Upload app.py

app.py

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+import streamlit as st
+import whisper
+
+# Load the Whisper model
+@st.cache_resource
+def load_model():
+    return whisper.load_model("turbo")
+
+model = load_model()
+
+# Streamlit app
+st.title("Audio Transcription App")
+st.header("Using Whisper for Audio Transcription")
+
+# File uploader
+uploaded_file = st.file_uploader("Upload an audio file (e.g., MP3, WAV, etc.)", type=["mp3", "wav", "m4a"])
+
+if uploaded_file is not None:
+    st.audio(uploaded_file, format="audio/mp3", start_time=0)
+
+    # Transcribe button
+    if st.button("Transcribe Audio"):
+        with st.spinner("Transcribing..."):
+            # Save the uploaded file to a temporary location
+            with open("temp_audio_file.mp3", "wb") as temp_file:
+                temp_file.write(uploaded_file.read())
+
+            # Perform transcription
+            result = model.transcribe("temp_audio_file.mp3")
+            transcription_text = result["text"]
+
+            st.success("Transcription Completed!")
+            st.subheader("Transcription:")
+            st.text_area("Here is the transcription:", transcription_text, height=300)
+else:
+    st.info("Please upload an audio file to start the transcription.")