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import gradio as gr
from huggingface_hub import InferenceClient
import os
# Usa tu token de Hugging Face (guárdalo como variable de entorno HF_TOKEN)
HF_TOKEN = os.getenv("HF_TOKEN")
# Cliente de inferencia
client = InferenceClient(api_key=HF_TOKEN)
def generate_image(prompt, steps, guidance):
"""
Genera una imagen con Flux.1 Schnell usando Hugging Face Inference API.
"""
image = client.text_to_image(
model="black-forest-labs/flux-1-schnell", # Modelo Flux
inputs=prompt,
parameters={
"num_inference_steps": steps,
"guidance_scale": guidance
}
)
return image
# Interfaz con Gradio
with gr.Blocks() as demo:
gr.Markdown("# 🚀 Generador de imágenes con Flux.1 Schnell")
with gr.Row():
prompt = gr.Textbox(label="Prompt", value="Astronauta montando un caballo")
with gr.Row():
steps = gr.Slider(1, 50, value=5, step=1, label="Pasos de inferencia")
guidance = gr.Slider(1, 20, value=7, step=1, label="Guidance scale")
output = gr.Image(type="pil")
btn = gr.Button("Generar imagen")
btn.click(generate_image, [prompt, steps, guidance], output)
demo.launch() |