app.py

import gradio as gr
from utils import load_model, generate_image, prompt_presets

pipe = load_model()

with gr.Blocks(css="style.css") as demo:
    gr.Markdown("# 🚀 Scriptify AI - Ultra Image Generator with ControlNet + Voice")
    gr.Markdown("Create beautiful, controlled images using AI. Supports voice prompts, styles, and ControlNet!")

    with gr.Row():
        prompt_input = gr.Textbox(placeholder="e.g., cinematic shot of a samurai in rain", label="📝 Text Prompt", lines=2)
        voice_input = gr.Audio(source="microphone", type="filepath", label="🎤 Or Speak Prompt")

    with gr.Accordion("🔧 Advanced Settings", open=False):
        with gr.Row():
            style_dropdown = gr.Dropdown(choices=list(prompt_presets.keys()), value="None", label="🎨 Style Presets")
            guidance = gr.Slider(minimum=1, maximum=20, value=7.5, label="🎚️ Guidance Scale")
            steps = gr.Slider(minimum=10, maximum=50, value=30, label="🧠 Inference Steps")

        with gr.Row():
            width = gr.Slider(minimum=512, maximum=1024, step=64, value=768, label="🖼️ Width")
            height = gr.Slider(minimum=512, maximum=1024, step=64, value=768, label="🖼️ Height")

    generate_button = gr.Button("✨ Generate Image")
    output_image = gr.Image(type="pil", label="🖼️ Result Image")
    status = gr.Textbox(visible=False)

    def run(prompt, voice, style, guidance, steps, width, height):
        import whisper
        if voice:
            model = whisper.load_model("base")
            result = model.transcribe(voice)
            prompt = result["text"]

        if style != "None":
            prompt = f"{prompt}, {prompt_presets[style]}"
        try:
            image = generate_image(pipe, prompt, guidance, steps, width, height)
            return image, ""
        except Exception as e:
            return None, f"⚠️ {str(e)}"

    generate_button.click(fn=run,
                          inputs=[prompt_input, voice_input, style_dropdown, guidance, steps, width, height],
                          outputs=[output_image, status])

demo.launch()