Video

Video models usually run as asynchronous tasks and may bill by seconds, resolution, or clip. Start with duration=5 or shorter, n=1, and a base resolution to verify model choice, parameters, and callback handling.

`POST /v1/video/generations`

Async video generation. Submit a prompt to receive a task ID, then poll task status for the final video. Use /v1/models and the model detail page for text-to-video, image-to-video, reference-image, or editing parameters.

Image-to-video, keyframe, and video-edit routes are most reliable with data:image/...;base64,... image inputs. Plain image or video URLs must be directly downloadable by the execution provider; avoid signed-in, blocked, very small, or private resources.

Use /v1/models model details as the source of truth; supported input modes, resolutions, and durations can differ by video model.

Parameters

Parameter	Type	Required	Description
model	string	Yes	Choose a video generation model from /v1/models
prompt	string	Yes*	Video description; can be generated from an existing prompt template via template_id
template_id	string	No	Existing prompt template ID, use with variables; unknown templates return 404
variables	object	No	Prompt template variables; values must be strings
image / image_url	string	No	Starting frame as base64 or URL
n	integer	No	1 - 4
size	string	No	832x480, 480x832, 624x624, 1280x720, 720x1280, 960x960, 1088x832, 832x1088, 1920x1080, 1080x1920, 1440x1440, 1632x1248, 1248x1632
duration	integer	No	1 - 60 seconds; use 5 seconds or shorter for first probes
fps	integer	No	1 - 60
negative_prompt	string	No	Negative prompt, max 1024 chars
seed	integer	No	Random seed for reproducible generation
webhook_url	string	No	Callback URL on completion (https only)
tags	array	No	Array of tag strings

cURL

curl https://test.sealink.io/v1/video/generations \
  -H "Authorization: Bearer $SEALINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kling-v3-omni",
    "prompt": "A serene lake at sunset, camera slowly panning across the water",
    "size": "1280x720",
    "duration": 5,
    "n": 1
  }'

Python

import os
from openai import OpenAI
import requests

# For async video generation, use the raw HTTP client
res = requests.post(
    "https://test.sealink.io/v1/video/generations",
    headers={"Authorization": f"Bearer {os.environ['SEALINK_API_KEY']}"},
    json={
        "model": "kling-v3-omni",
        "prompt": "A serene lake at sunset, camera slowly panning across the water",
        "size": "1280x720",
        "duration": 5,
        "n": 1,
    },
)
task = res.json()
print(f"Task ID: {task['id']}")

cURL - Image-to-video

IMG_B64="$(base64 -w0 first-frame.png)"
curl https://test.sealink.io/v1/video/generations \
  -H "Authorization: Bearer $SEALINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "<image-to-video-model-from-/v1/models>",
    "prompt": "A tiny product photo turning slowly on a clean table",
    "image_url": "data:image/png;base64,'"$IMG_B64"'",
    "size": "832x480",
    "duration": 5,
    "n": 1
  }'

Python - Image-to-video

import os
import requests

res = requests.post(
    "https://test.sealink.io/v1/video/generations",
    headers={"Authorization": f"Bearer {os.environ['SEALINK_API_KEY']}"},
    json={
        "model": "<image-to-video-model-from-/v1/models>",
        "prompt": "A tiny product photo turning slowly on a clean table",
        "image_url": "https://raw.githubusercontent.com/mathiasbynens/small/master/jpeg.jpg",
        "size": "832x480",
        "duration": 3,
        "n": 1,
    },
)
task = res.json()
print(f"Task ID: {task['id']}")

cURL - Keyframe video

FIRST_B64="$(base64 -w0 first-frame.png)"
LAST_B64="$(base64 -w0 last-frame.png)"
curl https://test.sealink.io/v1/video/generations \
  -H "Authorization: Bearer $SEALINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "<keyframe-video-model-from-/v1/models>",
    "prompt": "Smoothly move from the first frame to the last frame",
    "image_url": "data:image/png;base64,'"$FIRST_B64"'",
    "last_image_url": "data:image/png;base64,'"$LAST_B64"'",
    "size": "832x480",
    "duration": 5,
    "n": 1
  }'

`POST /v1/video/edits`

Video editing. Edit existing videos using prompts, including background replacement and style transfer. Animate-style edits usually require both a video input and a reference image, use /v1/video/edits, and human-body animation inputs should contain exactly one clearly visible human body.

Parameters

Parameter	Type	Required	Description
model	string	Yes	Choose a video editing model from /v1/models
video	string	Yes	Source video as base64 or URL
prompt	string	Yes	Edit instruction description
negative_prompt	string	No	Negative prompt
image / image_url	string	No	Reference image base64 or URL
reference_image_url / reference_url	string	No	Reference image URL aliases
resolution	string	No	Same as video size enum
duration	integer	No	1 - 60 seconds
seed	integer	No	Random seed
prompt_extend	boolean	No	Enable prompt expansion
watermark / check_image	boolean	No	Provider watermark and image validation toggles

cURL

curl https://test.sealink.io/v1/video/edits \
  -H "Authorization: Bearer $SEALINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kling-v3-omni",
    "video": "https://example.com/input-video.mp4",
    "prompt": "Change the background to a beach sunset",
    "resolution": "1280x720",
    "duration": 5
  }'

Python

import os
import requests

res = requests.post(
    "https://test.sealink.io/v1/video/edits",
    headers={"Authorization": f"Bearer {os.environ['SEALINK_API_KEY']}"},
    json={
        "model": "kling-v3-omni",
        "video": "https://example.com/input-video.mp4",
        "prompt": "Change the background to a beach sunset",
        "resolution": "1280x720",
        "duration": 5,
    },
)
task = res.json()
print(f"Task ID: {task['id']}")

cURL - Animate

IMG_B64="$(base64 -w0 character.png)"
curl https://test.sealink.io/v1/video/edits \
  -H "Authorization: Bearer $SEALINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "<video-animate-model-from-/v1/models>",
    "prompt": "Make the subject wave gently",
    "image_url": "data:image/png;base64,'"$IMG_B64"'",
    "video_url": "https://example.com/single-person.mp4",
    "size": "832x480",
    "duration": 5,
    "n": 1
  }'

`GET /v1/tasks/{task_id}`

Poll async task status. Completed video tasks return data or upstream_response and settle usage at terminal state.

Status values: pending | running | completed | failed. Async routes with cancellation support can use DELETE /v1/tasks/{task_id} to release the pre-authorization; tasks without upstream cancellation return 501. Do not keep the submit request open while the video renders.

cURL

# Poll task status
curl https://test.sealink.io/v1/tasks/task_abc123 \
  -H "Authorization: Bearer $SEALINK_API_KEY"

cURL - Cancel

# Cancel a running async task when the route supports cancellation
curl -X DELETE https://test.sealink.io/v1/tasks/task_abc123 \
  -H "Authorization: Bearer $SEALINK_API_KEY"

Python — Poll Loop

# Poll until complete
import os
import requests
import time

task_id = "task_abc123"
while True:
    res = requests.get(
        "https://test.sealink.io/v1/tasks/" + task_id,
        headers={"Authorization": f"Bearer {os.environ['SEALINK_API_KEY']}"},
    )
    task = res.json()
    if task["status"] in ("completed", "failed"):
        print(task["status"], task.get("data") or task.get("upstream_response"))
        break
    time.sleep(5)

Node.js — Poll Loop

const taskId = "task_abc123";

async function poll() {
  while (true) {
    const res = await fetch(
      `https://test.sealink.io/v1/tasks/${taskId}`,
      { headers: { Authorization: `Bearer ${process.env.SEALINK_API_KEY}` } }
    );
    const task = await res.json();
    if (task.status === "completed" || task.status === "failed") {
      console.log(task.status, task.data ?? task.upstream_response);
      break;
    }
    await new Promise(r => setTimeout(r, 5000));
  }
}
poll();