rename

tests/integration_tests/vectorstores/fake_embeddings.py

@@ -1,12 +1,12 @@
 """Fake Embedding class for testing purposes."""
 from typing import List
 
-from langchain.embeddings.base import Embeddings
+from langchain.embeddings.base import EmbeddingModel
 
 fake_texts = ["foo", "bar", "baz"]
 
 
-class FakeEmbeddings(Embeddings):
+class FakeEmbeddings(EmbeddingModel):
     """Fake embeddings functionality for testing."""
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:

tests/integration_tests/vectorstores/test_qdrant.py

@@ -4,7 +4,7 @@ from typing import Callable, Optional
 import pytest
 
 from langchain.docstore.document import Document
-from langchain.embeddings.base import Embeddings
+from langchain.embeddings.base import EmbeddingModel
 from langchain.vectorstores import Qdrant
 from tests.integration_tests.vectorstores.fake_embeddings import FakeEmbeddings
 
@@ -139,7 +139,7 @@ def test_qdrant_max_marginal_relevance_search(
     ],
 )
 def test_qdrant_embedding_interface(
-    embeddings: Optional[Embeddings], embedding_function: Optional[Callable]
+    embeddings: Optional[EmbeddingModel], embedding_function: Optional[Callable]
 ) -> None:
     from qdrant_client import QdrantClient
 
@@ -162,7 +162,7 @@ def test_qdrant_embedding_interface(
     ],
 )
 def test_qdrant_embedding_interface_raises(
-    embeddings: Optional[Embeddings], embedding_function: Optional[Callable]
+    embeddings: Optional[EmbeddingModel], embedding_function: Optional[Callable]
 ) -> None:
     from qdrant_client import QdrantClient
 

tests/unit_tests/chains/test_hyde.py

@@ -9,12 +9,12 @@ from langchain.callbacks.manager import (
 )
 from langchain.chains.hyde.base import HypotheticalDocumentEmbedder
 from langchain.chains.hyde.prompts import PROMPT_MAP
-from langchain.embeddings.base import Embeddings
+from langchain.embeddings.base import EmbeddingModel
 from langchain.llms.base import BaseLLM
 from langchain.schema import Generation, LLMResult
 
 
-class FakeEmbeddings(Embeddings):
+class FakeEmbeddings(EmbeddingModel):
     """Fake embedding class for tests."""
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:

tests/unit_tests/retrievers/test_time_weighted_retriever.py

@@ -5,7 +5,7 @@ from typing import Any, Iterable, List, Optional, Tuple, Type
 
 import pytest
 
-from langchain.embeddings.base import Embeddings
+from langchain.embeddings.base import EmbeddingModel
 from langchain.retrievers.time_weighted_retriever import (
     TimeWeightedVectorStoreRetriever,
     _get_hours_passed,
@@ -67,7 +67,7 @@ class MockVectorStore(VectorStore):
     def from_documents(
         cls: Type["MockVectorStore"],
         documents: List[Document],
-        embedding: Embeddings,
+        embedding: EmbeddingModel,
         **kwargs: Any,
     ) -> "MockVectorStore":
         """Return VectorStore initialized from documents and embeddings."""
@@ -79,7 +79,7 @@ class MockVectorStore(VectorStore):
     def from_texts(
         cls: Type["MockVectorStore"],
         texts: List[str],
-        embedding: Embeddings,
+        embedding: EmbeddingModel,
         metadatas: Optional[List[dict]] = None,
         **kwargs: Any,
     ) -> "MockVectorStore":