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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()
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