import requests
import gradio as gr
from PIL import Image
import base64

def t2i(text):
    prompt_url = f"https://aadarsh-text-to-image-mymvubi2mq-el.a.run.app/t2i/{text}"
    img_url = requests.get(prompt_url).json()["url"]
    response = requests.get(img_url)
    if response.status_code:
        fp = open('image.png', 'wb')
        fp.write(response.content)
        fp.close()

    image = Image.open('image.png')
    return image



allow_flagging = "never"

title = f"""
    <h2 style="background-image: linear-gradient(to right, #3A5FCD, #87CEFA); -webkit-background-clip: text;
        -webkit-text-fill-color: transparent; text-align: center;">
        Text to Image Generator
    </h2>
"""

description = f"""
<div style="display: flex; align-items: center; justify-content: center; flex-direction: column;">
    <p style="font-size: 18px; color: #4AAAFF; text-align: center;">
        Turn words into captivating visuals effortlessly within minutes.
    </p>
    <div style="display: flex; align-items: center; margin-bottom: 0px;">
        <img src='data:image/jpeg;base64,{image_base64}' width='50' height='30' style="margin-right: 5px;"/>
        <p style="font-size: 14px; color: #555;">
            Disclaimer: The purpose of this application is solely for demonstration. 1001epochs does not claim ownership for the results Contact: contact@1001epochs.co.uk for full solution.
        </p>
    </div>
</div>
"""
iface = gr.Interface(fn=t2i, inputs="text", outputs=[gr.Image(label="Generated Image")], title=title, description=description).launch()
iface.launch(share=True)