refactor: rename InMemory to InMemoryExactSearch

Signed-off-by: anna-charlotte <[email protected]>

Author: anna-charlotte

langchain/vectorstores/__init__.py

@@ -8,7 +8,7 @@
 from langchain.vectorstores.elastic_vector_search import ElasticVectorSearch
 from langchain.vectorstores.faiss import FAISS
 from langchain.vectorstores.hnsw_lib import HnswLib
-from langchain.vectorstores.in_memory import InMemory
+from langchain.vectorstores.in_memory_exact_search import InMemoryExactSearch
 from langchain.vectorstores.milvus import Milvus
 from langchain.vectorstores.myscale import MyScale, MyScaleSettings
 from langchain.vectorstores.opensearch_vector_search import OpenSearchVectorSearch
@@ -37,5 +37,5 @@
     "SupabaseVectorStore",
     "AnalyticDB",
     "HnswLib",
-    "InMemory",
+    "InMemoryExactSearch",
 ]

langchain/vectorstores/in_memory.py renamed to langchain/vectorstores/in_memory_exact_search.py

@@ -11,8 +11,8 @@
 )
 
 
-class InMemory(VecStoreFromDocIndex):
-    """Wrapper around in-memory storage.
+class InMemoryExactSearch(VecStoreFromDocIndex):
+    """Wrapper around in-memory storage for exact search.
 
     To use it, you should have the ``docarray`` package with version >=0.31.0 installed.
     You can install it with `pip install "langchain[in_memory_store]"`.
@@ -23,7 +23,7 @@ def __init__(
         embedding: Embeddings,
         metric: str = "cosine_sim",
     ) -> None:
-        """Initialize in-memory store.
+        """Initialize InMemoryExactSearch store.
 
         Args:
             embedding (Embeddings): Embedding function.
@@ -45,8 +45,8 @@ def from_texts(
         embedding: Embeddings,
         metadatas: Optional[List[dict]] = None,
         metric: str = "cosine_sim",
-    ) -> InMemory:
-        """Create an in-memory store and insert data.
+    ) -> InMemoryExactSearch:
+        """Create an InMemoryExactSearch store and insert data.
 
         Args:
             texts (List[str]): Text data.
@@ -58,7 +58,7 @@ def from_texts(
                 Defaults to "cosine_sim".
 
         Returns:
-            InMemory Vector Store
+            InMemoryExactSearch Vector Store
         """
         store = cls(
             embedding=embedding,

tests/integration_tests/vectorstores/test_in_memory.py renamed to tests/integration_tests/vectorstores/test_in_memory_exact_search.py

@@ -2,27 +2,27 @@
 import pytest
 
 from langchain.schema import Document
-from langchain.vectorstores.in_memory import InMemory
+from langchain.vectorstores.in_memory_exact_search import InMemoryExactSearch
 from tests.integration_tests.vectorstores.fake_embeddings import FakeEmbeddings
 
 
 def test_in_memory_vec_store_from_texts() -> None:
     """Test end to end construction and simple similarity search."""
     texts = ["foo", "bar", "baz"]
-    docsearch = InMemory.from_texts(
+    docsearch = InMemoryExactSearch.from_texts(
         texts,
         FakeEmbeddings(),
     )
-    assert isinstance(docsearch, InMemory)
+    assert isinstance(docsearch, InMemoryExactSearch)
     assert docsearch.doc_index.num_docs() == 3
 
 
 def test_in_memory_vec_store_add_texts(tmp_path) -> None:
     """Test end to end construction and simple similarity search."""
-    docsearch = InMemory(
+    docsearch = InMemoryExactSearch(
         embedding=FakeEmbeddings(),
     )
-    assert isinstance(docsearch, InMemory)
+    assert isinstance(docsearch, InMemoryExactSearch)
     assert docsearch.doc_index.num_docs() == 0
 
     texts = ["foo", "bar", "baz"]
@@ -34,7 +34,7 @@ def test_in_memory_vec_store_add_texts(tmp_path) -> None:
 def test_sim_search(metric) -> None:
     """Test end to end construction and simple similarity search."""
     texts = ["foo", "bar", "baz"]
-    in_memory_vec_store = InMemory.from_texts(
+    in_memory_vec_store = InMemoryExactSearch.from_texts(
         texts=texts,
         embedding=FakeEmbeddings(),
         metric=metric,
@@ -48,7 +48,7 @@ def test_sim_search(metric) -> None:
 def test_sim_search_with_score(metric) -> None:
     """Test end to end construction and similarity search with score."""
     texts = ["foo", "bar", "baz"]
-    in_memory_vec_store = InMemory.from_texts(
+    in_memory_vec_store = InMemoryExactSearch.from_texts(
         texts=texts,
         embedding=FakeEmbeddings(),
         metric=metric,
@@ -67,7 +67,7 @@ def test_sim_search_with_score(metric) -> None:
 def test_sim_search_by_vector(metric) -> None:
     """Test end to end construction and similarity search by vector."""
     texts = ["foo", "bar", "baz"]
-    in_memory_vec_store = InMemory.from_texts(
+    in_memory_vec_store = InMemoryExactSearch.from_texts(
         texts=texts,
         embedding=FakeEmbeddings(),
         metric=metric,
@@ -84,7 +84,7 @@ def test_max_marginal_relevance_search(metric) -> None:
     """Test MRR search."""
     texts = ["foo", "bar", "baz"]
     metadatas = [{"page": i} for i in range(len(texts))]
-    docsearch = InMemory.from_texts(
+    docsearch = InMemoryExactSearch.from_texts(
         texts,
         FakeEmbeddings(),
         metadatas=metadatas,