aigen/server/api/generate.post.ts

function frameLength(seconds: number) {
  const raw = Math.max(5, Math.round(seconds * 24))
  return raw + (5 - (raw % 17) + 17) % 17
}

export default defineEventHandler(async (event) => {
  const form = await readMultipartFormData(event)
  if (!form?.length) {
    throw createError({ statusCode: 400, statusMessage: 'Expected multipart form data' })
  }

  const fields: Record<string, string> = {}
  let image: { filename: string; data: Buffer; type?: string } | null = null
  for (const part of form) {
    if (part.name === 'image' && part.filename && part.data?.length) {
      image = { filename: part.filename, data: part.data, type: part.type }
    } else if (part.name && part.data) {
      fields[part.name] = part.data.toString('utf8')
    }
  }

  if (!image) {
    throw createError({ statusCode: 400, statusMessage: 'An initial image is required' })
  }
  const prompt = (fields.prompt || '').trim()
  if (!prompt) {
    throw createError({ statusCode: 400, statusMessage: 'A motion prompt is required' })
  }

  const { width, height } = resolveOutputSize(fields.aspect, image.data, Number(fields.width), Number(fields.height))
  const turbo = fields.turbo !== 'false'
  const steps = Number(fields.steps || (turbo ? 8 : 20))
  const seed = fields.seed && fields.seed !== 'random'
    ? Number(fields.seed)
    : Math.floor(Math.random() * 2_147_483_647)
  const length = frameLength(Number(fields.duration || 5))
  const hideThumbnail = fields.hideThumbnail === 'true'
  const clipName = (fields.name || '').trim().slice(0, 80)
  const ownerKey = libraryOwnerKey(event)
  const library = publicLibrary(event)
  const folderId = library.folders.some(folder => folder.id === fields.folderId)
    ? fields.folderId
    : library.folders[0]?.id
  if (!folderId) {
    throw createError({ statusCode: 400, statusMessage: 'Create a library folder before generating' })
  }
  assertFolderAccess(event, folderId)
  await saveStill({
    ownerKey,
    folderId,
    filename: image.filename,
    data: image.data,
    width,
    height
  })

  const job = createJob()
  job.maxStep = steps
  job.hideThumbnail = hideThumbnail
  job.library = {
    ownerKey,
    folderId,
    hideThumbnail,
    name: clipName,
    prompt,
    aspect: fields.aspect || 'auto',
    width,
    height,
    steps,
    turbo,
    seed,
    thumb: image.data
  }
  emitJob(job, { type: 'status', message: 'Checking ComfyUI...', progress: 1 })

  void runGeneration(job, { prompt, image, width, height, steps, seed, turbo, length }).catch((error) => {
    const message = error instanceof Error ? error.message : String(error)
    job.status = 'error'
    job.error = message
    emitJob(job, { type: 'error', error: message, message })
  })

  return {
    jobId: job.id,
    clientId: job.clientId,
    seed,
    width,
    height,
    aspect: fields.aspect || 'auto',
    steps,
    turbo,
    folderId,
    hideThumbnail
  }
})

async function runGeneration(
  job: ReturnType<typeof createJob>,
  params: {
    prompt: string
    image: { filename: string; data: Buffer; type?: string }
    width: number
    height: number
    steps: number
    seed: number
    turbo: boolean
    length: number
  }
) {
  await ensureComfyReady((status) => {
    emitJob(job, {
      type: status.state === 'busy' ? 'busy' : 'status',
      message: status.message,
      progress: status.state === 'online' ? Math.max(job.progress, 3) : Math.max(job.progress, 1),
      busy: status.state === 'busy',
      queueRunning: status.queueRunning,
      queuePending: status.queuePending
    })
  })

  const done = watchComfyJob(job)
  job.status = 'uploading'
  emitJob(job, { type: 'status', message: 'Uploading image to ComfyUI...', progress: 4 })
  const uploaded = await uploadImage(params.image)
  if (job.library) job.library.imageName = uploaded.name
  emitJob(job, { type: 'status', message: 'Queueing MiniMax H3 job...', progress: 6 })
  await waitForComfySocket(job, 4000)

  const graph = buildWorkflow({
    prompt: params.prompt,
    imageName: uploaded.name,
    width: params.width,
    height: params.height,
    steps: params.steps,
    seed: params.seed,
    turbo: params.turbo,
    length: params.length,
    filenamePrefix: comfyFilenamePrefix()
  })

  const queued = await queuePrompt(graph, job.clientId)
  job.promptId = queued.prompt_id
  job.status = 'running'
  if (job.library && job.promptId) {
    writePendingJob({
      jobId: job.id,
      promptId: job.promptId,
      clientId: job.clientId,
      ownerKey: job.library.ownerKey,
      folderId: job.library.folderId,
      hideThumbnail: job.library.hideThumbnail,
      name: job.library.name,
      prompt: job.library.prompt,
      aspect: job.library.aspect,
      width: job.library.width,
      height: job.library.height,
      steps: job.library.steps,
      turbo: job.library.turbo,
      seed: job.library.seed,
      startedAt: job.startedAt,
      imageName: job.library.imageName
    })
  }
  emitJob(job, { type: 'status', message: 'Job queued on ComfyUI', progress: 8 })
  await done
}