Update app.py

app.py

@@ -1,20 +1,13 @@
 import streamlit as st
-import matplotlib.pyplot as plt
-from mca_comment_analyzer import MCACommentAnalyzer
+from mca_comment_analyzer_light import MCACommentAnalyzerLight
 
-# Streamlit Page Config
-st.set_page_config(
-    page_title="MCA Comment Analyzer",
-    page_icon="📊",
-    layout="wide"
-)
-
-st.title("📊 MCA eConsultation Comment Analyzer")
+st.set_page_config(page_title="MCA Comment Analyzer Light", layout="wide")
+st.title("📊 MCA eConsultation Comment Analyzer (Light)")
 
 # Sidebar
 st.sidebar.header("Upload or Enter Comments")
-upload_file = st.sidebar.file_uploader("Upload a text file with comments", type=["txt"])
-manual_input = st.sidebar.text_area("Or enter comments (one per line):")
+upload_file = st.sidebar.file_uploader("Upload a text file (.txt)", type=["txt"])
+manual_input = st.sidebar.text_area("Or enter comments (one per line)")
 
 comments = []
 if upload_file:
@@ -22,28 +15,19 @@ if upload_file:
 elif manual_input.strip():
     comments = manual_input.strip().split("\n")
 
-if st.sidebar.button("🚀 Analyze"):
+if st.sidebar.button("Analyze"):
     if comments:
-        analyzer = MCACommentAnalyzer()
+        analyzer = MCACommentAnalyzerLight()
         df, keyword_freq = analyzer.process_comments(comments)
 
-        # Show Analysis Results
         st.subheader("📌 Analysis Results")
         st.dataframe(df, use_container_width=True)
 
-        # Sentiment Distribution Chart
         st.subheader("📊 Sentiment Distribution")
-        sentiment_counts = df["Sentiment"].value_counts()
-        st.bar_chart(sentiment_counts)
+        st.bar_chart(df["Sentiment"].value_counts())
 
-        # Word Cloud
         st.subheader("☁️ Word Cloud")
-        fig = analyzer.generate_wordcloud(keyword_freq)
-        st.pyplot(fig)
-
-        # Keyword Frequency Table
-        st.subheader("🔑 Keyword Frequency")
-        st.dataframe(keyword_freq, use_container_width=True)
-
+        plt = analyzer.generate_wordcloud(keyword_freq)
+        st.pyplot(plt)
     else:
         st.warning("⚠️ Please provide comments to analyze.")