community[patch]: deprecate langchain_community Chroma in favor of langchain_chroma (#24474)

libs/community/langchain_community/vectorstores/chroma.py

@@ -50,6 +50,7 @@ def _results_to_docs_and_scores(results: Any) -> List[Tuple[Document, float]]:
     ]
 
 
+@deprecated(since="0.2.9", removal="0.4", alternative_import="langchain_chroma.Chroma")
 class Chroma(VectorStore):
     """`ChromaDB` vector store.
 

libs/community/tests/integration_tests/embeddings/test_sentence_transformer.py

@@ -1,10 +1,11 @@
 # flake8: noqa
 """Test sentence_transformer embeddings."""
 
+from langchain_core.vectorstores import InMemoryVectorStore
+
 from langchain_community.embeddings.sentence_transformer import (
     SentenceTransformerEmbeddings,
 )
-from langchain_community.vectorstores import Chroma
 
 
 def test_sentence_transformer_embedding_documents() -> None:
@@ -34,7 +35,7 @@ def test_sentence_transformer_db_query() -> None:
     query = "what the foo is a bar?"
     query_vector = embedding.embed_query(query)
     assert len(query_vector) == 384
-    db = Chroma(embedding_function=embedding)
+    db = InMemoryVectorStore(embedding=embedding)
     db.add_texts(texts)
     docs = db.similarity_search_by_vector(query_vector, k=2)
     assert docs[0].page_content == "we will foo your bar until you can't foo any more"

libs/community/tests/integration_tests/retrievers/test_merger_retriever.py

@@ -1,7 +1,7 @@
 from langchain.retrievers.merger_retriever import MergerRetriever
+from langchain_core.vectorstores import InMemoryVectorStore
 
 from langchain_community.embeddings import OpenAIEmbeddings
-from langchain_community.vectorstores import Chroma
 
 
 def test_merger_retriever_get_relevant_docs() -> None:
@@ -17,12 +17,12 @@ def test_merger_retriever_get_relevant_docs() -> None:
         "Real stupidity beats artificial intelligence every time. TP",
     ]
     embeddings = OpenAIEmbeddings()
-    retriever_a = Chroma.from_texts(texts_group_a, embedding=embeddings).as_retriever(
-        search_kwargs={"k": 1}
-    )
-    retriever_b = Chroma.from_texts(texts_group_b, embedding=embeddings).as_retriever(
-        search_kwargs={"k": 1}
-    )
+    retriever_a = InMemoryVectorStore.from_texts(
+        texts_group_a, embedding=embeddings
+    ).as_retriever(search_kwargs={"k": 1})
+    retriever_b = InMemoryVectorStore.from_texts(
+        texts_group_b, embedding=embeddings
+    ).as_retriever(search_kwargs={"k": 1})
 
     # The Lord of the Retrievers.
     lotr = MergerRetriever(retrievers=[retriever_a, retriever_b])

libs/community/tests/integration_tests/test_long_context_reorder.py

@@ -1,10 +1,11 @@
 """Integration test for doc reordering."""
 
+from langchain_core.vectorstores import InMemoryVectorStore
+
 from langchain_community.document_transformers.long_context_reorder import (
     LongContextReorder,
 )
 from langchain_community.embeddings import OpenAIEmbeddings
-from langchain_community.vectorstores import Chroma
 
 
 def test_long_context_reorder() -> None:
@@ -22,9 +23,9 @@ def test_long_context_reorder() -> None:
         "Larry Bird was an iconic NBA player.",
     ]
     embeddings = OpenAIEmbeddings()
-    retriever = Chroma.from_texts(texts, embedding=embeddings).as_retriever(
-        search_kwargs={"k": 10}
-    )
+    retriever = InMemoryVectorStore.from_texts(
+        texts, embedding=embeddings
+    ).as_retriever(search_kwargs={"k": 10})
     reordering = LongContextReorder()
     docs = retriever.invoke("Tell me about the Celtics")
     actual = reordering.transform_documents(docs)

libs/community/tests/unit_tests/chains/test_pebblo_retrieval.py

@@ -11,7 +11,11 @@ from langchain_core.callbacks import (
     CallbackManagerForRetrieverRun,
 )
 from langchain_core.documents import Document
-from langchain_core.vectorstores import VectorStore, VectorStoreRetriever
+from langchain_core.vectorstores import (
+    InMemoryVectorStore,
+    VectorStore,
+    VectorStoreRetriever,
+)
 
 from langchain_community.chains import PebbloRetrievalQA
 from langchain_community.chains.pebblo_retrieval.models import (
@@ -19,7 +23,6 @@ from langchain_community.chains.pebblo_retrieval.models import (
     ChainInput,
     SemanticContext,
 )
-from langchain_community.vectorstores.chroma import Chroma
 from langchain_community.vectorstores.pinecone import Pinecone
 from tests.unit_tests.llms.fake_llm import FakeLLM
 
@@ -49,8 +52,8 @@ def unsupported_retriever() -> FakeRetriever:
     """
     retriever = FakeRetriever()
     retriever.search_kwargs = {}
-    # Set the class of vectorstore to Chroma
-    retriever.vectorstore.__class__ = Chroma
+    # Set the class of vectorstore
+    retriever.vectorstore.__class__ = InMemoryVectorStore
     return retriever
 
 

libs/langchain/langchain/memory/vectorstore_token_buffer_memory.py

@@ -67,7 +67,7 @@ class ConversationVectorStoreTokenBufferMemory(ConversationTokenBufferMemory):
         from langchain.memory.token_buffer_vectorstore_memory import (
                 ConversationVectorStoreTokenBufferMemory
         )
-        from langchain_community.vectorstores import Chroma
+        from langchain_chroma import Chroma
         from langchain_community.embeddings import HuggingFaceInstructEmbeddings
         from langchain_openai import OpenAI
 

libs/langchain/langchain/retrievers/parent_document_retriever.py

@@ -31,8 +31,8 @@ class ParentDocumentRetriever(MultiVectorRetriever):
 
         .. code-block:: python
 
+            from langchain_chroma import Chroma
             from langchain_community.embeddings import OpenAIEmbeddings
-            from langchain_community.vectorstores import Chroma
             from langchain_text_splitters import RecursiveCharacterTextSplitter
             from langchain.storage import InMemoryStore