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https://github.com/linyqh/NarratoAI.git
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5ef9f4a10c
删除了旧的提示词文件，并在多个文件中更新了字幕分析和脚本生成的实现，集成了统一的LLM服务架构。新增了对服务提供商的支持，优化了API调用和JSON响应解析，提升了系统的灵活性和稳定性，确保了对不同LLM的兼容性，增强了用户体验。
44 lines
1.2 KiB
Python
44 lines
1.2 KiB
Python
"""
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视频脚本生成pipeline，串联各个处理步骤
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"""
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import os
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from .utils.step1_subtitle_analyzer_openai import analyze_subtitle
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from .utils.step5_merge_script import merge_script
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def generate_script(srt_path: str, api_key: str, model_name: str, output_path: str, base_url: str = None, custom_clips: int = 5, provider: str = None):
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"""生成视频混剪脚本
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Args:
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srt_path: 字幕文件路径
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api_key: API密钥
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model_name: 模型名称
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output_path: 输出文件路径，可选
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base_url: API基础URL
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custom_clips: 自定义片段数量
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provider: LLM服务提供商
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Returns:
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str: 生成的脚本内容
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"""
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# 验证输入文件
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if not os.path.exists(srt_path):
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raise FileNotFoundError(f"字幕文件不存在: {srt_path}")
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# 分析字幕
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print("开始分析...")
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openai_analysis = analyze_subtitle(
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srt_path=srt_path,
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api_key=api_key,
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model_name=model_name,
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base_url=base_url,
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custom_clips=custom_clips,
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provider=provider
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)
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# 合并生成最终脚本
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adjusted_results = openai_analysis['plot_points']
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final_script = merge_script(adjusted_results, output_path)
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return final_script
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