mirror of
https://github.com/comfyanonymous/ComfyUI.git
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f1c9ca816a
* Added initial Flux.1 Kontext Pro Image node - recreated branch to save myself sanity from rebase crap after master got rebased * Add safety filter to Kontext. * Make safety = 2 and input image is optional. * Add BFL kontext API nodes. --------- Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>
191 lines
12 KiB
Python
191 lines
12 KiB
Python
from __future__ import annotations
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from enum import Enum
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from typing import Any, Dict, Optional
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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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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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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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)
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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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)
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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 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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class BFLFluxCannyImageRequest(BaseModel):
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prompt: str = Field(..., description='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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canny_low_threshold: Optional[int] = Field(None, description='Low threshold for Canny edge detection')
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canny_high_threshold: Optional[int] = Field(None, description='High threshold for Canny edge detection')
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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, 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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control_image: Optional[str] = Field(None, description='Base64 encoded image to use as control input if no preprocessed image is provided')
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preprocessed_image: Optional[str] = Field(None, description='Optional pre-processed image that will bypass the control preprocessing step')
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class BFLFluxDepthImageRequest(BaseModel):
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prompt: str = Field(..., description='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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steps: conint(ge=15, le=50) = Field(..., description='Number of steps for the image generation process')
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guidance: confloat(ge=1, 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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control_image: Optional[str] = Field(None, description='Base64 encoded image to use as control input if no preprocessed image is provided')
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preprocessed_image: Optional[str] = Field(None, description='Optional pre-processed image that will bypass the control preprocessing step')
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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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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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class BFLFluxKontextMaxGenerateRequest(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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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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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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class BFLStatus(str, Enum):
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task_not_found = "Task not found"
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pending = "Pending"
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request_moderated = "Request Moderated"
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content_moderated = "Content Moderated"
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ready = "Ready"
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error = "Error"
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class BFLFluxProStatusResponse(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(
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None, description="The result of the task (null if not completed)."
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)
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progress: confloat(ge=0.0, le=1.0) = Field(
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..., description="The progress of the task (0.0 to 1.0)."
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)
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details: Optional[Dict[str, Any]] = Field(
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None, description="Additional details about the task (null if not available)."
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)
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