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Formatting (#2750)

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This commit is contained in:
Dev Khant
2025-05-22 01:17:29 +05:30
committed by GitHub
parent dff91154a7
commit d85fcda037
71 changed files with 1391 additions and 1823 deletions
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38
tests/embeddings/test_vertexai_embeddings.py
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@@ -24,11 +24,20 @@ def mock_config():
with patch("mem0.configs.embeddings.base.BaseEmbedderConfig") as mock_config:
mock_config.return_value.vertex_credentials_json = "/path/to/credentials.json"
yield mock_config
@pytest.fixture
def mock_embedding_types():
return ["SEMANTIC_SIMILARITY", "CLASSIFICATION", "CLUSTERING", "RETRIEVAL_DOCUMENT", "RETRIEVAL_QUERY", "QUESTION_ANSWERING", "FACT_VERIFICATION", "CODE_RETRIEVAL_QUERY"]
return [
"SEMANTIC_SIMILARITY",
"CLASSIFICATION",
"CLUSTERING",
"RETRIEVAL_DOCUMENT",
"RETRIEVAL_QUERY",
"QUESTION_ANSWERING",
"FACT_VERIFICATION",
"CODE_RETRIEVAL_QUERY",
]
@pytest.fixture
@@ -79,30 +88,31 @@ def test_embed_custom_model(mock_text_embedding_model, mock_os_environ, mock_con
assert result == [0.4, 0.5, 0.6]
@patch("mem0.embeddings.vertexai.TextEmbeddingModel")
def test_embed_with_memory_action(mock_text_embedding_model, mock_os_environ, mock_config, mock_embedding_types, mock_text_embedding_input):
@patch("mem0.embeddings.vertexai.TextEmbeddingModel")
def test_embed_with_memory_action(
mock_text_embedding_model, mock_os_environ, mock_config, mock_embedding_types, mock_text_embedding_input
):
mock_config.return_value.model = "text-embedding-004"
mock_config.return_value.embedding_dims = 256
for embedding_type in mock_embedding_types:
mock_config.return_value.memory_add_embedding_type = embedding_type
mock_config.return_value.memory_update_embedding_type = embedding_type
mock_config.return_value.memory_search_embedding_type = embedding_type
config = mock_config()
embedder = VertexAIEmbedding(config)
mock_text_embedding_model.from_pretrained.assert_called_with("text-embedding-004")
for memory_action in ["add", "update", "search"]:
embedder.embed("Hello world", memory_action=memory_action)
mock_text_embedding_input.assert_called_with(text="Hello world", task_type=embedding_type)
mock_text_embedding_model.from_pretrained.return_value.get_embeddings.assert_called_with(
texts=[mock_text_embedding_input("Hello world", embedding_type)], output_dimensionality=256
)
@patch("mem0.embeddings.vertexai.os")
def test_credentials_from_environment(mock_os, mock_text_embedding_model, mock_config):
@@ -137,15 +147,15 @@ def test_embed_with_different_dimensions(mock_text_embedding_model, mock_os_envi
result = embedder.embed("Large embedding test")
assert result == [0.1] * 1024
@patch("mem0.embeddings.vertexai.TextEmbeddingModel")
@patch("mem0.embeddings.vertexai.TextEmbeddingModel")
def test_invalid_memory_action(mock_text_embedding_model, mock_config):
mock_config.return_value.model = "text-embedding-004"
mock_config.return_value.embedding_dims = 256
config = mock_config()
embedder = VertexAIEmbedding(config)
with pytest.raises(ValueError):
embedder.embed("Hello world", memory_action="invalid_action")
embedder.embed("Hello world", memory_action="invalid_action")