update app.py file

app.py file updated version .

app.py

@@ -1,95 +1,104 @@
-# ✅ Final Version - TweetPulse AI with Proper Sound Control
-# 💜 Created by Isneha Varshney
-
-import streamlit as st
-import joblib
-from PIL import Image
-import time
-import pygame  # New module for stable sound playback
-
-# -------------------------------
-# Load trained model & vectorizer
-# -------------------------------
-model = joblib.load("sentiment_model.pkl")
-vectorizer = joblib.load("tfidf_vectorizer.pkl")
-
-# -------------------------------
-# Function: Play sound for limited duration safely
-# -------------------------------
-def play_sound_limited(sound_file, duration=5):
-    try:
-        pygame.mixer.init()
-        pygame.mixer.music.load(sound_file)
-        pygame.mixer.music.play()
-        time.sleep(duration)
-        pygame.mixer.music.stop()
-        pygame.mixer.quit()
-    except Exception as e:
-        print(f"⚠️ Sound error: {e}")
-
-# -------------------------------
-# Streamlit Page Setup
-# -------------------------------
-st.set_page_config(page_title="TweetPulse AI 💬", page_icon="💫", layout="centered")
-
-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)
-
-# 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.")
-    else:
-        tweet_vector = vectorizer.transform([tweet])
-        prediction = model.predict(tweet_vector)[0]
-
-        # 🎵 Stop any previous sound (safety)
-        pygame.mixer.quit()
-
-        if prediction == "positive":
-            img = Image.open("positive.png")
-            st.image(img, width=180)
-            st.success("🌞 Sentiment Detected: **Positive 😍**")
-            play_sound_limited("positive.mp3", duration=3)
-
-        elif prediction == "negative":
-            img = Image.open("negative.png")
-            st.image(img, width=180)
-            st.error("💢 Sentiment Detected: **Negative 😡**")
-            play_sound_limited("negative.mp3", duration=4)
-
-        else:
-            img = Image.open("neutral.png")
-            st.image(img, width=180)
-            st.info("😐 Sentiment Detected: **Neutral 😐**")
-            play_sound_limited("neutral.mp3", duration=4)
-
-# -------------------------------
-# Footer
-# -------------------------------
-st.markdown("---")
-st.caption("💜 Created by **Isneha Varshney** | Powered by TweetPulse AI")
-
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+# ✅ 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
+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")
+
+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)
+
+# 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.")
+    else:
+        tweet_vector = vectorizer.transform([tweet])
+        prediction = model.predict(tweet_vector)[0]
+
+        if prediction == "positive":
+            img = Image.open("positive.png")
+            st.image(img, width=180)
+            st.success("🎉 Sentiment Detected: **Positive 😍**")
+            play_sound_limited("positive.mp3", duration=3)
+
+        elif prediction == "negative":
+            img = Image.open("negative.png")
+            st.image(img, width=180)
+            st.error("💢 Sentiment Detected: **Negative 😡**")
+            play_sound_limited("negative.mp3", duration=3)
+
+        else:
+            img = Image.open("neutral.png")
+            st.image(img, width=180)
+            st.info("😐 Sentiment Detected: **Neutral 😐**")
+            play_sound_limited("neutral.mp3", duration=3)
+
+# ------------------------------------------
+# Footer
+# ------------------------------------------
+st.markdown("---")
+st.caption("💜 Created by **Isneha Varshney** | Powered by TweetPulse AI")
+
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