diff --git a/libs/langchain/tests/integration_tests/vectorstores/qdrant/test_max_marginal_relevance.py b/libs/langchain/tests/integration_tests/vectorstores/qdrant/test_max_marginal_relevance.py
index 71d1643b78..654bd9a433 100644
--- a/libs/langchain/tests/integration_tests/vectorstores/qdrant/test_max_marginal_relevance.py
+++ b/libs/langchain/tests/integration_tests/vectorstores/qdrant/test_max_marginal_relevance.py
@@ -1,7 +1,6 @@
 from typing import Optional
 
 import pytest
-from qdrant_client import models
 
 from langchain.schema import Document
 from langchain.vectorstores import Qdrant
@@ -21,6 +20,8 @@ def test_qdrant_max_marginal_relevance_search(
     vector_name: Optional[str],
 ) -> None:
     """Test end to end construction and MRR search."""
+    from qdrant_client import models
+
     filter = models.Filter(
         must=[
             models.FieldCondition(
diff --git a/tests/integration_tests/vectorstores/test_vearch.py b/libs/langchain/tests/integration_tests/vectorstores/test_vearch.py
similarity index 72%
rename from tests/integration_tests/vectorstores/test_vearch.py
rename to libs/langchain/tests/integration_tests/vectorstores/test_vearch.py
index a6827b4b85..e6c70efe3d 100644
--- a/tests/integration_tests/vectorstores/test_vearch.py
+++ b/libs/langchain/tests/integration_tests/vectorstores/test_vearch.py
@@ -1,5 +1,7 @@
+# flake8: noqa
+
 from langchain.docstore.document import Document
-from langchain.vectorstores.vearch import VearchDb
+from langchain.vectorstores.vearch import Vearch
 from tests.integration_tests.vectorstores.fake_embeddings import FakeEmbeddings
 
 
@@ -14,16 +16,22 @@ def test_vearch() -> None:
     ]
     metadatas = [
         {
-            "source": "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/three_body.txt"
+            "source": (
+                "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/three_body.txt"
+            )
         },
         {
-            "source": "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/three_body.txt"
+            "source": (
+                "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/three_body.txt"
+            )
         },
         {
-            "source": "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/three_body.txt"
+            "source": (
+                "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/three_body.txt"
+            )
         },
     ]
-    vearch_db = VearchDb.from_texts(
+    vearch_db = Vearch.from_texts(
         texts=texts,
         embedding=FakeEmbeddings(),
         metadatas=metadatas,
@@ -37,7 +45,10 @@ def test_vearch() -> None:
         Document(
             page_content="Vearch 支持OpenAI, Llama, ChatGLM等模型，以及LangChain库",
             metadata={
-                "source": "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/three_body.txt"
+                "source": (
+                    "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/"
+                    "three_body.txt"
+                )
             },
         )
     ]
@@ -46,23 +57,26 @@ def test_vearch() -> None:
 def test_vearch_add_texts() -> None:
     """Test end to end adding of texts."""
     texts = [
-        "Vearch 是一款存储大语言模型数据的向量数据库，用于存储和快速搜索模型embedding后的向量，可用于基于个人知识库的大模型应用",
+        ("Vearch 是一款存储大语言模型数据的向量数据库，用于存储和快速搜索模型embedding后的向量，" "可用于基于个人知识库的大模型应用"),
         "Vearch 支持OpenAI, Llama, ChatGLM等模型，以及LangChain库",
         "vearch 是基于C语言,go语言开发的，并提供python接口，可以直接通过pip安装",
     ]
 
     metadatas = [
         {
-            "source": "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/three_body.txt"
+            "source": "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/"
+            "three_body.txt"
         },
         {
-            "source": "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/three_body.txt"
+            "source": "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/"
+            "three_body.txt"
         },
         {
-            "source": "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/three_body.txt"
+            "source": "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/"
+            "three_body.txt"
         },
     ]
-    vearch_db = VearchDb.from_texts(
+    vearch_db = Vearch.from_texts(
         texts=texts,
         embedding=FakeEmbeddings(),
         metadatas=metadatas,
@@ -72,9 +86,11 @@ def test_vearch_add_texts() -> None:
 
     vearch_db.add_texts(
         texts=["Vearch 支持OpenAI, Llama, ChatGLM等模型，以及LangChain库"],
-        metadatas={
-            "source": "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/three_body.txt"
-        },
+        metadatas=[
+            {
+                "source": "/data/zhx/zhx/langchain-ChatGLM_new/knowledge_base/santi/three_body.txt"
+            },
+        ],
     )
     result = vearch_db.similarity_search(
         "Vearch 支持OpenAI, Llama, ChatGLM等模型，以及LangChain库", 2
@@ -94,4 +110,3 @@ def test_vearch_add_texts() -> None:
             },
         ),
     ]
-