Update app.py

app.py

@@ -12,11 +12,11 @@ from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipe
 import pandas as pd
 import torch
 
-# Disable GPU usage for TensorFlow
-os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
+# Disable GPU usage for TensorFlow compatibility
+os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
 
-# Download required NLTK resources
-nltk.download('punkt')
+# Download necessary NLTK resources
+nltk.download("punkt")
 
 # Initialize Lancaster Stemmer
 stemmer = LancasterStemmer()
@@ -55,12 +55,13 @@ def bag_of_words(s, words):
 
 # Chatbot response generator
 def chatbot_response(message, history):
+    """Generates a response from the chatbot and appends it to the history."""
     history = history or []
     try:
         result = chatbot_model.predict([bag_of_words(message, words)])
         idx = np.argmax(result)
         tag = labels[idx]
-        response = "I'm not sure how to respond to that 🤔"
+        response = "I'm not sure how to respond to that. 🤔"
         for intent in intents_data["intents"]:
             if intent["tag"] == tag:
                 response = random.choice(intent["responses"])
@@ -68,8 +69,8 @@ def chatbot_response(message, history):
     except Exception as e:
         response = f"Error generating response: {str(e)} 💥"
 
-    history.append({"role": "user", "content": f"💬 {message}"})
-    history.append({"role": "assistant", "content": f"🤖 {response}"})
+    # Format output as tuples for Gradio Chatbot compatibility
+    history.append((message, response))
     return history, response
 
 # Hugging Face transformers model for emotion detection
@@ -150,43 +151,49 @@ def well_being_app(user_input, history):
 # Custom CSS for Beautification
 custom_css = """
 body {
-    background: linear-gradient(135deg, #8e44ad, #3498db);
+    background: linear-gradient(135deg, #28a745, #218838);
     font-family: 'Arial', sans-serif;
-    color: white;
-    text-align: center;
+    color: black;
 }
 #component-0 span {
-    color: #ffcccc;
+    color: white;
 }
 button {
-    background-color: #1abc9c;
-    border: none;
+    background-color: #20c997;
     color: white;
-    padding: 12px 24px;
-    text-align: center;
+    padding: 12px 20px;
     font-size: 16px;
-    border-radius: 8px;
+    border-radius: 12px;
     cursor: pointer;
 }
 button:hover {
-    background-color: #16a085;
+    background-color: #17a2b8;
+}
+input[type="text"],
+textarea {
+    background: #ffffff;
+    color: #000000;
+    border: solid 1px #ced4da;
+    padding: 10px;
+    font-size: 14px;
+    border-radius: 6px;
 }
 """
 
 # Gradio UI
 with gr.Blocks(css=custom_css) as interface:
-    gr.Markdown("# 🌸 **Mental Health & Well-Being Assistant**")
-    gr.Markdown("### Powered by NLP & AI")
+    gr.Markdown("# 🌱 **Well-being Companion**")
+    gr.Markdown("### Empowering your well-being journey with AI 💚")
 
     with gr.Row():
         user_input = gr.Textbox(lines=2, placeholder="How can I support you today?", label="Your Input")
-        
+    
     with gr.Row():
         submit_button = gr.Button("Submit", elem_id="submit")
     
     with gr.Row():
         chatbot_out = gr.Chatbot(label="Chat History")
-        sentiment_out = gr.Textbox(label="Sentiment")
+        sentiment_out = gr.Textbox(label="Sentiment Analysis")
         emotion_out = gr.Textbox(label="Detected Emotion")
         
     with gr.Row():