Update app.py

app.py

@@ -302,11 +302,11 @@ def calculate_statistics(results, search_time, vector_store, num_tokens, embeddi
         stats["silhouette_score"] = "N/A"
     
     query_embedding = embedding_model.embed_query(query)
-    result_embeddings = [embedding_model.embed_query(doc.page_content) for doc in results]
-    similarities = [np.inner(query_embedding, emb) for emb in result_embeddings]
+    #result_embeddings = [embedding_model.embed_query(doc.page_content) for doc in results]
+    #similarities = [np.inner(query_embedding, emb) for emb in result_embeddings]
     #similarities = [np.inner(query_embedding, emb)[0] for emb in result_embeddings]
-    rank_correlation, _ = spearmanr(similarities, range(len(similarities)))
-    stats["rank_correlation"] = rank_correlation
+    #rank_correlation, _ = spearmanr(similarities, range(len(similarities)))
+    #stats["rank_correlation"] = rank_correlation
     
     return stats