604 lines
22 KiB
TypeScript
604 lines
22 KiB
TypeScript
import { copyFileSync, existsSync, readFileSync, writeFileSync } from 'node:fs'
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import { join } from 'node:path'
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import { createJob, emitJob, type Job } from '~/server/utils/jobs'
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import { pendingFromJob, remainingAfterCurrentShot, writePendingJob } from '~/server/utils/pending'
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import { emitChainJob, waitForComfySocket, watchComfyJob } from '~/server/utils/watch'
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import { comfyFilenamePrefix, queuePrompt, uploadImage } from '~/server/utils/comfy'
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import { buildWorkflow } from '~/server/utils/workflow'
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import { isLtxWorkflow, isTextToVideo, parseVideoWorkflow, workflowForExtension, type VideoWorkflowId } from '~/utils/videoModels'
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import { clipVideoPath, clipTitle, deleteRetryDraft, extendTempDir, getClip, nextClipPartName, removeExtendTemp, stillPath } from '~/server/utils/library'
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import { extractLastFrame, probeHasAudio } from '~/server/utils/ffmpeg'
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import { ensureComfyReady } from '~/server/utils/comfyLifecycle'
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import { onLiveVideoSettled, onStudioQueueBurstStarted } from '~/server/utils/studioQueue'
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import {
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finishQueueBurst,
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getShotQueue,
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lastCompletedIndex,
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liveSegmentPrompt,
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prepareQueueBurst,
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remainingFromQueue,
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setQueueJob,
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updateShotQueue
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} from '~/server/utils/shotQueue'
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import { composeShotPrompt, allowIdentityRefs, type PermanenceRef } from '~/utils/globalLocks'
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import { persistLoraFields, ensureComfyLoraNames } from '~/server/utils/loras'
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import { readLoraStack, resolveLoraStack } from '~/utils/loras'
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import type { LoraStackItem } from '~/utils/loras'
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export type ChainImage = { filename: string; data: Buffer; type?: string }
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type VideoChainParams = {
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prompt: string
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image?: ChainImage | null
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width: number
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height: number
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steps: number
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seed: number
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turbo: boolean
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length: number
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sound: boolean
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cfg: number
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fps: number
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samplerName: string
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scheduler: string
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extensions: { prompt: string; duration: number; loraName?: string; loraStack?: LoraStackItem[]; permanenceRefs?: PermanenceRef[] }[]
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workflow: VideoWorkflowId
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duration: number
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useIdentityRefs: boolean
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referenceImages: Array<ChainImage | null>
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globalLocks?: string
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permanenceRefs?: PermanenceRef[]
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shotPermanenceRefs?: PermanenceRef[][]
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loraName?: string
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loraStack?: LoraStackItem[]
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shotLoras?: string[]
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shotLoraStacks?: LoraStackItem[][]
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}
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function sleep(ms: number) {
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return new Promise(resolve => setTimeout(resolve, ms))
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}
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export function frameLength(seconds: number, fps: number) {
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return Math.max(5, Math.floor(seconds * fps))
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}
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function assertJobActive(job: Job) {
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if (job.status === 'cancelled') {
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throw new Error('Job interrupted.')
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}
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if (job.status === 'error') {
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throw new Error(job.error || 'Generation failed')
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}
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}
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function loadStillImage(owner: string, stillId?: string, filename?: string): ChainImage | null {
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if (!stillId) return null
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const path = stillPath(owner, stillId)
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if (!existsSync(path)) return null
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return {
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filename: filename || 'still.png',
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data: readFileSync(path),
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type: 'image/png'
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}
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}
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function paramsFromJob(job: Job): VideoChainParams {
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const library = job.library
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if (!library) {
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throw new Error('Cannot continue the shot chain: job metadata is missing')
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}
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const image = loadStillImage(library.ownerKey, library.stillId, library.stillFilename)
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const workflow = parseVideoWorkflow(library.workflow)
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if (!image?.data.length && !isTextToVideo(workflow)) {
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throw new Error('Cannot continue the shot chain: the start still is missing from the library')
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}
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const referenceImages: Array<ChainImage | null> = [null, null, null, null]
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for (const [index, stillId] of (library.referenceStillIds || []).entries()) {
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if (!stillId || index >= 4) continue
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referenceImages[index] = loadStillImage(library.ownerKey, stillId, `identity-ref-${index + 2}.png`)
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}
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const fps = library.fps || 24
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const duration = library.duration || 5
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return {
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prompt: library.prompt,
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image,
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width: library.width,
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height: library.height,
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steps: library.steps,
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seed: library.seed,
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turbo: library.turbo,
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length: frameLength(duration, fps),
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sound: library.sound !== false,
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cfg: library.cfg || (library.turbo ? 1.5 : 4),
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fps,
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samplerName: library.samplerName || 'res_multistep',
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scheduler: library.scheduler || 'simple',
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extensions: library.extensions || [],
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workflow,
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duration,
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useIdentityRefs: allowIdentityRefs(
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library.useIdentityRefs === true,
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library.permanenceRefs,
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library.globalLocks,
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library.shotPermanenceRefs
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),
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referenceImages,
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globalLocks: library.globalLocks,
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permanenceRefs: library.permanenceRefs,
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shotPermanenceRefs: library.shotPermanenceRefs,
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...persistLoraFields(readLoraStack(library)),
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shotLoras: library.shotLoras,
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shotLoraStacks: library.shotLoraStacks
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}
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}
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export async function queueMiniMax(
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job: Job,
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params: Omit<VideoChainParams, 'extensions'> & { persist: boolean }
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) {
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assertJobActive(job)
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job.socketReady = false
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job.promptId = undefined
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job.video = undefined
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job.segmentBuffer = undefined
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const done = watchComfyJob(job, { persist: params.persist })
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job.status = 'uploading'
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const chainIndex = job.library?.chainIndex || 0
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const graphId = chainIndex > 0 ? workflowForExtension(params.workflow) : params.workflow
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if (job.library) Object.assign(job.library, persistLoraFields(params.loraStack || params.loraName || job.library.loraStack || job.library.loraName))
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const engineName = isLtxWorkflow(graphId) ? 'LTX-2.3' : 'MiniMax H3'
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const hasImage = Boolean(params.image?.data?.length)
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const uploading = !hasImage
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? `Queueing ${engineName} text-to-video…`
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: params.useIdentityRefs
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? (chainIndex > 0 ? 'Uploading identity stills for next shot...' : 'Uploading image to ComfyUI...')
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: (chainIndex > 0 ? 'Uploading last frame to ComfyUI...' : 'Uploading image to ComfyUI...')
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const queueing = chainIndex > 0
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? `Queueing extension on ${engineName}...`
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: `Queueing ${engineName} job...`
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emitChainJob(job, { type: 'status', message: uploading, progress: 4 })
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const uploaded = hasImage && params.image
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? await uploadImage(params.image, job.id)
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: { name: '', subfolder: '' }
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const referenceNames: string[] = ['', '', '', '']
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if (params.useIdentityRefs) {
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for (const [index, ref] of (params.referenceImages || []).entries()) {
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if (!ref?.data?.length) continue
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const next = await uploadImage({
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...ref,
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filename: `ref${index + 1}_${ref.filename || 'identity.png'}`
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}, job.id)
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referenceNames[index] = next.name
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}
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}
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if (job.library) {
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job.library.imageName = uploaded.name
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job.library.imageSubfolder = uploaded.subfolder
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job.library.referenceImageNames = referenceNames.filter(Boolean)
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}
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emitChainJob(job, { type: 'status', message: queueing, progress: 6 })
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await waitForComfySocket(job, 4000)
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await ensureComfyLoraNames('video')
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const shotIndex = job.library?.chainIndex || 0
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const composedPrompt = composeShotPrompt({
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globalLocks: job.library?.globalLocks || params.globalLocks,
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prompt: params.prompt,
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shotIndex,
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familyRefs: job.library?.permanenceRefs || params.permanenceRefs,
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shotRefs: job.library?.shotPermanenceRefs?.[shotIndex] || params.shotPermanenceRefs?.[shotIndex]
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})
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const graph = buildWorkflow({
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prompt: composedPrompt,
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imageName: uploaded.name,
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width: params.width,
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height: params.height,
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steps: params.steps,
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seed: params.seed,
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turbo: params.turbo,
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length: params.length,
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cfg: params.cfg,
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fps: params.fps,
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samplerName: params.samplerName,
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scheduler: params.scheduler,
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filenamePrefix: isLtxWorkflow(graphId) ? 'video/LTX23' : comfyFilenamePrefix(),
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sound: params.sound && !isLtxWorkflow(graphId),
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workflow: graphId,
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duration: params.duration,
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useIdentityRefs: params.useIdentityRefs,
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referenceImageNames: params.useIdentityRefs ? referenceNames : [],
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...persistLoraFields(params.loraStack || params.loraName)
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})
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const queued = await queuePrompt(graph, job.clientId)
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job.promptId = queued.prompt_id
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job.status = 'running'
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if (job.library?.draftId) {
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await deleteRetryDraft(job.library.ownerKey, job.library.draftId).catch(() => null)
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job.library.draftId = undefined
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}
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if (job.library && job.promptId) {
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writePendingJob(pendingFromJob(job))
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}
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emitChainJob(job, { type: 'status', message: 'Job queued on ComfyUI', progress: 8 })
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await done
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assertJobActive(job)
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if (!params.persist && !job.segmentBuffer?.length) {
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throw new Error('Segment finished without a video')
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}
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}
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function seedCurrentVideo(job: Job) {
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const library = job.library
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if (!library) {
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throw new Error('Cannot continue the shot chain: job metadata is missing')
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}
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const tmpDir = library.extendTmpDir || extendTempDir(library.ownerKey, job.id)
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library.extendTmpDir = tmpDir
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const currentPath = join(tmpDir, 'current.mp4')
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if (job.segmentBuffer?.length) {
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writeFileSync(currentPath, job.segmentBuffer)
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job.segmentBuffer = undefined
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} else if (!existsSync(currentPath)) {
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const clipId = job.clipId
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if (!clipId) {
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throw new Error('Cannot continue the shot chain: the previous clip is missing')
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}
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const source = clipVideoPath(library.ownerKey, clipId)
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if (!existsSync(source)) {
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throw new Error('Cannot continue the shot chain: the previous clip file is missing')
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}
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copyFileSync(source, currentPath)
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}
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return { tmpDir, currentPath, part1Path: join(tmpDir, 'part1.mp4'), framePath: join(tmpDir, 'last_frame.png') }
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}
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function chainShouldHold(job: Job) {
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if (!job.library) return false
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if (job.library.stopAfterCurrent) return true
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const queue = job.library.queueId
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? getShotQueue(job.library.ownerKey, job.library.queueId)
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: null
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if (queue?.stopAfterCurrent || queue?.status === 'paused') return true
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return false
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}
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export async function continueQueuedExtensions(
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job: Job,
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params: VideoChainParams,
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options: { maxShots?: number; autoRun?: boolean } = {}
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) {
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const extensions = params.extensions || []
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if (!extensions.length || !job.library) return
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if (job.library.chainContinuing) return
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job.library.chainContinuing = true
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const autoRun = options.autoRun === true || job.library.queueAutoRun === true
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let shotsLeft = options.maxShots ?? (autoRun ? extensions.length : (job.library.queueBudget || 0))
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const ready = (status: { state: string; message: string; queueRunning?: number; queuePending?: number }) => {
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emitChainJob(job, {
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type: status.state === 'busy' ? 'busy' : 'status',
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message: status.message,
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progress: status.state === 'online' ? 3 : 1,
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busy: status.state === 'busy',
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queueRunning: status.queueRunning,
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queuePending: status.queuePending
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})
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}
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try {
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if (shotsLeft <= 0) return
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const { currentPath, part1Path, framePath } = seedCurrentVideo(job)
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const startFrom = job.library.chainIndex || 0
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for (let i = startFrom; i < extensions.length; i++) {
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if (shotsLeft <= 0) break
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assertJobActive(job)
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if (chainShouldHold(job)) {
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job.library.stopAfterCurrent = true
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break
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}
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const liveQueue = job.library.queueId
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? getShotQueue(job.library.ownerKey, job.library.queueId)
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: null
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if (liveQueue?.stopAfterCurrent || liveQueue?.autoRun === false) {
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if (liveQueue.stopAfterCurrent) job.library.stopAfterCurrent = true
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if (liveQueue.autoRun === false) job.library.queueAutoRun = false
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}
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if (chainShouldHold(job)) {
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job.library.stopAfterCurrent = true
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break
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}
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const live = liveQueue ? liveSegmentPrompt(liveQueue, i) : extensions[i]
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const ext = {
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prompt: live.prompt || extensions[i].prompt,
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duration: live.duration || extensions[i].duration
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}
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const shotStack = resolveLoraStack(
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readLoraStack(liveQueue).length ? readLoraStack(liveQueue) : (params.loraStack || params.loraName),
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live.loraStack || live.loraName || extensions[i]?.loraStack || extensions[i]?.loraName
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)
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if (!ext.prompt.trim()) {
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throw new Error(`Shot ${i + 2} needs a prompt`)
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}
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emitChainJob(job, { type: 'status', message: 'Waiting 3s buffer...', progress: 1 })
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await sleep(3000)
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assertJobActive(job)
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if (chainShouldHold(job)) {
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job.library.stopAfterCurrent = true
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break
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}
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const remainingAfter = extensions.length - (i + 1)
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const lastOfChain = remainingAfter === 0
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const lastOfBurst = !autoRun && shotsLeft === 1
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const persist = lastOfChain || lastOfBurst || job.library.stopAfterCurrent === true
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job.library.chainIndex = i + 1
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job.library.chainStep = i + 2
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job.library.chainLabel = `Extension ${i + 1}`
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job.library.extendPart1Path = undefined
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job.library.thumb = undefined
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job.library.duration = ext.duration
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Object.assign(job.library, persistLoraFields(shotStack))
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if (liveQueue) {
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await updateShotQueue(job.library.ownerKey, liveQueue.id, (queue) => {
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const segment = queue.segments.find(item => item.index === i + 1)
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if (segment) {
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segment.status = 'running'
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delete segment.error
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}
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queue.status = 'running'
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queue.currentJobId = job.id
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}).catch(() => null)
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}
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copyFileSync(currentPath, part1Path)
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const parentId = job.library.parentClipId
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const parentVideo = parentId ? clipVideoPath(job.library.ownerKey, parentId) : ''
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const extractSource = parentVideo && existsSync(parentVideo) ? parentVideo : part1Path
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try {
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await extractLastFrame(extractSource, framePath)
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} catch (error) {
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const detail = error instanceof Error ? error.message : String(error)
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throw new Error(detail.includes('last frame')
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? detail
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: `Could not extract the last frame for the next extension: ${detail}`)
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}
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const frame = readFileSync(framePath)
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if (!frame.length || frame.length < 64) {
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throw new Error('Could not extract the last frame for the next extension: the frame file was empty')
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}
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job.library.extendPart1Path = part1Path
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job.library.prompt = ext.prompt
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if (live.permanenceRefs?.length) {
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const refs = [...(job.library.shotPermanenceRefs || [])]
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refs[i + 1] = live.permanenceRefs
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job.library.shotPermanenceRefs = refs
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}
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const sound = await probeHasAudio(currentPath)
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const seed = Math.floor(Math.random() * 2_147_483_647)
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const identity = allowIdentityRefs(
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params.useIdentityRefs,
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job.library.permanenceRefs || params.permanenceRefs,
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job.library.globalLocks || params.globalLocks,
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job.library.shotPermanenceRefs || params.shotPermanenceRefs
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)
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await ensureComfyReady(ready)
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await queueMiniMax(job, {
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prompt: ext.prompt,
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image: identity
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? params.image
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: { filename: 'last_frame.png', data: frame, type: 'image/png' },
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width: params.width,
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height: params.height,
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steps: params.steps,
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seed,
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turbo: params.turbo,
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length: frameLength(ext.duration, params.fps),
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sound,
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cfg: params.cfg,
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fps: params.fps,
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samplerName: params.samplerName,
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scheduler: params.scheduler,
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persist,
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workflow: workflowForExtension(params.workflow),
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duration: ext.duration,
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useIdentityRefs: identity,
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referenceImages: identity ? params.referenceImages : [],
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...persistLoraFields(shotStack)
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})
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shotsLeft -= 1
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if (job.library) job.library.queueBudget = shotsLeft
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if (!lastOfChain && !persist) {
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if (!job.segmentBuffer?.length) {
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throw new Error('Extension finished without a stitched video')
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}
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writeFileSync(currentPath, job.segmentBuffer)
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job.segmentBuffer = undefined
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job.library.extendPart1Path = undefined
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}
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if (shotsLeft <= 0 || chainShouldHold(job)) {
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if (chainShouldHold(job)) job.library.stopAfterCurrent = true
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break
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}
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}
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} finally {
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if (job.library) job.library.chainContinuing = false
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if (job.library?.queueId) {
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const paused = job.status !== 'error' && job.status !== 'cancelled'
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const hold = job.library.stopAfterCurrent === true && paused
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if (hold && job.status === 'running') job.status = 'complete'
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await finishQueueBurst(
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job.library.ownerKey,
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job.library.queueId,
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hold || (paused && !job.library.queueAutoRun),
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job.status === 'error' || job.status === 'cancelled' ? (job.error || 'Stopped') : undefined
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).catch(() => null)
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setQueueJob(job.library.queueId, null)
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}
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}
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}
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export async function continueQueuedExtensionsIfNeeded(job: Job) {
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if (!job.library) return
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if (job.status === 'error' || job.status === 'cancelled' || job.status === 'complete') return
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if (chainShouldHold(job)) {
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job.library.stopAfterCurrent = true
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return
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}
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const remaining = remainingAfterCurrentShot(job.library)
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if (!remaining.length) return
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const queue = job.library.queueId
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? getShotQueue(job.library.ownerKey, job.library.queueId)
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: null
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if (queue?.stopAfterCurrent) return
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const autoRun = queue ? queue.autoRun === true : job.library.queueAutoRun === true
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const budget = job.library.queueBudget || 0
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if (queue && !autoRun && budget <= 0) return
|
|
if (!queue && !autoRun && budget <= 0) {
|
|
// Legacy chains without a queue keep the old auto-continue behavior.
|
|
await continueQueuedExtensions(job, paramsFromJob(job), { autoRun: true })
|
|
return
|
|
}
|
|
const maxShots = autoRun ? remaining.length : budget
|
|
if (maxShots <= 0) return
|
|
await continueQueuedExtensions(job, paramsFromJob(job), { maxShots, autoRun })
|
|
}
|
|
|
|
export async function runGeneration(job: Job, params: VideoChainParams) {
|
|
const ready = (status: { state: string; message: string; queueRunning?: number; queuePending?: number }) => {
|
|
emitChainJob(job, {
|
|
type: status.state === 'busy' ? 'busy' : 'status',
|
|
message: status.message,
|
|
progress: status.state === 'online' ? 3 : 1,
|
|
busy: status.state === 'busy',
|
|
queueRunning: status.queueRunning,
|
|
queuePending: status.queuePending
|
|
})
|
|
}
|
|
|
|
try {
|
|
await ensureComfyReady(ready)
|
|
|
|
const { extensions, ...base } = params
|
|
const autoRun = job.library?.queueAutoRun === true
|
|
await queueMiniMax(job, {
|
|
...base,
|
|
persist: extensions.length === 0 || !autoRun
|
|
})
|
|
|
|
const stopNow = chainShouldHold(job)
|
|
const keepGoing = Boolean(autoRun && !stopNow && extensions.length && job.library)
|
|
if (job.library?.queueId && !keepGoing) {
|
|
await finishQueueBurst(job.library.ownerKey, job.library.queueId, true).catch(() => null)
|
|
setQueueJob(job.library.queueId, null)
|
|
}
|
|
|
|
if (!keepGoing) return
|
|
await continueQueuedExtensions(job, params, { maxShots: extensions.length, autoRun: true })
|
|
} finally {
|
|
await onLiveVideoSettled(job)
|
|
}
|
|
}
|
|
|
|
export async function startQueueBurst(owner: string, queueId: string, count: number | 'all') {
|
|
const { queue, count: n } = await prepareQueueBurst(owner, queueId, count)
|
|
const lastIndex = lastCompletedIndex(queue)
|
|
const clipId = queue.currentClipId
|
|
if (!clipId) {
|
|
throw createError({ statusCode: 409, statusMessage: 'The previous clip is missing, so the next shot cannot start' })
|
|
}
|
|
const source = getClip(owner, clipId)
|
|
const destFolderLocked = false
|
|
const job = createJob()
|
|
job.kind = 'video'
|
|
job.maxStep = queue.steps
|
|
job.hideThumbnail = queue.hideThumbnail
|
|
job.clipId = clipId
|
|
job.library = {
|
|
ownerKey: owner,
|
|
folderId: queue.folderId,
|
|
hideThumbnail: queue.hideThumbnail,
|
|
hideInput: queue.hideInput,
|
|
folderLocked: destFolderLocked,
|
|
name: nextClipPartName(clipTitle(source)),
|
|
prompt: queue.segments[lastIndex]?.prompt || source.prompt,
|
|
aspect: queue.aspect,
|
|
width: queue.width,
|
|
height: queue.height,
|
|
steps: queue.steps,
|
|
turbo: queue.turbo,
|
|
seed: Math.floor(Math.random() * 2_147_483_647),
|
|
cfg: queue.cfg,
|
|
fps: queue.fps,
|
|
samplerName: queue.samplerName,
|
|
scheduler: queue.scheduler,
|
|
duration: queue.segments[lastIndex]?.duration || source.duration,
|
|
stillId: queue.stillId,
|
|
stillFilename: queue.stillFilename,
|
|
referenceStillIds: queue.referenceStillIds,
|
|
sound: queue.sound,
|
|
extensions: remainingFromQueue(queue),
|
|
chainIndex: Math.max(0, lastIndex),
|
|
chainStep: lastIndex + 1,
|
|
chainTotal: queue.segments.length,
|
|
chainLabel: lastIndex <= 0 ? 'Initial' : `Extension ${lastIndex}`,
|
|
familyId: queue.familyId,
|
|
parentClipId: clipId,
|
|
workflow: queue.workflow,
|
|
useIdentityRefs: allowIdentityRefs(
|
|
queue.useIdentityRefs === true,
|
|
queue.permanenceRefs,
|
|
queue.globalLocks,
|
|
queue.segments.map(segment => segment.permanenceRefs || [])
|
|
),
|
|
queueId: queue.id,
|
|
queueAutoRun: count === 'all',
|
|
queueBudget: n,
|
|
globalLocks: queue.globalLocks,
|
|
permanenceRefs: queue.permanenceRefs,
|
|
shotPermanenceRefs: queue.segments.map(segment => segment.permanenceRefs || []),
|
|
...persistLoraFields(readLoraStack(queue))
|
|
}
|
|
setQueueJob(queue.id, job.id)
|
|
await updateShotQueue(owner, queue.id, (next) => {
|
|
next.currentJobId = job.id
|
|
next.status = 'running'
|
|
next.stopAfterCurrent = false
|
|
}).catch(() => null)
|
|
await onStudioQueueBurstStarted(owner, queue.id, job.id).catch(() => null)
|
|
|
|
emitChainJob(job, { type: 'status', message: 'Checking ComfyUI...', progress: 1 })
|
|
void continueQueuedExtensions(job, paramsFromJob(job), {
|
|
maxShots: n,
|
|
autoRun: count === 'all'
|
|
}).catch(async (error) => {
|
|
removeExtendTemp(job.library?.extendTmpDir)
|
|
const message = error instanceof Error ? error.message : String(error)
|
|
if (job.status === 'error' || job.status === 'cancelled') {
|
|
await finishQueueBurst(owner, queue.id, false, message).catch(() => null)
|
|
setQueueJob(queue.id, null)
|
|
return
|
|
}
|
|
job.status = 'error'
|
|
job.error = message
|
|
emitJob(job, { type: 'error', error: message, message })
|
|
await finishQueueBurst(owner, queue.id, false, message).catch(() => null)
|
|
setQueueJob(queue.id, null)
|
|
}).finally(() => {
|
|
void onLiveVideoSettled(job)
|
|
})
|
|
|
|
return { jobId: job.id, queueId: queue.id, count: n, chainTotal: queue.segments.length, chainStep: lastIndex + 1 }
|
|
}
|