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| import gradio as gr | |
| import requests | |
| import time | |
| import json | |
| import base64 | |
| import os | |
| from io import BytesIO | |
| import html | |
| import re | |
| from PIL import Image # Убедитесь, что PIL импортируется для работы с изображениями | |
| class Prodia: | |
| def __init__(self, api_key, base=None): | |
| self.base = base or "https://api.prodia.com/v1" | |
| self.headers = { | |
| "X-Prodia-Key": api_key | |
| } | |
| def generate(self, params): | |
| return self._post(f"{self.base}/sd/generate", params).json() | |
| def transform(self, params): | |
| return self._post(f"{self.base}/sd/transform", params).json() | |
| def controlnet(self, params): | |
| return self._post(f"{self.base}/sd/controlnet", params).json() | |
| def get_job(self, job_id): | |
| return self._get(f"{self.base}/job/{job_id}").json() | |
| def wait(self, job): | |
| job_result = job | |
| while job_result['status'] not in ['succeeded', 'failed']: | |
| time.sleep(0.25) | |
| job_result = self.get_job(job['job']) | |
| return job_result | |
| def list_models(self): | |
| return self._get(f"{self.base}/sd/models").json() | |
| def list_samplers(self): | |
| return self._get(f"{self.base}/sd/samplers").json() | |
| # Изменение: добавлены повторные попытки при сбоях сети | |
| def _post(self, url, params): | |
| headers = {**self.headers, "Content-Type": "application/json"} | |
| for _ in range(3): | |
| try: | |
| response = requests.post(url, headers=headers, data=json.dumps(params)) | |
| response.raise_for_status() | |
| return response | |
| except requests.exceptions.RequestException as e: | |
| print(f"Request failed: {e}, retrying...") | |
| time.sleep(1) | |
| raise Exception("Failed after 3 attempts") | |
| # Изменение: добавлены повторные попытки при сбоях сети | |
| def _get(self, url): | |
| for _ in range(3): | |
| try: | |
| response = requests.get(url, headers=self.headers) | |
| response.raise_for_status() | |
| return response | |
| except requests.exceptions.RequestException as e: | |
| print(f"Request failed: {e}, retrying...") | |
| time.sleep(1) | |
| raise Exception("Failed after 3 attempts") | |
| def image_to_base64(image, format="PNG"): | |
| buffered = BytesIO() | |
| image.save(buffered, format=format) | |
| img_str = base64.b64encode(buffered.getvalue()).decode('utf-8') | |
| return img_str | |
| def remove_id_and_ext(text): | |
| text = re.sub(r'\[.*\]$', '', text) | |
| extension = text[-12:].strip() | |
| if extension == "safetensors": | |
| text = text[:-13] | |
| elif extension == "ckpt": | |
| text = text[:-4] | |
| return text | |
| # Изменение: оптимизация функции get_data | |
| def get_data(text): | |
| patterns = { | |
| 'prompt': r'(.*)', | |
| 'negative_prompt': r'Negative prompt: (.*)', | |
| 'steps': r'Steps: (\d+),', | |
| 'seed': r'Seed: (\d+),', | |
| 'sampler': r'Sampler:\s*([^\s,]+(?:\s+[^\s,]+)*)', | |
| 'model': r'Model:\s*([^\s,]+)', | |
| 'cfg_scale': r'CFG scale:\s*([\d\.]+)', | |
| 'size': r'Size:\s*([0-9]+x[0-9]+)' | |
| } | |
| results = {key: re.search(pattern, text).group(1) if re.search(pattern, text) else None for key, pattern in patterns.items()} | |
| if results['size']: | |
| results['w'], results['h'] = map(int, results['size'].split("x")) | |
| else: | |
| results['w'], results['h'] = None, None | |
| return results | |
| # Изменение: оптимизация функции send_to_txt2img | |
| def send_to_txt2img(image): | |
| result = {tabs: gr.update(selected="t2i")} | |
| try: | |
| text = image.info['parameters'] | |
| data = get_data(text) | |
| fields = ['prompt', 'negative_prompt', 'steps', 'seed', 'cfg_scale', 'w', 'h', 'sampler', 'model'] | |
| for field in fields: | |
| result[field] = gr.update(value=data[field]) if data[field] is not None else gr.update() | |
| return result | |
| except Exception as e: | |
| print(e) | |
| return result | |
| prodia_client = Prodia(api_key=os.getenv("PRODIA_API_KEY")) | |
| model_list = prodia_client.list_models() | |
| model_names = {remove_id_and_ext(model_name): model_name for model_name in model_list} | |
| def txt2img(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed): | |
| result = prodia_client.generate({ | |
| "prompt": prompt, | |
| "negative_prompt": negative_prompt, | |
| "model": model, | |
| "steps": steps, | |
| "sampler": sampler, | |
| "cfg_scale": cfg_scale, | |
| "width": width, | |
| "height": height, | |
| "seed": seed | |
| }) | |
| job = prodia_client.wait(result) | |
| return job["imageUrl"] | |
| def img2img(input_image, denoising, prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed): | |
| result = prodia_client.transform({ | |
| "imageData": image_to_base64(input_image), | |
| "denoising_strength": denoising, | |
| "prompt": prompt, | |
| "negative_prompt": negative_prompt, | |
| "model": model, | |
| "steps": steps, | |
| "sampler": sampler, | |
| "cfg_scale": cfg_scale, | |
| "width": width, | |
| "height": height, | |
| "seed": seed | |
| }) | |
| job = prodia_client.wait(result) | |
| return job["imageUrl"] | |
| css = """ | |
| #generate { | |
| height: 100%; | |
| } | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| with gr.Row(): | |
| with gr.Column(scale=6): | |
| model = gr.Dropdown(interactive=True, value="childrensStories_v1ToonAnime.safetensors [2ec7b88b]", show_label=True, label="Stable Diffusion Checkpoint", choices=prodia_client.list_models()) | |
| with gr.Column(scale=1): | |
| gr.Markdown(elem_id="powered-by-prodia", value="AUTOMATIC1111 Stable Diffusion Web UI переделано masteroko.<br>Powered by [Prodia](https://prodia.com).<br>For more features and faster generation times check out our [API Docs](https://docs.prodia.com/reference/getting-started-guide).") | |
| with gr.Tabs() as tabs: | |
| with gr.Tab("txt2img", id='t2i'): | |
| with gr.Row(): | |
| with gr.Column(scale=6, min_width=600): | |
| prompt = gr.Textbox("nsfw", placeholder="Prompt", show_label=False, lines=3) | |
| negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=False, lines=3, value="3d, cartoon, anime, (deformed eyes, nose, ears, nose), bad anatomy, ugly") | |
| with gr.Column(): | |
| text_button = gr.Button("Сгенерировать", variant='primary', elem_id="generate") | |
| with gr.Row(): | |
| with gr.Column(scale=3): | |
| with gr.Tab("Генерация"): | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| sampler = gr.Dropdown(value="DPM++ 2M SDE Exponential", show_label=True, label="Sampling Method", choices=prodia_client.list_samplers()) | |
| with gr.Column(scale=1): | |
| steps = gr.Slider(label="количество обработок", minimum=1, maximum=100, value=20, step=1) | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| width = gr.Slider(label="Ширина", maximum=1024, value=512, step=8) | |
| height = gr.Slider(label="Высота", maximum=1024, value=512, step=8) | |
| with gr.Column(scale=1): | |
| batch_size = gr.Slider(label="Batch Size", maximum=1, value=1) | |
| batch_count = gr.Slider(label="Batch Count", maximum=1, value=1) | |
| cfg_scale = gr.Slider(label="CFG Scale(степень фантазии ии)", minimum=1, maximum=20, value=7, step=1) | |
| seed = gr.Number(label="Семя рандома", value=-1) | |
| with gr.Column(scale=2): | |
| image_output = gr.Image(value="https://images.prodia.xyz/8ede1a7c-c0ee-4ded-987d-6ffed35fc477.png") | |
| # Изменение: добавлен limit на одновременные запросы | |
| text_button.click(txt2img, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed], outputs=image_output, concurrency_limit=1024) | |
| with gr.Tab("img2img", id='i2i'): | |
| with gr.Row(): | |
| with gr.Column(scale=6, min_width=600): | |
| image = gr.Image(show_label=False) | |
| prompt = gr.Textbox(placeholder="Prompt", show_label=False, lines=3) | |
| negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=False, lines=3) | |
| with gr.Column(): | |
| text_button = gr.Button("Трансформировать", variant='primary', elem_id="generate") | |
| with gr.Row(): | |
| with gr.Column(scale=3): | |
| with gr.Tab("Генерация"): | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| sampler = gr.Dropdown(value="DPM++ 2M SDE Exponential", show_label=True, label="Sampling Method", choices=prodia_client.list_samplers()) | |
| with gr.Column(scale=1): | |
| steps = gr.Slider(label="количество обработок", minimum=1, maximum=100, value=20, step=1) | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| width = gr.Slider(label="Ширина", maximum=1024, value=512, step=8) | |
| height = gr.Slider(label="Высота", maximum=1024, value=512, step=8) | |
| with gr.Column(scale=1): | |
| batch_size = gr.Slider(label="Batch Size", maximum=1, value=1) | |
| batch_count = gr.Slider(label="Batch Count", maximum=1, value=1) | |
| cfg_scale = gr.Slider(label="CFG Scale(степень фантазии ии)", minimum=1, maximum=20, value=7, step=1) | |
| seed = gr.Number(label="Семя рандома", value=-1) | |
| denoising = gr.Slider(label="Denoising", value=0.5) | |
| with gr.Column(scale=2): | |
| image_output = gr.Image(value="https://images.prodia.xyz/8ede1a7c-c0ee-4ded-987d-6ffed35fc477.png") | |
| # Изменение: добавлен limit на одновременные запросы | |
| text_button.click(img2img, inputs=[image, denoising, prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed], outputs=image_output, concurrency_limit=1024) | |
| # Запуск Gradio интерфейса | |
| demo.launch() | |