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export type TTSVoice =
| "Cloée" // consent given (friend)
| "Julian" // consent given (HF employee)
export type ProjectionMode = 'cartesian' | 'spherical'
export type MouseEventType = "hover" | "click"
export type MouseEventHandler = (type: MouseEventType, x: number, y: number) => Promise<void>
export type CacheMode = "use" | "renew" | "ignore"
export interface RenderRequest {
prompt: string
// whether to use video segmentation
// disabled (default)
// firstframe: we only analyze the first frame
// allframes: we analyze all the frames
segmentation: 'disabled' | 'firstframe' | 'allframes'
// segmentation will only be executed if we have a non-empty list of actionnables
// actionnables are names of things like "chest", "key", "tree", "chair" etc
actionnables: string[]
// note: this is the number of frames for Zeroscope,
// which is currently configured to only output 3 seconds, so:
// nbFrames=8 -> 1 sec
// nbFrames=16 -> 2 sec
// nbFrames=24 -> 3 sec
nbFrames: number // min: 1, max: 24
nbSteps: number // min: 1, max: 50
seed: number
width: number // fixed at 1024 for now
height: number // fixed at 512 for now
// upscaling factor
// 0: no upscaling
// 1: no upscaling
// 2: 2x larger
// 3: 3x larger
// 4x: 4x larger, up to 4096x4096 (warning: a PNG of this size can be 50 Mb!)
upscalingFactor: number
projection: ProjectionMode
/**
* Use turbo mode
*
* At the time of writing this will use SSD-1B + LCM
* https://huggingface.co/spaces/ruslanmv/ai-fast-image-server
*/
turbo: boolean
cache: CacheMode
wait: boolean // wait until the job is completed
analyze: boolean // analyze the image to generate a caption (optional)
}
export interface ImageSegment {
id: number
box: number[]
color: number[]
label: string
score: number
}
export type RenderedSceneStatus =
| "pending"
| "completed"
| "error"
export interface RenderedScene {
renderId: string
status: RenderedSceneStatus
assetUrl: string
alt: string
error: string
maskUrl: string
segments: ImageSegment[]
}
export interface ImageAnalysisRequest {
image: string // in base64
prompt: string
}
export interface ImageAnalysisResponse {
result: string
error?: string
}
export type RenderingEngine =
| "VIDEOCHAIN"
| "OPENAI"
| "REPLICATE"
export type PostVisibility =
| "featured" // featured by admins
| "trending" // top trending / received more than 10 upvotes
| "normal" // default visibility
export type Post = {
postId: string
appId: string
prompt: string
model: string
previewUrl: string
assetUrl: string
createdAt: string
visibility: PostVisibility
upvotes: number
downvotes: number
}
export type CreatePostResponse = {
success?: boolean
error?: string
post: Post
}
export type GetAppPostsResponse = {
success?: boolean
error?: string
posts: Post[]
}
export type GetAppPostResponse = {
success?: boolean
error?: string
post: Post
}
export type CurrentPanel =
| "join"
| "play"
| "results"
// vendor-specific types
export type HotshotImageInferenceSize =
| '320x768'
| '384x672'
| '416x608'
| '512x512'
| '608x416'
| '672x384'
| '768x320'
| '1024x1024' // custom ratio - this isn't supported / supposed to work properly
| '1024x512' // custom panoramic ratio - this isn't supported / supposed to work properly
| '1024x576' // movie ratio (16:9) this isn't supported / supposed to work properly
| '576x1024' // tiktok ratio (9:16) this isn't supported / supposed to work properly
export type VideoOptions = {
positivePrompt: string
negativePrompt?: string
size?: HotshotImageInferenceSize
/**
* Must be a model *name*
*/
huggingFaceLora?: string
replicateLora?: string
triggerWord?: string
nbFrames?: number // FPS (eg. 8)
duration?: number // in milliseconds
steps?: number
key?: string // a semi-unique key to prevent abuse from some users
}
export type SDXLModel = {
image: string
title: string
repo: string
trigger_word: string
weights: string
is_compatible: boolean
likes: number
downloads: number
}
export type QualityLevel = "low" | "medium" | "high"
export type QualityOption = {
level: QualityLevel
label: string
}
export type StoryLine = {
text: string
audio: string // in base64
}
export type Story = {
lines: StoryLine[]
} |