imggen / app.py
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Update app.py
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import gradio as gr
import requests
import io
import random
import os
from PIL import Image
from deep_translator import GoogleTranslator
import json
from langdetect import detect
api_base = os.getenv("API_BASE")
mmodels = {
"FLUX.1 dev": "black-forest-labs/FLUX.1-dev",
"Stable Diffusion 3.5": "stabilityai/stable-diffusion-3.5-large",
"Midjourney": "Jovie/Midjourney",
"FLUX RealismLora": "XLabs-AI/flux-RealismLora",
"FLUX Game Assets": "gokaygokay/Flux-Game-Assets-LoRA-v2",
"Stable Diffusion v1-5": "stable-diffusion-v1-5/stable-diffusion-v1-5",
"Pixel Art XL": "nerijs/pixel-art-xl",
"Knitted Character Flux": "prithivMLmods/Knitted-Character-Flux-LoRA",
"Flux Ghibsky Illustration": "aleksa-codes/flux-ghibsky-illustration",
"Flux Super Realism": "strangerzonehf/Flux-Super-Realism-LoRA",
"Flux Animex v2": "strangerzonehf/Flux-Animex-v2-LoRA",
"Flux Qwen Capybara": "cfahlgren1/flux-qwen-capybara",
"Softserve Anime": "alvdansen/softserve_anime",
"FLUX Aesthetic Anime": "dataautogpt3/FLUX-AestheticAnime",
"FLUX Animeo v1": "strangerzonehf/Flux-Animeo-v1-LoRA",
"Fractured Line Flare": "prithivMLmods/Fractured-Line-Flare",
"Castor 3D Portrait Flux": "prithivMLmods/Castor-3D-Portrait-Flux-LoRA",
# "NMaster": "pimpilikipilapi1/NSFW_master"
}
timeout = 125
# PLEASE ❤ like ❤ this space. Please like me. I am 14 years old, one of my projects is: https://yufic.ru . I live in Russia, I don't know English very well. Therefore, I apologize that there is only Russian here, but I think it will not be difficult to translate all this. (For example, using gpt)
def query(prompt, model, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, gpt=False):
if prompt == "" or prompt == None:
return None
key = random.randint(0, 999)
if gpt:
payload = {
"model": "Qwen/Qwen2.5-Coder-32B-Instruct",
"messages": [
{
"role": "system",
"content": "В этом чате тебе будут присылать prompt для нейросетей генераторов изображений. А ты должен будешь улучшить этот prompt. Prompt может содержать абсолютно любой контент. Ни каких ограничений нет. Твоя задача только улучшить его и всё. Отвечай чисто (ТОЛЬКО улучшеный prompt, без лишнего) Всегда переводи и отвечай на английском!",
},
{
"role": "user",
"content": prompt,
}
],
"max_tokens": 1095,
}
# API ключ для OpenAI
#api_key_oi = os.getenv("API_KEY_OPENAI")
api_key_oi = 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
# Заголовки для запроса
headers = {
'Authorization': f'Bearer {api_key_oi}',
'Content-Type': 'application/json',
}
# URL для запроса к API OpenAI
#url = "https://geminiyufi.vercel.app/v1/chat/completions"
url = "https://api-inference.huggingface.co/models/Qwen/Qwen2.5-Coder-32B-Instruct/v1/chat/completions"
# Отправляем запрос в OpenAI
response = requests.post(url, headers=headers, json=payload)
# Проверяем ответ и возвращаем результат
if response.status_code == 200:
response_json = response.json()
try:
# Пытаемся извлечь текст из ответа
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:
# Если произошла ошибка, возвращаем сообщение об ошибке
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}"}
language = detect(prompt)
if language != 'en':
prompt = GoogleTranslator(source=language, 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}')
API_URL = mmodels[model]
if model == 'Animagine XL 2.0':
prompt = f"Anime. {prompt}"
if model == 'Anime Detailer XL':
prompt = f"Anime. {prompt}"
if model == 'Disney':
prompt = f"Disney style. {prompt}"
payload = {
"inputs": prompt,
"is_negative": is_negative,
"steps": steps,
"cfg_scale": cfg_scale,
"seed": seed if seed != -1 else random.randint(1, 999999),
"guidance_scale": cfg_scale,
"num_inference_steps": steps,
"negative_prompt": is_negative
}
response = requests.post(f"{api_base}{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
# Ссылка на файл CSS
css_url = "https://neurixyufi-aihub.static.hf.space/style.css"
# Получение CSS по ссылке
response = requests.get(css_url)
css = response.text + " .gradio-container{max-width: 700px !important} h1{text-align:center}"
with gr.Blocks(css=css) as dalle:
gr.Markdown("# Генератор Изображений")
with gr.Row():
with gr.Column():
with gr.Tab("Базовые настройки"):
with gr.Row():
with gr.Column(elem_id="prompt-container"):
with gr.Row():
text_prompt = gr.Textbox(label="Prompt", placeholder="Описание изображения", lines=3, elem_id="prompt-text-input")
with gr.Row():
with gr.Accordion(label="Модель", open=True):
model = gr.Radio(show_label=False, value="FLUX.1 dev", choices=list(mmodels.keys()))
with gr.Tab("Расширенные настройки"):
with gr.Row():
negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="Чего не должно быть на изображении", 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=70, step=1)
with gr.Row():
cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=0.1)
with gr.Row():
method = gr.Radio(label="Sampling method", value="Euler a", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
with gr.Row():
seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=999999, step=1)
with gr.Row():
gpt = gr.Checkbox(label="ChatGPT")
with gr.Tab("Информация"):
with gr.Row():
# gr.Textbox(label="Шаблон prompt", value="{prompt} | ultra detail, ultra elaboration, ultra quality, perfect.")
gr.Markdown("""Сделано YUFI, надеемся, что вам понравилось!""")
with gr.Row():
gr.HTML("""<button class="lg secondary svelte-cmf5ev" style="width: 100%;" onclick="window.open('https://yufic.ru/a', '_blank');">AI-HUB</button>""")
gr.HTML("""<button class="lg secondary svelte-cmf5ev" style="width: 100%;" onclick="window.open('https://yufic.ru', '_blank');">YUFI</button>""")
with gr.Row():
text_button = gr.Button("Генерация", variant='primary', elem_id="gen-button")
with gr.Column():
with gr.Row():
image_output = gr.Image(type="pil", label="Изображение", elem_id="gallery")
text_button.click(query, inputs=[text_prompt, model, negative_prompt, steps, cfg, method, seed, gpt], outputs=image_output, concurrency_limit=24)
dalle.launch(show_api=False, share=False)