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import gradio as gr
import requests
import os
from PIL import Image
from io import BytesIO
from tqdm import tqdm
import time
# Definindo as informações do repositório e a trigger word
repo = "artificialguybr/StudioGhibli.Redmond-V2"
trigger_word = "Studio Ghibli, StdGBRedmAF"
def generate_image(prompt):
api_url = f"https://api-inference.huggingface.co/models/{repo}"
#token = os.getenv("API_TOKEN") # Descomente e use seu token da API do Hugging Face
headers = {
#"Authorization": f"Bearer {token}"
}
full_prompt = f"{prompt} {trigger_word}"
payload = {
"inputs": full_prompt,
"parameters": {
"negative_prompt": "bad art, ugly, watermark, deformed",
"num_inference_steps": 30,
"scheduler": "DPMSolverMultistepScheduler"
},
}
error_count = 0
pbar = tqdm(total=None, desc="Loading model")
while True:
response = requests.post(api_url, headers=headers, json=payload)
if response.status_code == 200:
return Image.open(BytesIO(response.content)) # Alterado para corresponder ao primeiro código
elif response.status_code == 503:
time.sleep(1)
pbar.update(1)
elif response.status_code == 500 and error_count < 5:
time.sleep(1)
error_count += 1
else:
raise Exception(f"API Error: {response.status_code}")
iface = gr.Interface(
fn=generate_image,
inputs=gr.Textbox(lines=2, placeholder="Digite seu prompt aqui..."),
outputs="image",
title="Gerador de Imagens Studio Ghibli V2",
description="Insira um prompt de texto para gerar uma imagem com o estilo do Studio Ghibli."
)
iface.launch()
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