update app.py

app.py

@@ -1,80 +1,64 @@
-# 💫 TweetPulse AI - Sentiment Analyzer (Animated Edition)
+# ✅ Final Version – TweetPulse AI Sentiment Analyzer (Hugging Face Compatible)
+# 🎯 Sound system automatically disabled for online run
+# 💜 Created by Isneha Varshney
+
 import streamlit as st
 import joblib
 from PIL import Image
-
-# -------------------------------
-# Load trained model & vectorizer
-# -------------------------------
+import threading
+import time
+import os
+
+# Try importing playsound (works only on local system)
+try:
+    from playsound import playsound
+    SOUND_ENABLED = True
+except Exception:
+    SOUND_ENABLED = False
+
+# ------------------------------------------
+# Load trained model and TF-IDF vectorizer
+# ------------------------------------------
 model = joblib.load("sentiment_model.pkl")
 vectorizer = joblib.load("tfidf_vectorizer.pkl")
 
-# -------------------------------
+# ------------------------------------------
+# Function: Play sound for few seconds (only for local)
+# ------------------------------------------
+def play_sound_limited(sound_file, duration=3):
+    if not SOUND_ENABLED:
+        return
+    def play():
+        try:
+            playsound(sound_file)
+        except Exception:
+            pass
+    t = threading.Thread(target=play)
+    t.start()
+    time.sleep(duration)
+    os.system("taskkill /IM wmplayer.exe /F >nul 2>&1")
+
+# ------------------------------------------
 # Streamlit Page Setup
-# -------------------------------
+# ------------------------------------------
 st.set_page_config(page_title="TweetPulse AI 💬", page_icon="💫", layout="centered")
 
-# Custom CSS for animations
-st.markdown("""
-    <style>
-    body {
-        background-color: #f8f8ff;
-    }
-    .pulse {
-        animation: pulse 1.5s infinite;
-    }
-    @keyframes pulse {
-        0% { transform: scale(1); opacity: 0.8; }
-        50% { transform: scale(1.05); opacity: 1; }
-        100% { transform: scale(1); opacity: 0.8; }
-    }
-    .flash-green {
-        background: rgba(0,255,0,0.15);
-        animation: flash-green 1.5s;
-    }
-    @keyframes flash-green {
-        from {background-color: #d4edda;}
-        to {background-color: white;}
-    }
-    .flash-red {
-        background: rgba(255,0,0,0.15);
-        animation: flash-red 1.5s;
-    }
-    @keyframes flash-red {
-        from {background-color: #f8d7da;}
-        to {background-color: white;}
-    }
-    .flash-blue {
-        background: rgba(0,0,255,0.1);
-        animation: flash-blue 1.5s;
-    }
-    @keyframes flash-blue {
-        from {background-color: #d1ecf1;}
-        to {background-color: white;}
-    }
-    </style>
-""", unsafe_allow_html=True)
-
-# -------------------------------
-# Header
-# -------------------------------
 st.markdown("""
     <h1 style='text-align:center; color:#6a0dad;'>💫 TweetPulse AI - Sentiment Analyzer 💫</h1>
     <h4 style='text-align:center; color:gray;'>Analyze tweet emotions instantly ⚡</h4>
 """, unsafe_allow_html=True)
 
-# -------------------------------
-# Input Box
-# -------------------------------
+# Stylish Input Box
 tweet = st.text_area(
     "✍️ Type your tweet below:",
     placeholder="e.g. I absolutely loved this movie! 🎬",
     height=120,
+    help="Type any sentence or tweet to analyze its emotion."
 )
 
-# -------------------------------
+# ------------------------------------------
 # Predict Sentiment
-# -------------------------------
+# ------------------------------------------
 if st.button("🔍 Analyze Sentiment"):
     if tweet.strip() == "":
         st.warning("⚠️ Please type something to analyze.")
@@ -83,31 +67,29 @@ if st.button("🔍 Analyze Sentiment"):
         prediction = model.predict(tweet_vector)[0]
 
         if prediction == "positive":
-            st.markdown("<div class='flash-green pulse'>", unsafe_allow_html=True)
             img = Image.open("positive.png")
-            st.image(img, width=200)
+            st.image(img, width=180)
             st.success("🎉 Sentiment Detected: **Positive 😍**")
-            st.markdown("</div>", unsafe_allow_html=True)
+            play_sound_limited("positive.mp3", duration=3)
 
         elif prediction == "negative":
-            st.markdown("<div class='flash-red pulse'>", unsafe_allow_html=True)
             img = Image.open("negative.png")
-            st.image(img, width=200)
+            st.image(img, width=180)
             st.error("💢 Sentiment Detected: **Negative 😡**")
-            st.markdown("</div>", unsafe_allow_html=True)
+            play_sound_limited("negative.mp3", duration=3)
 
         else:
-            st.markdown("<div class='flash-blue pulse'>", unsafe_allow_html=True)
             img = Image.open("neutral.png")
-            st.image(img, width=200)
+            st.image(img, width=180)
             st.info("😐 Sentiment Detected: **Neutral 😐**")
-            st.markdown("</div>", unsafe_allow_html=True)
+            play_sound_limited("neutral.mp3", duration=3)
 
-# -------------------------------
+# ------------------------------------------
 # Footer
-# -------------------------------
+# ------------------------------------------
 st.markdown("---")
-st.caption("💜 Created by **Isneha Varshney** | Powered by TweetPulse AI 💫")
+st.caption("💜 Created by **Isneha Varshney** | Powered by TweetPulse AI")
+