langchain[patch],community[minor]: Move some unit tests from langchain to community, use core for fake models (#21190)

libs/langchain/langchain/llms/__init__.py

@@ -177,7 +177,7 @@ def _import_edenai() -> Any:
 
 
 def _import_fake() -> Any:
-    from langchain_community.llms.fake import FakeListLLM
+    from langchain_core.language_models import FakeListLLM
 
     return FakeListLLM
 

libs/langchain/langchain/llms/fake.py

@@ -3,8 +3,8 @@ from typing import TYPE_CHECKING, Any
 from langchain._api import create_importer
 
 if TYPE_CHECKING:
-    from langchain_community.llms import FakeListLLM
     from langchain_community.llms.fake import FakeStreamingListLLM
+    from langchain_core.language_models import FakeListLLM
 
 # Create a way to dynamically look up deprecated imports.
 # Used to consolidate logic for raising deprecation warnings and

libs/langchain/tests/unit_tests/agents/test_agent_iterator.py

@@ -1,7 +1,7 @@
 from uuid import UUID
 
 import pytest
-from langchain_community.llms import FakeListLLM
+from langchain_core.language_models import FakeListLLM
 from langchain_core.tools import Tool
 
 from langchain.agents import (

libs/langchain/tests/unit_tests/agents/test_react.py

@@ -2,9 +2,9 @@
 
 from typing import Union
 
-from langchain_community.llms.fake import FakeListLLM
 from langchain_core.agents import AgentAction
 from langchain_core.documents import Document
+from langchain_core.language_models import FakeListLLM
 from langchain_core.prompts.prompt import PromptTemplate
 from langchain_core.tools import Tool
 

libs/langchain/tests/unit_tests/agents/test_serialization.py

@@ -1,7 +1,7 @@
 from pathlib import Path
 from tempfile import TemporaryDirectory
 
-from langchain_community.llms.fake import FakeListLLM
+from langchain_core.language_models import FakeListLLM
 from langchain_core.tools import Tool
 
 from langchain.agents.agent_types import AgentType

libs/langchain/tests/unit_tests/chains/test_conversation_retrieval.py

@@ -1,6 +1,6 @@
 """Test conversation chain and memory."""
-from langchain_community.llms.fake import FakeListLLM
 from langchain_core.documents import Document
+from langchain_core.language_models import FakeListLLM
 
 from langchain.chains.conversational_retrieval.base import (
     ConversationalRetrievalChain,

libs/langchain/tests/unit_tests/chains/test_history_aware_retriever.py

@@ -1,5 +1,5 @@
-from langchain_community.llms.fake import FakeListLLM
 from langchain_core.documents import Document
+from langchain_core.language_models import FakeListLLM
 from langchain_core.prompts import PromptTemplate
 
 from langchain.chains import create_history_aware_retriever

libs/langchain/tests/unit_tests/chains/test_retrieval.py

@@ -1,6 +1,6 @@
 """Test conversation chain and memory."""
-from langchain_community.llms.fake import FakeListLLM
 from langchain_core.documents import Document
+from langchain_core.language_models import FakeListLLM
 from langchain_core.prompts.prompt import PromptTemplate
 
 from langchain.chains import create_retrieval_chain

libs/langchain/tests/unit_tests/evaluation/test_loading.py

@@ -2,7 +2,7 @@
 from typing import List
 
 import pytest
-from langchain_community.embeddings.fake import FakeEmbeddings
+from langchain_core.embeddings import FakeEmbeddings
 
 from langchain.evaluation.loading import EvaluatorType, load_evaluators
 from langchain.evaluation.schema import PairwiseStringEvaluator, StringEvaluator

libs/langchain/tests/unit_tests/retrievers/document_compressors/test_cohere_rerank.py

@@ -1,52 +0,0 @@
-import os
-
-import pytest
-from pytest_mock import MockerFixture
-
-from langchain.retrievers.document_compressors import CohereRerank
-from langchain.schema import Document
-
-os.environ["COHERE_API_KEY"] = "foo"
-
-
-@pytest.mark.requires("cohere")
-def test_init() -> None:
-    CohereRerank()
-
-    CohereRerank(
-        top_n=5, model="rerank-english_v2.0", cohere_api_key="foo", user_agent="bar"
-    )
-
-
-@pytest.mark.requires("cohere")
-def test_rerank(mocker: MockerFixture) -> None:
-    mock_client = mocker.MagicMock()
-    mock_result = mocker.MagicMock()
-    mock_result.results = [
-        mocker.MagicMock(index=0, relevance_score=0.8),
-        mocker.MagicMock(index=1, relevance_score=0.6),
-    ]
-    mock_client.rerank.return_value = mock_result
-
-    test_documents = [
-        Document(page_content="This is a test document."),
-        Document(page_content="Another test document."),
-    ]
-    test_query = "Test query"
-
-    mocker.patch("cohere.Client", return_value=mock_client)
-
-    reranker = CohereRerank(cohere_api_key="foo")
-    results = reranker.rerank(test_documents, test_query)
-
-    mock_client.rerank.assert_called_once_with(
-        query=test_query,
-        documents=[doc.page_content for doc in test_documents],
-        model="rerank-english-v2.0",
-        top_n=3,
-        max_chunks_per_doc=None,
-    )
-    assert results == [
-        {"index": 0, "relevance_score": 0.8},
-        {"index": 1, "relevance_score": 0.6},
-    ]

libs/langchain/tests/unit_tests/retrievers/document_compressors/test_cross_encoder_reranker.py

@@ -1,34 +0,0 @@
-"""Integration test for CrossEncoderReranker."""
-from typing import List
-
-from langchain_community.cross_encoders import FakeCrossEncoder
-from langchain_core.documents import Document
-
-from langchain.retrievers.document_compressors import CrossEncoderReranker
-
-
-def test_rerank() -> None:
-    texts = [
-        "aaa1",
-        "bbb1",
-        "aaa2",
-        "bbb2",
-        "aaa3",
-        "bbb3",
-    ]
-    docs = list(map(lambda text: Document(page_content=text), texts))
-    compressor = CrossEncoderReranker(model=FakeCrossEncoder())
-    actual_docs = compressor.compress_documents(docs, "bbb2")
-    actual = list(map(lambda doc: doc.page_content, actual_docs))
-    expected_returned = ["bbb2", "bbb1", "bbb3"]
-    expected_not_returned = ["aaa1", "aaa2", "aaa3"]
-    assert all([text in actual for text in expected_returned])
-    assert all([text not in actual for text in expected_not_returned])
-    assert actual[0] == "bbb2"
-
-
-def test_rerank_empty() -> None:
-    docs: List[Document] = []
-    compressor = CrossEncoderReranker(model=FakeCrossEncoder())
-    actual_docs = compressor.compress_documents(docs, "query")
-    assert len(actual_docs) == 0

libs/langchain/tests/unit_tests/test_cache.py

@@ -4,9 +4,8 @@ from typing import Dict, Generator, List, Union
 
 import pytest
 from _pytest.fixtures import FixtureRequest
-from langchain_community.chat_models import FakeListChatModel
-from langchain_community.llms import FakeListLLM
 from langchain_core.caches import InMemoryCache
+from langchain_core.language_models import FakeListChatModel, FakeListLLM
 from langchain_core.language_models.chat_models import BaseChatModel
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.load import dumps