80805449ca
- skill/ 技能库：index.json 11 技能 + community_techniques.md 社区技巧 + character_sheet_learn.md 角色版学习 + scene_4view_learn.md 场景四视图工业级方法 + character-sheet-generator 开源技能(7风格模板) - tools/character_turnaround.py：人物三/四视图(主视觉+三视图/展示台)+场景四视角，Z-Image 本地 - tools/audio_pipeline.py：Edge-TTS配音+字幕+BGM+混音，Agent stage⑥有声成片 - agent_short_drama.py：一键短剧 Agent --until audio 全链路 - eed_web.py：技能库端点(/api/skills,/api/skill)+E2BIG根治(字节截断+巨兽降级)+一键短剧按钮
118 lines
4.3 KiB
Python
118 lines
4.3 KiB
Python
#!/usr/bin/env python3
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# 步骤⑦ storyboard 引擎: 豆包 AI 拆解剧本 → 结构化分镜 JSON
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# 通用版 — 支持任意剧本文件
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# DEPENDS: lib/doubao_chat.py
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import sys, os, json, argparse
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from lib.doubao_chat import breakdown_script
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def extract_json(text):
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"""从 AI 回复中提取 JSON 内容（兼容带 ```json 包裹的情况）"""
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if '```json' in text:
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return text.split('```json')[1].split('```')[0].strip()
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if '```' in text:
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return text.split('```')[1].split('```')[0].strip()
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# 尝试直接解析
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maybe = text.strip()
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if maybe.startswith('{'):
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return maybe
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return maybe
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def main():
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parser = argparse.ArgumentParser(description='豆包AI → 拆解剧本为结构化分镜JSON')
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parser.add_argument('script', help='剧本文件路径 (.hdlp 或 .txt)')
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parser.add_argument('-e', '--episode', type=int, default=1, help='集号 (默认: 1)')
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parser.add_argument('-o', '--output', help='输出路径 (默认: 自动推导)')
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parser.add_argument('--pro', action='store_true', help='使用 Pro 模型 (doubao-pro, 更强更贵)')
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parser.add_argument('--dry-run', action='store_true', help='只打印将发送的提示词，不调API')
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args = parser.parse_args()
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# 读剧本
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if not os.path.isfile(args.script):
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print(f'❌ 找不到剧本文件: {args.script}')
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sys.exit(1)
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with open(args.script, 'r', encoding='utf-8') as f:
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script_text = f.read()
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print(f'📖 剧本: {args.script}')
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print(f'📐 长度: {len(script_text)} 字符')
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print(f'🎬 集号: EP{args.episode:02d}')
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print(f'🧠 模型: {"doubao-pro" if args.pro else "doubao-lite"}')
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print()
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if args.dry_run:
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print('🧪 DRY RUN — 将发送的提示词:')
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print('=' * 60)
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from lib.doubao_chat import breakdown_script as bd
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print(bd.__doc__)
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print('=' * 60)
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return
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# 调用豆包 API
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print('🚀 发送豆包 AI 拆解剧本...')
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result = breakdown_script(script_text, args.episode, model='pro' if args.pro else 'lite')
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if 'error' in result:
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print('❌ API ERROR:', json.dumps(result, ensure_ascii=False, indent=2))
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sys.exit(1)
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if 'content' not in result or not result['content']:
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print('❌ API 返回空内容:', json.dumps(result, ensure_ascii=False, indent=2))
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sys.exit(1)
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content = result['content']
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json_str = extract_json(content)
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# 解析 JSON 验证有效性
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try:
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parsed = json.loads(json_str)
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shot_count = len(parsed.get('shots', []))
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except json.JSONDecodeError as e:
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print(f'⚠️ JSON 解析失败: {e}')
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print('原始内容:')
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print(content[:500])
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shot_count = 0
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parsed = None
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# 确定输出路径
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if args.output:
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out_path = args.output
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else:
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# 从剧本路径自动推导
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script_dir = os.path.dirname(os.path.abspath(args.script))
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script_base = os.path.splitext(os.path.basename(args.script))[0]
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# 如果剧本文件名包含 SCRIPT 或 BREAKDOWN，替换为 STORYBOARD
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if 'SCRIPT' in script_base.upper() or 'BREAKDOWN' in script_base.upper():
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storyboard_name = script_base.replace('SCRIPT', 'STORYBOARD').replace('BREAKDOWN', 'STORYBOARD')
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else:
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model_tag = 'PRO' if args.pro else 'AI'
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storyboard_name = f'STORYBOARD-{model_tag}-EP{args.episode:02d}'
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out_path = os.path.join(script_dir, f'{storyboard_name}.json')
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# 保存
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with open(out_path, 'w', encoding='utf-8') as f:
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f.write(json_str if parsed else content.strip())
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print(f'\n✅ 分镜已保存: {out_path}')
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if parsed:
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print(f'📊 共 {shot_count} 镜')
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print(f'💰 tokens: {result.get("tokens", "N/A")}')
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print(f'⏱️ 完成原因: {result.get("finish", "N/A")}')
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# 打印前3镜预览
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if parsed and shot_count > 0:
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print('\n📋 前3镜预览:')
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for s in parsed['shots'][:3]:
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print(f' {s.get("shot_number","?"):>4} | {s.get("camera","?"): <4} | {s.get("duration","?"):>2}s | {s.get("description","")[:40]}')
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if __name__ == '__main__':
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main()
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