Update app.py

app.py

@@ -32,11 +32,9 @@ def generate_music_tensors(descriptions, duration: int):
     st.success("Music Generation Complete!")
     return output
 
-
 def save_audio(samples: torch.Tensor):
     sample_rate = 30000
-    # save_path = "/content/drive/MyDrive/Colab Notebooks/audio_output"
-    save_path= "audio_output/"
+    save_path = "audio_output/"
     assert samples.dim() == 2 or samples.dim() == 3
 
     samples = samples.detach().cpu()
@@ -55,13 +53,13 @@ def get_binary_file_downloader_html(bin_file, file_label='File'):
     return href
 
 st.set_page_config(
-    page_icon= "musical_note",
-    page_title= "Music Gen"
+    page_icon="musical_note",
+    page_title="Music Gen"
 )
 
 def main():
     with st.sidebar:
-        st.header("""⚙️Generate Music ⚙️""",divider="rainbow")
+        st.header("""⚙️Generate Music ⚙️""", divider="rainbow")
         st.text("")
         st.subheader("1. Enter your music description.......")
         bpm = st.number_input("Enter Speed in BPM", min_value=60)
@@ -70,49 +68,42 @@ def main():
         st.text('')
         # Dropdown for genres
         selected_genre = st.selectbox("Select Genre", genres)
-        
+
         st.subheader("2. Select time duration (In Seconds)")
         time_slider = st.slider("Select time duration (In Seconds)", 0, 60, 10)
 
     st.title("""🎵 Song Lab AI 🎵""")
     st.text('')
-    left_co,right_co = st.columns(2)
+    left_co, right_co = st.columns(2)
     left_co.write("""Music Generation through a prompt""")
     left_co.write(("""PS : First generation may take some time ......."""))
 
-
-if st.sidebar.button('Generate !'):
-     with left_co:
-         st.text('')
-         st.text('')
-         st.text('')
-         st.text('')
-         st.text('')
-         st.text('')
-         st.subheader("Generated Music")
-
-         # Generate audio
-         descriptions = [f"{text_area} {selected_genre} {bpm} BPM" for _ in range(5)]  # Adjust the batch size (5 in this case)
-         music_tensors = generate_music_tensors(descriptions, time_slider)
-
-         # Only play the full audio for index 0
-         idx = 0
-         music_tensor = music_tensors[idx]
-         save_music_file = save_audio(music_tensor)
-         # audio_filepath = f'/content/drive/MyDrive/Colab Notebooks/audio_output/audio_{idx}.wav'
-         audio_filepath = 'audio_output/audio_0.wav'
-         audio_file = open(audio_filepath, 'rb')
-         audio_bytes = audio_file.read()
-
-         # Play the full audio
-         st.audio(audio_bytes, format='audio/wav')
-         st.markdown(get_binary_file_downloader_html(audio_filepath, 'Audio'), unsafe_allow_html=True)
-
-save_path = "audio_output/"
-os.makedirs(save_path, exist_ok=True)  # Create the directory if it doesn't exist
-
-
+    if st.sidebar.button('Generate !'):
+        with left_co:
+            st.text('')
+            st.text('')
+            st.text('')
+            st.text('')
+            st.text('')
+            st.text('')
+            st.subheader("Generated Music")
+
+            # Generate audio
+            descriptions = [f"{text_area} {selected_genre} {bpm} BPM" for _ in range(5)]  # Adjust the batch size (5 in this case)
+            music_tensors = generate_music_tensors(descriptions, time_slider)
+
+            # Only play the full audio for index 0
+            idx = 0
+            music_tensor = music_tensors[idx]
+            save_music_file = save_audio(music_tensor)
+            # audio_filepath = f'/content/drive/MyDrive/Colab Notebooks/audio_output/audio_{idx}.wav'
+            audio_filepath = 'audio_output/audio_0.wav'
+            audio_file = open(audio_filepath, 'rb')
+            audio_bytes = audio_file.read()
+
+            # Play the full audio
+            st.audio(audio_bytes, format='audio/wav')
+            st.markdown(get_binary_file_downloader_html(audio_filepath, 'Audio'), unsafe_allow_html=True)
 
 if __name__ == "__main__":
     main()
-