app.py

import gradio as gr
import os

# ---------- Helpers ----------
def file_if_exists(p):
    return p if os.path.exists(p) else None

# ---------- Case Data ----------
# Case 1 (ALS)
case1_images = ["1.png", "2.png", "3.png", "4.png"]
case1_audio = ["1.wav"]
case1_score = 0.940
case1_text = (
    "A 57-year-old male presents with progressive weakness in his right hand over the past 6 months. "
    "Over the past 2 months, he has noticed slurred speech and difficulty projecting his voice with occasional choking on liquids. "
    "Exam: fasciculations, hyperreflexia, mild dysarthria."
    "Diagnosis: ALS with early bulbar involvement."
)

# Case 2 (Congenital mutism)
case2_images = ["5.png", "6.png", "7.png", "8.png"]
case2_audio = ["1.wav", "2.wav", "3.wav"]
case2_score = 0.750
case2_text = (
    "A 23-year-old male was born with congenital mutism and has never spoken. He now seeks to restore his voice using "
    "rt-MRI of the vocal tract. Normal cognition and hearing. Physical exam shows no structural abnormalities. "
    "Imaging guides personalized speech restoration."
)

# ---------- Step Handlers ----------
def case1_next(step):
    step += 1
    # Show images (steps 1..len(images)-1)
    if step < len(case1_images):
        img = file_if_exists(case1_images[step])
        return step, img, case1_text, None, ""  # audio, score
    # Audio step
    elif step == len(case1_images):
        audio_file = file_if_exists(case1_audio[0])
        return step, None, case1_text, audio_file, ""
    # Score step
    else:
        return step, None, case1_text, None, f"{case1_score:.3f}"

def case2_next(step):
    step += 1
    # Show images (steps 1..len(images)-1)
    if step < len(case2_images):
        img = file_if_exists(case2_images[step])
        return step, img, case2_text, None, None, None, ""  # audios a,b,c, score
    # Audio step: show all three players at once
    elif step == len(case2_images):
        a1 = file_if_exists(case2_audio[0])
        a2 = file_if_exists(case2_audio[1])
        a3 = file_if_exists(case2_audio[2])
        return step, None, case2_text, a1, a2, a3, ""
    # Score step
    else:
        return step, None, case2_text, None, None, None, f"{case2_score:.3f}"

# ---------- UI ----------
with gr.Blocks(css="""
#img1, #img2 { max-height: 70vh; }
""") as demo:
    gr.Markdown("# Voice Reconstruction Demo")

    with gr.Tabs():
        # ---------------- Case 1 ----------------
        with gr.Tab("Case 1: ALS Patient"):
            step1 = gr.State(0)
            with gr.Row():
                # Wider image area (scale=3), smaller case box (scale=2, lines=6)
                img_out1 = gr.Image(
                    value=file_if_exists(case1_images[0]), type="filepath", interactive=False, elem_id="img1", label="Image",
                    show_download_button=False
                )
                text_out1 = gr.Textbox(value=case1_text, label="Case Description", lines=6)

            audio_out1 = gr.Audio(label="Predicted Audio", type="filepath")
            score_out1 = gr.Textbox(label="Score", lines=1)

            with gr.Row():
                next_btn1 = gr.Button("Next Step", variant="primary")
                reset_btn1 = gr.Button("Reset")

            def reset_case1():
                return 0, file_if_exists(case1_images[0]), case1_text, None, ""
            reset_btn1.click(
                fn=reset_case1,
                inputs=[],
                outputs=[step1, img_out1, text_out1, audio_out1, score_out1]
            )

            next_btn1.click(
                fn=case1_next,
                inputs=[step1],
                outputs=[step1, img_out1, text_out1, audio_out1, score_out1]
            )

        # ---------------- Case 2 ----------------
        with gr.Tab("Case 2: Congenital Mutism"):
            step2 = gr.State(0)
            with gr.Row():
                img_out2 = gr.Image(
                    value=file_if_exists(case2_images[0]), type="filepath", interactive=False, elem_id="img2", label="Image",
                    show_download_button=False
                )
                text_out2 = gr.Textbox(value=case2_text, label="Case Description", lines=6)

            with gr.Row():
                audio_out2a = gr.Audio(label="Predicted Audio 1", type="filepath")
                audio_out2b = gr.Audio(label="Predicted Audio 2", type="filepath")
                audio_out2c = gr.Audio(label="Predicted Audio 3", type="filepath")

            score_out2 = gr.Textbox(label="Score", lines=1)

            with gr.Row():
                next_btn2 = gr.Button("Next Step", variant="primary")
                reset_btn2 = gr.Button("Reset")

            def reset_case2():
                return 0, file_if_exists(case2_images[0]), case2_text, None, None, None, ""
            reset_btn2.click(
                fn=reset_case2,
                inputs=[],
                outputs=[step2, img_out2, text_out2, audio_out2a, audio_out2b, audio_out2c, score_out2]
            )

            next_btn2.click(
                fn=case2_next,
                inputs=[step2],
                outputs=[step2, img_out2, text_out2, audio_out2a, audio_out2b, audio_out2c, score_out2]
            )

demo.launch()