diff --git a/comps/retrievers/langchain/pinecone/retriever_pinecone.py b/comps/retrievers/langchain/pinecone/retriever_pinecone.py
index d28aea5294..ba8e6526f5 100644
--- a/comps/retrievers/langchain/pinecone/retriever_pinecone.py
+++ b/comps/retrievers/langchain/pinecone/retriever_pinecone.py
@@ -54,14 +54,10 @@ def retrieve(input: EmbedDoc) -> SearchedDoc:
     elif input.search_type == "similarity_distance_threshold":
         if input.distance_threshold is None:
             raise ValueError("distance_threshold must be provided for " + "similarity_distance_threshold retriever")
-        docs_and_similarities = vector_db.similarity_search_by_vector_with_score(
-            embedding=input.embedding, k=input.k
-        )
+        docs_and_similarities = vector_db.similarity_search_by_vector_with_score(embedding=input.embedding, k=input.k)
         search_res = [doc for doc, similarity in docs_and_similarities if similarity > input.distance_threshold]
     elif input.search_type == "similarity_score_threshold":
-        docs_and_similarities = vector_db.similarity_search_by_vector_with_score(
-            query=input.text, k=input.k
-        )
+        docs_and_similarities = vector_db.similarity_search_by_vector_with_score(query=input.text, k=input.k)
         search_res = [doc for doc, similarity in docs_and_similarities if similarity > input.score_threshold]
     elif input.search_type == "mmr":
         search_res = vector_db.max_marginal_relevance_search(