app.py

import gradio as gr
import requests
import io
import os
from PIL import Image

API_URL = "https://api-inference.huggingface.co/models/Kvikontent/kviimager2.0"
api_key = os.environ.get('API_KEY')
headers = {"Authorization": f"Bearer {api_key}"}

def query(payload):
    response = requests.post(API_URL, headers=headers, json=payload)
    return response.content

def generate_image_from_prompt(prompt_text):
    image_bytes = query({"inputs": prompt_text})
    generated_image = Image.open(io.BytesIO(image_bytes))
    return generated_image

title = "KVIImager 2.0 Demo 🎨"
description = "This app uses Hugging Face AI model to generate an image based on the provided text prompt 🖼️."

input_prompt = gr.inputs.Textbox(label="Enter Prompt 📝", placeholder="E.g. 'A peaceful garden with a small cottage'")
output_generated_image = gr.outputs.Image(label="Generated Image")

with gr.Blocks(theme=gr.theme.Soft()) as app:
    caption = "Generate Image"
    iface = gr.Interface(
        generate_image_from_prompt,
        inputs=input_prompt, 
        outputs=output_generated_image, 
        title=title,
        description=description
    )
    iface.launch(share=True, inline=True)