Update app.py

app.py

@@ -37,10 +37,17 @@ def generate_audio_question(question):
     waveforms = voc_model.decode_batch(mel_output)
     return waveforms[0].numpy()
 
-# Function to process audio response
 def process_audio_response(audio):
-    text_response = asr_model.transcribe_file(audio)
-    return text_response
+    # Check if the audio input is None
+    if audio is None:
+        return "No audio provided"
+    
+    # Process the audio if it's a valid input
+    try:
+        text_response = asr_model.transcribe_file(audio)
+        return text_response
+    except Exception as e:
+        return f"Error processing audio: {str(e)}"
 
 # Gradio interface functions
 def text_part(candidate_name, responses):
@@ -56,8 +63,14 @@ def text_part(candidate_name, responses):
     return df, plt
 
 def audio_part(candidate_name, audio_responses):
-    text_responses = [process_audio_response(audio) for audio in audio_responses]
-    traits = analyze_text_responses(text_responses)
+    # Check if any audio response is invalid (None)
+    valid_audio_responses = [process_audio_response(audio) for audio in audio_responses if audio is not None]
+    
+    # If all responses are invalid, return an error message
+    if not valid_audio_responses:
+        return "No valid audio responses provided", None
+
+    traits = analyze_text_responses(valid_audio_responses)
     df = pd.DataFrame(traits.items(), columns=["Trait", "Score"])
     plt.figure(figsize=(8, 6))
     plt.bar(df["Trait"], df["Score"], color="lightcoral")
@@ -68,6 +81,7 @@ def audio_part(candidate_name, audio_responses):
     plt.tight_layout()
     return df, plt
 
+
 # Gradio UI function
 def chat_interface(candidate_name, *responses):
     # Separate text responses and audio responses