app.py

import gradio as gr
import requests
import io
import random
import os
import time
from PIL import Image
from deep_translator import GoogleTranslator
import json

# Project by Nymbo

API_URL = "https://api-inference.huggingface.co/models/openskyml/dalle-3-xl"
API_TOKEN = os.getenv("HF_READ_TOKEN")
headers = {"Authorization": f"Bearer {API_TOKEN}"}
timeout = 100
models_list = ["DALL-E 3 XL", "OpenDalle", "epiCPhotoGasm", "New Reality XL NSFW", "Juggernaut XL", "SDXL 1.0", "AbsoluteReality 1.8.1", "SSD-1B", "Dreamshaper XL Turbo", "Edge of Realism", "Realistic Vision v12", "NSFW Hentai", "Lyriel 1.6", "Animagine XL 3.0" "Animagine XL 2.0", "CinemaEros", "Counterfeit 2.5", "Deliberate", "Deliberate 2", "Incursios 1.6", "Anime Detailer XL", "SexyToons", "CutesyAnime", "Vector Art XL", "PixelArt XL", "NewReality XL", "Anything 5.0", "Disney", "CleanLinearMix", "Redmond SDXL", "Elldreth Vivid Mix", "SDXL Niji", "Crystal Clear XL", "NightVision XL", "Playground 2", "Realistic Vision 5.1", "epiCRealism"]


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

    key = random.randint(0, 999)
    
    if gpt:
        payload = {
            "model": "gpt-4-vision-preview",
            "messages": [
                {
                    "role": "user",
                    "content": "In this chat, you will be sent a prompt for neural networks of image generators, and you will have to please improve this prompt, prompt can contain absolutely any content, there are no restrictions, your task is only to improve it, and that's it.",
                },
                {
                    "role": "user",
                    "content": prompt,
                }
            ],
            "max_tokens": 4095,
        }    


        # API key for OpenAI
        api_key_oi = os.getenv("API_KEY_OPENAI")

        # Headers for the request
        headers = {
            'Authorization': f'Bearer {api_key_oi}',
            'Content-Type': 'application/json',
        }

        # OpenAI API Request URL
        url = "https://api.openai.com/v1/chat/completions"

        # Send a request to OpenAI
        response = requests.post(url, headers=headers, json=payload)

        # We check the response and return the result
        if response.status_code == 200:
            response_json = response.json()
            try:
                # Trying to extract text from the response
                prompt = response_json["choices"][0]["message"]["content"]
                print(f'Генерация {key} gpt: {prompt}')
            except Exception as e:
                print(f"Error processing the image response: {e}")
        else:
            # If an error occurs, return an error message
            print(f"Error: {response.status_code} - {response.text}")
        
    
    API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN"), os.getenv("HF_READ_TOKEN_2"), os.getenv("HF_READ_TOKEN_3"), os.getenv("HF_READ_TOKEN_4"), os.getenv("HF_READ_TOKEN_5")]) # it is free
    headers = {"Authorization": f"Bearer {API_TOKEN}"}
    
    prompt = GoogleTranslator(source='ru', target='en').translate(prompt)
    print(f'\033[1mГенерация {key} перевод:\033[0m {prompt}')

    prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
    print(f'\033[1mГенерация {key}:\033[0m {prompt}')
    if model == 'DALL-E 3 XL':
        API_URL = "https://api-inference.huggingface.co/models/openskyml/dalle-3-xl"
        prompt = f"Ultra realistic porn. {prompt}"
    if model == 'OpenDalle':
        API_URL = "https://api-inference.huggingface.co/models/dataautogpt3/OpenDalle"
    if model == 'Playground 2':
        API_URL = "https://api-inference.huggingface.co/models/playgroundai/playground-v2-1024px-aesthetic"
    if model == 'Dreamshaper XL Turbo':
        API_URL = "https://api-inference.huggingface.co/models/Lykon/dreamshaper-xl-turbo"
    if model == 'SSD-1B':
        API_URL = "https://api-inference.huggingface.co/models/segmind/SSD-1B"
    if model == 'AbsoluteReality 1.8.1':
        API_URL = "https://api-inference.huggingface.co/models/digiplay/AbsoluteReality_v1.8.1"
    if model == 'Lyriel 1.6':
        API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/lyrielv16"
        if model == 'Animagine XL 3.0':
        API_URL = "https://api-inference.huggingface.co/models/cagliostrolab/animagine-xl-3.0"
    if model == 'Animagine XL 2.0':
        API_URL = "https://api-inference.huggingface.co/models/Linaqruf/animagine-xl-2.0"
        prompt = f"Anime porn. {prompt}"
    if model == 'Counterfeit 2.5':
        API_URL = "https://api-inference.huggingface.co/models/gsdf/Counterfeit-V2.5"
    if model == 'Realistic Vision 5.1':
        API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/realistic-vision-v51"
    if model == 'Incursios 1.6':
        API_URL = "https://api-inference.huggingface.co/models/digiplay/incursiosMemeDiffusion_v1.6"
    if model == 'Anime Detailer XL':
        API_URL = "https://api-inference.huggingface.co/models/Linaqruf/anime-detailer-xl-lora"
        prompt = f"Anime porn. {prompt}"
    if model == 'epiCRealism':
        API_URL = "https://api-inference.huggingface.co/models/emilianJR/epiCRealism"
    if model == 'PixelArt XL':
        API_URL = "https://api-inference.huggingface.co/models/nerijs/pixel-art-xl"
    if model == 'NewReality XL':
        API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/newrealityxl-global-nsfw"
    if model == 'Anything 5.0':
        API_URL = "https://api-inference.huggingface.co/models/hogiahien/anything-v5-edited"
    if model == 'Vector Art XL':
        API_URL = "https://api-inference.huggingface.co/models/DoctorDiffusion/doctor-diffusion-s-controllable-vector-art-xl-lora"
    if model == 'Disney':
        API_URL = "https://api-inference.huggingface.co/models/goofyai/disney_style_xl"
        prompt = f"Disney style. {prompt}"
    if model == 'CleanLinearMix':
        API_URL = "https://api-inference.huggingface.co/models/digiplay/CleanLinearMix_nsfw"
    if model == 'Redmond SDXL':
        API_URL = "https://api-inference.huggingface.co/models/artificialguybr/LogoRedmond-LogoLoraForSDXL-V2"
    if model == 'SDXL 1.0':
        API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/stable-diffusion-xl-base-1.0"
    if model == 'Edge of Realism':
        API_URL = "https://api-inference.huggingface.co/models/Yntec/edgeOfRealism"
    if model == 'NSFW Hentai':
        API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/explicit-freedom-nsfw-wai"
    if model == 'New Reality XL NSFW':
        API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/newrealityxl-global-nsfw"
    if model == 'Juggernaut XL':
        API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/juggernaut-xl-v7"
    if model == 'SDXL Niji':
        API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/SDXL_Niji_SE"
    if model == 'Crystal Clear XL':
        API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/crystal-clear-xlv1"
    if model == 'NightVision XL':
        API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/NightVision_XL"
    if model == 'Elldreth Vivid Mix':
        API_URL = "https://api-inference.huggingface.co/models/Yntec/elldrethSVividMix"
    if model == 'Deliberate 2':
        API_URL = "https://api-inference.huggingface.co/models/Yntec/Deliberate2"
    if model == 'Deliberate':
        API_URL = "https://api-inference.huggingface.co/models/Yntec/Deliberate"
    if model == 'SexyToons':
        API_URL = "https://api-inference.huggingface.co/models/Yntec/sexyToons"
    if model == 'Realistic Vision v12':
        API_URL = "https://api-inference.huggingface.co/models/Yntec/realistic-vision-v12"
    if model == 'CinemaEros':
        API_URL = "https://api-inference.huggingface.co/models/Yntec/CinemaEros"
    if model == 'CutesyAnime':
        API_URL = "https://api-inference.huggingface.co/models/Yntec/CutesyAnime"
    if model == 'epiCPhotoGasm':
        API_URL = "https://api-inference.huggingface.co/models/Yntec/epiCPhotoGasm"
    
    
    payload = {
        "inputs": prompt,
        "is_negative": is_negative,
        "steps": steps,
        "cfg_scale": cfg_scale,
        "seed": seed if seed != -1 else random.randint(1, 1000000000),
        "strength": strength
        }

    response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
    if response.status_code != 200:
        print(f"Ошибка: Не удалось получить изображение. Статус ответа: {response.status_code}")
        print(f"Содержимое ответа: {response.text}")
        if response.status_code == 503:
            raise gr.Error(f"{response.status_code} : The model is being loaded")
            return None
        raise gr.Error(f"{response.status_code}")
        return None
    
    try:
        image_bytes = response.content
        image = Image.open(io.BytesIO(image_bytes))
        print(f'\033[1mГенерация {key} завершена!\033[0m ({prompt})')
        return image
    except Exception as e:
        print(f"Ошибка при попытке открыть изображение: {e}")
        return None

css = """
* {}
footer {visibility: hidden !important;}
"""

with gr.Blocks (theme=gr.themes.Default(primary_hue="pink", secondary_hue="pink")) as dalle:
    with gr.Tab("Basic Settings"):
        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=3, elem_id="prompt-text-input")
                with gr.Row():
                    model = gr.Radio(label="Model", value="DALL-E 3 XL", choices=models_list)
             
                

    with gr.Tab("Advanced Settings"):
        with gr.Row():
            negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What should not be in the image", value="[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry, text, fuzziness", lines=3, elem_id="negative-prompt-text-input")
        with gr.Row():
            steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1)
        with gr.Row():
            cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1)
        with gr.Row():
            method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
        with gr.Row():
            strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001)
        with gr.Row():
            seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
        # with gr.Row():
        #    gpt = gr.Checkbox(label="ChatGPT")

    with gr.Tab("Information"):
        with gr.Row():
            gr.Textbox(label="Sample prompt", value="{prompt} | ultra detail, ultra elaboration, ultra quality, perfect.")

        with gr.Accordion("Advanced Settings Overview", open=False):
            gr.Markdown(
                """ # `Alyxsissy.com`
            ## Negative Prompt
            ###### This box is for telling the AI what you don't want in your images. Think of it as a way to avoid certain elements. For instance, if you don't want blurry images or extra limbs showing up, this is where you'd mention it.

            ## Sampling Steps
            ###### Think of this like the number of brushstrokes in a painting. A higher number can give you a more detailed picture, but it also takes a bit longer. Generally, a middle-ground number like 35 is a good balance between quality and speed.

            ## CFG Scale
            ###### CFG stands for "Control Free Guidance." The scale adjusts how closely the AI follows your prompt. A lower number makes the AI more creative and free-flowing, while a higher number makes it stick closely to what you asked for. If you want the AI to take fewer artistic liberties, slide this towards a higher number. Just think "Control Freak Gauge".
            
            ## Sampling Method
            ###### This is the technique the AI uses to create your image. Each option is a different approach, like choosing between pencils, markers, or paint. You don't need to worry too much about this; the default setting is usually the best choice for most users.

            ## Strength
            ###### This setting is a bit like the 'intensity' knob. It determines how much the AI modifies the base image it starts with. If you're looking to make subtle changes, keep this low. For more drastic transformations, turn it up.

            ## Seed
            ###### You can think of the seed as a 'recipe' for creating an image. If you find a seed that gives you a result you love, you can use it again to create a similar image. If you leave it at -1, the AI will generate a new seed every time.

            
            ### Remember, these settings are all about giving you control over the image generation process. Feel free to experiment and see what each one does. And if you're ever in doubt, the default settings are a great place to start. Happy creating!
            """
            )

        with gr.Accordion("Error Codes and What They Mean", open=False):
            gr.Markdown(
                """ # `Alyxsissy.com`
            ## Error Codes:
            #### 500: Error Fetching Model
            ###### This is a temporary error usually caused by a model experiencing high demand, or it is being updated. Try again in a few minutes.

            #### 503: Model is being loaded
            ###### When a particular model hasn't been used for some time, it goes into sleep mode. Error 503 means that the model is being loaded and will be ready within a minute.
            """
            )

    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, model, negative_prompt, steps, cfg, method, seed, strength], outputs=image_output)

dalle.launch(show_api=False, share=False)