Update app.py

app.py

@@ -1,4 +1,5 @@
 #INFERENCE NLP+EMOTION DETECTION CV+TTS+Memory Management
+#INFERENCE NLP+EMOTION DETECTION CV+TTS+Memory Management
 import spaces
 
 import gradio as gr
@@ -466,7 +467,7 @@ def analyze_emotion(image):
 
         output = {}
         for emotion, score in sorted(emotions.items(), key=lambda x: x[1], reverse=True):
-            output[emotion.capitalize()] = score 
+            output[emotion.capitalize()] = score
 
         return output
 
@@ -497,11 +498,11 @@ def chat_with_kenko(message, history):
 
     emotion_context = get_emotion_context()
 
-    threat_context = get_threat_context()
+    # Removed the call to the undefined get_threat_context() function
 
     prompt = f"""### Instruction:
 You are Kenko, a compassionate mental health therapist. Provide empathetic, helpful, and professional responses to support the user's mental wellbeing.
-{emotion_context}{threat_context}
+{emotion_context}
 {conversation}User: {message}
 ### Response:
 """
@@ -597,7 +598,7 @@ with gr.Blocks(
             audio_output = gr.Audio(
                 label="Kenko's Voice Response",
                 autoplay=True,
-                show_label=True
+                show_label=true
             )
 
             with gr.Row():
@@ -632,7 +633,7 @@ with gr.Blocks(
 
             emotion_status = gr.Markdown("*Waiting for emotion data...*")
 
-    
+
     with gr.Row(visible=False) as examples_row:
         gr.Examples(
             examples=[
@@ -707,8 +708,8 @@ with gr.Blocks(
     analyze_emotion,
     inputs=webcam_input,
     outputs=emotion_output,
-    stream_every=1, 
-    time_limit=60   
+    stream_every=1,
+    time_limit=60
 )
 
     timer = gr.Timer(value=5)
@@ -724,6 +725,6 @@ with gr.Blocks(
 if __name__ == "__main__":
     print("🚀 Starting Kenko Mental Health Assistant with Emotion Detection...")
     demo.launch(
-    share=True, 
+    share=True,
     show_error=True
 )