app.py

import gradio as gr
import requests
from io import BytesIO
from PIL import Image
inport os
# Load Stable Diffusion model
HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None
model = gr.load("models/stabilityai/stable-diffusion-3.5-large", hf_token=HF_TOKEN)

# Chevereto API details
CHEVERETO_API_URL = os.environ.get("api_url")  # Replace with your Chevereto API endpoint
CHEVERETO_API_KEY =  os.environ.get("API_KEY")  # Replace with your API key
CHEVERETO_ALBUM_ID =  os.environ.get("ALBUM_ID")  # Replace with the album ID where you want to store images

# Upload image to Chevereto
def upload_to_chevereto(image: Image.Image) -> str:
    # Convert image to bytes
    buffered = BytesIO()
    image.save(buffered, format="PNG")
    files = {"source": buffered.getvalue()}  # Convert to binary for upload
    
    # Set API parameters
    data = {
        "key": CHEVERETO_API_KEY,
        "format": "json",
        "album": CHEVERETO_ALBUM_ID  # Specify album ID
    }

    # Upload request
    response = requests.post(CHEVERETO_API_URL, files=files, data=data)

    if response.status_code == 200:
        return response.json()["image"]["url"]  # Return public URL of uploaded image
    return "Error uploading image"

# Generate and upload the image
def generate_image_and_upload(prompt: str) -> str:
    img = model.predict(prompt)[0]  # Get generated image
    return upload_to_chevereto(img)  # Upload and return the URL

# Define Gradio API returning the Chevereto public URL
iface = gr.Interface(fn=generate_image_and_upload, inputs="text", outputs="text")

iface.launch()