Added transcribe

app.py

@@ -1,4 +1,34 @@
 import streamlit as st
+import whisper
+import os
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+# Load the Whisper model
+model = whisper.load_model("base")  # You can choose "tiny", "small", "medium", or "large"
+
+def transcribe_audio(audio_file):
+    # Save the uploaded audio file to a temporary location
+    temp_file_path = "temp_audio.wav"
+    with open(temp_file_path, "wb") as f:
+        f.write(audio_file.getbuffer())
+
+    # Transcribe the audio
+    result = model.transcribe(temp_file_path)
+    os.remove(temp_file_path)  # Clean up the temporary file
+    return result['text']
+
+# Streamlit app layout
+st.title("Audio Transcription App")
+st.write("Upload an audio file to transcribe it using Whisper.")
+
+# File uploader for audio files
+audio_file = st.file_uploader("Choose an audio file", type=["wav", "mp3", "m4a"])
+
+if audio_file is not None:
+    st.audio(audio_file, format='audio/wav')
+    
+    # Transcribe the audio when the button is clicked
+    if st.button("Transcribe"):
+        with st.spinner("Transcribing..."):
+            transcription = transcribe_audio(audio_file)
+        st.success("Transcription complete!")
+        st.text_area("Transcription:", transcription, height=300)