community[patch]: Support passing graph object to Neo4j integrations (#20876)

For driver connection reusage, we introduce passing the graph object to
neo4j integrations

libs/community/tests/integration_tests/chat_message_histories/test_neo4j.py

@@ -0,0 +1,66 @@
+import os
+
+from langchain_core.messages import AIMessage, HumanMessage
+
+from langchain_community.chat_message_histories import Neo4jChatMessageHistory
+from langchain_community.graphs import Neo4jGraph
+
+
+def test_add_messages() -> None:
+    """Basic testing: adding messages to the Neo4jChatMessageHistory."""
+    assert os.environ.get("NEO4J_URI") is not None
+    assert os.environ.get("NEO4J_USERNAME") is not None
+    assert os.environ.get("NEO4J_PASSWORD") is not None
+    message_store = Neo4jChatMessageHistory("23334")
+    message_store.clear()
+    assert len(message_store.messages) == 0
+    message_store.add_user_message("Hello! Language Chain!")
+    message_store.add_ai_message("Hi Guys!")
+
+    # create another message store to check if the messages are stored correctly
+    message_store_another = Neo4jChatMessageHistory("46666")
+    message_store_another.clear()
+    assert len(message_store_another.messages) == 0
+    message_store_another.add_user_message("Hello! Bot!")
+    message_store_another.add_ai_message("Hi there!")
+    message_store_another.add_user_message("How's this pr going?")
+
+    # Now check if the messages are stored in the database correctly
+    assert len(message_store.messages) == 2
+    assert isinstance(message_store.messages[0], HumanMessage)
+    assert isinstance(message_store.messages[1], AIMessage)
+    assert message_store.messages[0].content == "Hello! Language Chain!"
+    assert message_store.messages[1].content == "Hi Guys!"
+
+    assert len(message_store_another.messages) == 3
+    assert isinstance(message_store_another.messages[0], HumanMessage)
+    assert isinstance(message_store_another.messages[1], AIMessage)
+    assert isinstance(message_store_another.messages[2], HumanMessage)
+    assert message_store_another.messages[0].content == "Hello! Bot!"
+    assert message_store_another.messages[1].content == "Hi there!"
+    assert message_store_another.messages[2].content == "How's this pr going?"
+
+    # Now clear the first history
+    message_store.clear()
+    assert len(message_store.messages) == 0
+    assert len(message_store_another.messages) == 3
+    message_store_another.clear()
+    assert len(message_store.messages) == 0
+    assert len(message_store_another.messages) == 0
+
+
+def test_add_messages_graph_object() -> None:
+    """Basic testing: Passing driver through graph object."""
+    assert os.environ.get("NEO4J_URI") is not None
+    assert os.environ.get("NEO4J_USERNAME") is not None
+    assert os.environ.get("NEO4J_PASSWORD") is not None
+    graph = Neo4jGraph()
+    # rewrite env for testing
+    os.environ["NEO4J_USERNAME"] = "foo"
+    message_store = Neo4jChatMessageHistory("23334", graph=graph)
+    message_store.clear()
+    assert len(message_store.messages) == 0
+    message_store.add_user_message("Hello! Language Chain!")
+    message_store.add_ai_message("Hi Guys!")
+    # Now check if the messages are stored in the database correctly
+    assert len(message_store.messages) == 2

libs/community/tests/integration_tests/vectorstores/test_neo4jvector.py

@@ -4,6 +4,7 @@ from typing import Any, Dict, List, cast
 
 from langchain_core.documents import Document
 
+from langchain_community.graphs import Neo4jGraph
 from langchain_community.vectorstores.neo4j_vector import (
     Neo4jVector,
     SearchType,
@@ -902,3 +903,20 @@ OPTIONS {indexConfig: {
     assert output == [Document(page_content="foo-text", metadata={"foo": "bar"})]
 
     drop_vector_indexes(docsearch)
+
+
+def test_neo4jvector_passing_graph_object() -> None:
+    """Test end to end construction and search with passing graph object."""
+    graph = Neo4jGraph()
+    # Rewrite env vars to make sure it fails if env is used
+    os.environ["NEO4J_URI"] = "foo"
+    docsearch = Neo4jVector.from_texts(
+        texts=texts,
+        embedding=FakeEmbeddingsWithOsDimension(),
+        graph=graph,
+        pre_delete_collection=True,
+    )
+    output = docsearch.similarity_search("foo", k=1)
+    assert output == [Document(page_content="foo")]
+
+    drop_vector_indexes(docsearch)