Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+import numpy as np
+from scipy.io.wavfile import write
+
+# Title of the Streamlit app
+st.title("Text-to-Audio Generation App")
+
+# Text area for user input
+text_input = st.text_area('Enter text to generate audio!')
+
+# Create the audio generation pipeline
+try:
+    pipe = pipeline(model="suno/bark-small")
+except ImportError as e:
+    st.error(f"Error importing pipeline from transformers: {e}")
+    st.stop()
+
+# Generate audio based on user input
+if text_input:
+    with st.spinner('Generating audio...'):
+        output = pipe(text_input)
+
+        # Extract audio array and sampling rate from the output
+        audio_array = output["audio"]
+        sampling_rate = output["sampling_rate"]
+        
+        # Ensure the audio array is a numpy array
+        audio_array = np.array(audio_array, dtype=np.float32)
+        
+        # Squeeze to remove single-dimensional entries from the shape of the array
+        audio_array = np.squeeze(audio_array)
+        
+        # Save the audio array as a WAV file
+        write("output.wav", sampling_rate, audio_array)
+
+        # Read the saved WAV file
+        audio_file = open("output.wav", "rb")
+        audio_bytes = audio_file.read()
+        
+        # Display the output audio
+        st.audio(audio_bytes, format="audio/wav")
+
+# Optional: Display JSON output for debugging
+if st.checkbox('Show raw output'):
+    st.json(output)