Update app.py

app.py

@@ -1,6 +1,19 @@
-import random
+import numpy as np
 from pydub import AudioSegment
 
+def sine_wave(frequency, duration_ms):
+    """Generate a sine wave tone at a given frequency and duration."""
+    sample_rate = 44100  # Sample rate in Hz
+    t = np.linspace(0, duration_ms / 1000, int(sample_rate * (duration_ms / 1000)), False)
+    wave = 0.5 * np.sin(2 * np.pi * frequency * t)  # Sine wave formula
+    audio_segment = AudioSegment(
+        wave.tobytes(), 
+        frame_rate=sample_rate,
+        sample_width=2,  # 16-bit audio
+        channels=1  # Mono audio
+    )
+    return audio_segment
+
 def generate_kids_music(theme):
     # Create a simple melody based on themes
     notes = {
@@ -10,19 +23,30 @@ def generate_kids_music(theme):
     }
     
     selected_notes = notes.get(theme, ["C4", "E4", "G4"])  # Default notes if theme not found
-    music = AudioSegment.silent(duration=1000)  # Start with 1 second of silence
+    music = AudioSegment.silent(duration=0)  # Start with silence
     
+    # Define frequencies for notes
+    frequencies = {
+        "C4": 261.63,
+        "D4": 293.66,
+        "E4": 329.63,
+        "F4": 349.23,
+        "G4": 392.00,
+        "A4": 440.00,
+        "C5": 523.25
+    }
+
     for note in selected_notes:
-        # Generate a simple sine wave for each note
-        frequency = 261.63 if note == "C4" else 329.63 if note == "E4" else 392.00 if note == "G4" else 523.25
-        sine_wave = AudioSegment.sine(frequency=frequency, duration=500)  # 0.5 second for each note
-        music += sine_wave
+        frequency = frequencies[note]
+        sine = sine_wave(frequency, duration_ms=500)  # 0.5 second for each note
+        music += sine
         
     # Export the generated music
     output_file = f"{theme}_kids_music.wav"
     music.export(output_file, format="wav")
     return output_file
 
+
 from transformers import pipeline
 
 # Load the GPT-2 model for text generation