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refactor: 移除废弃脚本文件并更新项目版本至0.7.0
删除不再使用的脚本文件(check_gpu_cuda_cudnn.bat, changelog.py, main.py, release-notes.md, video_pipeline.py) 将项目版本从0.6.8更新至0.7.0，并同步更新config.example.toml中的版本号
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linyq
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changelog.py
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changelog.py
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from git_changelog.cli import build_and_render
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# 运行这段脚本自动生成CHANGELOG.md文件
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build_and_render(
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repository=".",
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output="CHANGELOG.md",
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convention="angular",
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provider="github",
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template="keepachangelog",
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parse_trailers=True,
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parse_refs=False,
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sections=["build", "deps", "feat", "fix", "refactor"],
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versioning="pep440",
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bump="1.1.2", # 指定bump版本
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in_place=True,
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)
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[app]
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project_version="0.6.8"
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project_version="0.7.0"
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# 模型验证模式配置
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# true: 严格模式，只允许使用预定义支持列表中的模型（默认）
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main.py
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main.py
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import os
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import uvicorn
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from loguru import logger
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from app.config import config
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if __name__ == "__main__":
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logger.info(
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"start server, docs: http://127.0.0.1:" + str(config.listen_port) + "/docs"
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)
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os.environ["HTTP_PROXY"] = config.proxy.get("http")
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os.environ["HTTPS_PROXY"] = config.proxy.get("https")
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uvicorn.run(
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app="app.asgi:app",
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host=config.listen_host,
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port=config.listen_port,
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reload=config.reload_debug,
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log_level="warning",
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)
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@ -1 +1 @@
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0.6.8
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0.7.0
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# Release Notes
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## Latest Changes
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* docs(README): 更新README. PR [#138](https://github.com/linyqh/NarratoAI/pull/138) by [@linyqh](https://github.com/linyqh).
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* Dev 0.6.0. PR [#137](https://github.com/linyqh/NarratoAI/pull/137) by [@linyqh](https://github.com/linyqh).
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* Dev 0.6.0 . PR [#134](https://github.com/linyqh/NarratoAI/pull/134) by [@linyqh](https://github.com/linyqh).
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* Dev-0.3.9. PR [#73](https://github.com/linyqh/NarratoAI/pull/73) by [@linyqh](https://github.com/linyqh).
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* 0.3.9 版本发布. PR [#71](https://github.com/linyqh/NarratoAI/pull/71) by [@linyqh](https://github.com/linyqh).
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* docs: add Japanese README. PR [#66](https://github.com/linyqh/NarratoAI/pull/66) by [@eltociear](https://github.com/eltociear).
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* docs: 测试 release 2. PR [#62](https://github.com/linyqh/NarratoAI/pull/62) by [@linyqh](https://github.com/linyqh).
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* docs: 测试 release. PR [#61](https://github.com/linyqh/NarratoAI/pull/61) by [@linyqh](https://github.com/linyqh).
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* docs: 测试commit. PR [#60](https://github.com/linyqh/NarratoAI/pull/60) by [@linyqh](https://github.com/linyqh).
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* Dev. PR [#59](https://github.com/linyqh/NarratoAI/pull/59) by [@linyqh](https://github.com/linyqh).
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* 0.2.0新版预发布. PR [#37](https://github.com/linyqh/NarratoAI/pull/37) by [@linyqh](https://github.com/linyqh).
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* v0.3.6. PR [#58](https://github.com/linyqh/NarratoAI/pull/58) by [@linyqh](https://github.com/linyqh).
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* 0.3.4 修改各种bug. PR [#49](https://github.com/linyqh/NarratoAI/pull/49) by [@linyqh](https://github.com/linyqh).
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import requests
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import json
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import os
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import time
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from typing import Dict, Any
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class VideoPipeline:
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def __init__(self, base_url: str = "http://127.0.0.1:8080"):
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self.base_url = base_url
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def download_video(self, url: str, resolution: str = "1080p",
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output_format: str = "mp4", rename: str = None) -> Dict[str, Any]:
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"""下载视频的第一步"""
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endpoint = f"{self.base_url}/api/v2/youtube/download"
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payload = {
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"url": url,
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"resolution": resolution,
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"output_format": output_format,
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"rename": rename or time.strftime("%Y-%m-%d")
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}
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response = requests.post(endpoint, json=payload)
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response.raise_for_status()
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return response.json()
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def generate_script(self, video_path: str, skip_seconds: int = 0,
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threshold: int = 30, vision_batch_size: int = 10,
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vision_llm_provider: str = "gemini") -> Dict[str, Any]:
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"""生成脚本的第二步"""
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endpoint = f"{self.base_url}/api/v2/scripts/generate"
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payload = {
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"video_path": video_path,
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"skip_seconds": skip_seconds,
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"threshold": threshold,
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"vision_batch_size": vision_batch_size,
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"vision_llm_provider": vision_llm_provider
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}
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response = requests.post(endpoint, json=payload)
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response.raise_for_status()
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return response.json()
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def crop_video(self, video_path: str, script: list) -> Dict[str, Any]:
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"""剪辑视频的第三步"""
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endpoint = f"{self.base_url}/api/v2/scripts/crop"
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payload = {
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"video_origin_path": video_path,
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"video_script": script
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}
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response = requests.post(endpoint, json=payload)
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response.raise_for_status()
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return response.json()
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def generate_final_video(self, task_id: str, video_path: str,
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script_path: str, script: list, subclip_videos: Dict[str, str], voice_name: str) -> Dict[str, Any]:
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"""生成最终视频的第四步"""
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endpoint = f"{self.base_url}/api/v2/scripts/start-subclip"
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request_data = {
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"video_clip_json": script,
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"video_clip_json_path": script_path,
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"video_origin_path": video_path,
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"video_aspect": "16:9",
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"video_language": "zh-CN",
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"voice_name": voice_name,
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"voice_volume": 1,
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"voice_rate": 1.2,
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"voice_pitch": 1,
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"bgm_name": "random",
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"bgm_type": "random",
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"bgm_file": "",
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"bgm_volume": 0.3,
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"subtitle_enabled": True,
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"subtitle_position": "bottom",
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"font_name": "STHeitiMedium.ttc",
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"text_fore_color": "#FFFFFF",
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"text_background_color": "transparent",
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"font_size": 75,
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"stroke_color": "#000000",
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"stroke_width": 1.5,
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"custom_position": 70,
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"n_threads": 8
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}
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payload = {
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"request": request_data,
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"subclip_videos": subclip_videos
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}
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params = {"task_id": task_id}
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response = requests.post(endpoint, params=params, json=payload)
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response.raise_for_status()
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return response.json()
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def save_script_to_json(self, script: list, script_path: str) -> str:
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"""保存脚本到json文件"""
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try:
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with open(script_path, 'w', encoding='utf-8') as f:
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json.dump(script, f, ensure_ascii=False, indent=2)
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print(f"脚本已保存到: {script_path}")
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return script_path
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except Exception as e:
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print(f"保存脚本失败: {str(e)}")
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raise
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def run_pipeline(self, task_id: str, script_name: str, youtube_url: str, video_name: str="null", skip_seconds: int = 0, threshold: int = 30, vision_batch_size: int = 10, vision_llm_provider: str = "gemini", voice_name: str = "zh-CN-YunjianNeural") -> Dict[str, Any]:
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"""运行完整的pipeline"""
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try:
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current_path = os.path.dirname(os.path.abspath(__file__))
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video_path = os.path.join(current_path, "resource", "videos", f"{video_name}.mp4")
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# 判断视频是否存在
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if not os.path.exists(video_path):
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# 1. 下载视频
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print(f"视频不存在, 开始下载视频: {video_path}")
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download_result = self.download_video(url=youtube_url, resolution="1080p", output_format="mp4", rename=video_name)
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video_path = download_result["output_path"]
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else:
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print(f"视频已存在: {video_path}")
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# 2. 判断script_name是否存在
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# 2.1.1 拼接脚本路径 NarratoAI/resource/scripts
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script_path = os.path.join(current_path, "resource", "scripts", script_name)
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if os.path.exists(script_path):
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script = json.load(open(script_path, "r", encoding="utf-8"))
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else:
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# 2.1.2 生成脚本
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print("开始生成脚本...")
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script_result = self.generate_script(video_path=video_path, skip_seconds=skip_seconds, threshold=threshold, vision_batch_size=vision_batch_size, vision_llm_provider=vision_llm_provider)
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script = script_result["script"]
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# 2.2 保存脚本到json文件
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print("保存脚本到json文件...")
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self.save_script_to_json(script=script, script_path=script_path)
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# 3. 剪辑视频
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print("开始剪辑视频...")
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crop_result = self.crop_video(video_path=video_path, script=script)
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subclip_videos = crop_result["subclip_videos"]
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# 4. 生成最终视频
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print("开始生成最终视频...")
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self.generate_final_video(
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task_id=task_id,
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video_path=video_path,
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script_path=script_path,
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script=script,
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subclip_videos=subclip_videos,
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voice_name=voice_name
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)
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return {
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"status": "等待异步生成视频",
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"path": os.path.join(current_path, "storage", "tasks", task_id)
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}
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except Exception as e:
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return {
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"status": "error",
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"error": str(e)
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}
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# 使用示例
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if __name__ == "__main__":
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pipeline = VideoPipeline()
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result = pipeline.run_pipeline(
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task_id="test_111901",
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script_name="test.json",
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youtube_url="https://www.youtube.com/watch?v=vLJ7Yed6FQ4",
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video_name="2024-11-19-01",
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skip_seconds=50,
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threshold=35,
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vision_batch_size=10,
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vision_llm_provider="gemini",
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voice_name="zh-CN-YunjianNeural",
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)
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print(result)
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