mirror of
https://github.com/linyqh/NarratoAI.git
synced 2025-12-11 18:42:49 +00:00
c065800072
-重构音频设置面板，增加语音音量、背景音乐等设置 - 添加背景音乐文件选择功能 - 优化字幕设置，支持自定义字体和样式 -调整视频生成流程，支持新音频设置 - 更新文档示例，反映新功能
187 lines
8.2 KiB
TOML
187 lines
8.2 KiB
TOML
[app]
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project_version="0.3.9"
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# 支持视频理解的大模型提供商
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# gemini
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# NarratoAPI
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# qwen2-vl (待增加)
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vision_llm_provider="gemini"
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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"
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########## Vision Gemini API Key
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vision_gemini_api_key = ""
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vision_gemini_model_name = "gemini-1.5-flash"
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########## Vision Qwen API Key
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vision_qwenvl_api_key = ""
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vision_qwenvl_model_name = "qwen-vl-max-latest"
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vision_qwenvl_base_url = "https://dashscope.aliyuncs.com/compatible-mode/v1"
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########### Vision NarratoAPI Key
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narrato_api_key = "0N0iEjU77aTqPW4d9YHCmTW2mPrfgWjDmaWAz1lTVTM"
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narrato_api_url = "https://narratoinsight.scsmtech.cn/api/v1"
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narrato_vision_model = "gemini-1.5-flash"
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narrato_vision_key = ""
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narrato_llm_model = "gpt-4o"
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narrato_llm_key = ""
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# 用于生成文案的大模型支持的提供商 (Supported providers):
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# openai (默认)
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# moonshot (月之暗面)
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# oneapi
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# g4f
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# azure
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# qwen (通义千问)
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# gemini
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text_llm_provider="openai"
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########## OpenAI API Key
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# Get your API key at https://platform.openai.com/api-keys
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text_openai_api_key = ""
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text_openai_base_url = "https://api.openai.com/v1"
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text_openai_model_name = "gpt-4o-mini"
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########## Moonshot API Key
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# Visit https://platform.moonshot.cn/console/api-keys to get your API key.
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text_moonshot_api_key=""
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text_moonshot_base_url = "https://api.moonshot.cn/v1"
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text_moonshot_model_name = "moonshot-v1-8k"
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########## G4F
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# Visit https://github.com/xtekky/gpt4free to get more details
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# Supported model list: https://github.com/xtekky/gpt4free/blob/main/g4f/models.py
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text_g4f_model_name = "gpt-3.5-turbo"
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########## Azure API Key
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# Visit https://learn.microsoft.com/zh-cn/azure/ai-services/openai/ to get more details
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# API documentation: https://learn.microsoft.com/zh-cn/azure/ai-services/openai/reference
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text_azure_api_key = ""
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text_azure_base_url=""
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text_azure_model_name="gpt-35-turbo" # replace with your model deployment name
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text_azure_api_version = "2024-02-15-preview"
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########## Gemini API Key
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text_gemini_api_key=""
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text_gemini_model_name = "gemini-1.5-flash"
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########## Qwen API Key
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# Visit https://dashscope.console.aliyun.com/apiKey to get your API key
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# Visit below links to get more details
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# https://tongyi.aliyun.com/qianwen/
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# https://help.aliyun.com/zh/dashscope/developer-reference/model-introduction
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text_qwen_api_key = ""
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text_qwen_model_name = "qwen-plus-1127"
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text_qwen_base_url = "https://dashscope.aliyuncs.com/compatible-mode/v1"
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########## DeepSeek API Key
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# Visit https://platform.deepseek.com/api_keys to get your API key
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text_deepseek_api_key = ""
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text_deepseek_base_url = "https://api.deepseek.com"
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text_deepseek_model_name = "deepseek-chat"
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# 字幕提供商、可选，支持 whisper 和 faster-whisper-large-v2"whisper"
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# 默认为 faster-whisper-large-v2 模型地址：https://huggingface.co/guillaumekln/faster-whisper-large-v2
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subtitle_provider = "faster-whisper-large-v2"
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subtitle_enabled = true
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# ImageMagick
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# 安装后，将自动检测到 ImageMagick，Windows 除外！
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# 例如，在 Windows 上 "C:\Program Files (x86)\ImageMagick-7.1.1-Q16-HDRI\magick.exe"
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# 下载位置 https://imagemagick.org/archive/binaries/ImageMagick-7.1.1-29-Q16-x64-static.exe
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# imagemagick_path = "C:\\Program Files (x86)\\ImageMagick-7.1.1-Q16\\magick.exe"
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# FFMPEG
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#
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# 通常情况下，ffmpeg 会被自动下载，并且会被自动检测到。
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# 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：
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# RuntimeError: No ffmpeg exe could be found.
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# Install ffmpeg on your system, or set the IMAGEIO_FFMPEG_EXE environment variable.
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# 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/
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# ffmpeg_path = "C:\\Users\\harry\\Downloads\\ffmpeg.exe"
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#########################################################################################
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# 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
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# 比如 http://127.0.0.1:8080/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
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# 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
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# 比如 https://xxxx.com/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
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# endpoint="https://xxxx.com"
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# 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.
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# For example, http://127.0.0.1:8080/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
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# 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.
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# For example, https://xxxx.com/tasks/6357f542-a4e1-46a1-b4c9-bf3bd0df5285/final-1.mp4
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# endpoint="https://xxxx.com"
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endpoint=""
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# Video material storage location
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# material_directory = "" # Indicates that video materials will be downloaded to the default folder, the default folder is ./storage/cache_videos under the current project
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# material_directory = "/user/harry/videos" # Indicates that video materials will be downloaded to a specified folder
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# 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
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# 视频素材存放位置
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# 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
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# material_directory = "/user/harry/videos" #表示将视频素材下载到指定的文件夹中
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# 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
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material_directory = ""
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# 用于任务的状态管理
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enable_redis = false
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redis_host = "localhost"
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redis_port = 6379
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redis_db = 0
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redis_password = ""
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# 文生视频时的最大并发任务数
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max_concurrent_tasks = 5
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# webui界面是否显示配置项
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hide_config = false
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[whisper]
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# Only effective when subtitle_provider is "whisper"
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# Run on GPU with FP16
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# model = WhisperModel(model_size, device="cuda", compute_type="float16")
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# Run on GPU with INT8
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# model = WhisperModel(model_size, device="cuda", compute_type="int8_float16")
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# Run on CPU with INT8
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# model = WhisperModel(model_size, device="cpu", compute_type="int8")
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# recommended model_size: "large-v3"
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model_size="faster-whisper-large-v2"
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# 如果要使用 GPU，请设置 device=“cuda”
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device="CPU"
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compute_type="int8"
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[proxy]
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### Use a proxy to access the Pexels API
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### Format: "http://<username>:<password>@<proxy>:<port>"
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### Example: "http://user:pass@proxy:1234"
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### Doc: https://requests.readthedocs.io/en/latest/user/advanced/#proxies
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http = "http://127.0.0.1:7890"
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https = "http://127.0.0.1:7890"
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[azure]
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# Azure Speech API Key
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# Get your API key at https://portal.azure.com/#view/Microsoft_Azure_ProjectOxford/CognitiveServicesHub/~/SpeechServices
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speech_key=""
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speech_region=""
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[frames]
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skip_seconds = 0
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# 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
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# 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
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# 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
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# 默认值 30：在实践中是一个比较平衡的选择
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threshold = 30
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version = "v2"
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# 大模型单次处理的关键帧数量
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vision_batch_size = 5
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