claude AI 分析上述字幕文本，生成精细章节")
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except Exception as e:
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print(f"\n❌ 错误: {str(e)}")
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import traceback
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traceback.print_exc()
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sys.exit(1)
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if __name__ == "__main__":
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main()
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