content: [app]
      # Pexels API Key
      # Register at https://www.pexels.com/api/ to get your API key.
      # You can use multiple keys to avoid rate limits.
      # For example: pexels_api_keys = ["123adsf4567adf89","abd1321cd13efgfdfhi"]
      # 特别注意格式，Key 用英文双引号括起来，多个Key用逗号隔开
      pexels_api_keys = ["zyRfgPTqKkIxX6F9deLkKycYLroBPd7wNUcgbSQWf5XZliONHY4dzvNr"]
  
      # 如果你没有 OPENAI API Key，可以使用 g4f 代替，或者使用国内的 Moonshot API
      # If you don't have an OPENAI API Key, you can use g4f instead
  
      # 支持的提供商 (Supported providers):
      #   openai
      #   moonshot (月之暗面)
      #   oneapi
      #   g4f
      #   azure
      #   qwen (通义千问)
      #   gemini
      llm_provider="qwen"
  
      ########## Ollama Settings
      # No need to set it unless you want to use your own proxy
      ollama_base_url = ""
      # Check your available models at https://ollama.com/library
      ollama_model_name = ""
  
      ########## OpenAI API Key
      # Get your API key at https://platform.openai.com/api-keys
      openai_api_key = ""
      # No need to set it unless you want to use your own proxy
      openai_base_url = ""
      # Check your available models at https://platform.openai.com/account/limits
      openai_model_name = "gpt-4-turbo-preview"
  
      ########## Moonshot API Key
      # Visit https://platform.moonshot.cn/console/api-keys to get your API key.
      moonshot_api_key=""
      moonshot_base_url = "https://api.moonshot.cn/v1"
      moonshot_model_name = "moonshot-v1-8k"
  
      ########## OneAPI API Key
      # Visit https://github.com/songquanpeng/one-api to get your API key
      oneapi_api_key=""
      oneapi_base_url=""
      oneapi_model_name=""
  
      ########## G4F
      # Visit https://github.com/xtekky/gpt4free to get more details
      # Supported model list: https://github.com/xtekky/gpt4free/blob/main/g4f/models.py
      g4f_model_name = "gpt-3.5-turbo-16k-0613"
  
      ########## Azure API Key
      # Visit https://learn.microsoft.com/zh-cn/azure/ai-services/openai/ to get more details
      # API documentation: https://learn.microsoft.com/zh-cn/azure/ai-services/openai/reference
      azure_api_key = ""
      azure_base_url=""
      azure_model_name="gpt-35-turbo" # replace with your model deployment name
      azure_api_version = "2024-02-15-preview"
  
      ########## Gemini API Key
      gemini_api_key=""
      gemini_model_name = "gemini-1.0-pro"
  
      ########## Qwen API Key
      # Visit https://dashscope.console.aliyun.com/apiKey to get your API key
      # Visit below links to get more details
      # https://tongyi.aliyun.com/qianwen/
      # https://help.aliyun.com/zh/dashscope/developer-reference/model-introduction
      qwen_api_key = ""
      qwen_model_name = "qwen-max" 
  
  
      # Subtitle Provider, "edge" or "whisper"
      # If empty, the subtitle will not be generated
      subtitle_provider = "edge"
  
      #
      # ImageMagick
      #
      # Once you have installed it, ImageMagick will be automatically detected, except on Windows!
      # On Windows, for example "C:\Program Files (x86)\ImageMagick-7.1.1-Q16-HDRI\magick.exe"
      # Download from https://imagemagick.org/archive/binaries/ImageMagick-7.1.1-29-Q16-x64-static.exe
  
      # imagemagick_path = "C:\\Program Files (x86)\\ImageMagick-7.1.1-Q16\\magick.exe"
  
  
      #
      # FFMPEG
      #
      # 通常情况下，ffmpeg 会被自动下载，并且会被自动检测到。
      # 但是如果你的环境有问题，无法自动下载，可能会遇到如下错误：
      #   RuntimeError: No ffmpeg exe could be found.
      #   Install ffmpeg on your system, or set the IMAGEIO_FFMPEG_EXE environment variable.
      # 此时你可以手动下载 ffmpeg 并设置 ffmpeg_path，下载地址：https://www.gyan.dev/ffmpeg/builds/
  
      # Under normal circumstances, ffmpeg is downloaded automatically and detected automatically.
      # However, if there is an issue with your environment that prevents automatic downloading, you might encounter the following error:
      #   RuntimeError: No ffmpeg exe could be found.
      #   Install ffmpeg on your system, or set the IMAGEIO_FFMPEG_EXE environment variable.
      # In such cases, you can manually download ffmpeg and set the ffmpeg_path, download link: https://www.gyan.dev/ffmpeg/builds/
  
      # ffmpeg_path = "C:\\Users\\harry\\Downloads\\ffmpeg.exe"
      #########################################################################################
  
      # 当视频生成成功后，API服务提供的视频下载接入点，默认为当前服务的地址和监听端口
      # 比如 http://127.0.0.1:8080/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
      # 如果你需要使用域名对外提供服务（一般会用nginx做代理），则可以设置为你的域名
      # 比如 https://xxxx.com/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
      # endpoint="https://xxxx.com"
  
      # When the video is successfully generated, the API service provides a download endpoint for the video, defaulting to the service's current address and listening port.
      # For example, http://127.0.0.1:8080/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
      # If you need to provide the service externally using a domain name (usually done with nginx as a proxy), you can set it to your domain name.
      # For example, https://xxxx.com/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
      # endpoint="https://xxxx.com"
      endpoint=""
  
  
      # Video material storage location
      # material_directory = ""                    # Indicates that video materials will be downloaded to the default folder, the default folder is ./storage/cache_videos under the current project
      # material_directory = "/user/harry/videos"  # Indicates that video materials will be downloaded to a specified folder
      # material_directory = "task"                # Indicates that video materials will be downloaded to the current task's folder, this method does not allow sharing of already downloaded video materials
  
      # 视频素材存放位置
      # material_directory = ""                    #表示将视频素材下载到默认的文件夹，默认文件夹为当前项目下的 ./storage/cache_videos
      # material_directory = "/user/harry/videos"  #表示将视频素材下载到指定的文件夹中
      # material_directory = "task"                #表示将视频素材下载到当前任务的文件夹中，这种方式无法共享已经下载的视频素材
  
      material_directory = ""
  
      # Used for state management of the task
      enable_redis = false
      redis_host = "localhost"
      redis_port = 6379
      redis_db = 0
  
  [whisper]
      # Only effective when subtitle_provider is "whisper"
  
      # Run on GPU with FP16
      # model = WhisperModel(model_size, device="cuda", compute_type="float16")
  
      # Run on GPU with INT8
      # model = WhisperModel(model_size, device="cuda", compute_type="int8_float16")
  
      # Run on CPU with INT8
      # model = WhisperModel(model_size, device="cpu", compute_type="int8")
  
      # recommended model_size: "large-v3"
      model_size="large-v3"
      # if you want to use GPU, set device="cuda"
      device="CPU"
      compute_type="int8"
  
  [pexels]
      video_concat_mode="sequential"
      [pexels.proxies]
          ### Use a proxy to access the Pexels API
          ### Format: "http://<username>:<password>@<proxy>:<port>"
          ### Example: "http://user:pass@proxy:1234"
          ### Doc: https://requests.readthedocs.io/en/latest/user/advanced/#proxies
          # http = "http://10.10.1.10:3128"
          # https = "http://10.10.1.10:1080"