Update app.py

app.py

@@ -70,29 +70,24 @@ def transcribe_audio(openai_key, file_path, model):
         st.write(response.json())
         st.error("Error in API call.")
         return None
-        
-def save_and_play_audio(audio_recorder):
-    col1 = st.sidebar.columns([1])  # adjust the ratio as needed
-    with col1:
-        try:
-            audio_bytes = audio_recorder()
-            if audio_bytes:
-                filename = generate_filename("Recording", "wav")
-                with open(filename, 'wb') as f:
-                    f.write(audio_bytes)
-                st.audio(audio_bytes, format="audio/wav")
-                return filename
-        except Exception as e:
-            st.error(f"Error occurred while processing audio recording")    
-    return None
 
+def save_and_play_audio(audio_recorder):
+    audio_bytes = st.sidebar.audio_recorder()
+    if audio_bytes:
+        filename = generate_filename("Recording", "wav")
+        with open(filename, 'wb') as f:
+            f.write(audio_bytes)
+        st.audio(audio_bytes, format="audio/wav")
+        return filename
 # Updated to call direct from transcription to chat inference.
-filename = save_and_play_audio(audio_recorder)
-if filename is not None:
-    #if st.button("Transcribe"):
-    transcription = transcribe_audio(openai.api_key, filename, "whisper-1")
-    st.markdown('### Transcription:')
-    st.write(transcription)
+USEAUDIO=False
+if USEAUDIO:
+    filename = save_and_play_audio(audio_recorder)
+    if filename is not None:
+        #if st.button("Transcribe"):
+        transcription = transcribe_audio(openai.api_key, filename, "whisper-1")
+        st.markdown('### Transcription:')
+        st.write(transcription)
 
 def truncate_document(document, length):
     return document[:length]