Melatih Gaya Kustom

import requests
import os
from dotenv import load_dotenv
import mimetypes

load_dotenv()

API_BASE = "https://api.krea.ai"
API_TOKEN = os.getenv("API_TOKEN")

image_dir = "training_images"
uploaded_urls = []

for filename in os.listdir(image_dir):
    if filename.lower().endswith(('.jpg', '.jpeg', '.png', '.webp')):
        filepath = os.path.join(image_dir, filename)
        mime_type, _ = mimetypes.guess_type(filepath)

        with open(filepath, 'rb') as f:
            response = requests.post(
                f"{API_BASE}/assets",
                headers={"Authorization": f"Bearer {API_TOKEN}"},
                files={"file": (filename, f, mime_type)},
                data={"description": f"Training image: {filename}"}
            )

        if response.ok:
            data = response.json()
            uploaded_urls.append(data["image_url"])
            print(f"Uploaded: {filename}")
        else:
            print(f"Failed: {filename}")

print(f"\nUploaded {len(uploaded_urls)} images")

import requests
import os
from dotenv import load_dotenv

load_dotenv()

API_BASE = "https://api.krea.ai"
API_TOKEN = os.getenv("API_TOKEN")

# Training URLs from the upload step
urls = [
    "https://krea.ai/assets/img1.jpg",
    "https://krea.ai/assets/img2.jpg",
    "https://krea.ai/assets/img3.jpg",
    # ... more images
]

response = requests.post(
    f"{API_BASE}/styles/train",
    headers={
        "Authorization": f"Bearer {API_TOKEN}",
        "Content-Type": "application/json"
    },
    json={
        "name": "Ukiyo-E Style",
        "urls": urls,
        "model": "flux_dev",
        "type": "Style",
        "max_train_steps": 500
    }
)

response.raise_for_status()
job = response.json()
print(f"Training started! Job ID: {job['job_id']}")

import requests
import time
import os
from dotenv import load_dotenv

load_dotenv()

API_BASE = "https://api.krea.ai"
API_TOKEN = os.getenv("API_TOKEN")
job_id = "your-job-id"

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

    print(f"Status: {status}")

    if status == "completed":
        style_id = job["result"]["style_id"]
        print(f"Training complete! Style ID: {style_id}")
        break
    elif status in ["failed", "cancelled"]:
        print(f"Training {status}")
        break

    time.sleep(30)

import requests
import time
import os
from dotenv import load_dotenv

load_dotenv()

API_BASE = "https://api.krea.ai"
API_TOKEN = os.getenv("API_TOKEN")
STYLE_ID = "w29t6pvy0"

response = requests.post(
    f"{API_BASE}/generate/image/krea/krea-2/medium",
    headers={
        "Authorization": f"Bearer {API_TOKEN}",
        "Content-Type": "application/json"
    },
    json={
        "prompt": "An abstract, colorful, surreal composition of symmetry and balance. Swirling colors, imagery of trees and coalescing patterns converge. The lantern of light and death. It is as if the world was at once dark, and yet again lit.",
        "aspect_ratio": "1:1",
        "resolution": "1K",
        "styles": [
            {
                "id": STYLE_ID,
                "strength": 0.95
            }
        ]
    }
)

job = response.json()
job_id = job["job_id"]
print(f"Generation started! Job ID: {job_id}")

# Poll for completion
while True:
    check = requests.get(
        f"{API_BASE}/jobs/{job_id}",
        headers={"Authorization": f"Bearer {API_TOKEN}"}
    )
    status_data = check.json()

    if status_data["status"] == "completed":
        image_url = status_data["result"]["urls"][0]
        print(f"Image ready: {image_url}")
        break
    elif status_data["status"] == "failed":
        print("Generation failed")
        break

    time.sleep(2)