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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", | |
| "PixelArt": "nerijs/pixel-art-xl", | |
| "FLUX Game Assets": "gokaygokay/Flux-Game-Assets-LoRA-v2", | |
| } | |
| timeout = 100 | |
| # 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": "gemini-1.5-pro-latest", | |
| "messages": [ | |
| { | |
| "role": "user", | |
| "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)", | |
| }, | |
| { | |
| "role": "user", | |
| "content": prompt, | |
| } | |
| ], | |
| "max_tokens": 4095, | |
| } | |
| # API ключ для OpenAI | |
| api_key_oi = os.getenv("API_KEY_OPENAI") | |
| # 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" | |
| # 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, 1000000000), | |
| "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://aihubyufi-aihub.static.hf.space/style.css" | |
| # Получение CSS по ссылке | |
| response = requests.get(css_url) | |
| css = response.text | |
| with gr.Blocks(css=css) as dalle: | |
| 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="DALL-E 3 XL", 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=1000000000, 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.") | |
| with gr.Row(): | |
| gr.HTML("""<button class="lg secondary svelte-cmf5ev" style="width: 100%;" onclick="window.open('http://ai-hub.rf.gd', '_blank');">AI-HUB</button>""") | |
| gr.HTML("""<button class="lg secondary svelte-cmf5ev" style="width: 100%;" onclick="window.open('http://yufi.rf.gd', '_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) |