Update app.py

app.py

@@ -305,7 +305,6 @@ 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) 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