chore(tests): fix Gemini embeddings test filename, add Langchain embedder tests

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

tests/embeddings/test_langchain_embeddings.py

@@ -0,0 +1,61 @@
+from unittest.mock import Mock
+
+import pytest
+
+pytest.importorskip("langchain", reason="langchain not installed")
+
+from mem0.configs.embeddings.base import BaseEmbedderConfig
+from mem0.embeddings.langchain import LangchainEmbedding
+
+try:
+    from langchain.embeddings.base import Embeddings
+except ImportError:
+    from unittest.mock import MagicMock
+
+    Embeddings = MagicMock
+
+
+@pytest.fixture
+def mock_langchain_model():
+    """Mock a Langchain embeddings model for testing."""
+    mock_model = Mock(spec=Embeddings)
+    mock_model.embed_query.return_value = [0.1, 0.2, 0.3]
+    return mock_model
+
+
+def test_langchain_initialization(mock_langchain_model):
+    """LangchainEmbedding keeps the configured model instance."""
+    embedder = LangchainEmbedding(BaseEmbedderConfig(model=mock_langchain_model))
+
+    assert embedder.langchain_model is mock_langchain_model
+
+
+def test_embed_delegates_to_embed_query(mock_langchain_model):
+    """embed() forwards the text to the model's embed_query and returns its vector."""
+    embedder = LangchainEmbedding(BaseEmbedderConfig(model=mock_langchain_model))
+
+    embedding = embedder.embed("Sample text to embed.")
+
+    mock_langchain_model.embed_query.assert_called_once_with("Sample text to embed.")
+    assert embedding == [0.1, 0.2, 0.3]
+
+
+def test_embed_ignores_memory_action(mock_langchain_model):
+    """memory_action is accepted for interface parity and never reaches the model."""
+    embedder = LangchainEmbedding(BaseEmbedderConfig(model=mock_langchain_model))
+
+    embedder.embed("Sample text to embed.", memory_action="add")
+
+    mock_langchain_model.embed_query.assert_called_once_with("Sample text to embed.")
+
+
+def test_invalid_model():
+    """A model that is not an Embeddings instance is rejected."""
+    with pytest.raises(ValueError, match="`model` must be an instance of Embeddings"):
+        LangchainEmbedding(BaseEmbedderConfig(model="not-a-valid-model-instance"))
+
+
+def test_missing_model():
+    """A missing model is rejected before any embedding call."""
+    with pytest.raises(ValueError, match="`model` parameter is required"):
+        LangchainEmbedding(BaseEmbedderConfig(model=None))