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# gradio_interface.py (HuggingFace Spaces)
import gradio as gr
from config.config import prompts, models, api_token # Direct import
from src.img_gen import generate_image
# Gradio Interface
def gradio_interface():
with gr.Blocks(css="""
.output-image img {
width: 2500px; /* Force image to fill container width */
object-fit: cover; /* ACTIVATE FOR IMAGE-FIT CONTAINER */
}
""") as demo:
gr.Markdown("# CtB AI Image Generator - Inference version (HF)")
with gr.Row():
# Set default values for dropdowns
prompt_dropdown = gr.Dropdown(choices=[p["alias"] for p in prompts], label="Select Prompt", value=prompts[0]["alias"])
team_dropdown = gr.Dropdown(choices=["Red", "Blue"], label="Select Team", value="Red")
#model_dropdown = gr.Dropdown(choices=[m["alias"] for m in models], label="Select Model", value=models[0]["alias"])
with gr.Row():
# Add a text box for custom user input (max 200 characters)
custom_prompt_input = gr.Textbox(label="Custom Prompt (Optional)", placeholder="Enter additional details (max 200 chars)...", max_lines=1, max_length=200)
with gr.Row():
generate_button = gr.Button("Generate Image")
with gr.Row():
output_image = gr.Image(elem_classes="output-image", label="Generated Image", show_label=False, scale=1, width="100%")
with gr.Row():
status_text = gr.Textbox(label="Status", placeholder="Waiting for input...", interactive=False)
# Connect the button to the function
generate_button.click(
generate_image,
inputs=[prompt_dropdown,
team_dropdown,
custom_prompt_input,
#model_dropdown,
],
outputs=[output_image, status_text]
)
return demo
# Create the demo instance
demo = gradio_interface()
# Only launch if running directly
if __name__ == "__main__":
demo.queue().launch() |