Update app.py

app.py

@@ -1,5 +1,8 @@
-!pip install  -U transformers
+!pip install -U transformers sounddevice
+
 import streamlit as st
+import sounddevice as sd
+import soundfile as sf
 from transformers import pipeline
 
 # Load the model pipeline
@@ -31,11 +34,16 @@ def classify_audio(audio_input):
 # Streamlit app
 def main():
     st.title("Stutter Classification App")
-    st.audio("path_to_your_audio_file", format="audio/wav")  # Add audio input widget here
-    if st.button("Classify"):
-        audio_input = st.audio("path_to_your_audio_file", format="audio/wav")  # Add audio input widget here
-        stutter_type = classify_audio(audio_input)
-        st.write("Predicted Stutter Type:", stutter_type)
+    audio_input = st.audio("Capture Audio", format="audio/wav", start_recording=True, channels=1)
+    if st.button("Stop Recording"):
+        sd.stop()
+        with st.spinner("Classifying..."):
+            # Read the recorded audio file
+            recording_path = "recording.wav"
+            audio_data, sampling_rate = sf.read(recording_path)
+            # Classify the audio
+            stutter_type = classify_audio(audio_data)
+            st.write("Predicted Stutter Type:", stutter_type)
 
 if __name__ == "__main__":
     main()