[app] project_version="0.3.9" # 支持视频理解的大模型提供商 # gemini # NarratoAPI # qwen2-vl (待增加) vision_llm_provider="gemini" vision_analysis_prompt = "你是资深视频内容分析专家，擅长分析视频画面信息，分析下面视频画面内容，只输出客观的画面描述不要给任何总结或评价" ########## Vision Gemini API Key vision_gemini_api_key = "" vision_gemini_model_name = "gemini-1.5-flash" ########## Vision Qwen API Key vision_qwenvl_api_key = "" vision_qwenvl_model_name = "qwen-vl-max-latest" vision_qwenvl_base_url = "https://dashscope.aliyuncs.com/compatible-mode/v1" ########### Vision NarratoAPI Key narrato_api_key = "0N0iEjU77aTqPW4d9YHCmTW2mPrfgWjDmaWAz1lTVTM" narrato_api_url = "https://narratoinsight.scsmtech.cn/api/v1" narrato_vision_model = "gemini-1.5-flash" narrato_vision_key = "" narrato_llm_model = "gpt-4o" narrato_llm_key = "" # 用于生成文案的大模型支持的提供商 (Supported providers): # openai (默认) # moonshot (月之暗面) # oneapi # g4f # azure # qwen (通义千问) # gemini text_llm_provider="openai" ########## OpenAI API Key # Get your API key at https://platform.openai.com/api-keys text_openai_api_key = "" text_openai_base_url = "https://api.openai.com/v1" text_openai_model_name = "gpt-4o-mini" ########## Moonshot API Key # Visit https://platform.moonshot.cn/console/api-keys to get your API key. text_moonshot_api_key="" text_moonshot_base_url = "https://api.moonshot.cn/v1" text_moonshot_model_name = "moonshot-v1-8k" ########## G4F # Visit https://github.com/xtekky/gpt4free to get more details # Supported model list: https://github.com/xtekky/gpt4free/blob/main/g4f/models.py text_g4f_model_name = "gpt-3.5-turbo" ########## 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 text_azure_api_key = "" text_azure_base_url="" text_azure_model_name="gpt-35-turbo" # replace with your model deployment name text_azure_api_version = "2024-02-15-preview" ########## Gemini API Key text_gemini_api_key="" text_gemini_model_name = "gemini-1.5-flash" ########## 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 text_qwen_api_key = "" text_qwen_model_name = "qwen-plus-1127" text_qwen_base_url = "https://dashscope.aliyuncs.com/compatible-mode/v1" ########## DeepSeek API Key # Visit https://platform.deepseek.com/api_keys to get your API key text_deepseek_api_key = "" text_deepseek_base_url = "https://api.deepseek.com" text_deepseek_model_name = "deepseek-chat" # 字幕提供商、可选，支持 whisper 和 faster-whisper-large-v2"whisper" # 默认为 faster-whisper-large-v2 模型地址：https://huggingface.co/guillaumekln/faster-whisper-large-v2 subtitle_provider = "faster-whisper-large-v2" subtitle_enabled = true # ImageMagick # 安装后，将自动检测到 ImageMagick，Windows 除外！ # 例如，在 Windows 上 "C:\Program Files (x86)\ImageMagick-7.1.1-Q16-HDRI\magick.exe" # 下载位置 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/ # 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 = "" # 用于任务的状态管理 enable_redis = false redis_host = "localhost" redis_port = 6379 redis_db = 0 redis_password = "" # 文生视频时的最大并发任务数 max_concurrent_tasks = 5 # webui界面是否显示配置项 hide_config = false [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="faster-whisper-large-v2" # 如果要使用 GPU，请设置 device=“cuda” device="CPU" compute_type="int8" [proxy] ### Use a proxy to access the Pexels API ### Format: "http://:@:" ### Example: "http://user:pass@proxy:1234" ### Doc: https://requests.readthedocs.io/en/latest/user/advanced/#proxies http = "http://127.0.0.1:7890" https = "http://127.0.0.1:7890" [azure] # Azure Speech API Key # Get your API key at https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/SpeechServices speech_key="" speech_region="" [frames] skip_seconds = 0 # threshold（差异阈值）用于判断两个连续帧之间是否发生了场景切换 # 较小的阈值（如 20）：更敏感，能捕捉到细微的场景变化，但可能会误判，关键帧图片更多 # 较大的阈值（如 40）：更保守，只捕捉明显的场景切换，但可能会漏掉渐变场景，关键帧图片更少 # 默认值 30：在实践中是一个比较平衡的选择 threshold = 30 version = "v2" # 大模型单次处理的关键帧数量 vision_batch_size = 5