Update app.py

app.py

@@ -1,7 +1,6 @@
 import streamlit as st
 from transformers import pipeline
 import torch
-import time
 
 # ---- Page Configuration ----
 st.set_page_config(
@@ -12,31 +11,22 @@ st.set_page_config(
 )
 
 # ---- App Title ----
-st.title("🌺 Emotion Prediction App 🌈")
-st.subheader("Aloha! Enter your thoughts and let me predict your emotions. 🧠💡")
-
-# ---- Background Information ----
-st.markdown(
-    """
-    Welcome to the Emotion Prediction App! 
-    This tool uses a state-of-the-art natural language processing (NLP) model to analyze your responses and predict your emotions.
-    Perfect for everyone in Hawaii or anywhere looking for a simple, fun way to understand feelings better! 🌴✨
-    """
-)
+st.title("🌟 Emotion Prediction App 🌈")
+st.subheader("Understand your emotions better with AI-powered predictions!")
 
 # ---- Function to Load Emotion Analysis Model ----
 @st.cache_resource
 def load_emotion_model():
     try:
         st.info("⏳ Loading the emotion analysis model, please wait...")
-        # Using a public model for emotion classification
-        model = pipeline(
+        # Using a publicly available model
+        emotion_analyzer = pipeline(
             "text-classification",
             model="bhadresh-savani/distilbert-base-uncased-emotion",
-            device=0 if torch.cuda.is_available() else -1,  # Automatically use GPU if available
+            device=0 if torch.cuda.is_available() else -1,  # Use GPU if available
         )
         st.success("✅ Model loaded successfully!")
-        return model
+        return emotion_analyzer
     except Exception as e:
         st.error(f"⚠️ Error loading model: {e}")
         return None
@@ -57,8 +47,7 @@ def predict_emotion(text):
         return {"Error": f"Prediction failed: {e}"}
 
 # ---- User Input Section ----
-st.write("### 🌟 Let's Get Started!")
-
+st.write("### 🌺 Let's Get Started!")
 questions = [
     "How are you feeling today?",
     "Describe your mood in a few words.",
@@ -71,7 +60,7 @@ responses = {}
 
 # ---- Ask Questions and Analyze Responses ----
 for i, question in enumerate(questions, start=1):
-    st.write(f"#### 🧐 Question {i}: {question}")
+    st.write(f"#### ❓ Question {i}: {question}")
     user_response = st.text_input(f"Your answer to Q{i}:", key=f"q{i}")
     
     if user_response:
@@ -95,7 +84,7 @@ if st.button("Submit Responses"):
 st.markdown(
     """
     ---
-    **Developed with 🤗 Transformers by OpenAI**  
-    Designed for an intuitive and aesthetic experience. 🌺  
+    **Developed using 🤗 Transformers**  
+    Designed for a fun and intuitive experience! 🌟  
     """
 )