mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2025-06-13 15:02:09 +08:00
254 lines
8.0 KiB
Python
254 lines
8.0 KiB
Python
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from __future__ import annotations
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import torch
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from enum import Enum
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from typing import Optional, Union
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from pydantic import BaseModel, Field, confloat
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class LumaIO:
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LUMA_REF = "LUMA_REF"
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LUMA_CONCEPTS = "LUMA_CONCEPTS"
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class LumaReference:
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def __init__(self, image: torch.Tensor, weight: float):
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self.image = image
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self.weight = weight
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def create_api_model(self, download_url: str):
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return LumaImageRef(url=download_url, weight=self.weight)
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class LumaReferenceChain:
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def __init__(self, first_ref: LumaReference=None):
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self.refs: list[LumaReference] = []
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if first_ref:
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self.refs.append(first_ref)
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def add(self, luma_ref: LumaReference=None):
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self.refs.append(luma_ref)
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def create_api_model(self, download_urls: list[str], max_refs=4):
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if len(self.refs) == 0:
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return None
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api_refs: list[LumaImageRef] = []
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for ref, url in zip(self.refs, download_urls):
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api_ref = LumaImageRef(url=url, weight=ref.weight)
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api_refs.append(api_ref)
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return api_refs
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def clone(self):
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c = LumaReferenceChain()
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for ref in self.refs:
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c.add(ref)
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return c
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class LumaConcept:
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def __init__(self, key: str):
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self.key = key
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class LumaConceptChain:
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def __init__(self, str_list: list[str] = None):
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self.concepts: list[LumaConcept] = []
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if str_list is not None:
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for c in str_list:
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if c != "None":
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self.add(LumaConcept(key=c))
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def add(self, concept: LumaConcept):
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self.concepts.append(concept)
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def create_api_model(self):
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if len(self.concepts) == 0:
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return None
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api_concepts: list[LumaConceptObject] = []
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for concept in self.concepts:
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if concept.key == "None":
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continue
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api_concepts.append(LumaConceptObject(key=concept.key))
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if len(api_concepts) == 0:
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return None
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return api_concepts
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def clone(self):
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c = LumaConceptChain()
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for concept in self.concepts:
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c.add(concept)
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return c
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def clone_and_merge(self, other: LumaConceptChain):
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c = self.clone()
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for concept in other.concepts:
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c.add(concept)
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return c
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def get_luma_concepts(include_none=False):
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concepts = []
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if include_none:
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concepts.append("None")
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return concepts + [
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"truck_left",
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"pan_right",
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"pedestal_down",
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"low_angle",
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"pedestal_up",
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"selfie",
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"pan_left",
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"roll_right",
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"zoom_in",
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"over_the_shoulder",
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"orbit_right",
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"orbit_left",
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"static",
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"tiny_planet",
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"high_angle",
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"bolt_cam",
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"dolly_zoom",
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"overhead",
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"zoom_out",
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"handheld",
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"roll_left",
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"pov",
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"aerial_drone",
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"push_in",
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"crane_down",
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"truck_right",
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"tilt_down",
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"elevator_doors",
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"tilt_up",
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"ground_level",
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"pull_out",
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"aerial",
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"crane_up",
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"eye_level"
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]
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class LumaImageModel(str, Enum):
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photon_1 = "photon-1"
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photon_flash_1 = "photon-flash-1"
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class LumaVideoModel(str, Enum):
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ray_2 = "ray-2"
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ray_flash_2 = "ray-flash-2"
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ray_1_6 = "ray-1-6"
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class LumaAspectRatio(str, Enum):
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ratio_1_1 = "1:1"
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ratio_16_9 = "16:9"
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ratio_9_16 = "9:16"
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ratio_4_3 = "4:3"
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ratio_3_4 = "3:4"
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ratio_21_9 = "21:9"
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ratio_9_21 = "9:21"
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class LumaVideoOutputResolution(str, Enum):
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res_540p = "540p"
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res_720p = "720p"
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res_1080p = "1080p"
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res_4k = "4k"
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class LumaVideoModelOutputDuration(str, Enum):
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dur_5s = "5s"
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dur_9s = "9s"
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class LumaGenerationType(str, Enum):
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video = 'video'
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image = 'image'
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class LumaState(str, Enum):
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queued = "queued"
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dreaming = "dreaming"
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completed = "completed"
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failed = "failed"
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class LumaAssets(BaseModel):
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video: Optional[str] = Field(None, description='The URL of the video')
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image: Optional[str] = Field(None, description='The URL of the image')
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progress_video: Optional[str] = Field(None, description='The URL of the progress video')
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class LumaImageRef(BaseModel):
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'''Used for image gen'''
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url: str = Field(..., description='The URL of the image reference')
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weight: confloat(ge=0.0, le=1.0) = Field(..., description='The weight of the image reference')
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class LumaImageReference(BaseModel):
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'''Used for video gen'''
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type: Optional[str] = Field('image', description='Input type, defaults to image')
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url: str = Field(..., description='The URL of the image')
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class LumaModifyImageRef(BaseModel):
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url: str = Field(..., description='The URL of the image reference')
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weight: confloat(ge=0.0, le=1.0) = Field(..., description='The weight of the image reference')
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class LumaCharacterRef(BaseModel):
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identity0: LumaImageIdentity = Field(..., description='The image identity object')
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class LumaImageIdentity(BaseModel):
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images: list[str] = Field(..., description='The URLs of the image identity')
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class LumaGenerationReference(BaseModel):
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type: str = Field('generation', description='Input type, defaults to generation')
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id: str = Field(..., description='The ID of the generation')
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class LumaKeyframes(BaseModel):
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frame0: Optional[Union[LumaImageReference, LumaGenerationReference]] = Field(None, description='')
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frame1: Optional[Union[LumaImageReference, LumaGenerationReference]] = Field(None, description='')
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class LumaConceptObject(BaseModel):
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key: str = Field(..., description='Camera Concept name')
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class LumaImageGenerationRequest(BaseModel):
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prompt: str = Field(..., description='The prompt of the generation')
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model: LumaImageModel = Field(LumaImageModel.photon_1, description='The image model used for the generation')
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aspect_ratio: Optional[LumaAspectRatio] = Field(LumaAspectRatio.ratio_16_9, description='The aspect ratio of the generation')
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image_ref: Optional[list[LumaImageRef]] = Field(None, description='List of image reference objects')
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style_ref: Optional[list[LumaImageRef]] = Field(None, description='List of style reference objects')
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character_ref: Optional[LumaCharacterRef] = Field(None, description='The image identity object')
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modify_image_ref: Optional[LumaModifyImageRef] = Field(None, description='The modify image reference object')
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class LumaGenerationRequest(BaseModel):
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prompt: str = Field(..., description='The prompt of the generation')
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model: LumaVideoModel = Field(LumaVideoModel.ray_2, description='The video model used for the generation')
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duration: Optional[LumaVideoModelOutputDuration] = Field(None, description='The duration of the generation')
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aspect_ratio: Optional[LumaAspectRatio] = Field(None, description='The aspect ratio of the generation')
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resolution: Optional[LumaVideoOutputResolution] = Field(None, description='The resolution of the generation')
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loop: Optional[bool] = Field(None, description='Whether to loop the video')
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keyframes: Optional[LumaKeyframes] = Field(None, description='The keyframes of the generation')
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concepts: Optional[list[LumaConceptObject]] = Field(None, description='Camera Concepts to apply to generation')
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class LumaGeneration(BaseModel):
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id: str = Field(..., description='The ID of the generation')
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generation_type: LumaGenerationType = Field(..., description='Generation type, image or video')
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state: LumaState = Field(..., description='The state of the generation')
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failure_reason: Optional[str] = Field(None, description='The reason for the state of the generation')
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created_at: str = Field(..., description='The date and time when the generation was created')
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assets: Optional[LumaAssets] = Field(None, description='The assets of the generation')
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model: str = Field(..., description='The model used for the generation')
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request: Union[LumaGenerationRequest, LumaImageGenerationRequest] = Field(..., description="The request used for the generation")
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