kartik-mem0
83f2d23ddb
tests/embeddings/test_gemini_emeddings.py has a typo in its name. #6095 reported it as a duplicate of test_gemini_embeddings.py, but the correctly-spelled file has never existed in this repo, so the typo file is the only Gemini embeddings coverage there is. Renaming keeps all 119 lines; deleting it would drop the suite. mem0/embeddings/langchain.py had no tests at all. Adds five covering the model-instance validation, the missing-model guard, and embed() delegating to embed_query, mirroring tests/llms/test_langchain.py including its importorskip guard. Closes #6095
62 lines
2.1 KiB
Python
62 lines
2.1 KiB
Python
from unittest.mock import Mock
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import pytest
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pytest.importorskip("langchain", reason="langchain not installed")
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from mem0.configs.embeddings.base import BaseEmbedderConfig
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from mem0.embeddings.langchain import LangchainEmbedding
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try:
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from langchain.embeddings.base import Embeddings
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except ImportError:
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from unittest.mock import MagicMock
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Embeddings = MagicMock
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@pytest.fixture
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def mock_langchain_model():
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"""Mock a Langchain embeddings model for testing."""
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mock_model = Mock(spec=Embeddings)
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mock_model.embed_query.return_value = [0.1, 0.2, 0.3]
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return mock_model
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def test_langchain_initialization(mock_langchain_model):
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"""LangchainEmbedding keeps the configured model instance."""
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embedder = LangchainEmbedding(BaseEmbedderConfig(model=mock_langchain_model))
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assert embedder.langchain_model is mock_langchain_model
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def test_embed_delegates_to_embed_query(mock_langchain_model):
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"""embed() forwards the text to the model's embed_query and returns its vector."""
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embedder = LangchainEmbedding(BaseEmbedderConfig(model=mock_langchain_model))
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embedding = embedder.embed("Sample text to embed.")
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mock_langchain_model.embed_query.assert_called_once_with("Sample text to embed.")
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assert embedding == [0.1, 0.2, 0.3]
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def test_embed_ignores_memory_action(mock_langchain_model):
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"""memory_action is accepted for interface parity and never reaches the model."""
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embedder = LangchainEmbedding(BaseEmbedderConfig(model=mock_langchain_model))
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embedder.embed("Sample text to embed.", memory_action="add")
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mock_langchain_model.embed_query.assert_called_once_with("Sample text to embed.")
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def test_invalid_model():
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"""A model that is not an Embeddings instance is rejected."""
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with pytest.raises(ValueError, match="`model` must be an instance of Embeddings"):
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LangchainEmbedding(BaseEmbedderConfig(model="not-a-valid-model-instance"))
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def test_missing_model():
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"""A missing model is rejected before any embedding call."""
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with pytest.raises(ValueError, match="`model` parameter is required"):
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LangchainEmbedding(BaseEmbedderConfig(model=None))
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