Add librosa to requirements.txt and include ffmpeg in packages.txt

app.py

@@ -2,36 +2,8 @@ import gradio as gr
 import numpy as np
 import librosa
 import soundfile as sf
-import json
-import websocket
-import threading
-import time
 from io import BytesIO
 
-# Global variables for WebSocket communication
-ws = None
-clients = []
-
-# WebSocket server to send visualization data to frontend
-def start_websocket_server():
-    def on_open(ws):
-        print("WebSocket server opened")
-        clients.append(ws)
-
-    def on_close(ws):
-        print("WebSocket server closed")
-        clients.remove(ws)
-
-    def on_message(ws, message):
-        print(f"Received: {message}")
-
-    global ws
-    ws = websocket.WebSocketApp("ws://localhost:8765",
-                                on_open=on_open,
-                                on_message=on_message,
-                                on_close=on_close)
-    threading.Thread(target=ws.run_forever, daemon=True).start()
-
 # Process audio file or recording
 def process_audio(audio_input, sample_rate=44100):
     # Handle Gradio audio input (tuple of (sample_rate, numpy_array))
@@ -56,34 +28,23 @@ def process_audio(audio_input, sample_rate=44100):
         "volume": float(np.mean(np.abs(audio_data)) * 100)
     }
 
-    # Send data to connected WebSocket clients
-    if ws and clients:
-        for client in clients:
-            try:
-                client.send(json.dumps(vis_data))
-            except:
-                pass
+    # Save audio to a temporary file for playback
+    temp_audio = BytesIO()
+    sf.write(temp_audio, audio_data, sr, format='wav')
+    temp_audio.seek(0)
 
-    return vis_data, audio_data, sr
+    return vis_data, temp_audio
 
 # Gradio interface function
 def audio_visualizer(audio_file, audio_record):
     if audio_file:
-        vis_data, audio_data, sr = process_audio(audio_file)
+        vis_data, audio_output = process_audio(audio_file)
     elif audio_record:
-        vis_data, audio_data, sr = process_audio(audio_record)
+        vis_data, audio_output = process_audio(audio_record)
     else:
-        return "Please upload an audio file or record audio."
-
-    # Save audio to a temporary file for playback
-    temp_audio = BytesIO()
-    sf.write(temp_audio, audio_data, sr, format='wav')
-    temp_audio.seek(0)
-
-    return vis_data, temp_audio
+        return "Please upload an audio file or record audio.", None
 
-# Start WebSocket server
-start_websocket_server()
+    return vis_data, audio_output
 
 # Gradio interface
 with gr.Blocks() as demo: