Update app.py

app.py

@@ -283,6 +283,7 @@ def calculate_statistics(results, search_time, vector_store, num_tokens, embeddi
         # Silhouette Score
         if len(embeddings) > 2:
             print('-----')
+            stats["silhouette_score"] = "N/A"
             #stats["silhouette_score"] = silhouette_score(embeddings, range(len(embeddings)))
         else:
             stats["silhouette_score"] = "N/A"
@@ -292,7 +293,8 @@ def calculate_statistics(results, search_time, vector_store, num_tokens, embeddi
     
     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)[0] for emb in result_embeddings]
+    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