Update app.py

app.py

@@ -1,18 +1,16 @@
-# Import required libraries
-from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
+# Importing necessary libraries
 import gradio as gr
+from transformers import pipeline
+from speechbrain.pretrained import Tacotron2, HIFIGAN, EncoderDecoderASR
 import matplotlib.pyplot as plt
 import pandas as pd
-from speechbrain.pretrained import Tacotron2, HIFIGAN, EncoderDecoderASR
 
-# Load Hugging Face psychometric model
-psych_model_name = "KevSun/Personality_LM"  # Big Five personality traits
+# Initialize psychometric model
+psych_model_name = "KevSun/Personality_LM"
 psych_model = pipeline("text-classification", model=psych_model_name)
 
-# Load ASR model
+# Initialize ASR and TTS models
 asr_model = EncoderDecoderASR.from_hparams(source="speechbrain/asr-crdnn-rnnlm-librispeech", savedir="tmp_asr")
-
-# Load TTS model
 tts_model = Tacotron2.from_hparams(source="speechbrain/tts-tacotron2-ljspeech", savedir="tmp_tts")
 voc_model = HIFIGAN.from_hparams(source="speechbrain/tts-hifigan-ljspeech", savedir="tmp_voc")
 
@@ -28,7 +26,7 @@ audio_questions = [
     "How do you handle stressful situations?"
 ]
 
-# Function to analyze text response
+# Function to analyze text responses
 def analyze_text_responses(responses):
     analysis = [psych_model(response)[0] for response in responses]
     traits = {response["label"]: response["score"] for response in analysis}
@@ -77,8 +75,9 @@ def chat_interface(candidate_name, text_responses, audio_responses):
     audio_df, audio_plot = audio_part(candidate_name, audio_responses)
     return text_df, text_plot, audio_df, audio_plot
 
+# Create text inputs and audio inputs
 text_inputs = [gr.Textbox(label=f"Response to Q{i+1}: {q}") for i, q in enumerate(text_questions)]
-audio_inputs = [gr.Audio(label=f"Response to Q{i+1}: {q}", type="file") for i, q in enumerate(audio_questions)]
+audio_inputs = [gr.Audio(label=f"Response to Q{i+1}: {q}", type="filepath") for i, q in enumerate(audio_questions)]
 
 interface = gr.Interface(
     fn=chat_interface,
@@ -87,5 +86,5 @@ interface = gr.Interface(
     title="Psychometric Analysis Chatbot"
 )
 
-# Launch chatbot
-interface.launch()
+# Launch the interface
+interface.launch()