app.py

import gradio as gr

from prog.image import detect_image
from prog.audio import detect_audio
from prog.video import detect_video

print(" DeepGuard Premium UI Running...")

def detect(file):

    if file is None:
        return " Please upload a file"

    name = file.name.lower()

    try:
        if name.endswith((".jpg", ".jpeg", ".png")):
            return detect_image(file.name)

        elif name.endswith((".wav", ".mp3", ".ogg")):
            return detect_audio(file.name)

        elif name.endswith((".mp4", ".avi", ".mov")):
            return detect_video(file.name)

        else:
            return " Unsupported file format"

    except Exception as e:
        return f"Error: {str(e)}"

with gr.Blocks(theme=gr.themes.Soft(), css="""
body {background: #0f172a;}
.card {border-radius: 12px; padding: 15px; background: #1e293b;}
.result {font-size: 18px; font-weight: bold;}
""") as demo:

    # HEADER
    gr.Markdown("""
      DeepGuard AI
     Multi-Modal Deepfake Detection System
    """)

    with gr.Row():

        # LEFT PANEL
        with gr.Column(scale=1):
            gr.Markdown(" Upload File")

            file_input = gr.File(label="Upload Image / Audio / Video")

            analyze_btn = gr.Button(" Analyze", variant="primary")
            clear_btn = gr.Button("Clear")

        # RIGHT PANEL
        with gr.Column(scale=2):

            gr.Markdown(" Result")

            output = gr.Textbox(
                label="Detection Output",
                lines=10
            )

    # FOOTER
    gr.Markdown("This system uses AI predictions and may not be 100% accurate.")

    # BUTTON ACTIONS
    analyze_btn.click(detect, inputs=file_input, outputs=output)
    clear_btn.click(lambda: "", None, output)
if __name__ == "__main__":
    demo.launch()