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https://github.com/comfyanonymous/ComfyUI.git
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Add Moonvalley nodes (#8832)
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@@ -1,6 +1,6 @@
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# generated by datamodel-codegen:
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# filename: filtered-openapi.yaml
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# timestamp: 2025-05-19T21:38:55+00:00
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# timestamp: 2025-07-06T09:47:31+00:00
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from __future__ import annotations
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@@ -1355,6 +1355,158 @@ class ModelResponseProperties(BaseModel):
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)
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class Keyframes(BaseModel):
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image_url: Optional[str] = None
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class MoonvalleyPromptResponse(BaseModel):
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error: Optional[Dict[str, Any]] = None
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frame_conditioning: Optional[Dict[str, Any]] = None
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id: Optional[str] = None
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inference_params: Optional[Dict[str, Any]] = None
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meta: Optional[Dict[str, Any]] = None
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model_params: Optional[Dict[str, Any]] = None
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output_url: Optional[str] = None
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prompt_text: Optional[str] = None
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status: Optional[str] = None
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class MoonvalleyTextToVideoInferenceParams(BaseModel):
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add_quality_guidance: Optional[bool] = Field(
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True, description='Whether to add quality guidance'
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)
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caching_coefficient: Optional[float] = Field(
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0.3, description='Caching coefficient for optimization'
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)
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caching_cooldown: Optional[int] = Field(
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3, description='Number of caching cooldown steps'
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)
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caching_warmup: Optional[int] = Field(
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3, description='Number of caching warmup steps'
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)
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clip_value: Optional[float] = Field(
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3, description='CLIP value for generation control'
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)
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conditioning_frame_index: Optional[int] = Field(
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0, description='Index of the conditioning frame'
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)
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cooldown_steps: Optional[int] = Field(
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None, description='Number of cooldown steps (calculated based on num_frames)'
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)
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fps: Optional[int] = Field(
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24, description='Frames per second of the generated video'
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)
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guidance_scale: Optional[float] = Field(
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12.5, description='Guidance scale for generation control'
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)
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height: Optional[int] = Field(
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1080, description='Height of the generated video in pixels'
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)
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negative_prompt: Optional[str] = Field(None, description='Negative prompt text')
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num_frames: Optional[int] = Field(64, description='Number of frames to generate')
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seed: Optional[int] = Field(
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None, description='Random seed for generation (default: random)'
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)
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shift_value: Optional[float] = Field(
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3, description='Shift value for generation control'
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)
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steps: Optional[int] = Field(80, description='Number of denoising steps')
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use_guidance_schedule: Optional[bool] = Field(
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True, description='Whether to use guidance scheduling'
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)
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use_negative_prompts: Optional[bool] = Field(
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False, description='Whether to use negative prompts'
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)
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use_timestep_transform: Optional[bool] = Field(
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True, description='Whether to use timestep transformation'
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)
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warmup_steps: Optional[int] = Field(
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None, description='Number of warmup steps (calculated based on num_frames)'
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)
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width: Optional[int] = Field(
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1920, description='Width of the generated video in pixels'
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)
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class MoonvalleyTextToVideoRequest(BaseModel):
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image_url: Optional[str] = None
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inference_params: Optional[MoonvalleyTextToVideoInferenceParams] = None
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prompt_text: Optional[str] = None
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webhook_url: Optional[str] = None
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class MoonvalleyUploadFileRequest(BaseModel):
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file: Optional[StrictBytes] = None
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class MoonvalleyUploadFileResponse(BaseModel):
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access_url: Optional[str] = None
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class MoonvalleyVideoToVideoInferenceParams(BaseModel):
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add_quality_guidance: Optional[bool] = Field(
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True, description='Whether to add quality guidance'
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)
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caching_coefficient: Optional[float] = Field(
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0.3, description='Caching coefficient for optimization'
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)
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caching_cooldown: Optional[int] = Field(
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3, description='Number of caching cooldown steps'
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)
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caching_warmup: Optional[int] = Field(
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3, description='Number of caching warmup steps'
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)
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clip_value: Optional[float] = Field(
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3, description='CLIP value for generation control'
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)
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conditioning_frame_index: Optional[int] = Field(
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0, description='Index of the conditioning frame'
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)
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cooldown_steps: Optional[int] = Field(
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None, description='Number of cooldown steps (calculated based on num_frames)'
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)
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guidance_scale: Optional[float] = Field(
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12.5, description='Guidance scale for generation control'
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)
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negative_prompt: Optional[str] = Field(None, description='Negative prompt text')
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seed: Optional[int] = Field(
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None, description='Random seed for generation (default: random)'
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)
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shift_value: Optional[float] = Field(
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3, description='Shift value for generation control'
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)
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steps: Optional[int] = Field(80, description='Number of denoising steps')
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use_guidance_schedule: Optional[bool] = Field(
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True, description='Whether to use guidance scheduling'
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)
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use_negative_prompts: Optional[bool] = Field(
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False, description='Whether to use negative prompts'
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)
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use_timestep_transform: Optional[bool] = Field(
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True, description='Whether to use timestep transformation'
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)
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warmup_steps: Optional[int] = Field(
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None, description='Number of warmup steps (calculated based on num_frames)'
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)
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class ControlType(str, Enum):
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motion_control = 'motion_control'
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pose_control = 'pose_control'
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class MoonvalleyVideoToVideoRequest(BaseModel):
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control_type: ControlType = Field(
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..., description='Supported types for video control'
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)
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inference_params: Optional[MoonvalleyVideoToVideoInferenceParams] = None
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prompt_text: str = Field(..., description='Describes the video to generate')
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video_url: str = Field(..., description='Url to control video')
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webhook_url: Optional[str] = Field(
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None, description='Optional webhook URL for notifications'
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)
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class Moderation(str, Enum):
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low = 'low'
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auto = 'auto'
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@@ -3107,6 +3259,23 @@ class LumaUpscaleVideoGenerationRequest(BaseModel):
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resolution: Optional[LumaVideoModelOutputResolution] = None
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class MoonvalleyImageToVideoRequest(MoonvalleyTextToVideoRequest):
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keyframes: Optional[Dict[str, Keyframes]] = None
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class MoonvalleyResizeVideoRequest(MoonvalleyVideoToVideoRequest):
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frame_position: Optional[List[int]] = Field(None, max_length=2, min_length=2)
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frame_resolution: Optional[List[int]] = Field(None, max_length=2, min_length=2)
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scale: Optional[List[int]] = Field(None, max_length=2, min_length=2)
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class MoonvalleyTextToImageRequest(BaseModel):
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image_url: Optional[str] = None
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inference_params: Optional[MoonvalleyTextToVideoInferenceParams] = None
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prompt_text: Optional[str] = None
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webhook_url: Optional[str] = None
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class OutputContent(RootModel[Union[OutputTextContent, OutputAudioContent]]):
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root: Union[OutputTextContent, OutputAudioContent]
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