import gradio as gr
from huggingface_hub import InferenceClient
import random
import os
import time
from PIL import Image
from deep_translator import GoogleTranslator
import json

# Project by Nymbo

MODEL = "stabilityai/stable-diffusion-xl-base-1.0"
# The free serverless endpoint (api-inference.huggingface.co) is gone; SDXL is served through
# Inference Providers now. Signed-in visitors use their own quota; otherwise the Space's
# HF_READ_TOKEN secret is used.


def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, oauth_token: gr.OAuthToken | None = None):
    if prompt == "" or prompt == None:
        return None

    key = random.randint(0, 999)

    try:
        prompt = GoogleTranslator(source='auto', target='en').translate(prompt) or prompt
    except Exception as e:
        print(f"Translation skipped: {e}")
    print(f'Generation {key} translation: {prompt}')

    prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
    print(f'Generation {key}: {prompt}')

    token = oauth_token.token if oauth_token else os.getenv("HF_READ_TOKEN")
    if not token:
        raise gr.Error("Sign in with Hugging Face to generate images.")
    client = InferenceClient(provider="auto", token=token)
    try:
        image = client.text_to_image(
            prompt,
            model=MODEL,
            negative_prompt=is_negative or None,
            num_inference_steps=int(steps),
            guidance_scale=float(cfg_scale),
            seed=int(seed) if seed != -1 else random.randint(1, 1000000000),
        )
    except Exception as e:
        print(f"Error: Failed to get image: {e}")
        raise gr.Error(f"Inference error: {e}")
    print(f'Generation {key} completed! ({prompt})')
    return image

css = """
#app-container {
    max-width: 600px;
    margin-left: auto;
    margin-right: auto;
}
"""

with gr.Blocks() as app:
    gr.HTML("<center><h1>Stable Diffusion XL</h1></center>")
    gr.LoginButton()
    with gr.Column(elem_id="app-container"):
        with gr.Row():
            with gr.Column(elem_id="prompt-container"):
                with gr.Row():
                    text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt here", lines=2, elem_id="prompt-text-input")
                with gr.Row():
                    with gr.Accordion("Advanced Settings", open=False):
                        negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What should not be in the image", value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos", lines=3, elem_id="negative-prompt-text-input")
                        steps = gr.Slider(label="Sampling steps", value=25, minimum=1, maximum=100, step=1)
                        cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
                        method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
                        strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
                        seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)

        with gr.Row():
            text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
        with gr.Row():
            image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
        
        text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength], outputs=image_output)

app.launch(theme='Nymbo/Nymbo_Theme', css=css)