Update app.py


app.py

@@ -4,43 +4,17 @@ from transformers import pipeline
 
 # Load the model
 classifier = pipeline("text-classification", model="Mpavan45/Telugu_Sentimental_Analysis")
+
+# Background & Style
 st.markdown("""
     <style>
-    /* Background image for the entire app */
     .stApp {
-        background-image: url('https://cdn-uploads.huggingface.co/production/uploads/675fab3a2d0851e23d23cad3/IEdqI5m41-Xs4hWbSmzLB.jpeg'); /* Replace with your image URL */
+        background-image: url('https://cdn-uploads.huggingface.co/production/uploads/675fab3a2d0851e23d23cad3/zMmw55ImaQKf-ExZcw9w4.jpeg');
         background-size: cover;
         background-position: center;
         background-repeat: no-repeat;
         background-attachment: fixed;
     }
-    /* Radium title styling */
-    .radium-title {
-        font-size: 40px;
-        text-align: center;
-        color: #fff;
-        padding: 10px;
-        border-radius: 10px;
-        background: linear-gradient(90deg, #ff416c, #ff4b2b);
-        box-shadow: 0 0 20px #ff416c, 0 0 30px #ff4b2b;
-    }
-    /* Radium label styling */
-    .radium-label {
-        font-size: 24px;
-        font-weight: bold;
-        color: white;
-        padding: 10px;
-        border-radius: 8px;
-        background: linear-gradient(90deg, #36d1dc, #5b86e5);
-        display: inline-block;
-        margin-top: 10px;
-    }
-    </style>
-""", unsafe_allow_html=True)
-
-# CSS for radium effect
-st.markdown("""
-    <style>
     .radium-title {
         font-size: 40px;
         text-align: center;
@@ -64,10 +38,10 @@ st.markdown("""
 """, unsafe_allow_html=True)
 
 # Title
-st.markdown('<div class="radium-title">Sentiment Analysis with BERT</div>', unsafe_allow_html=True)
+st.markdown('<div class="radium-title"> Telugu Sentiment Analysis with BERT</div>', unsafe_allow_html=True)
 st.write("This app uses a fine-tuned BERT model to classify Telugu text as Positive, Negative, or Neutral.")
 
-# Emoji mapping
+# Label mapping
 label_map = {
     "LABEL_0": ("Negative", "😞"),
     "LABEL_1": ("Neutral", "😐"),
@@ -76,17 +50,16 @@ label_map = {
 
 # Telugu input checker
 def is_telugu_text(text):
-    # Remove Telugu chars, punctuation and whitespace. If anything remains (like English), it's invalid
-    cleaned_text = re.sub(r'[\u0C00-\u0C7F\s\.\,\!\?]', '', text)
+    cleaned_text = re.sub(r'[\u0C00-\u0C7F0-9\s\.\,\!\?]', '', text)
     return len(cleaned_text) == 0
 
-# Session state initialization
+# Session state setup
 if "text_input" not in st.session_state:
     st.session_state.text_input = ""
 if "result_shown" not in st.session_state:
     st.session_state.result_shown = False
 
-# Example inputs
+# Examples
 st.subheader("Try one of the following examples:")
 examples = [
     "ఈ ఆహారం చాలా చెడుగా ఉంది",
@@ -97,7 +70,6 @@ examples = [
     "ఈ వాతావరణం నాకు చాలా ఉష్ణంగా ఉంది"
 ]
 
-# Display examples in 3 rows × 2 columns
 for i in range(0, len(examples), 2):
     cols = st.columns(2)
     for j in range(2):
@@ -105,26 +77,26 @@ for i in range(0, len(examples), 2):
             example = examples[i + j]
             if cols[j].button(example[:30] + "..."):
                 st.session_state.text_input = example
-                st.session_state.result_shown = True
+                st.session_state.result_shown = False
 
-# Text area
-input_text = st.text_area("Enter text to analyze sentiment:", value=st.session_state.text_input, height=150)
+# Text Area for user input
+input_text = st.text_area("Enter text to analyze sentiment:", height=150)
 
 # Analyze button
 if st.button("Analyze Sentiment"):
-    st.session_state.text_input = input_text
-    st.session_state.result_shown = True
-
-# Output
-if st.session_state.result_shown:
-    if not st.session_state.text_input.strip():
+    if not input_text.strip():
         st.warning("Please enter some text to analyze!")
-    elif not is_telugu_text(st.session_state.text_input):
-        st.error("Please enter valid **Telugu** text only. English or other characters are not allowed.")
+        st.session_state.result_shown = False
+    elif not is_telugu_text(input_text):
+        st.error("Please enter valid **Telugu** text only.")
         st.session_state.result_shown = False
     else:
-        result = classifier(st.session_state.text_input)
-        raw_label = result[0]['label']
-        sentiment, emoji = label_map.get(raw_label, (raw_label, ""))
-        st.markdown(f'<div class="radium-label">Sentiment: {sentiment} {emoji}</div>', unsafe_allow_html=True)
- 
+        st.session_state.text_input = input_text
+        st.session_state.result_shown = True
+
+# Output
+if st.session_state.result_shown:
+    result = classifier(st.session_state.text_input)
+    raw_label = result[0]['label']
+    sentiment, emoji = label_map.get(raw_label, (raw_label, ""))
+    st.markdown(f'<div class="radium-label">Sentiment: {sentiment} {emoji}</div>', unsafe_allow_html=True)