old app

app.py

@@ -1,66 +1,14 @@
-# import gradio as gr
-
-
-# def process(name):
-#     return "Hello re malakako" + name + "!"
-
-
-# with gr.Blocks() as demo:
-#     name = gr.Textbox(label="Score (vextab or musicxml)")
-#     output = gr.Textbox(label="Difficulty Analysis Report")
-#     greet_btn = gr.Button("Process")
-#     greet_btn.click(fn=process, inputs=name, outputs=output, api_name="process")
-
-# demo.launch()
-
-
-import time
 import gradio as gr
 
 
-def fake_diffusion(steps):
-    for i in range(steps):
-        print(f"Current step: {i}")
-        time.sleep(1)
-        yield str(i)
-
-
-def long_prediction(*args, **kwargs):
-    time.sleep(10)
-    return 42
+def process(name):
+    return "Difficulty Report for " + name + "!"
 
 
 with gr.Blocks() as demo:
-    with gr.Row():
-        with gr.Column():
-            n = gr.Slider(1, 10, value=9, step=1, label="Number Steps")
-            run = gr.Button(value="Start Iterating")
-            output = gr.Textbox(label="Iterative Output")
-            stop = gr.Button(value="Stop Iterating")
-        with gr.Column():
-            textbox = gr.Textbox(label="Prompt")
-            prediction = gr.Number(label="Expensive Calculation")
-            run_pred = gr.Button(value="Run Expensive Calculation")
-        with gr.Column():
-            cancel_on_change = gr.Textbox(label="Cancel Iteration and Expensive Calculation on Change")
-            cancel_on_submit = gr.Textbox(label="Cancel Iteration and Expensive Calculation on Submit")
-            echo = gr.Textbox(label="Echo")
-    with gr.Row():
-        with gr.Column():
-            image = gr.Image(sources=["webcam"], label="Cancel on clear", interactive=True)
-        with gr.Column():
-            video = gr.Video(sources=["webcam"], label="Cancel on start recording", interactive=True)
-
-    click_event = run.click(fake_diffusion, n, output)
-    stop.click(fn=None, inputs=None, outputs=None, cancels=[click_event])
-    pred_event = run_pred.click(fn=long_prediction, inputs=[textbox], outputs=prediction)
-
-    cancel_on_change.change(None, None, None, cancels=[click_event, pred_event])
-    cancel_on_submit.submit(lambda s: s, cancel_on_submit, echo, cancels=[click_event, pred_event])
-    image.clear(None, None, None, cancels=[click_event, pred_event])
-    video.start_recording(None, None, None, cancels=[click_event, pred_event])
-
-    demo.queue(max_size=20)
+    name = gr.Textbox(label="Score (vextab or musicxml)")
+    output = gr.Textbox(label="Difficulty Analysis Report")
+    greet_btn = gr.Button("Process")
+    greet_btn.click(fn=process, inputs=name, outputs=output, api_name="process")
 
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()