Update app.py

app.py

@@ -11,7 +11,7 @@ client = Groq(api_key=os.getenv("GROQ_API_KEY"))
 
 # Streamlit UI
 st.title("Voice Cloning Application")
-st.markdown("Clone your voice using Groq's Whisper Model and generate natural responses.")
+st.markdown("Clone your voice using Groq's Whisper Model for transcription.")
 
 # Upload audio file
 uploaded_file = st.file_uploader(
@@ -24,34 +24,21 @@ if uploaded_file is not None:
     st.audio(uploaded_file, format=f"audio/{uploaded_file.type.split('.')[-1]}")
     st.write("Transcription in progress...")
 
-    # Transcription Logic
+    # Read file contents as binary
+    audio_bytes = uploaded_file.read()
+
     try:
-        transcription = client.chat.completions.create(
-            messages=[
-                {
-                    "role": "user",
-                    "content": f"Transcribe the following audio file: {uploaded_file.name}"
-                }
-            ],
+        # Transcription request to the Whisper model
+        transcription = client.audio.transcriptions.create(
+            file=audio_bytes,
             model="whisper-large-v3-turbo",
+            response_format="text",  # Options: "text", "json"
         )
 
         # Display the transcription
-        transcribed_text = transcription.choices[0].message.content
         st.success("Transcription completed!")
-        st.write("**Transcribed Text:**", transcribed_text)
-
-        # Placeholder for voice cloning (TTS integration can go here)
-        st.markdown("---")
-        st.subheader("Generate Speech from Transcription")
-        tts_input = st.text_area("Enter text to generate speech:", value=transcribed_text)
-
-        if st.button("Generate Speech"):
-            if tts_input:
-                # Simulate TTS functionality (placeholder for TTS model integration)
-                st.success("Generated speech successfully! (Placeholder)")
-            else:
-                st.warning("Please enter some text.")
+        st.write("**Transcribed Text:**")
+        st.text_area("Transcription", transcription, height=200)
 
     except Exception as e:
         st.error(f"Error during transcription: {e}")