mirror of
https://github.com/linyqh/NarratoAI.git
synced 2026-09-19 10:26:22 +00:00
342fc15f3b
新增OmniVoice语音合成引擎全流程支持，包含配置项、WebUI界面与服务实现 集成Tavily联网搜索能力，支持短剧剧情分析前自动检索剧情背景信息 新增多视频源剪辑支持，完善脚本校验规则并重构剪辑逻辑适配多视频路径 重构LLM剧情分析Prompt，优化输出格式适配多场景与联网检索结果 调整streamlit版本至1.56.0修复兼容性问题 新增相关单元测试与多语言翻译，更新配置示例文件
262 lines
9.6 KiB
Python
262 lines
9.6 KiB
Python
import json
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import os
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import subprocess
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import time
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from os import path
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from typing import Dict
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from loguru import logger
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from app.config import config
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from app.models import const
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from app.models.schema import VideoClipParams
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from app.services import voice, clip_video, update_script
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from app.services.jianying_draft_builder import write_plaintext_jianying_draft
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from app.services import state as sm
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from app.utils import utils
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def get_media_duration_ffprobe(media_file: str) -> float:
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"""
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使用ffprobe获取媒体文件的精确时长（秒）
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Args:
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media_file: 媒体文件路径
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Returns:
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float: 媒体时长（秒），精确到微秒
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"""
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try:
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cmd = [
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'ffprobe',
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'-v', 'error',
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'-show_entries', 'format=duration',
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'-of', 'csv=p=0',
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media_file
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]
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result = subprocess.run(cmd, capture_output=True, text=True, check=True)
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duration = float(result.stdout.strip())
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logger.debug(f"使用ffprobe获取媒体时长: {duration:.6f}秒, 文件: {media_file}")
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return duration
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except subprocess.CalledProcessError as e:
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logger.error(f"ffprobe执行失败: {e.stderr}")
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raise
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except Exception as e:
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logger.error(f"获取媒体时长失败: {str(e)}")
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raise
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def get_audio_duration_ffprobe(audio_file: str) -> float:
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return get_media_duration_ffprobe(audio_file)
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def _strip_tts_voice_prefix(voice_name: str, prefix: str) -> str:
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voice_name = voice_name or ""
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if voice_name.startswith(prefix):
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return voice_name[len(prefix):]
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return voice_name
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def _strip_indextts_prefix(voice_name: str) -> str:
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return _strip_tts_voice_prefix(
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config.normalize_indextts_voice_prefix(voice_name or ""),
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config.INDEXTTS_VOICE_PREFIX,
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)
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def _floor_duration_to_milliseconds(duration: float) -> float:
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return int(duration * 1000) / 1000.0
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def _format_seconds_for_trange(seconds: float) -> str:
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return f"{seconds:.3f}s"
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def _get_cached_media_duration(media_file: str, duration_cache: Dict[str, float]) -> float:
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if media_file not in duration_cache:
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duration_cache[media_file] = _floor_duration_to_milliseconds(
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get_media_duration_ffprobe(media_file)
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)
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return duration_cache[media_file]
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def _clamp_duration_to_media(
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requested_duration: float,
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media_file: str,
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duration_cache: Dict[str, float],
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media_label: str,
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source_start_time: float = 0.0,
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) -> float:
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requested_duration = _floor_duration_to_milliseconds(max(requested_duration, 0.0))
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actual_duration = _get_cached_media_duration(media_file, duration_cache)
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available_duration = _floor_duration_to_milliseconds(
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max(actual_duration - max(source_start_time, 0.0), 0.0)
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)
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safe_duration = min(requested_duration, available_duration)
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logger.info(
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f"{media_label}实际时长: {actual_duration:.6f}秒, "
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f"可用时长: {available_duration:.6f}秒, 请求时长: {requested_duration:.3f}秒"
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)
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if safe_duration < requested_duration:
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logger.warning(
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f"{media_label}短于脚本时长，已将剪映片段时长从 "
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f"{requested_duration:.3f}秒 调整为 {safe_duration:.3f}秒"
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)
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return safe_duration
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def _normalize_indextts_reference_audio(params: VideoClipParams) -> None:
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"""Ensure local clone TTS engines use configured reference audio instead of a stale UI voice."""
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params.tts_engine = config.normalize_tts_engine_name(params.tts_engine)
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if params.tts_engine == config.INDEXTTS_ENGINE:
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tts_config = config.indextts
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voice_prefix = config.INDEXTTS_VOICE_PREFIX
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display_name = "IndexTTS-1.5"
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elif params.tts_engine == config.INDEXTTS2_ENGINE:
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tts_config = config.indextts2
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voice_prefix = config.INDEXTTS2_VOICE_PREFIX
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display_name = "IndexTTS-2"
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elif params.tts_engine == config.OMNIVOICE_ENGINE:
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tts_config = config.omnivoice
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if tts_config.get("mode", "auto") != "voice_clone":
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return
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voice_prefix = config.OMNIVOICE_VOICE_PREFIX
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display_name = "OmniVoice"
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else:
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return
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candidate = _strip_tts_voice_prefix(getattr(params, "voice_name", "") or "", voice_prefix)
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if candidate and os.path.isfile(candidate):
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params.voice_name = f"{voice_prefix}{candidate}"
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logger.info(f"{display_name} 使用参考音频: {candidate}")
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return
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configured_ref = _strip_tts_voice_prefix(tts_config.get("reference_audio", "") or "", voice_prefix)
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if configured_ref and os.path.isfile(configured_ref):
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params.voice_name = f"{voice_prefix}{configured_ref}"
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logger.info(f"{display_name} 使用配置中的参考音频: {configured_ref}")
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return
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raise ValueError(f"{display_name} 参考音频不存在，请在音频设置中上传或选择有效的参考音频")
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def start_export_jianying_draft(task_id: str, params: VideoClipParams):
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"""
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导出到剪映草稿的后台任务
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Args:
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task_id: 任务ID
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params: 视频参数
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"""
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logger.info(f"\n\n## 开始导出到剪映草稿任务: {task_id}")
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sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=0)
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"""
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1. 加载剪辑脚本
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"""
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logger.info("\n\n## 1. 加载视频脚本")
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video_script_path = path.join(params.video_clip_json_path)
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if path.exists(video_script_path):
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try:
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with open(video_script_path, "r", encoding="utf-8") as f:
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list_script = json.load(f)
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video_list = [i['narration'] for i in list_script]
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video_ost = [i['OST'] for i in list_script]
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time_list = [i['timestamp'] for i in list_script]
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video_script = " ".join(video_list)
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logger.debug(f"解说完整脚本: \n{video_script}")
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logger.debug(f"解说 OST 列表: \n{video_ost}")
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logger.debug(f"解说时间戳列表: \n{time_list}")
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except Exception as e:
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logger.error(f"无法读取视频json脚本，请检查脚本格式是否正确")
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raise ValueError("无法读取视频json脚本，请检查脚本格式是否正确")
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else:
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logger.error(f"解说脚本文件不存在: {video_script_path}，请先点击【保存脚本】按钮保存脚本后再生成视频")
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raise ValueError("解说脚本文件不存在！请先点击【保存脚本】按钮保存脚本后再生成视频。")
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"""
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2. 使用 TTS 生成音频素材
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"""
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logger.info("\n\n## 2. 根据OST设置生成音频列表")
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_normalize_indextts_reference_audio(params)
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tts_segments = [
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segment for segment in list_script
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if segment['OST'] in [0, 2]
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]
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logger.debug(f"需要生成TTS的片段数: {len(tts_segments)}")
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tts_results = voice.tts_multiple(
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task_id=task_id,
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list_script=tts_segments, # 只传入需要TTS的片段
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tts_engine=params.tts_engine,
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voice_name=params.voice_name,
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voice_rate=params.voice_rate,
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voice_pitch=params.voice_pitch,
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)
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sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=20)
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"""
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3. 统一视频裁剪 - 基于OST类型的差异化裁剪策略
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"""
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logger.info("\n\n## 3. 统一视频裁剪（基于OST类型）")
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video_clip_result = clip_video.clip_video_unified(
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video_origin_path=params.video_origin_path,
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video_origin_paths=getattr(params, "video_origin_paths", []),
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script_list=list_script,
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tts_results=tts_results
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)
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tts_clip_result = {tts_result['_id']: tts_result['audio_file'] for tts_result in tts_results}
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subclip_clip_result = {
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tts_result['_id']: tts_result['subtitle_file'] for tts_result in tts_results
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}
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new_script_list = update_script.update_script_timestamps(list_script, video_clip_result, tts_clip_result, subclip_clip_result)
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logger.info(f"统一裁剪完成，处理了 {len(video_clip_result)} 个视频片段")
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sm.state.update_task(task_id, state=const.TASK_STATE_PROCESSING, progress=60)
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"""
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4. 导出到剪映草稿
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"""
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logger.info("\n\n## 4. 导出到剪映草稿")
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try:
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jianying_draft_path = config.ui.get("jianying_draft_path", "")
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if not jianying_draft_path:
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raise ValueError("剪映草稿路径未配置")
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# 使用从参数中获取的草稿名称，如果为空则使用默认名称
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draft_name = getattr(params, 'draft_name', "")
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logger.debug(f"从params获取的草稿名称: '{draft_name}' (类型: {type(draft_name)})")
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if not draft_name:
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draft_name = f"NarratoAI_{int(time.time())}"
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logger.debug(f"使用默认草稿名称: '{draft_name}'")
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output_dir = utils.task_dir(task_id)
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draft_path, draft_name = write_plaintext_jianying_draft(
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jianying_draft_path=jianying_draft_path,
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draft_name=draft_name,
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new_script_list=new_script_list,
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params=params,
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output_dir=output_dir,
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)
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logger.success(f"成功导出到剪映草稿: {draft_name}")
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logger.info(f"草稿已保存到: {draft_path}")
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# 更新任务状态
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sm.state.update_task(task_id, state=const.TASK_STATE_COMPLETE, progress=100, draft_path=draft_path, draft_name=draft_name)
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return {"draft_path": draft_path, "draft_name": draft_name}
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except Exception as e:
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logger.error(f"导出到剪映草稿失败: {e}")
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import traceback
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logger.error(f"错误详情: {traceback.format_exc()}")
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raise Exception(f"导出到剪映草稿失败: {e}")
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