import gradio_client
from gradio_client import Client, file
from urllib.parse import quote


import numpy as np
import gradio as gr
def generate_img(prompt):
    client = Client("ameerazam08/SDXS-GPU-Demo")
    client.view_api()
    result = client.predict(
    		prompt=prompt,
    		api_name="/generate_image"
    )
    return result

def pollinations_url_seedless(a, width=512, height=512):
        urlprompt=quote(str(a))
        url=f"https://image.pollinations.ai/prompt/{urlprompt}?width={width}&height={height}"
        return url

def interrogate(img):
    from gradio_client import Client
    # client = Client("fffiloni/CLIP-Interrogator-2")
    # client.view_api()
    client = Client("https://pharmapsychotic-clip-interrogator.hf.space/")
    client.view_api()
    result = client.predict(
    				img,	# str (filepath or URL to image)	
    				"ViT-L (best for Stable Diffusion 1.*)",	# str (Option from: ['ViT-L (best for Stable Diffusion 1.*)'])							
    				"best",	# str in 'Mode' Radio component
    				fn_index=3
    )
    return result
def rountrip(img):
    prompt=interrogate(img)
    print(prompt)
    url=pollinations_url_seedless(prompt)
    return generate_img(prompt),prompt

demo = gr.Interface(rountrip, gr.Image(type= 'filepath'),[gr.Image(type= 'filepath'),"textbox"])
demo.launch()