Update app.py

app.py

@@ -55,8 +55,6 @@
 
 # iface.launch()
 
-
-
 import os
 import gradio as gr
 import whisper
@@ -66,51 +64,53 @@ from groq import Groq
 
 # Initialize the Groq client
 groq_api_key = os.getenv('GROQ_API_KEY')
-client = Groq(api_key=groq_api_key)
+if not groq_api_key:
+    raise ValueError("GROQ_API_KEY environment variable is not set.")
+client = Groq(api_key=groq_api_key) 
 
 # Load the Whisper model
 model = whisper.load_model("base")  # You can choose other models like "small", "medium", "large"
 
 def process_audio(file_path):
-  if not file_path:
-    return "Please upload an audio file.", None
-  try:
-    # Load the audio file
-    audio = whisper.load_audio(file_path)
-
-    # Transcribe the audio using Whisper
-    result = model.transcribe(audio)
-    text = result["text"]
-
-    # Generate a response using Groq
-    chat_completion = client.chat.completions.create(
-      messages=[{"role": "user", "content": text}],
-      model="llama3-8b-8192",  # Replace with the correct model if necessary
-    )
-
-    # Access the response using dot notation
-    response_message = chat_completion.choices[0].message.content.strip()
-
-    # Convert the response text to speech
-    tts = gTTS(response_message)
-    response_audio_io = io.BytesIO()
-    tts.write_to_fp(response_audio_io)  # Save the audio to the BytesIO object
-    response_audio_io.seek(0)
-
-    # Save audio to a file to ensure it's generated correctly
-    with open("response.mp3", "wb") as audio_file:
-      audio_file.write(response_audio_io.getvalue())
-
-    # Return the response text and the path to the saved audio file
-    return response_message, "response.mp3"
-  except Exception as e:
-    return f"An error occurred: {e}", None
+    try:
+        # Load the audio file
+        audio = whisper.load_audio(file_path)
+
+        # Transcribe the audio using Whisper
+        result = model.transcribe(audio)
+        text = result["text"]
+
+        # Generate a response using Groq
+        chat_completion = client.chat.completions.create(
+            messages=[{"role": "user", "content": text}],
+            model="llama3-8b-8192",  # Replace with the correct model if necessary
+        )
+
+        # Access the response using dot notation
+        response_message = chat_completion.choices[0].message.content.strip()
+
+        # Convert the response text to speech
+        tts = gTTS(response_message)
+        response_audio_io = io.BytesIO()
+        tts.write_to_fp(response_audio_io)  # Save the audio to the BytesIO object
+        response_audio_io.seek(0)
+
+        # Save audio to a file to ensure it's generated correctly
+        response_audio_path = "response.mp3"
+        with open(response_audio_path, "wb") as audio_file:
+            audio_file.write(response_audio_io.getvalue())
+
+        # Return the response text and the path to the saved audio file
+        return response_message, response_audio_path
+
+    except Exception as e:
+        return f"An error occurred: {e}", None
 
 iface = gr.Interface(
-  fn=process_audio,
-  inputs=gr.Audio(type="filepath"),  # Use type="filepath"
-  outputs=[gr.Textbox(label="Response Text"), gr.Audio(label="Response Audio")],
-  live=True
+    fn=process_audio,
+    inputs=gr.Audio(type="filepath"),  # Use type="filepath"
+    outputs=[gr.Textbox(label="Response Text"), gr.Audio(label="Response Audio")],
+    live=True
 )
 
 iface.launch()