Create text_processing.py

natural_language_processing/text_processing.py

@@ -0,0 +1,14 @@
+import nltk
+
+def preprocess_text(text, config):
+    # Preprocess text using the specified configuration
+    # For example, tokenize, remove stop words, or stem the words
+
+    # Tokenize the text
+    tokens = nltk.word_tokenize(text)
+
+    # Remove stop words
+    stop_words = set(nltk.corpus.stopwords.words('english'))
+    filtered_tokens = [token for token in tokens if token.lower() not in stop_words]
+
+    return filtered_tokens