Update app.py

app.py

@@ -1,5 +1,194 @@
+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
 
-exec(os.environ.get('CODE'))
+api_base = os.getenv("API_BASE")
+mmodels = {
+    "DALL-E 3 XL": "openskyml/dalle-3-xl",
+    "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 ❤ 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)
 
-# PLEASE ❤ like ❤ 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.
+def query(prompt, model, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, gpt=False, width=1024, height=1024):
+    if prompt == "" or prompt == None:
+        return None
+
+    key = random.randint(0, 999)
+    
+    if gpt:
+        payload = {
+            "model": "gpt-4-vision-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 = 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),
+        "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 = """
+* {}
+footer {visibility: hidden !important;}
+"""
+
+with gr.Blocks(css=css) as dalle:
+    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():
+                    model = gr.Radio(label="Модель", 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=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("Beta"):
+        with gr.Row():
+            width = gr.Slider(label="Ширина", minimum=15, maximum=2000, value=1024, 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():
+            with gr.Column():
+                gr.HTML("""<button class="lg secondary  svelte-cmf5ev" onclick="window.open('http://ai-hub.rf.gd', '_blank');">AI-HUB</button>""")
+                gr.HTML("""<button class="lg secondary  svelte-cmf5ev" 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.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)
+
+dalle.launch(show_api=False, share=False)