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| #!/usr/bin/env python | |
| # -*- coding: UTF-8 -*- | |
| ''' | |
| @Project: NarratoAI | |
| @File : 短剧解说脚本生成 | |
| @Author : 小林同学 | |
| @Date : 2025/5/10 下午10:26 | |
| ''' | |
| import os | |
| import json | |
| import time | |
| import traceback | |
| import streamlit as st | |
| from loguru import logger | |
| from app.config import config | |
| from app.services.SDE.short_drama_explanation import analyze_subtitle, generate_narration_script | |
| def generate_script_short_sunmmary(params, subtitle_path, video_theme, temperature): | |
| """ | |
| 生成 短剧解说 视频脚本 | |
| 要求: 提供高质量短剧字幕 | |
| 适合场景: 短剧 | |
| """ | |
| progress_bar = st.progress(0) | |
| status_text = st.empty() | |
| def update_progress(progress: float, message: str = ""): | |
| progress_bar.progress(progress) | |
| if message: | |
| status_text.text(f"{progress}% - {message}") | |
| else: | |
| status_text.text(f"进度: {progress}%") | |
| try: | |
| with st.spinner("正在生成脚本..."): | |
| if not params.video_origin_path: | |
| st.error("请先选择视频文件") | |
| return | |
| """ | |
| 1. 获取字幕 | |
| """ | |
| update_progress(30, "正在解析字幕...") | |
| # 判断字幕文件是否存在 | |
| if not os.path.exists(subtitle_path): | |
| st.error("字幕文件不存在") | |
| return | |
| """ | |
| 2. 分析字幕总结剧情 | |
| """ | |
| text_provider = config.app.get('text_llm_provider', 'gemini').lower() | |
| text_api_key = config.app.get(f'text_{text_provider}_api_key') | |
| text_model = config.app.get(f'text_{text_provider}_model_name') | |
| text_base_url = config.app.get(f'text_{text_provider}_base_url') | |
| analysis_result = analyze_subtitle( | |
| subtitle_file_path=subtitle_path, | |
| api_key=text_api_key, | |
| model=text_model, | |
| base_url=text_base_url, | |
| save_result=True, | |
| temperature=temperature | |
| ) | |
| """ | |
| 3. 根据剧情生成解说文案 | |
| """ | |
| if analysis_result["status"] == "success": | |
| logger.info("字幕分析成功！") | |
| update_progress(60, "正在生成文案...") | |
| # 根据剧情生成解说文案 | |
| narration_result = generate_narration_script( | |
| short_name=video_theme, | |
| plot_analysis=analysis_result["analysis"], | |
| api_key=text_api_key, | |
| model=text_model, | |
| base_url=text_base_url, | |
| save_result=True, | |
| temperature=temperature | |
| ) | |
| if narration_result["status"] == "success": | |
| logger.info("\n解说文案生成成功！") | |
| logger.info(narration_result["narration_script"]) | |
| else: | |
| logger.info(f"\n解说文案生成失败: {narration_result['message']}") | |
| st.error("生成脚本失败，请检查日志") | |
| st.stop() | |
| else: | |
| logger.error(f"分析失败: {analysis_result['message']}") | |
| st.error("生成脚本失败，请检查日志") | |
| st.stop() | |
| """ | |
| 4. 生成文案 | |
| """ | |
| logger.info("开始准备生成解说文案") | |
| # 结果转换为JSON字符串 | |
| narration_script = narration_result["narration_script"] | |
| narration_dict = json.loads(narration_script) | |
| script = json.dumps(narration_dict['items'], ensure_ascii=False, indent=2) | |
| if script is None: | |
| st.error("生成脚本失败，请检查日志") | |
| st.stop() | |
| logger.success(f"剪辑脚本生成完成") | |
| if isinstance(script, list): | |
| st.session_state['video_clip_json'] = script | |
| elif isinstance(script, str): | |
| st.session_state['video_clip_json'] = json.loads(script) | |
| update_progress(90, "整理输出...") | |
| time.sleep(0.1) | |
| progress_bar.progress(100) | |
| status_text.text("脚本生成完成！") | |
| st.success("视频脚本生成成功！") | |
| except Exception as err: | |
| st.error(f"生成过程中发生错误: {str(err)}") | |
| logger.exception(f"生成脚本时发生错误\n{traceback.format_exc()}") | |
| finally: | |
| time.sleep(2) | |
| progress_bar.empty() | |
| status_text.empty() | |