Update app.py

app.py

@@ -14,51 +14,51 @@ import pickle
 # Page Config
 st.set_page_config(page_title="Newsense AI", page_icon="📰", layout="wide")
 
-# Download necessary resources
-nltk.download('stopwords')
+# # Download necessary resources
+# # nltk.download('stopwords')
 
-# Load SpaCy model
-nlp = spacy.load("en_core_web_sm")
+# # Load SpaCy model
+# nlp = spacy.load("en_core_web_sm")
 
-# Stopwords
-stop_words = set(stopwords.words('english')).union({"pm"})
+# # Stopwords
+# stop_words = set(stopwords.words('english')).union({"pm"})
 
-# Pre-processing function (without parentheses extraction)
-def pre_process(x):
-    # Convert to lowercase
-    x = x.lower()
+# # Pre-processing function (without parentheses extraction)
+# def pre_process(x):
+#     # Convert to lowercase
+#     x = x.lower()
 
-    # Remove HTML tags
-    x = re.sub(r"<.*?>", "", x)
+#     # Remove HTML tags
+#     x = re.sub(r"<.*?>", "", x)
 
-    # Remove URLs
-    x = re.sub(r"http[s]?://\S+", "", x)
+#     # Remove URLs
+#     x = re.sub(r"http[s]?://\S+", "", x)
 
-    # Remove mentions (@, #)
-    x = re.sub(r"[@#]\S+", "", x)
+#     # Remove mentions (@, #)
+#     x = re.sub(r"[@#]\S+", "", x)
 
-    # Remove emojis
-    x = emoji.replace_emoji(x, replace="")
+#     # Remove emojis
+#     x = emoji.replace_emoji(x, replace="")
 
-    # Remove special characters (-, ., :, \, ,)
-    x = re.sub(r"[-.:,\\]", " ", x)
+#     # Remove special characters (-, ., :, \, ,)
+#     x = re.sub(r"[-.:,\\]", " ", x)
 
-    # Remove single and double quotes
-    x = re.sub(r"['\"](.*?)['\"]", r'\1', x)
+#     # Remove single and double quotes
+#     x = re.sub(r"['\"](.*?)['\"]", r'\1', x)
 
-    # Remove content inside parentheses
-    x = re.sub(r"\(.*?\)", "", x)
+#     # Remove content inside parentheses
+#     x = re.sub(r"\(.*?\)", "", x)
 
-    # Remove extra spaces
-    x = re.sub(r"\s+", " ", x).strip()
+#     # Remove extra spaces
+#     x = re.sub(r"\s+", " ", x).strip()
 
-    # Spell checking
-    x = str(TextBlob(x).correct())
+#     # Spell checking
+#     x = str(TextBlob(x).correct())
 
-    # Lemmatization using SpaCy
-    x = " ".join([token.lemma_ for token in nlp(x)])
+#     # Lemmatization using SpaCy
+#     x = " ".join([token.lemma_ for token in nlp(x)])
 
-    return " ".join(x)
+#     return " ".join(x)
 
 # @st.cache_resource
 # def load_model():