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Image-to-video generation combines your input image with motion generation. The output maintains visual consistency with your source image while adding realistic motion.

Step 1: Prepare Your Image

First, you need to provide the source image. You can either upload a file, reference a URL or provide a base64 data URI.
// npm install @krea-ai/sdk
import { openAsBlob } from "node:fs";
import { Krea } from "@krea-ai/sdk";

const krea = new Krea({ apiKey: process.env.KREA_API_KEY });

// Option 1: Upload a local file and use the hosted asset URL
const file = await openAsBlob("./input-image.jpg", { type: "image/jpeg" });
const asset = await krea.assets.upload(file, {
  description: "Input image",
});
const imageUrl = asset.image_url;

// Option 2: Using image URL
// const imageUrl = "https://example.com/input-image.jpg";
import requests

API_BASE = "https://api.krea.ai"
API_TOKEN = "YOUR_API_TOKEN"

# Option 1: Upload a local file and use the hosted asset URL
with open("input-image.jpg", "rb") as image_file:
    upload = requests.post(
        f"{API_BASE}/assets",
        headers={"Authorization": f"Bearer {API_TOKEN}"},
        files={"file": ("input-image.jpg", image_file, "image/jpeg")},
        data={"description": "Input image"},
    )
upload.raise_for_status()
image_url = upload.json()["image_url"]

# Option 2: Using image URL
# image_url = "https://example.com/input-image.jpg"
Replace with your API TokenTo replace the YOUR_API_TOKEN placeholder in the above examples, you’ll need to generate an API token in krea.ai/settings/api-tokens. Follow the instructions on the API Keys & Billing page if you need help.

Step 2: Generate the Video

Make a POST request to /generate/video/kling/kling-2.5 with your image and motion parameters.
// npm install @krea-ai/sdk
import { Krea } from "@krea-ai/sdk";

const krea = new Krea({ apiKey: process.env.KREA_API_KEY });

const job = await krea.video("kling/kling-2.5", {
  start_image: imageUrl,
  prompt: "gentle camera pan from left to right, subtle depth",
  duration: 5,
  aspect_ratio: "16:9"
});

console.log(`Job ID: ${job.job_id}`);
curl -X POST https://api.krea.ai/generate/video/kling/kling-2.5 \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "start_image": "https://example.com/input-image.jpg",
    "prompt": "gentle camera pan from left to right, subtle depth",
    "duration": 5,
    "aspect_ratio": "16:9"
  }'
response = requests.post(
    f"{API_BASE}/generate/video/kling/kling-2.5",
    headers={
        "Authorization": f"Bearer {API_TOKEN}",
        "Content-Type": "application/json"
    },
    json={
        "start_image": image_url,
        "prompt": "gentle camera pan from left to right, subtle depth",
        "duration": 5,
        "aspect_ratio": "16:9"
    }
)

job = response.json()
print(f"Job ID: {job['job_id']}")
package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "net/http"
)

func main() {
    apiBase := "https://api.krea.ai"
    apiToken := "YOUR_API_TOKEN"

    payload := map[string]interface{}{
        "start_image": "https://example.com/input-image.jpg",
        "prompt": "gentle camera pan from left to right, subtle depth",
        "duration": 5,
        "aspect_ratio": "16:9",
    }

    jsonData, _ := json.Marshal(payload)
    req, _ := http.NewRequest("POST", apiBase+"/generate/video/kling/kling-2.5", bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer "+apiToken)
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, _ := client.Do(req)
    defer resp.Body.Close()

    var job map[string]interface{}
    json.NewDecoder(resp.Body).Decode(&job)
    fmt.Printf("Job ID: %s\n", job["job_id"])
}
Replace with your API TokenTo replace the YOUR_API_TOKEN placeholder in the above examples, you’ll need to generate an API token in krea.ai/settings/api-tokens. Follow the instructions on the API Keys & Billing page if you need help.
Example Response
{
  "job_id": "550e8400-e29b-41d4-a716-446655440000",
  "status": "queued",
  "created_at": "2025-01-15T10:30:00.000Z",
  "estimated_time": "60-120 seconds"
}

Step 3: Poll for Results

Poll /jobs/{job_id} every 5 seconds to check the video generation progress.
// npm install @krea-ai/sdk
import { Krea } from "@krea-ai/sdk";

const krea = new Krea({ apiKey: process.env.KREA_API_KEY });

async function waitForVideo(jobId) {
  const completed = await krea.jobs.wait(jobId, { intervalMs: 5000 });
  return completed.result.urls[0];
}

const videoUrl = await waitForVideo(job.job_id);
console.log(`Video ready: ${videoUrl}`);
curl -X GET https://api.krea.ai/jobs/YOUR_JOB_ID \
  -H "Authorization: Bearer YOUR_API_TOKEN"
import time

def wait_for_video(job_id):
    while True:
        response = requests.get(
            f"{API_BASE}/jobs/{job_id}",
            headers={"Authorization": f"Bearer {API_TOKEN}"}
        )
        job = response.json()

        if job["status"] == "completed":
            return job["result"]["urls"][0]
        if job["status"] in ("failed", "cancelled"):
            raise Exception(f"Job failed: {job['status']}")

        # Show progress if available
        if "progress" in job:
            print(f"Progress: {job['progress']}%")
        else:
            print(f"Status: {job['status']}")

        time.sleep(5)

video_url = wait_for_video(job["job_id"])
print(f"Video ready: {video_url}")
func waitForVideo(jobID string) (string, error) {
    for {
        req, _ := http.NewRequest("GET", apiBase+"/jobs/"+jobID, nil)
        req.Header.Set("Authorization", "Bearer "+apiToken)

        resp, _ := client.Do(req)
        var job map[string]interface{}
        json.NewDecoder(resp.Body).Decode(&job)
        resp.Body.Close()

        switch job["status"] {
        case "completed":
            result := job["result"].(map[string]interface{})
            urls := result["urls"].([]interface{})
            return urls[0].(string), nil
        case "failed", "cancelled":
            return "", fmt.Errorf("job failed: %s", job["status"])
        }

        // Show progress if available
        if progress, ok := job["progress"]; ok {
            fmt.Printf("Progress: %.0f%%\n", progress)
        } else {
            fmt.Printf("Status: %s\n", job["status"])
        }

        time.Sleep(5 * time.Second)
    }
}
Example Completed Response
{
  "job_id": "550e8400-e29b-41d4-a716-446655440000",
  "status": "completed",
  "created_at": "2025-01-15T10:30:00.000Z",
  "completed_at": "2025-01-15T10:31:45.000Z",
  "result": {
    "urls": ["https://gen.krea.ai/videos/your-video.mp4"]
  }
}
Webhooks available!Set up webhooks to receive notifications when jobs complete. See the Webhooks guide to get started.

Common Parameters

For a list of detailed parameters for all models, see the Model APIs page.
ParameterTypeDescription
start_imagestringURL of the source image
promptstringDescription of desired motion and camera movement
durationnumberVideo length in seconds. Supported values depend on the model.
aspect_ratiostringVideo aspect ratio, such as 16:9, 9:16, or 1:1
end_imagestringOptional ending frame URL for supported models
modestringOptional quality mode for models that expose one
Motion Prompt Tips:
  • Describe camera movement (pan, zoom, dolly, tilt)
  • Specify motion direction and speed
  • Mention depth and parallax effects
  • Use restrained camera language for subtle animations
  • Use stronger action verbs for dramatic effects