Update extractive_model.py

extractive_model.py

@@ -44,3 +44,31 @@ def summarize_with_textrank(text, sentences_count=5):
     summary_text = "\n".join(str(sentence) for sentence in text_rank_summary)
     
     return summary_text
+
+
+# Define LSA summarization function
+def summarize_with_lsa(text, sentences_count=5):
+    """
+    Summarizes the provided text using LSA (Latent Semantic Analysis) algorithm.
+    Args:
+    text (str): Text to summarize.
+    sentences_count (int): Number of sentences for the summary.
+    Returns:
+    str: Summarized text.
+    """
+
+    # Check if the text is not empty
+    if not text.strip():
+        return "Provided text is empty."
+
+    # Create a parser for the provided text
+    parser = PlaintextParser.from_string(text, Tokenizer("english"))
+
+    # Use LSA for summarization
+    lsa_summarizer = LsaSummarizer()
+    lsa_summary = lsa_summarizer(parser.document, sentences_count=sentences_count)
+
+    # Compile summary into a single string
+    summary_text = "\n".join(str(sentence) for sentence in lsa_summary)
+    
+    return summary_text