Update utils.py

utils.py

@@ -1,50 +1,52 @@
-
-import joblib
-
-import re
-import string
-from nltk.corpus import stopwords
-
-
-
-def load_model(model_path):
-    """
-    Load a joblib model
-
-    Args:
-    - model_path (str): path to the model
-
-    Returns:
-    - model: loaded model
-    """
-    model = joblib.load(model_path)
-    return model
-
-
-
-# Set of English stopwords
-stop_words = set(stopwords.words('english'))
-
-def preprocess_text(text:str):
-    # Step 1: Lowercase
-    text = text.lower()
-
-    # Step 2: Strip extra whitespace
-    text = re.sub(r'\s+', ' ', text.strip())
-
-    # Step 3: Remove punctuation
-    text = text.translate(str.maketrans('', '', string.punctuation))
-
-    # Step 4: Remove stopwords
-    text = ' '.join(word for word in text.split() if word not in stop_words)
-
-    # Step 5: Remove noise (URLs, emails, hashtags, mentions, numbers, non-printables)
-    text = re.sub(r'http\S+|www\.\S+', '', text)       # URLs
-    text = re.sub(r'\S+@\S+\.\S+', '', text)           # Emails
-    text = re.sub(r'#[A-Za-z0-9_]+', '', text)         # Hashtags
-    text = re.sub(r'@[A-Za-z0-9_]+', '', text)         # Mentions
-    text = re.sub(r'\d+', '', text)                    # Numbers
-    text = ''.join(ch for ch in text if ch.isprintable())  # Non-printables
-
-    return text
-
+
+import joblib
+
+import re
+import string
+from nltk.corpus import stopwords
+
+
+nltk.download('stopwords')
+
+
+def load_model(model_path):
+    """
+    Load a joblib model
+
+    Args:
+    - model_path (str): path to the model
+
+    Returns:
+    - model: loaded model
+    """
+    model = joblib.load(model_path)
+    return model
+
+
+
+# Set of English stopwords
+stop_words = set(stopwords.words('english'))
+
+def preprocess_text(text:str):
+    # Step 1: Lowercase
+    text = text.lower()
+
+    # Step 2: Strip extra whitespace
+    text = re.sub(r'\s+', ' ', text.strip())
+
+    # Step 3: Remove punctuation
+    text = text.translate(str.maketrans('', '', string.punctuation))
+
+    # Step 4: Remove stopwords
+    text = ' '.join(word for word in text.split() if word not in stop_words)
+
+    # Step 5: Remove noise (URLs, emails, hashtags, mentions, numbers, non-printables)
+    text = re.sub(r'http\S+|www\.\S+', '', text)       # URLs
+    text = re.sub(r'\S+@\S+\.\S+', '', text)           # Emails
+    text = re.sub(r'#[A-Za-z0-9_]+', '', text)         # Hashtags
+    text = re.sub(r'@[A-Za-z0-9_]+', '', text)         # Mentions
+    text = re.sub(r'\d+', '', text)                    # Numbers
+    text = ''.join(ch for ch in text if ch.isprintable())  # Non-printables
+
+    return text
+