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 = { "DALL-E 3 XL": "openskyml/dalle-3-xl", "OpenDALL-E 1.1": "dataautogpt3/OpenDalleV1.1", "Playground 2": "playgroundai/playground-v2-1024px-aesthetic", "Openjourney 4": "prompthero/openjourney-v4", "AbsoluteReality 1.8.1": "digiplay/AbsoluteReality_v1.8.1", "Lyriel 1.6": "stablediffusionapi/lyrielv16", "Animagine XL 2.0": "Linaqruf/animagine-xl-2.0", "Counterfeit 2.5": "gsdf/Counterfeit-V2.5", "Realistic Vision 5.1": "stablediffusionapi/realistic-vision-v51", "Incursios 1.6": "digiplay/incursiosMemeDiffusion_v1.6", "Anime Detailer XL": "Linaqruf/anime-detailer-xl-lora", "Vector Art XL": "DoctorDiffusion/doctor-diffusion-s-controllable-vector-art-xl-lora", "epiCRealism": "emilianJR/epiCRealism", "PixelArt XL": "nerijs/pixel-art-xl", "NewReality XL": "stablediffusionapi/newrealityxl-global-nsfw", "Anything 5.0": "hogiahien/anything-v5-edited", "Disney": "goofyai/disney_style_xl", "CleanLinearMix": "digiplay/CleanLinearMix_nsfw", "Redmond SDXL": "artificialguybr/LogoRedmond-LogoLoraForSDXL-V2", "Arcane": "nitrosocke/Arcane-Diffusion" } timeout = 100 # PLEASE ❤ like t❤ this space. Please like me. I am 12 years old, one of my projects is: https://ai-hub.rf.gd . 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, strength=0.7, gpt=False, width=512, height=1024): if prompt == "" or prompt == None: return None key = random.randint(0, 999) if gpt: payload = { "model": "gpt-4-1106-preview", "messages": [ { "role": "user", "content": "В этом чате тебе будут присылать prompt для нейросетей генераторов изображений. А ты должен будешь пожалуйста 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://api.openai.com/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 = os.getenv("HF_READ_TOKEN") 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), "strength": strength, "width": width, "height": height, "guidance_scale": cfg_scale, "num_inference_steps": steps, "resolution": f"{width} x {height}", "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 css = """ """ 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=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=0.1) 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("Beta"): with gr.Row(): width = gr.Slider(label="Ширина", minimum=15, maximum=2000, value=512, step=1) height = gr.Slider(label="Высота", minimum=15, maximum=2000, value=1024, step=1) 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("""""") gr.HTML("""""") 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, strength, gpt, width, height], outputs=image_output, concurrency_limit=24, api_name="predict") dalle.launch(share=True)