import gradio as gr
import numpy as np
import random

import tenacity


import requests
from urllib.parse import quote
from PIL import Image

from io import BytesIO

MAX_SEED = np.iinfo(np.int32).max
MAX_IMAGE_SIZE = 1024


models_list=['flux', 'turbo', 'gptimage']
try:
    models_list=requests.get('https://image.pollinations.ai/models',timeout=2).json()
except:
    pass


    
@tenacity.retry(stop=tenacity.stop_after_attempt(3)|tenacity.stop_after_delay(120),
                wait=tenacity.wait_exponential(multiplier=2, min=10, max=120)
               )
def infer(
    prompt,
    
    seed,
    randomize_seed,
    width,
    height,
            # Enhancement
    enhance=False,            # Auto-enhance prompt (default: False)
    

    image=None,              # Input image URL for img2img
    
    # Privacy
    private=False,           # Private generation (default: False)
    nologo=False,            # Remove watermark (default: False)
    nofeed=False,            # Don't add to public feed (default: False)
    model="flux"
 
    

):
    """
    calling the pollinations.ai image generator
        Args: 
            prompt: 	 	The description of the image (required) 	- 	"a fluffy dog in a forest"
            width:	 	Image width in pixels 	 	
            height: 	 	Image height in pixels 	 	
            seed: 	 	A number to get the same image every time
         Returns:
            PIL.Image: The generated image.

    """
    if randomize_seed:
        seed = random.randint(0, MAX_SEED)

    # Encode the prompt to handle spaces
    url = f"https://image.pollinations.ai/prompt/{quote(prompt)}"
    # Customize the image size and model
    params = {"width": width, "height": height, "model": model,"seed":seed}
    if image is not None and len(image)>1:
        params["image"]=image
    # Make the request
    response = requests.get(url, params=params, timeout=60)
    image_data = BytesIO(response.content)
    image = Image.open(image_data)
    
    
    return image, seed


examples = [
    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
    "An astronaut riding a green horse",
    "A delicious ceviche cheesecake slice"
]

css = """
#col-container {
    margin: 0 auto;
    max-width: 640px;
}
"""

with gr.Blocks(css=css) as demo:
    with gr.Column(elem_id="col-container"):
        gr.Markdown(" # Text-to-Image using pollinations ai")

        with gr.Row():
            prompt = gr.Text(
                label="Prompt",
                show_label=False,
                max_lines=3,
                placeholder="Enter your prompt",
                container=False,
            )

            run_button = gr.Button("Run", scale=0, variant="primary")

        result = gr.Image(label="Result", show_label=False)

        with gr.Accordion("Advanced Settings", open=False):

            seed = gr.Slider(
                label="Seed",
                minimum=0,
                maximum=MAX_SEED,
                step=1,
                value=0,
            )

            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)

            with gr.Row():
                width = gr.Slider(
                    label="Width",
                    minimum=256,
                    maximum=MAX_IMAGE_SIZE,
                    step=32,
                    value=1024,  # Replace with defaults that work for your model
                )

                height = gr.Slider(
                    label="Height",
                    minimum=256,
                    maximum=MAX_IMAGE_SIZE,
                    step=32,
                    value=1024,  # Replace with defaults that work for your model
                )

            with gr.Row():
                enhance= gr.Checkbox(label="enhance prompt", value=False)
                nologo=gr.Checkbox(label="nologo", value=False)
                nofeed=gr.Checkbox(label="nofeed", value=False)
                private=gr.Checkbox(label="private", value=False)
            image=gr.Text(
                label="image",
                show_label=False,
                max_lines=3,
                placeholder="image url",
                container=False,
            )
            model=gr.Dropdown(models_list,
                              label="model",
                              info="selected model",
                              interactive=True,
                              show_label=False,
                              container=False
                             )

        gr.Examples(examples=examples, inputs=[prompt])
    gr.on(
        triggers=[run_button.click, prompt.submit],
        fn=infer,
        inputs=[
            prompt,
            seed,
            randomize_seed,
            width,
            height,
            enhance,
            image,
            private,
            nologo,            # Remove watermark (default: False)
            nofeed,            # Don't add to public feed (default: False)
                        
        ],
        outputs=[result, seed],
    )

if __name__ == "__main__":
    demo.launch(mcp_server=True)