Audio display

app.py

@@ -4,50 +4,51 @@ import scipy.io.wavfile
 import tempfile
 import numpy as np
 
-
 # -----------------------------------------------------------
 def load_css(file_path):
     with open(file_path) as f:
         css_to_load = f.read()
         st.markdown(f"<style>{css_to_load}</style>", unsafe_allow_html=True)
 
-
 # -----------------------------------------------------------
 def load_model():
+    # Initializes and returns the pipeline for text-to-audio generation
     return pipeline("text-to-audio", model="facebook/musicgen-small")
 
-
 # -----------------------------------------------------------
 def main():
     try:
-        st.set_page_config(page_title="Text to Music", page_icon="Music")
+        st.set_page_config(page_title="Text to Music", page_icon="🎵")
         load_css("styles/styles.css")
         st.title("Turn Your Text Into Music")
 
+        # Load the model
         synthesizer = load_model()
         user_text = st.text_area("What type of beat would you like to hear: ")
 
+        # Generate and play music based on user input
         if user_text:
+            # Generate music with the synthesizer
             music = synthesizer(user_text, forward_params={"do_sample": True})
 
+            # Create a temporary file to store the generated audio
             with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp:
                 print(f"Temporary file created at: {tmp.name}")
-                # Ensure the audio data is in the correct format (int16 for WAV)
+                
+                # Check if the audio data needs scaling and convert to int16
                 if music["audio"].dtype != np.int16:
-                    # Assuming the audio is normalized between -1 and 1, scale to int16
                     audio_data = np.int16(music["audio"] / np.max(np.abs(music["audio"])) * 32767)
                 else:
                     audio_data = music["audio"]
                 
-                # Write the audio data to the temporary file
+                # Write the scaled audio data to the temporary WAV file
                 scipy.io.wavfile.write(tmp.name, rate=music["sampling_rate"], data=audio_data)
                 
-                # Display the audio player in Streamlit
-                st.audio(tmp.name, format="audio/wav", start_time=0)
+                # Use Streamlit's audio widget to display the audio player
+                st.audio(tmp.name, format="audio/wav")
 
     except Exception as e:
-        st.error(e)
-
+        st.error(f"An error occurred: {e}")
 
 # -----------------------------------------------------------