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import gradio as gr
import requests
import os
from PIL import Image
import os
# Load environment variables
CHEVERETO_API_URL = os.environ.get("API_URL") # Your Chevereto API endpoint
CHEVERETO_API_KEY = os.environ.get("API_KEY") # Your Chevereto API Key
CHEVERETO_ALBUM_ID = os.environ.get("ALBUM_ID") # Your Album ID
# Load the Gradio model
model = gr.Interface.load("models/stabilityai/stable-diffusion-3.5-large")
def upload_to_chevereto(img_path: str) -> str:
"""Uploads an image to Chevereto and returns the public image URL."""
with open(img_path, "rb") as image_file:
files = {"source": image_file}
data = {
"key": CHEVERETO_API_KEY,
"format": "json",
"album": CHEVERETO_ALBUM_ID # Include the album ID
}
response = requests.post(CHEVERETO_API_URL, files=files, data=data)
if response.status_code == 200:
return response.json().get("image", {}).get("url") # Return the image URL
else:
return f"Error uploading image: {response.text}" # Debugging error message
def generate_image_and_upload(prompt: str) -> str:
"""Generates an image using the AI model and uploads it to Chevereto."""
img = model(prompt) # Generate image
if isinstance(img, list):
img = img[0] # If Gradio returns a list, get the first image
if isinstance(img, Image.Image):
img_path = "generated_image.png"
img.save(img_path, format="PNG") # Save locally before uploading
return upload_to_chevereto(img_path) # Upload and return URL
else:
return "Error: Model did not return a valid image"
# Define Gradio API returning the Chevereto public URL
iface = gr.Interface(fn=generate_image_and_upload, inputs="text", outputs="text")
iface.launch()
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