Create app.py

app.py

@@ -0,0 +1,36 @@
+import gradio as gr
+import math
+import time
+
+def stream(audio, chunk_length_s):
+    start_time = time.time()
+    sampling_rate, array = audio
+    chunk_length = int(chunk_length_s * sampling_rate)
+    time_length = chunk_length_s / 2  # always stream outputs faster than it takes to process
+    audio_length = len(array)
+    num_batches = math.ceil(audio_length / chunk_length)
+
+    for idx in range(num_batches):
+        time.sleep(time_length)
+        start_pos = idx * chunk_length
+        end_pos = min((idx + 1) * chunk_length, audio_length)
+        chunk = array[start_pos : end_pos]
+        if idx == 0:
+            first_time = round(time.time() - start_time, 2)
+        run_time = round(time.time() - start_time, 2)
+        yield (sampling_rate, chunk), first_time, run_time
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            audio_in = gr.Audio(value="librispeech.wav", sources=["upload"], type="numpy")
+            chunk_length = gr.Slider(minimum=1, maximum=3, value=2, step=1, label="Chunk length (s)")
+            run_button = gr.Button("Stream audio")
+        with gr.Column():
+            audio_out = gr.Audio(streaming=True, autoplay=True)
+            first_time = gr.Textbox(label="Time to first chunk (s)")
+            run_time = gr.Textbox(label="Time to current chunk (s)")
+
+    run_button.click(fn=stream, inputs=[audio_in, chunk_length], outputs=[audio_out, first_time, run_time])
+
+demo.launch()