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Step 1: Upload or Reference an Image

First, you need to provide the source image. You can either:
  • Upload an image file as a base64 data URI.
  • Provide a publicly accessible image URL.
import { readFileSync } from "node:fs";

// Option 1: Using a base64 data URI
const imageBuffer = readFileSync("input_image.jpg");
const imageDataUri = `data:image/jpeg;base64,${imageBuffer.toString("base64")}`;

// Option 2: Using image URL
const imageUrl = "https://s.krea.ai/logo-icon-black.jpg";
import requests
import base64

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

# Option 1: Using a base64 data URI
with open("input_image.jpg", "rb") as image_file:
    image_data_uri = f"data:image/jpeg;base64,{base64.b64encode(image_file.read()).decode('utf-8')}"

# Option 2: Using image URL
image_url = "https://s.krea.ai/logo-icon-black.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 Image

Make a POST request to the appropriate endpoint with your image and 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.image("google/nano-banana-pro", {
  image_urls: [imageDataUri],
  prompt: "Turn this logo into an aesthetic rug. Product Photography style, with an aura that would make me want it in my own living room."
});

console.log(`Job ID: ${job.job_id}`);
IMAGE_DATA_URI="data:image/jpeg;base64,$(base64 < ./input_image.jpg | tr -d '\n')"

curl -X POST https://api.krea.ai/generate/image/google/nano-banana-pro \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "image_urls": ["'"$IMAGE_DATA_URI"'"],
    "prompt": "Turn this logo into an aesthetic rug. Product Photography style, with an aura that would make me want it in my own living room."
  }'
response = requests.post(
    f"{API_BASE}/generate/image/google/nano-banana-pro",
    headers={
        "Authorization": f"Bearer {API_TOKEN}",
        "Content-Type": "application/json"
    },
    json={
        "image_urls": [image_data_uri],
        "prompt": "Turn this logo into an aesthetic rug. Product Photography style, with an aura that would make me want it in my own living room.",
    }
)

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

import (
    "bytes"
    "encoding/base64"
    "encoding/json"
    "fmt"
    "net/http"
    "os"
)

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

    imageBytes, _ := os.ReadFile("input_image.jpg")
    imageDataURI := "data:image/jpeg;base64," + base64.StdEncoding.EncodeToString(imageBytes)

    payload := map[string]interface{}{
        "image_urls": []interface{}{imageDataURI},
        "prompt": "Turn this logo into an aesthetic rug. Product Photography style, with an aura that would make me want it in my own living room.",
    }

    jsonData, _ := json.Marshal(payload)
    req, _ := http.NewRequest("POST", apiBase+"/generate/image/google/nano-banana-pro", 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"])
}
Example Response
{
  "created_at":"2026-02-13T02:20:58.265Z",
  "completed_at":null,
  "job_id":"757a315b-b3ed-457b-b1ba-cff5e140cfd4",
  "status":"processing",
  "type":"externalImage",
  "result":{}
}

Step 3: Poll for Results

Image generation is asynchronous. You’ll receive a job ID immediately, then poll for results until the image is ready. Poll /jobs/{job_id} every 2 seconds until the job completes.
// npm install @krea-ai/sdk
import { Krea } from "@krea-ai/sdk";

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

async function waitForJob(jobId) {
  const completed = await krea.jobs.wait(jobId, { intervalMs: 2000 });
  return completed.result.urls[0];
}

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

def wait_for_job(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']}")

        print(f"Status: {job['status']}")
        time.sleep(2)

image_url = wait_for_job(job["job_id"])
print(f"Image ready: {image_url}")
func waitForJob(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"])
        }

        fmt.Printf("Status: %s\n", job["status"])
        time.Sleep(2 * time.Second)
    }
}
Example Completed Response

{
  "created_at":"2026-02-13T02:20:58.265Z",
  "completed_at":"2026-02-13T02:21:21.948Z",
  "job_id":"757a315b-b3ed-457b-b1ba-cff5e140cfd4",
  "status":"completed",
  "type":"externalImage",
  "result": {
    "urls": [
      "https://app-uploads.krea.ai/public/757a315b-b3ed-457b-b1ba-cff5e140cfd4-image.png"
    ]
  }
}
Webhooks available!Set up webhooks to receive notifications when jobs complete. See the Webhooks guide to get started.