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https://github.com/Comfy-Org/ComfyUI.git
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[Partner Nodes] feat: add Flux Virtual Try-On and Erase nodes (#14207)
This commit is contained in:
Alexander Piskun
@@ -1,71 +1,71 @@
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from enum import Enum
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from typing import Any, Dict, Optional
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from typing import Any
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from pydantic import BaseModel, Field, confloat, conint
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class BFLOutputFormat(str, Enum):
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png = 'png'
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jpeg = 'jpeg'
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from pydantic import BaseModel, Field
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class BFLFluxExpandImageRequest(BaseModel):
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prompt: str = Field(..., description='The description of the changes you want to make. This text guides the expansion process, allowing you to specify features, styles, or modifications for the expanded areas.')
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prompt_upsampling: Optional[bool] = Field(
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None, description='Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation.'
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)
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seed: Optional[int] = Field(None, description='The seed value for reproducibility.')
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top: conint(ge=0, le=2048) = Field(..., description='Number of pixels to expand at the top of the image')
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bottom: conint(ge=0, le=2048) = Field(..., description='Number of pixels to expand at the bottom of the image')
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left: conint(ge=0, le=2048) = Field(..., description='Number of pixels to expand at the left side of the image')
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right: conint(ge=0, le=2048) = Field(..., description='Number of pixels to expand at the right side of the image')
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steps: conint(ge=15, le=50) = Field(..., description='Number of steps for the image generation process')
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guidance: confloat(ge=1.5, le=100) = Field(..., description='Guidance strength for the image generation process')
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safety_tolerance: Optional[conint(ge=0, le=6)] = Field(
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6, description='Tolerance level for input and output moderation. Between 0 and 6, 0 being most strict, 6 being least strict. Defaults to 2.'
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)
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output_format: Optional[BFLOutputFormat] = Field(
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BFLOutputFormat.png, description="Output format for the generated image. Can be 'jpeg' or 'png'.", examples=['png']
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)
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image: str = Field(None, description='A Base64-encoded string representing the image you wish to expand')
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prompt: str = Field(...)
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prompt_upsampling: bool | None = Field(None)
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seed: int | None = Field(None)
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top: int = Field(...)
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bottom: int = Field(...)
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left: int = Field(...)
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right: int = Field(...)
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steps: int = Field(...)
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guidance: float = Field(...)
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safety_tolerance: int = Field(6)
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output_format: str = Field("png")
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image: str = Field(None, description="A Base64-encoded string representing the image you wish to expand")
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class BFLFluxFillImageRequest(BaseModel):
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prompt: str = Field(..., description='The description of the changes you want to make. This text guides the expansion process, allowing you to specify features, styles, or modifications for the expanded areas.')
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prompt_upsampling: Optional[bool] = Field(
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None, description='Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation.'
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prompt: str = Field(...)
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prompt_upsampling: bool | None = Field(None)
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seed: int | None = Field(None)
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steps: int = Field(...)
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guidance: float = Field(...)
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safety_tolerance: int = Field(6)
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output_format: str = Field("png")
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image: str = Field(
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None, description="Base64-encoded string representing the image to modify. Can contain alpha mask if desired.",
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)
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seed: Optional[int] = Field(None, description='The seed value for reproducibility.')
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steps: conint(ge=15, le=50) = Field(..., description='Number of steps for the image generation process')
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guidance: confloat(ge=1.5, le=100) = Field(..., description='Guidance strength for the image generation process')
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safety_tolerance: Optional[conint(ge=0, le=6)] = Field(
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6, description='Tolerance level for input and output moderation. Between 0 and 6, 0 being most strict, 6 being least strict. Defaults to 2.'
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mask: str = Field(
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None, description="Base64-encoded string representing the mask of the areas you wish to modify."
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)
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output_format: Optional[BFLOutputFormat] = Field(
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BFLOutputFormat.png, description="Output format for the generated image. Can be 'jpeg' or 'png'.", examples=['png']
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class BFLFluxEraseRequest(BaseModel):
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image: str = Field(..., description="A Base64-encoded string representing the image to erase from.")
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mask: str = Field(
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...,
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description="A Base64-encoded black/white mask matching the input dimensions; "
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"white (255) marks areas to remove, black (0) marks areas to preserve.",
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)
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image: str = Field(None, description='A Base64-encoded string representing the image you wish to modify. Can contain alpha mask if desired.')
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mask: str = Field(None, description='A Base64-encoded string representing the mask of the areas you with to modify.')
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dilate_pixels: int = Field(10)
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output_format: str = Field("png")
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class BFLFluxVTORequest(BaseModel):
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prompt: str = Field(
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..., description="Natural-language styling instruction. Required field, but may be an empty string."
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)
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person: str = Field(..., description="A Base64-encoded string representing the person image.")
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garment: str = Field(..., description="A Base64-encoded string representing the garment reference image.")
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seed: int | None = Field(None)
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safety_tolerance: int = Field(5)
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output_format: str = Field("png")
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class BFLFluxProGenerateRequest(BaseModel):
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prompt: str = Field(..., description='The text prompt for image generation.')
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prompt_upsampling: Optional[bool] = Field(
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None, description='Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation.'
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)
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seed: Optional[int] = Field(None, description='The seed value for reproducibility.')
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width: conint(ge=256, le=1440) = Field(1024, description='Width of the generated image in pixels. Must be a multiple of 32.')
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height: conint(ge=256, le=1440) = Field(768, description='Height of the generated image in pixels. Must be a multiple of 32.')
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safety_tolerance: Optional[conint(ge=0, le=6)] = Field(
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6, description='Tolerance level for input and output moderation. Between 0 and 6, 0 being most strict, 6 being least strict. Defaults to 2.'
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)
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output_format: Optional[BFLOutputFormat] = Field(
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BFLOutputFormat.png, description="Output format for the generated image. Can be 'jpeg' or 'png'.", examples=['png']
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)
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image_prompt: Optional[str] = Field(None, description='Optional image to remix in base64 format')
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# image_prompt_strength: Optional[confloat(ge=0.0, le=1.0)] = Field(
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# None, description='Blend between the prompt and the image prompt.'
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# )
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prompt: str = Field(...)
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prompt_upsampling: bool | None = Field(None)
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seed: int | None = Field(None)
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width: int = Field(1024, description="Must be a multiple of 32.")
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height: int = Field(768, description="Must be a multiple of 32.")
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safety_tolerance: int = Field(6)
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output_format: str = Field("png")
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image_prompt: str | None = Field(None, description="Optional image to remix in base64 format")
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class Flux2ProGenerateRequest(BaseModel):
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@@ -83,55 +83,37 @@ class Flux2ProGenerateRequest(BaseModel):
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input_image_7: str | None = Field(None, description="Base64 encoded image for image-to-image generation")
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input_image_8: str | None = Field(None, description="Base64 encoded image for image-to-image generation")
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input_image_9: str | None = Field(None, description="Base64 encoded image for image-to-image generation")
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safety_tolerance: int | None = Field(
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5, description="Tolerance level for input and output moderation. Value 0 being most strict.", ge=0, le=5
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)
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output_format: str | None = Field(
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"png", description="Output format for the generated image. Can be 'jpeg' or 'png'."
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)
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safety_tolerance: int = Field(5)
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output_format: str = Field("png")
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class BFLFluxKontextProGenerateRequest(BaseModel):
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prompt: str = Field(..., description='The text prompt for what you wannt to edit.')
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input_image: Optional[str] = Field(None, description='Image to edit in base64 format')
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seed: Optional[int] = Field(None, description='The seed value for reproducibility.')
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guidance: confloat(ge=0.1, le=99.0) = Field(..., description='Guidance strength for the image generation process')
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steps: conint(ge=1, le=150) = Field(..., description='Number of steps for the image generation process')
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safety_tolerance: Optional[conint(ge=0, le=2)] = Field(
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2, description='Tolerance level for input and output moderation. Between 0 and 2, 0 being most strict, 6 being least strict. Defaults to 2.'
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)
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output_format: Optional[BFLOutputFormat] = Field(
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BFLOutputFormat.png, description="Output format for the generated image. Can be 'jpeg' or 'png'.", examples=['png']
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)
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aspect_ratio: Optional[str] = Field(None, description='Aspect ratio of the image between 21:9 and 9:21.')
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prompt_upsampling: Optional[bool] = Field(
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None, description='Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation.'
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)
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prompt: str = Field(...)
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input_image: str | None = Field(None, description="Image to edit in base64 format")
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seed: int | None = Field(None)
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guidance: float = Field(...)
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steps: int = Field(...)
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safety_tolerance: int = Field(2)
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output_format: str = Field("png")
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aspect_ratio: str | None = Field(None)
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prompt_upsampling: bool | None = Field(None)
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class BFLFluxProUltraGenerateRequest(BaseModel):
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prompt: str = Field(..., description='The text prompt for image generation.')
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prompt_upsampling: Optional[bool] = Field(
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None, description='Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation.'
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)
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seed: Optional[int] = Field(None, description='The seed value for reproducibility.')
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aspect_ratio: Optional[str] = Field(None, description='Aspect ratio of the image between 21:9 and 9:21.')
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safety_tolerance: Optional[conint(ge=0, le=6)] = Field(
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6, description='Tolerance level for input and output moderation. Between 0 and 6, 0 being most strict, 6 being least strict. Defaults to 2.'
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)
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output_format: Optional[BFLOutputFormat] = Field(
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BFLOutputFormat.png, description="Output format for the generated image. Can be 'jpeg' or 'png'.", examples=['png']
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)
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raw: Optional[bool] = Field(None, description='Generate less processed, more natural-looking images.')
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image_prompt: Optional[str] = Field(None, description='Optional image to remix in base64 format')
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image_prompt_strength: Optional[confloat(ge=0.0, le=1.0)] = Field(
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None, description='Blend between the prompt and the image prompt.'
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)
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prompt: str = Field(...)
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prompt_upsampling: bool | None = Field(None)
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seed: int | None = Field(None)
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aspect_ratio: str | None = Field(None)
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safety_tolerance: int = Field(6)
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output_format: str = Field("png")
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raw: bool | None = Field(None)
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image_prompt: str | None = Field(None, description="Optional image to remix in base64 format")
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image_prompt_strength: float | None = Field(None)
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class BFLFluxProGenerateResponse(BaseModel):
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id: str = Field(..., description="The unique identifier for the generation task.")
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polling_url: str = Field(..., description="URL to poll for the generation result.")
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id: str = Field(...)
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polling_url: str = Field(...)
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cost: float | None = Field(None, description="Price in cents")
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@@ -145,7 +127,7 @@ class BFLStatus(str, Enum):
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class BFLFluxStatusResponse(BaseModel):
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id: str = Field(..., description="The unique identifier for the generation task.")
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status: BFLStatus = Field(..., description="The status of the task.")
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result: Optional[Dict[str, Any]] = Field(None, description="The result of the task (null if not completed).")
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progress: Optional[float] = Field(None, description="The progress of the task (0.0 to 1.0).", ge=0.0, le=1.0)
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id: str = Field(...)
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status: BFLStatus = Field(...)
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result: dict[str, Any] | None = Field(None)
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progress: float | None = Field(None, ge=0.0, le=1.0)
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