Update app.py

app.py

@@ -1,19 +1,35 @@
+
+# Step 2: Import Libraries and Set Up Models
+import gradio as gr
+from transformers import pipeline
+from gtts import gTTS
+import os
+import IPython.display as ipd
+
+# Load sentiment analysis and text generation models
+sentiment_model = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")
+text_gen_model = pipeline("text-generation", model="microsoft/DialoGPT-medium")
+
+# Step 3: Define the Response Function
 def virtual_psychologist(input_text):
     # Check for empty or invalid input
     if not input_text.strip():
         return "Please provide some input about how you're feeling.", None, None
 
-    # Sentiment analysis
+    # Step 1: Sentiment Analysis
     sentiment = sentiment_model(input_text)[0]
     label = sentiment['label']
     confidence = sentiment['score']
-    
+
+    # Step 2: Display Sentiment Information
     sentiment_feedback = f"Your input sentiment is detected as **{label}** with confidence {confidence:.2f}.\n\n"
 
-    if confidence > 0.7:  # Confident sentiment analysis
+    # Step 3: Generate a Response Based on Sentiment
+    if confidence > 0.7:  # Threshold for confident sentiment analysis
         if label == 'POSITIVE':
             response = "I'm glad you're feeling positive! Tell me more about what’s bringing you joy, and let’s keep this energy up together."
         elif label == 'NEGATIVE':
+            # Check for sensitive keywords like "suicide" or "worthless"
             if "suicide" in input_text.lower() or "worthless" in input_text.lower():
                 response = ("I'm really sorry you're feeling this way, but please know you're not alone. "
                             "It's really important to talk to someone who can provide support. Would you like to share more "
@@ -25,18 +41,30 @@ def virtual_psychologist(input_text):
     else:
         response = "I'm not quite sure I understand. Could you elaborate a bit more? I'm here to listen."
 
-    # Generate response
+    # Step 4: Generate a Longer Response for the User
     generated_text = text_gen_model(response, max_length=100, num_return_sequences=1)[0]['generated_text']
-    
+
+    # Combine sentiment feedback and generated text into the final output
     full_response = sentiment_feedback + generated_text
-    
+
     # Convert response to speech using gTTS
     tts = gTTS(text=full_response, lang='en')
-    # Save the audio to a temporary location
-    audio_path = "/tmp/response.mp3"
-    tts.save(audio_path)
-    
+    tts.save("response.mp3")
+
+    # Return the response text and audio file path
     response_type = "Supportive Response" if "suicide" in input_text.lower() or "worthless" in input_text.lower() else "General Response"
-    
-    # Return audio file path
-    return full_response, response_type, audio_path
+
+    # Return response as text, response type, and audio file path for Gradio
+    return full_response, response_type, "response.mp3"
+
+# Step 5: Create a Gradio interface for the app
+interface = gr.Interface(
+    fn=virtual_psychologist,
+    inputs=gr.Textbox(lines=5, placeholder="How are you feeling today?"),
+    outputs=[gr.Textbox(), gr.Textbox(), gr.Audio()],
+    title="Virtual Psychologist Assistant",
+    description="Share your feelings, and this assistant will analyze your sentiment and respond as a supportive psychologist."
+)
+
+# Step 6: Launch the Gradio interface
+interface.launch()