Update app.py

app.py

@@ -15,6 +15,28 @@ def main():
     # Extract keywords
     if st.button("Extract Keywords"):
         keywords = kw_model.extract_keywords(doc)
+
+        # Get user choice for MMR
+        apply_mmr = st.checkbox("Apply Maximal Marginal Relevance (MMR)")
+
+        if apply_mmr:
+            # Apply Maximal Marginal Relevance (MMR)
+            selected_keywords = []
+            selected_keywords.append(keywords[0])  # Select the top-scoring keyword
+
+            # Set the MMR hyperparameters
+            lambda_param = 0.7  # Weight for the trade-off between relevance and diversity
+            num_keywords = 5  # Number of keywords to select
+
+            for i in range(1, num_keywords):
+                selected_keywords_scores = [kw[1] for kw in selected_keywords]
+                remaining_keywords = [kw for kw in keywords if kw[0] not in [kw[0] for kw in selected_keywords]]
+                mmr_scores = kw_model.maximal_marginal_relevance(doc, remaining_keywords, selected_keywords_scores, lambda_param)
+                max_mmr_index = mmr_scores.index(max(mmr_scores))
+                selected_keywords.append(remaining_keywords[max_mmr_index])
+
+            keywords = selected_keywords  # Update keywords with MMR-selected keywords
+
         st.write("Keywords:")
         for keyword, score in keywords:
             st.write(f"- {keyword} (Score: {score})")