Update app.py

app.py

@@ -1,77 +1,115 @@
-
 import os
 import pandas as pd
 import numpy as np
 import streamlit as st
 import re
 import pickle
+import nltk
+import string
+import contractions
+
+from nltk.corpus import stopwords
+
+nltk.download("stopwords")
+sw_list = stopwords.words('english')
+
 def remove_tags(text):
-    return re.sub(re.compile('<.*?>'),'',text)
+    return re.sub(re.compile('<.*?>'), '', text)
 
 def lwr(text):
     return text.lower()
-    
-import nltk
-
-nltk.download("stopwords")
-from nltk.corpus import stopwords
-sw_list=stopwords.words('english')
 
 def stopword(text):
     return " ".join([word for word in text.split() if word not in sw_list])
 
-import string 
 def remove_punctuation(text):
     return text.translate(str.maketrans('', '', string.punctuation))
 
-import contractions
 def remove_contractions(text):
     return contractions.fix(text)
 
 def dec_vector(doc):
     with open("Sentimental_Analysis_WV.pkl", 'rb') as file:  
         model = pickle.load(file)
-    doc=[word for word in doc.split() if word in model.wv.index_to_key]
-    return np.mean(model.wv[doc],axis=0)
+    doc = [word for word in doc.split() if word in model.wv.index_to_key]
+    return np.mean(model.wv[doc], axis=0)
 
 def xvalue(text):
-    X=[]
+    X = []
     X.append(dec_vector(text))
     return X
 
 def preprocessed(text):
-    
-    text=remove_tags(text)
-    text=lwr(text)
-    text=stopword(text)
-    text=remove_punctuation(text)
-    text=remove_contractions(text)
-    X=xvalue(text)
-    X=np.array(X)
+    text = remove_tags(text)
+    text = lwr(text)
+    text = stopword(text)
+    text = remove_punctuation(text)
+    text = remove_contractions(text)
+    X = xvalue(text)
+    X = np.array(X)
     return X
 
 def clear_text():
     st.session_state["text"] = ""
 
-
 def main():
-    
+    st.set_page_config(page_title="Sentiment Analysis AI", page_icon=":smiley:", layout="wide")
     
     with open("Sentimental_Analysis_Word2Vec.pkl", 'rb') as file1:  
         rf = pickle.load(file1)
-    st.title('Sentiment Analysis')
     
+    st.title('Sentiment Analysis AI')
+    st.markdown("""
+        <style>
+        .main {
+            background-color: #f5f5f5;
+            padding: 20px;
+            border-radius: 10px;
+        }
+        .stButton > button {
+            background-color: #4CAF50;
+            color: white;
+            padding: 10px 24px;
+            border: none;
+            border-radius: 4px;
+            cursor: pointer;
+        }
+        .stButton > button:hover {
+            background-color: #45a049;
+        }
+        .stTextInput > div > input {
+            padding: 10px;
+            border: 2px solid #ccc;
+            border-radius: 4px;
+        }
+        </style>
+        """, unsafe_allow_html=True)
+
+    st.markdown("<div class='main'>", unsafe_allow_html=True)
+    
+    st.header('Welcome to Sentiment Analysis AI')
+    st.subheader('Analyze the sentiment of your text in an instant!')
+
     text = st.text_input(
-        "Enter some text 👇", key="text")
+        "Enter some text 👇", key="text", help="Type in any text to analyze its sentiment.")
+    
+    col1, col2 = st.columns(2)
     
-    if st.button('Classify'):
-        z=preprocessed(text)
-        if rf.predict(z)[0]==1:
-            st.success("Positive")
-        else:
-            st.success("Negative")
+    with col1:
+        if st.button('Classify'):
+            if text:
+                z = preprocessed(text)
+                if rf.predict(z)[0] == 1:
+                    st.success("Positive")
+                else:
+                    st.success("Negative")
+            else:
+                st.warning("Please enter some text to analyze.")
+    
+    with col2:
         st.button("Clear", on_click=clear_text)
+    
+    st.markdown("</div>", unsafe_allow_html=True)
 
-
-if __name__=='__main__':
+if __name__ == '__main__':
     main()