Image-to-Video API Reference

Sora 2 image-to-video API reference and live playground — multipart upload of input_reference to animate a static image.

POST /v1/videos

Image-to-video: submit a video generation task from a reference image

cURL

curl --request POST \
  --url https://api.apiyi.com/v1/videos \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: multipart/form-data' \
  --form model=sora-2 \
  --form 'prompt=Animate this scene: gentle waves lapping, leaves swaying, cinematic camera push-in' \
  --form input_reference='@example-file'

import requests

url = "https://api.apiyi.com/v1/videos"

files = { "input_reference": ("example-file", open("example-file", "rb")) }
payload = {
    "model": "sora-2",
    "prompt": "Animate this scene: gentle waves lapping, leaves swaying, cinematic camera push-in"
}
headers = {"Authorization": "Bearer <token>"}

response = requests.post(url, data=payload, files=files, headers=headers)

print(response.text)

const form = new FormData();
form.append('model', 'sora-2');
form.append('prompt', 'Animate this scene: gentle waves lapping, leaves swaying, cinematic camera push-in');
form.append('input_reference', '{
  "fileName": "example-file"
}');

const options = {method: 'POST', headers: {Authorization: 'Bearer <token>'}};

options.body = form;

fetch('https://api.apiyi.com/v1/videos', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.apiyi.com/v1/videos",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => "-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"model\"\r\n\r\nsora-2\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"prompt\"\r\n\r\nAnimate this scene: gentle waves lapping, leaves swaying, cinematic camera push-in\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"input_reference\"; filename=\"example-file\"\r\nContent-Type: application/octet-stream\r\n\r\n{\r\n  \"fileName\": \"example-file\"\r\n}\r\n-----011000010111000001101001--",
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: multipart/form-data"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.apiyi.com/v1/videos"

	payload := strings.NewReader("-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"model\"\r\n\r\nsora-2\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"prompt\"\r\n\r\nAnimate this scene: gentle waves lapping, leaves swaying, cinematic camera push-in\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"input_reference\"; filename=\"example-file\"\r\nContent-Type: application/octet-stream\r\n\r\n{\r\n  \"fileName\": \"example-file\"\r\n}\r\n-----011000010111000001101001--")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.apiyi.com/v1/videos")
  .header("Authorization", "Bearer <token>")
  .body("-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"model\"\r\n\r\nsora-2\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"prompt\"\r\n\r\nAnimate this scene: gentle waves lapping, leaves swaying, cinematic camera push-in\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"input_reference\"; filename=\"example-file\"\r\nContent-Type: application/octet-stream\r\n\r\n{\r\n  \"fileName\": \"example-file\"\r\n}\r\n-----011000010111000001101001--")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.apiyi.com/v1/videos")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request.body = "-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"model\"\r\n\r\nsora-2\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"prompt\"\r\n\r\nAnimate this scene: gentle waves lapping, leaves swaying, cinematic camera push-in\r\n-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"input_reference\"; filename=\"example-file\"\r\nContent-Type: application/octet-stream\r\n\r\n{\r\n  \"fileName\": \"example-file\"\r\n}\r\n-----011000010111000001101001--"

response = http.request(request)
puts response.read_body

200

{
  "id": "video_abc123def456",
  "object": "video",
  "model": "sora-2",
  "status": "queued",
  "progress": 0,
  "created_at": 1712697600,
  "completed_at": 1712697900,
  "size": "1280x720",
  "seconds": "8",
  "quality": "standard"
}

The interactive Playground on the right supports live debugging. Set your API Key in the Authorization field (format: Bearer sk-xxx), upload a reference image, enter a prompt, choose model / size / seconds, and send.

Scope: This page covers “generate video from a reference image” — upload one image as the starting frame / visual anchor to animate static visuals. If you don’t need a reference image, use the Text-to-Video endpoint (same path, JSON body).

⚠️ Reference image dimensions must exactly match size

• The uploaded image’s pixel dimensions must equal the size field (e.g. size=1280x720 requires a 1280×720 image)
• Mismatch returns 400: Inpaint image must match the requested width and height
• Pre-crop with ffmpeg / Pillow before upload

Other notes:

• Content-Type must be multipart/form-data (not JSON)
• Only one file is supported; the field name is fixed as input_reference
• Accepted formats: image/jpeg / image/png / image/webp

Code Samples

Python (OpenAI SDK Drop-In)

from openai import OpenAI
import time

client = OpenAI(
    api_key="sk-your-api-key",
    base_url="https://api.apiyi.com/v1"
)

# Step 1: Submit (the OpenAI SDK auto-handles multipart when input_reference is provided)
with open("./reference.png", "rb") as f:
    video = client.videos.create(
        model="sora-2",
        prompt="Animate this scene: gentle waves lapping against the shore, leaves swaying in the breeze",
        seconds="8",
        size="1280x720",
        input_reference=f
    )
print(f"Video ID: {video.id}, status: {video.status}")

# Step 2: Poll
while True:
    video = client.videos.retrieve(video.id)
    print(f"Status: {video.status}, progress: {getattr(video, 'progress', 0)}%")
    if video.status == "completed":
        break
    if video.status == "failed":
        raise RuntimeError(f"Generation failed: {video}")
    time.sleep(15)

# Step 3: Download
client.videos.download_content(video.id).write_to_file("output.mp4")
print("Saved: output.mp4")

Python (Raw requests + multipart)

import requests
import time

API_KEY = "sk-your-api-key"
BASE_URL = "https://api.apiyi.com/v1"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

# Step 1: Multipart upload (image dimensions must equal size)
with open("./reference.png", "rb") as f:
    resp = requests.post(
        f"{BASE_URL}/videos",
        headers=HEADERS,  # Don't manually set Content-Type — requests handles the multipart boundary
        data={
            "model": "sora-2",
            "prompt": "Animate this scene with cinematic camera push-in, soft golden hour lighting",
            "seconds": "8",
            "size": "1280x720"
        },
        files={
            "input_reference": ("reference.png", f, "image/png")
        },
        timeout=60  # Multipart uploads of large images can be slow; use a 60-second timeout
    ).json()
video_id = resp["id"]
print(f"Video ID: {video_id}, status: {resp['status']}")

# Step 2: Poll
deadline = time.time() + 900
while time.time() < deadline:
    status_resp = requests.get(f"{BASE_URL}/videos/{video_id}", headers=HEADERS).json()
    print(f"Status: {status_resp['status']}, progress: {status_resp.get('progress', 0)}%")
    if status_resp["status"] == "completed":
        break
    if status_resp["status"] == "failed":
        raise RuntimeError(f"Generation failed: {status_resp}")
    time.sleep(15)

# Step 3: Download
with requests.get(f"{BASE_URL}/videos/{video_id}/content", headers=HEADERS, stream=True) as r:
    r.raise_for_status()
    with open("output.mp4", "wb") as f:
        for chunk in r.iter_content(chunk_size=8192):
            f.write(chunk)
print("Saved: output.mp4")

cURL

{/* Step 1: Multipart upload + submit */}
curl -X POST "https://api.apiyi.com/v1/videos" \
  -H "Authorization: Bearer sk-your-api-key" \
  -F "model=sora-2" \
  -F "prompt=Animate this scene: gentle waves lapping, leaves swaying, cinematic" \
  -F "seconds=8" \
  -F "size=1280x720" \
  -F "input_reference=@./reference.png;type=image/png"

{/* Step 2: Poll */}
curl -X GET "https://api.apiyi.com/v1/videos/video_abc123" \
  -H "Authorization: Bearer sk-your-api-key"

{/* Step 3: Download */}
curl -X GET "https://api.apiyi.com/v1/videos/video_abc123/content" \
  -H "Authorization: Bearer sk-your-api-key" \
  -o output.mp4

Node.js (fetch + FormData)

import fs from 'node:fs';
import { fileFromPath } from 'formdata-node/file-from-path';
import { FormData } from 'formdata-node';

const API_KEY = 'sk-your-api-key';
const BASE_URL = 'https://api.apiyi.com/v1';

// Step 1: Multipart upload
const form = new FormData();
form.set('model', 'sora-2');
form.set('prompt', 'Animate this scene with cinematic camera push-in, soft lighting');
form.set('seconds', '8');
form.set('size', '1280x720');
form.set('input_reference', await fileFromPath('./reference.png'));

const submitResp = await fetch(`${BASE_URL}/videos`, {
    method: 'POST',
    headers: { 'Authorization': `Bearer ${API_KEY}` },  // Don't manually set Content-Type
    body: form
});
const { id: videoId } = await submitResp.json();
console.log(`Video ID: ${videoId}`);

// Step 2: Poll
let status = 'queued';
while (status !== 'completed' && status !== 'failed') {
    await new Promise(r => setTimeout(r, 15000));
    const data = await (await fetch(`${BASE_URL}/videos/${videoId}`, {
        headers: { 'Authorization': `Bearer ${API_KEY}` }
    })).json();
    status = data.status;
    console.log(`Status: ${status}, progress: ${data.progress ?? 0}%`);
}

if (status === 'failed') throw new Error('Generation failed');

// Step 3: Download
const contentResp = await fetch(`${BASE_URL}/videos/${videoId}/content`, {
    headers: { 'Authorization': `Bearer ${API_KEY}` }
});
fs.writeFileSync('output.mp4', Buffer.from(await contentResp.arrayBuffer()));
console.log('Saved: output.mp4');

Browser JavaScript

{/* Demo only; route through your backend in production to avoid leaking the API key. */}
const fileInput = document.getElementById('refImage');  // <input type="file" />
const file = fileInput.files[0];

const form = new FormData();
form.append('model', 'sora-2');
form.append('prompt', 'Animate this scene, gentle motion');
form.append('seconds', '4');
form.append('size', '1280x720');
form.append('input_reference', file);

const submitResp = await fetch('https://api.apiyi.com/v1/videos', {
    method: 'POST',
    headers: { 'Authorization': 'Bearer sk-your-api-key' },
    body: form
});
const { id } = await submitResp.json();
console.log('Video ID:', id);

{/* After polling completes, route the video URL through a backend proxy to avoid downloading large files in the browser. */}

Parameters Quick Reference

Parameter	Type	Required	Default	Description
model	string	Yes	—	sora-2 (720p only) or sora-2-pro (720p / 1024p / 1080p tiers)
prompt	string	Yes	—	Video description; focus on how the static image should animate (camera motion, object motion, lighting changes)
seconds	string	No	"4"	Duration as string enum: "4" / "8" / "12"
size	string	No	720x1280	Output resolution, must equal the input_reference image dimensions exactly
input_reference	file	Yes	—	Reference image file: image/jpeg / image/png / image/webp, dimensions must equal size

Detailed parameter constraints, allowed values, and examples are visible in the right-hand Playground. input_reference must be uploaded via multipart — URLs and base64 are not accepted.

Reference Image Preparation

1. Pick the target resolution

   Choose size first based on your use case: portrait 720x1280, landscape 1280x720, Pro 1080p landscape 1920x1080, etc.

2. Crop locally to exact pixels

   Use Pillow / ffmpeg to crop the image to the target dimensions:

   from PIL import Image
   img = Image.open("source.jpg")
   img = img.resize((1280, 720), Image.LANCZOS)  # Or crop first then resize to preserve aspect ratio
   img.save("reference.png")
   

   Or one-line ffmpeg:

   ffmpeg -i source.jpg -vf "scale=1280:720" reference.png
   
3. Pick the right format

   Prefer PNG (lossless, ideal for illustrations / screenshots), JPEG for photos to save bytes, WebP if you need transparency.

4. Focus the prompt on "motion" not "appearance"

   The reference image already defines the visuals. The prompt should focus on how it should animate: camera push/pull, object motion, lighting changes, character expressions, etc. Example: "Camera slowly pushes in, leaves gently swaying, sunlight flickering through branches".

Response Format

The response shape is identical to Text-to-Video: submit returns id + status: "queued", polling reports progress, completion downloads via /v1/videos/{id}/content as MP4.

{
  "id": "video_abc123def456",
  "object": "video",
  "model": "sora-2",
  "status": "queued",
  "progress": 0,
  "created_at": 1712697600,
  "size": "1280x720",
  "seconds": "8",
  "quality": "standard"
}

⚠️ Common 400 errors

• Inpaint image must match the requested width and height — reference image dimensions don’t match size. Most common. Validate dimensions client-side before upload
• Invalid file format — uploaded file is not jpeg / png / webp, or is corrupted
• Missing required parameter: input_reference — multipart field name is wrong (must be input_reference, not image or reference)
• seconds must be one of "4", "8", "12" — passed integer 4 instead of string "4"

Image-to-video and text-to-video have the same per-second pricing (billed by seconds); uploading a reference image does not cost extra. See the pricing table.

Authorizations

Authorization · string · header · required

API Key from the APIYI console (must use Sora2官转 group + usage-based billing)

Body

multipart/form-data

model · enum<string> · default: sora-2 · required

Model ID. sora-2 supports 720p only; sora-2-pro supports 720p / 1024p / 1080p

Available options: sora-2, sora-2-pro

prompt · string · required

Video generation prompt. Focus on how the image should animate: camera motion, object motion, lighting changes

Example:

"Animate this scene: gentle waves lapping, leaves swaying, cinematic camera push-in"

input_reference · file · required

Reference image file used as the video's starting frame / visual anchor.

• Accepted formats: image/jpeg / image/png / image/webp
• Dimensions must equal size, otherwise you get Inpaint image must match the requested width and height
• Only one file is supported; field name is fixed as input_reference

seconds · enum<string> · default: 4

Video duration as string enum: "4" / "8" / "12"

Available options: 4, 8, 12

size · enum<string> · default: 720x1280

Output resolution. Must exactly match the input_reference image dimensions:

• sora-2 (720p only): 720x1280 / 1280x720
• sora-2-pro additionally: 1024x1792 / 1792x1024 / 1080x1920 / 1920x1080

Available options: 720x1280, 1280x720, 1024x1792, 1792x1024, 1080x1920, 1920x1080

Response

200

application/json

Task submitted, returns video_id with queued status

id · string

Task ID for subsequent polling and download

Example:

"video_abc123def456"

object · string

Object type, fixed video

Example:

"video"

model · string

Model ID used for this task

Example:

"sora-2"

status · enum<string>

Task status:

• queued — submitted, waiting in queue
• in_progress — generating
• completed — done, ready to download (/v1/videos/{id}/content)
• failed — failed (not billed), safe to retry

Available options: queued, in_progress, completed, failed

Example:

"queued"

progress · integer

Generation progress percentage (0–100), not strictly linear

Example:

0

created_at · integer

Task creation Unix timestamp (seconds)

Example:

1712697600

completed_at · integer

Task completion Unix timestamp (seconds), present only on completed status

Example:

1712697900

size · string

Actual output resolution (matches the requested size)

Example:

"1280x720"

seconds · string

Actual duration generated (matches the requested seconds)

Example:

"8"

quality · string

Quality tier (standard for sora-2, high for sora-2-pro)

Example:

"standard"