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import gradio as gr
from gradio_client import Client
import os
import logging
import requests
from PIL import Image
import io
import base64
# ๋ก๊น
์ค์
logging.basicConfig(level=logging.DEBUG, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
# API ํด๋ผ์ด์ธํธ ์ค์
api_client = Client("http://211.233.58.202:7960/")
# Webhook URL
WEBHOOK_URL = "https://connect.pabbly.com/workflow/sendwebhookdata/IjU3NjUwNTY0MDYzMTA0MzE1MjZlNTUzYzUxM2Ei_pc"
# Imgur ํด๋ผ์ด์ธํธ ID
IMGUR_CLIENT_ID = "์ฌ๊ธฐ์_๋น์ ์_IMGUR_CLIENT_ID๋ฅผ_์
๋ ฅํ์ธ์"
def upload_to_imgur(image_data):
try:
logger.debug(f"Image data type: {type(image_data)}")
logger.debug(f"Image data length: {len(image_data)}")
# ์ด๋ฏธ์ง ๋ฐ์ดํฐ๋ฅผ PIL Image ๊ฐ์ฒด๋ก ๋ณํ
image = Image.open(io.BytesIO(image_data))
# PNG ํ์์ผ๋ก ๋ณํ
buffered = io.BytesIO()
image.save(buffered, format="PNG")
# Base64๋ก ์ธ์ฝ๋ฉ
im_b64 = base64.b64encode(buffered.getvalue()).decode("utf-8")
url = "https://api.imgur.com/3/image"
payload = {'image': im_b64, 'type': 'base64'}
headers = {'Authorization': f'Client-ID {IMGUR_CLIENT_ID}'}
logger.debug("Sending request to Imgur API")
response = requests.post(url, headers=headers, data=payload)
logger.debug(f"Imgur API response status: {response.status_code}")
logger.debug(f"Imgur API response content: {response.text}")
response.raise_for_status()
return response.json()['data']['link']
except Exception as e:
logger.error(f"Failed to upload image to Imgur: {e}")
if hasattr(e, 'response'):
logger.error(f"Response content: {e.response.text}")
return None
def send_to_webhook(prompt, image_url):
payload = {
"prompt": prompt,
"image": image_url
}
try:
response = requests.post(WEBHOOK_URL, json=payload)
response.raise_for_status()
logger.info(f"Successfully sent data to webhook. Status code: {response.status_code}")
except requests.exceptions.RequestException as e:
logger.error(f"Failed to send data to webhook: {e}")
def respond(message, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
logger.info(f"Received message: {message}, seed: {seed}, randomize_seed: {randomize_seed}, "
f"width: {width}, height: {height}, guidance_scale: {guidance_scale}, "
f"num_inference_steps: {num_inference_steps}")
try:
# ์ด๋ฏธ์ง ์์ฑ ์์ฒญ
result = api_client.predict(
prompt=message,
seed=seed,
randomize_seed=randomize_seed,
width=width,
height=height,
guidance_scale=guidance_scale,
num_inference_steps=num_inference_steps,
api_name="/infer_t2i"
)
logger.info("API response received: %s", result)
# ๊ฒฐ๊ณผ ํ์ธ ๋ฐ ์ฒ๋ฆฌ
if isinstance(result, tuple) and len(result) >= 1:
local_image_path = result[0]
# ์ด๋ฏธ์ง ํ์ผ์ ๋ฉ๋ชจ๋ฆฌ์ ๋ก๋
with open(local_image_path, "rb") as f:
image_data = f.read()
# Imgur์ ์ด๋ฏธ์ง ์
๋ก๋
imgur_url = upload_to_imgur(image_data)
if imgur_url:
# Webhook์ผ๋ก ๋ฐ์ดํฐ ์ ์ก
send_to_webhook(message, imgur_url)
return Image.open(io.BytesIO(image_data))
else:
raise ValueError("Failed to upload image to Imgur")
else:
raise ValueError("Unexpected API response format")
except Exception as e:
logger.error("Error during API request: %s", str(e))
return "Failed to generate image due to an error."
# ... (๋๋จธ์ง ์ฝ๋๋ ๊ทธ๋๋ก ์ ์ง)
css = """
footer {
visibility: hidden;
}
"""
# ์ด๋ฏธ์ง ์์ฑ์ ์ํ ์์ ํ๋กฌํํธ
examples = [
["A glamorous young woman with long, wavy blonde hair and smokey eye makeup, posing in a luxury hotel room. Sheโs wearing a sparkly gold cocktail dress and holding up a white card with 'openfree.ai' written on it in elegant calligraphy. Soft, warm lighting creates a luxurious atmosphere. ", "q1.webp"],
["A fit male fitness influencer with short dark hair and stubble, standing shirtless in a modern gym. He has defined abs and arm muscles, and is holding a protein shake in one hand and a card that says 'openfree.ai' in the other. Bright, clean lighting highlights his physique.", "q2.webp"],
["A bohemian-style female travel blogger with sun-kissed skin and messy beach waves, sitting on a tropical beach at sunset. Sheโs wearing a flowy white sundress and holding up a weathered postcard with 'openfree.ai' scrawled on it. Golden hour lighting bathes the scene in warm tones. ", "q3.webp"],
["A trendy male fashion influencer with perfectly styled hair and designer stubble, posing on a city street. Heโs wearing a tailored suit and holding up a sleek black business card with 'openfree.ai' printed in minimalist white font. The background shows blurred city lights, creating a chic urban atmosphere.", "q4.webp"],
["A fresh-faced young female beauty guru with freckles and natural makeup, sitting at a vanity covered in cosmetics. Sheโs wearing a pastel pink robe and holding up a makeup palette with 'openfree.ai' written on it in lipstick. Soft, flattering lighting enhances her radiant complexion. ", "q5.webp"],
["A stylish young woman with long, wavy ombre hair and winged eyeliner, posing in front of a neon-lit city skyline at night. Sheโs wearing a sleek black leather jacket over a sparkly crop top and holding up a holographic business card that says 'openfree.ai' in futuristic font. The card reflects the colorful neon lights, creating a cyberpunk aesthetic.", "q6.webp"],
["Create a surreal advertisement poster for a fictional time travel agency. The background should depict a swirling vortex of clock faces and historical landmarks from different eras. In the foreground, place large, bold text that reads โAI TOURS: YOUR PAST IS OUR FUTUREโ in a retro-futuristic font. The text should appear to be partially disintegrating into particles that are being sucked into the time vortex. Include smaller text at the bottom with fictional pricing and the slogan โHistory is just a ticket away!โ", "q7.webp"],
["Photo realistic scene inspired by LOTR: [A tiny red dragon sleeps curled up in a nest on a medieval wizard's table]. Shot with a macro lens (f/2.8, 50mm) and a Canon EOSR5, the soft focus captures [the cozy morning light filtering through a near by window]. The pastel colors and whimsical steam shapes enhance the serene atmosphere, evoking a DnD RPG setting. The image is rendered in 16K and 8K, highlighting [the intricate details and medieval charm].", "q8.webp"],
["์ฌ๊ธ๋ผ์ค๋ฅผ ์ฐฉ์ฉํ ๊ท์ฌ์ด ๊ฐ์์ง๊ฐ 'Openfree.ai'๋ผ๊ณ ์ฐ์ฌ์ง ํ์งํ์ ๋ค๊ณ ์๋ค.", "q9.webp"],
["๋ฏธ๋ ์ ์ธ ๋์์ ํด์ง๋ ํ๊ฒฝ", "q10.webp"],
["๋นจ๊ฐ์ ๋ฐ์ค์ 'openfree.ai'๋ผ๊ณ ๊ธ์จ๊ฐ ์ฐ์ฌ์๊ณ , ๊ทธ์์ ๊ฐ์์ง์ ๊ณ ์์ด๊ฐ ์์์๋ค.", "q11.webp"],
["๋ก๋ด์ด ๊ณต์ฌ์ฅ์์ ์์
์ค์ด๋ค. ๋ฐฐ๊ฒฝ์ 'Coming soon~'๋ผ๋ ๊ธ์๊ฐ ์ฐ์ฌ์๋ค.", "q20.webp"],
["A serene landscape with mountains in the background and a clear lake in the foreground.", "q12.webp"],
["A street scene from Tokyo at night, vibrant and full of lights.", "q13.webp"],
["An astronaut riding a horse on Mars.", "q14.webp"],
["A surreal painting of a tree growing books.", "q15.webp"],
["A cottage in a snowy forest, lit by warm lights.", "q16.webp"],
["A still life of various fruits and a wine glass on a table.", "q17.webp"],
["A digital artwork of a neon-lit alley in a cyberpunk city.", "q18.webp"],
["A fantasy map of a fictional world, with detailed terrain and cities.", "q19.webp"]
]
def use_prompt(prompt):
return prompt
with gr.Blocks(theme="Nymbo/Nymbo_Theme", css=css) as demo:
with gr.Row():
input_text = gr.Textbox(label="Enter your prompt for image generation")
output_image = gr.Image(label="Generated Image")
with gr.Row():
seed = gr.Slider(minimum=0, maximum=1000000, step=1, label="Seed", value=123)
randomize_seed = gr.Checkbox(label="Randomize Seed", value=False)
with gr.Row():
width = gr.Slider(minimum=256, maximum=1024, step=64, label="Width", value=1024)
height = gr.Slider(minimum=256, maximum=1024, step=64, label="Height", value=576)
with gr.Row():
guidance_scale = gr.Slider(minimum=1, maximum=20, step=0.1, label="Guidance Scale", value=5)
num_inference_steps = gr.Slider(minimum=1, maximum=100, step=1, label="Number of Inference Steps", value=28)
with gr.Row():
for prompt, image_file in examples:
with gr.Column():
gr.Image(image_file, label=prompt[:50] + "...") # ํ๋กฌํํธ์ ์ฒ์ 50์๋ง ํ์
gr.Button("Use this prompt").click(
fn=use_prompt,
inputs=[],
outputs=input_text,
api_name=False
).then(
lambda x=prompt: x,
inputs=[],
outputs=input_text
)
input_text.submit(
fn=respond,
inputs=[input_text, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
outputs=output_image
)
if __name__ == "__main__":
logger.info(f"Starting application with Imgur Client ID: {IMGUR_CLIENT_ID[:5]}...")
demo.launch() |