メディアとアップロード

upload(file: File): Promise<UploadResult>

const result = await client.uploads.upload(file)

const clip = await client.nodes.runAndWait("generate-video", {
  prompt: "The camera slowly pushes in",
  imageUrl: result.url,
})

list(params?: ListLibraryParams): Promise<{ data: LibraryAsset[]; nextCursor: string | null; totalCount?: number }>

const { data: videos, nextCursor } = await client.library.list({ type: "video", limit: 20 })
for (const asset of videos) console.log(asset.filename, asset.url)

downloadVideo(input: {
  url: string
  maxHeight?: number
  sectionStartSec?: number
  sectionEndSec?: number
  requireAudio?: boolean
}): Promise<{ downloadId: string }>

const { downloadId } = await client.media.downloadVideo({
  url: "https://youtu.be/dQw4w9WgXcQ",
  maxHeight: 720,
})

downloadVideoProgress(downloadId: string, opts?: { signal?: AbortSignal }): AsyncGenerator<DownloadVideoProgress>

for await (const event of client.media.downloadVideoProgress(downloadId)) {
  console.log(`${event.phase} ${event.percent}%`)
  if (event.phase === "completed") console.log("Stored at", event.videoUrl)
  if (event.phase === "failed") console.error(event.error)
}

videoMetadata(input: { url: string }): Promise<VideoMetadata>

const meta = await client.media.videoMetadata({ url: "https://youtu.be/dQw4w9WgXcQ" })

saveToStorage(input: { mediaUrl: string; filename?: string; mediaType?: "image" | "video" | "audio" }): Promise<{ jobId: string }>

const { jobId } = await client.media.saveToStorage({ mediaUrl: "https://example.com/intro.mp4", mediaType: "video" })

process(input: {
  sourceUrl: string
  type: "video" | "audio"
  trim?: { startTime: number; endTime: number }
  crop?: { x: number; y: number; width: number; height: number }
  format?: "mp4" | "webm" | "mp3" | "wav" | "m4a" | "aac"
  deleteSource?: boolean
}): Promise<{ data: MediaProcessResult }>

const { data } = await client.media.process({
  sourceUrl: stored.url,
  type: "video",
  trim: { startTime: 12, endTime: 42 },
})
console.log(data.url, data.sizeBytes)

trimVideo(input: {
  videoUrl: string
  startTime?: number
  endTime?: number
  trimStartFrames?: number
  trimEndFrames?: number
  trimStartSeconds?: number
  trimEndSeconds?: number
  keepFirstSeconds?: number
  keepLastSeconds?: number
}): Promise<{ jobId: string }>

const { jobId } = await client.media.trimVideo({ videoUrl, keepFirstSeconds: 15 })

trimAudio(input: {
  videoUrl?: string
  audioUrl?: string
  audioFormat?: "mp3" | "wav" | "aac"
  startTime?: number
  endTime?: number
}): Promise<{ jobId: string }>

const { jobId } = await client.media.trimAudio({ videoUrl, startTime: 5, endTime: 35 })

addCaptions(input: AddCaptionsInput): Promise<{ jobId: string }>

const { jobId } = await client.media.addCaptions({
  videoUrl: "https://example.com/talk.mp4",
  style: "word-highlight",
  maxWordsPerLine: 2,
})

import type { TranscribeJobOutput } from "@nodaro/sdk"

const { jobId } = await client.audio.transcribe({
  audioUrl: "https://example.com/talk.mp3",
  provider: "elevenlabs-stt", // always returns word timings
})
// ...poll until the job completes, then:
const { data: job } = await client.jobs.get(jobId)
const { words = [] } = job.output_data as TranscribeJobOutput

const corrected = words.map((w, i) => (i === 7 ? { ...w, text: "Nodaro" } : w))
await client.media.addCaptions({
  videoUrl: "https://example.com/talk.mp4",
  captions: corrected,
  autoTranscribe: false,
  style: "word-highlight",
})

stillToVideo(input: {
  imageUrl: string
  audioUrl: string
  motion?: "none" | "zoom-in" | "zoom-out" | "pan-left" | "pan-right" | "ken-burns"
  intensity?: number
  resolution?: "720p" | "1080p" | "4K"
  aspectRatio?: "16:9" | "9:16" | "1:1" | "4:3"
  fps?: 24 | 30
  fit?: "cover" | "contain"
  padColor?: string
}): Promise<{ jobId: string }>

const { jobId } = await client.media.stillToVideo({ imageUrl: coverUrl, audioUrl: podcastUrl, motion: "ken-burns" })

slideshow(input: {
  imageUrls: string[]
  audioUrl?: string
  imageDurations?: Array<number | null>
  perImageDuration?: number
  transition?: string
  transitionDuration?: number
  motion?: "none" | "zoom-in" | "zoom-out" | "ken-burns" | "alternate"
  intensity?: number
  resolution?: "720p" | "1080p" | "4K"
  aspectRatio?: "16:9" | "9:16" | "1:1" | "4:3"
  fps?: 24 | 30
  fit?: "cover" | "contain"
  padColor?: string
}): Promise<{ jobId: string }>

const { jobId } = await client.media.slideshow({ imageUrls: frames, audioUrl: musicUrl, motion: "alternate" })

videoOverlay(input: VideoOverlayRequest): Promise<{ jobId: string }>

const { jobId } = await client.media.videoOverlay({
  videoUrl,
  layers: [
    { imageUrl: logoUrl, start: 0, preset: "corner-badge", corner: "top-right" },
    { imageUrl: offerCardUrl, start: 8, end: 14, preset: "card" },
  ],
})

imageCollage(input: {
  imageUrls: string[]
  imageSizes?: Array<0 | 1 | 2 | 3>
  numbered?: boolean
  imageLabels?: Array<string | null>
  badgePosition?: "top-left" | "top-right"
  layout?: "smart" | "grid"
  resolution?: "2K" | "4K"
  aspectRatio?: string
  gap?: number
  backgroundColor?: string
}): Promise<{ jobId: string }>

const { jobId } = await client.media.imageCollage({
  imageUrls: shotUrls,
  numbered: true,
  imageLabels: ["Wide", "Medium", "Close-up"],
})

imageOverlay(input: {
  imageUrl: string
  layers: Array<{
    kind?: "image" | "text" | "qr" | "shape"
    imageUrl?: string
    anchor?: "top-left" | "top" | "top-right" | "left" | "center" | "right" | "bottom-left" | "bottom" | "bottom-right"
    x?: number
    y?: number
    width?: number
    height?: number
    opacity?: number
    rotation?: number
    blend?: "over" | "multiply" | "screen"
    fit?: "contain" | "cover" | "stretch"
    shadow?: { blur: number; offsetX: number; offsetY: number; color: string; opacity: number }
    roundedCorners?: number
    zIndex?: number
    text?: OverlayTextStyle
    qr?: OverlayQrStyle
    shape?: OverlayShapeStyle
    effects?: OverlayImageEffects
  }>
  canvas?: { width: number; height: number; backgroundColor?: string }
  baseFit?: "contain" | "cover"
  outputFormat?: "png" | "jpg" | "webp"
  variants?: string[]
  maskMode?: "none" | "layers" | "around" | "outside"
  maskSpread?: number
  qrText?: string
}): Promise<{ jobId: string }>

const { jobId } = await client.media.imageOverlay({
  imageUrl: productShotUrl,
  layers: [{ imageUrl: logoUrl, anchor: "bottom-right", x: -4, y: -6, width: 12, opacity: 0.95 }],
  variants: ["youtube-thumbnail"],
})

suggestOverlayPlacement(input: {
  imageUrl: string
  layerAspect?: number
  intent?: string
  safeArea?: { x: number; y: number; w: number; h: number }
  llmModel?: string
}): Promise<{ jobId: string; placement: OverlayPlacement }>

const { placement } = await client.media.suggestOverlayPlacement({
  imageUrl: baseUrl,
  intent: "a logo",
  layerAspect: 2.5,
})
const { reason, ...box } = placement // anchor, x, y and width, in imageOverlay's units
await client.media.imageOverlay({ imageUrl: baseUrl, layers: [{ imageUrl: logoUrl, ...box }] })