Update app.py

app.py

@@ -1,6 +1,7 @@
 # Importing Libraries
 import os 
 os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
+os.environ['GRADIO_HOT_RELOAD'] = '0'  # Disable hot reload to prevent threading errors
 
 import re
 import nltk
@@ -17,49 +18,45 @@ MAX_LEN = 100
 MODEL_PATH = "sentiment_analysis_best.keras"
 TOKENIZER_PATH = "tokenizer.pkl"
 
-nltk.download('stopwords')
-
-with open("tokenizer.pkl", "rb") as f:
-    tokenizer = pickle.load(f)
+nltk.download('stopwords', quiet=True)
 
 # Expand common English contractions
 def expand_contractions(text):
-  """Expand common English contractions"""
-  contractions = {
-      "i'm": "i am", "you're": "you are", "he's": "he is",
-      "she's": "she is", "it's": "it is", "we're": "we are",
-      "they're": "they are", "i've": "i have", "you've": "you have",
-      "we've": "we have", "they've": "they have", "i'll": "i will",
-      "you'll": "you will", "he'll": "he will", "she'll": "she will",
-      "we'll": "we will", "they'll": "they will", "i'd": "i would",
-      "you'd": "you would", "he'd": "he would", "she'd": "she would",
-      "we'd": "we would", "they'd": "they would", "don't": "do not",
-      "doesn't": "does not", "didn't": "did not", "can't": "cannot",
-      "couldn't": "could not", "won't": "will not", "wouldn't": "would not",
-      "shouldn't": "should not", "isn't": "is not", "aren't": "are not",
-      "wasn't": "was not", "weren't": "were not", "hasn't": "has not",
-      "haven't": "have not", "hadn't": "had not", "mightn't": "might not",
-      "mustn't": "must not", "needn't": "need not", "shan't": "shall not"
-  }
+    """Expand common English contractions"""
+    contractions = {
+        "i'm": "i am", "you're": "you are", "he's": "he is",
+        "she's": "she is", "it's": "it is", "we're": "we are",
+        "they're": "they are", "i've": "i have", "you've": "you have",
+        "we've": "we have", "they've": "they have", "i'll": "i will",
+        "you'll": "you will", "he'll": "he will", "she'll": "she will",
+        "we'll": "we will", "they'll": "they will", "i'd": "i would",
+        "you'd": "you would", "he'd": "he would", "she'd": "she would",
+        "we'd": "we would", "they'd": "they would", "don't": "do not",
+        "doesn't": "does not", "didn't": "did not", "can't": "cannot",
+        "couldn't": "could not", "won't": "will not", "wouldn't": "would not",
+        "shouldn't": "should not", "isn't": "is not", "aren't": "are not",
+        "wasn't": "was not", "weren't": "were not", "hasn't": "has not",
+        "haven't": "have not", "hadn't": "had not", "mightn't": "might not",
+        "mustn't": "must not", "needn't": "need not", "shan't": "shall not"
+    }
 
-  for contraction, expansion in contractions.items():
-    text = re.sub(r'\b' + contraction + r'\b', expansion, text, flags=re.IGNORECASE)
-  
-  return text
+    for contraction, expansion in contractions.items():
+        text = re.sub(r'\b' + contraction + r'\b', expansion, text, flags=re.IGNORECASE)
+    
+    return text
 
 # Preprocessing Function
 def preprocess(text):
-
     # Define words to keep
     negations = {"not", "no", "nor", "never", "n't", "nobody", "nothing", "neither", "nowhere", "none"}
     important_words = {"am", "is", "are", "was", "were", "be", "been", "being"}
     
     try:
-       from nltk.corpus import stopwords
-       stop_words = set(stopwords.words("english")) - negations - important_words
+        from nltk.corpus import stopwords
+        stop_words = set(stopwords.words("english")) - negations - important_words
     except:
-       # Fallback if NLTK not available
-       stop_words =set()
+        # Fallback if NLTK not available
+        stop_words = set()
 
     # Convert to lowercase
     text = text.lower()
@@ -80,25 +77,25 @@ def preprocess(text):
 
 # Load Train Model and Tokenizer
 def load_resources():
-   try:
-      # Load model
-      model = load_model(MODEL_PATH)
-      print(f"Model loaded successfully from {MODEL_PATH}")
+    try:
+        # Load model
+        model = load_model(MODEL_PATH)
+        print(f"✓ Model loaded successfully from {MODEL_PATH}")
 
-      # Load Tokenizer
-      with open(TOKENIZER_PATH, "rb") as f:
-         tokenizer = pickle.load(f)
-      print(f"Tokenizer loaded successfully from {TOKENIZER_PATH}")
+        # Load Tokenizer
+        with open(TOKENIZER_PATH, "rb") as f:
+            tokenizer = pickle.load(f)
+        print(f"✓ Tokenizer loaded successfully from {TOKENIZER_PATH}")
 
-      return model, tokenizer
+        return model, tokenizer
 
-   except FileNotFoundError as e:
-      print(f"Error: Model or Tokenizer file not found!")
-      print(f" Make sure {MODEL_PATH} AND {TOKENIZER_PATH} are in the same directory.")
-      raise e
-   except Exception as e:
-      print(f"Error loading resources: {e}")
-      raise e
+    except FileNotFoundError as e:
+        print(f"✗ Error: Model or Tokenizer file not found!")
+        print(f"  Make sure {MODEL_PATH} AND {TOKENIZER_PATH} are in the same directory.")
+        raise e
+    except Exception as e:
+        print(f"✗ Error loading resources: {e}")
+        raise e
 
 # Load model and tokenizer globally
 model, tokenizer = load_resources()
@@ -132,20 +129,20 @@ def predict_sentiment(text):
     
     # Create detailed results
     detailed_results = f"""
-    ### 📊 Detailed Analysis:
+### 📊 Detailed Analysis:
 
-    **Original Text:** {text}
+**Original Text:** {text}
 
-    **Processed Text:** {processed_text}
+**Processed Text:** {processed_text}
 
-    **Prediction Probabilities:**
-    - 😞 Negative: {pred[0][0] * 100:.2f}%
-    - 😊 Positive: {pred[0][1] * 100:.2f}%
-    - 😐 Neutral: {pred[0][2] * 100:.2f}%
+**Prediction Probabilities:**
+- 😞 Negative: {pred[0][0] * 100:.2f}%
+- 😊 Positive: {pred[0][1] * 100:.2f}%
+- 😐 Neutral: {pred[0][2] * 100:.2f}%
 
-    **Final Sentiment:** {sentiment}
-    **Confidence:** {confidence_percentage}
-    """
+**Final Sentiment:** {sentiment}
+**Confidence:** {confidence_percentage}
+"""
     
     return sentiment, confidence_percentage, detailed_results
 
@@ -178,7 +175,7 @@ def create_gradio_interface():
     ]
     
     # Create interface
-    with gr.Blocks(title="Sentiment Analysis") as interface:
+    with gr.Blocks(title="Sentiment Analysis", theme=gr.themes.Soft()) as interface:
         
         # Header
         gr.Markdown("""
@@ -262,25 +259,23 @@ def create_gradio_interface():
     return interface
 
 
-
 # MAIN EXECUTION
 if __name__ == "__main__":
     print("\n" + "=" * 70)
     print("🚀 Starting Sentiment Analysis Gradio Interface...")
-    print("=" * 70)
+    print("=" * 70 + "\n")
     
     # Create and launch interface
     interface = create_gradio_interface()
     
     # Launch with configuration
     interface.launch(
-    server_name="0.0.0.0",
-    server_port=7860,
-    theme=gr.themes.Soft(),
-    ssr_mode=False,
-    share=False,
-    show_error=True
-)
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False,
+        show_error=True,
+        quiet=False
+    )
     
     print("\n" + "=" * 70)
     print("✓ Interface is running!")