use invoke for test_vectorstores

Author: ssh-esh

libs/elasticsearch/tests/integration_tests/_async/test_vectorstores.py

@@ -104,7 +104,7 @@ async def test_search_with_relevance_threshold(
             search_type="similarity_score_threshold",
             search_kwargs={"score_threshold": similarity_of_second_ranked},
         )
-        output = await retriever.aget_relevant_documents(query=query_string)
+        output = await retriever.ainvoke(query_string)
 
         assert output == [
             top3[0][0],
@@ -145,7 +145,7 @@ async def test_search_by_vector_with_relevance_threshold(
             search_type="similarity_score_threshold",
             search_kwargs={"score_threshold": similarity_of_second_ranked},
         )
-        output = await retriever.aget_relevant_documents(query=query_string)
+        output = await retriever.ainvoke(query_string)
 
         assert output == [
             top3[0][0],
@@ -1081,7 +1081,7 @@ async def test_elasticsearch_with_relevance_threshold(
             search_type="similarity_score_threshold",
             search_kwargs={"score_threshold": similarity_of_second_ranked},
         )
-        output = await retriever.aget_relevant_documents(query=query_string)
+        output = await retriever.ainvoke(query_string)
 
         assert output == [
             top3[0][0],

libs/elasticsearch/tests/integration_tests/_sync/test_vectorstores.py

@@ -104,7 +104,7 @@ def test_search_with_relevance_threshold(
             search_type="similarity_score_threshold",
             search_kwargs={"score_threshold": similarity_of_second_ranked},
         )
-        output = retriever.get_relevant_documents(query=query_string)
+        output = retriever.invoke(query_string)
 
         assert output == [
             top3[0][0],
@@ -145,7 +145,7 @@ def test_search_by_vector_with_relevance_threshold(
             search_type="similarity_score_threshold",
             search_kwargs={"score_threshold": similarity_of_second_ranked},
         )
-        output = retriever.get_relevant_documents(query=query_string)
+        output = retriever.invoke(query_string)
 
         assert output == [
             top3[0][0],
@@ -1061,7 +1061,7 @@ def test_elasticsearch_with_relevance_threshold(
             search_type="similarity_score_threshold",
             search_kwargs={"score_threshold": similarity_of_second_ranked},
         )
-        output = retriever.get_relevant_documents(query=query_string)
+        output = retriever.invoke(query_string)
 
         assert output == [
             top3[0][0],