Soumil Rathi
66446bd118
1. Fix _create_procedural_memory metadata mutation: use spread operator
instead of in-place dict assignment (sync + async)
2. Fix test_add assertion: remove trailing None arg that doesn't match
_add_to_vector_store(messages, metadata, filters, infer) signature
3. Restore output_format: "v1.1" in TS client search payload as fallback
4. Fix infer=False path: pass {text: embedding} dict to _create_memory
instead of raw embedding list to avoid redundant embed() calls (sync + async)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
332 lines
13 KiB
Python
332 lines
13 KiB
Python
import os
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from unittest.mock import Mock, patch
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import pytest
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from mem0.configs.base import MemoryConfig
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from mem0.memory.main import Memory
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@pytest.fixture(autouse=True)
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def mock_openai():
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os.environ["OPENAI_API_KEY"] = "123"
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with patch("openai.OpenAI") as mock:
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mock.return_value = Mock()
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yield mock
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@pytest.fixture
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def memory_instance():
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with (
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patch("mem0.utils.factory.EmbedderFactory") as mock_embedder,
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patch("mem0.memory.main.VectorStoreFactory") as mock_vector_store,
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patch("mem0.utils.factory.LlmFactory") as mock_llm,
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patch("mem0.memory.telemetry.capture_event"),
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patch("mem0.memory.graph_memory.MemoryGraph"),
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patch("mem0.memory.main.GraphStoreFactory") as mock_graph_store,
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):
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mock_embedder.create.return_value = Mock()
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mock_vector_store.create.return_value = Mock()
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mock_vector_store.create.return_value.search.return_value = []
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mock_llm.create.return_value = Mock()
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# Create a mock instance that won't try to access config attributes
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mock_graph_instance = Mock()
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mock_graph_store.create.return_value = mock_graph_instance
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config = MemoryConfig(version="v1.1")
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config.graph_store.config = {"some_config": "value"}
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return Memory(config)
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@pytest.fixture
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def memory_custom_instance():
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with (
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patch("mem0.utils.factory.EmbedderFactory") as mock_embedder,
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patch("mem0.memory.main.VectorStoreFactory") as mock_vector_store,
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patch("mem0.utils.factory.LlmFactory") as mock_llm,
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patch("mem0.memory.telemetry.capture_event"),
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patch("mem0.memory.graph_memory.MemoryGraph"),
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patch("mem0.memory.main.GraphStoreFactory") as mock_graph_store,
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):
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mock_embedder.create.return_value = Mock()
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mock_vector_store.create.return_value = Mock()
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mock_vector_store.create.return_value.search.return_value = []
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mock_llm.create.return_value = Mock()
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# Create a mock instance that won't try to access config attributes
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mock_graph_instance = Mock()
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mock_graph_store.create.return_value = mock_graph_instance
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config = MemoryConfig(
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version="v1.1",
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custom_instructions="custom prompt extracting memory in json format",
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)
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config.graph_store.config = {"some_config": "value"}
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return Memory(config)
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@pytest.mark.parametrize("version, enable_graph", [("v1.0", False), ("v1.1", True)])
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def test_add(memory_instance, version, enable_graph):
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memory_instance.config.version = version
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if not enable_graph:
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memory_instance.graph = None
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memory_instance._add_to_vector_store = Mock(return_value=[{"memory": "Test memory", "event": "ADD"}])
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memory_instance._add_to_graph = Mock(return_value=[])
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result = memory_instance.add(messages=[{"role": "user", "content": "Test message"}], user_id="test_user")
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if enable_graph:
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assert "results" in result
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assert result["results"] == [{"memory": "Test memory", "event": "ADD"}]
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assert "relations" in result
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assert result["relations"] == []
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else:
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assert "results" in result
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assert result["results"] == [{"memory": "Test memory", "event": "ADD"}]
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memory_instance._add_to_vector_store.assert_called_once_with(
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[{"role": "user", "content": "Test message"}], {"user_id": "test_user"}, {"user_id": "test_user"}, True
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)
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# Remove the conditional assertion for _add_to_graph
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memory_instance._add_to_graph.assert_called_once_with(
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[{"role": "user", "content": "Test message"}], {"user_id": "test_user"}
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)
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def test_get(memory_instance):
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mock_memory = Mock(
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id="test_id",
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payload={
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"data": "Test memory",
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"user_id": "test_user",
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"hash": "test_hash",
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"created_at": "2023-01-01T00:00:00",
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"updated_at": "2023-01-02T00:00:00",
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"extra_field": "extra_value",
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},
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)
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memory_instance.vector_store.get = Mock(return_value=mock_memory)
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result = memory_instance.get("test_id")
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assert result["id"] == "test_id"
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assert result["memory"] == "Test memory"
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assert result["user_id"] == "test_user"
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assert result["hash"] == "test_hash"
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assert result["created_at"] == "2023-01-01T00:00:00"
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assert result["updated_at"] == "2023-01-02T00:00:00"
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assert result["metadata"] == {"extra_field": "extra_value"}
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@pytest.mark.parametrize("version, enable_graph", [("v1.0", False), ("v1.1", True)])
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def test_search(memory_instance, version, enable_graph):
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memory_instance.config.version = version
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if not enable_graph:
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memory_instance.graph = None
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mock_memories = [
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Mock(id="1", payload={"data": "Memory 1", "user_id": "test_user"}, score=0.9),
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Mock(id="2", payload={"data": "Memory 2", "user_id": "test_user"}, score=0.8),
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]
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memory_instance.vector_store.search = Mock(return_value=mock_memories)
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memory_instance.vector_store.keyword_search = Mock(return_value=None) # No BM25
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memory_instance.embedding_model.embed = Mock(return_value=[0.1, 0.2, 0.3])
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if memory_instance.graph:
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memory_instance.graph.search = Mock(return_value=[{"relation": "test_relation"}])
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with patch("mem0.memory.main.lemmatize_for_bm25", return_value="test query"), \
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patch("mem0.memory.main.extract_entities", return_value=[]):
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result = memory_instance.search("test query", user_id="test_user")
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assert "results" in result
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assert len(result["results"]) == 2
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assert result["results"][0]["id"] == "1"
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assert result["results"][0]["memory"] == "Memory 1"
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assert result["results"][0]["user_id"] == "test_user"
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# Score is now combined score (semantic only since no BM25/entity), still 0.9
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assert result["results"][0]["score"] == pytest.approx(0.9)
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assert "score_breakdown" in result["results"][0]
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if enable_graph:
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assert "relations" in result
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assert result["relations"] == [{"relation": "test_relation"}]
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else:
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assert "relations" not in result
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# Hybrid pipeline over-fetches: max(100*4, 60) = 400
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memory_instance.vector_store.search.assert_called_once_with(
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query="test query", vectors=[0.1, 0.2, 0.3], top_k=400, filters={"user_id": "test_user"}
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)
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if enable_graph:
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memory_instance.graph.search.assert_called_once_with("test query", {"user_id": "test_user"}, 100)
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def test_update(memory_instance):
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memory_instance.embedding_model = Mock()
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memory_instance.embedding_model.embed = Mock(return_value=[0.1, 0.2, 0.3])
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memory_instance._update_memory = Mock()
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result = memory_instance.update("test_id", "Updated memory")
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memory_instance._update_memory.assert_called_once_with(
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"test_id", "Updated memory", {"Updated memory": [0.1, 0.2, 0.3]}, None
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)
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assert result["message"] == "Memory updated successfully!"
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def test_update_with_metadata(memory_instance):
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memory_instance.embedding_model = Mock()
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memory_instance.embedding_model.embed = Mock(return_value=[0.1, 0.2, 0.3])
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memory_instance._update_memory = Mock()
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metadata = {"category": "sports", "priority": "high"}
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result = memory_instance.update("test_id", "Updated memory", metadata=metadata)
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memory_instance._update_memory.assert_called_once_with(
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"test_id", "Updated memory", {"Updated memory": [0.1, 0.2, 0.3]}, metadata
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)
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assert result["message"] == "Memory updated successfully!"
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def test_update_with_empty_metadata(memory_instance):
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memory_instance.embedding_model = Mock()
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memory_instance.embedding_model.embed = Mock(return_value=[0.1, 0.2, 0.3])
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memory_instance._update_memory = Mock()
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memory_instance.update("test_id", "Updated memory", metadata={})
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memory_instance._update_memory.assert_called_once_with(
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"test_id", "Updated memory", {"Updated memory": [0.1, 0.2, 0.3]}, {}
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)
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def test_delete(memory_instance):
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memory_instance._delete_memory = Mock()
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result = memory_instance.delete("test_id")
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# delete() now fetches the memory first and passes it to _delete_memory
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existing_memory = memory_instance.vector_store.get.return_value
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memory_instance._delete_memory.assert_called_once_with("test_id", existing_memory)
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assert result["message"] == "Memory deleted successfully!"
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@pytest.mark.parametrize("version, enable_graph", [("v1.0", False), ("v1.1", True)])
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def test_delete_all(memory_instance, version, enable_graph):
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memory_instance.config.version = version
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if not enable_graph:
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memory_instance.graph = None
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mock_memories = [Mock(id="1"), Mock(id="2")]
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memory_instance.vector_store.list = Mock(return_value=(mock_memories, None))
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memory_instance.vector_store.reset = Mock()
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memory_instance._delete_memory = Mock()
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if memory_instance.graph:
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memory_instance.graph.delete_all = Mock()
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result = memory_instance.delete_all(user_id="test_user")
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assert memory_instance._delete_memory.call_count == 2
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# Ensure the collection is NOT dropped — only matched memories should be removed
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memory_instance.vector_store.reset.assert_not_called()
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if enable_graph:
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memory_instance.graph.delete_all.assert_called_once_with({"user_id": "test_user"})
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assert result["message"] == "Memories deleted successfully!"
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@pytest.mark.parametrize(
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"version, enable_graph, expected_result",
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[
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("v1.0", False, {"results": [{"id": "1", "memory": "Memory 1", "user_id": "test_user"}]}),
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("v1.1", False, {"results": [{"id": "1", "memory": "Memory 1", "user_id": "test_user"}]}),
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(
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"v1.1",
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True,
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{
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"results": [{"id": "1", "memory": "Memory 1", "user_id": "test_user"}],
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"relations": [{"source": "entity1", "relationship": "rel", "target": "entity2"}],
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},
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),
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],
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)
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def test_get_all(memory_instance, version, enable_graph, expected_result):
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memory_instance.config.version = version
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if not enable_graph:
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memory_instance.graph = None
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mock_memories = [Mock(id="1", payload={"data": "Memory 1", "user_id": "test_user"})]
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memory_instance.vector_store.list = Mock(return_value=(mock_memories, None))
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if memory_instance.graph:
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memory_instance.graph.get_all = Mock(
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return_value=[{"source": "entity1", "relationship": "rel", "target": "entity2"}]
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)
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result = memory_instance.get_all(user_id="test_user")
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assert isinstance(result, dict)
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assert "results" in result
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assert len(result["results"]) == len(expected_result["results"])
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for expected_item, result_item in zip(expected_result["results"], result["results"]):
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assert all(key in result_item for key in expected_item)
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assert result_item["id"] == expected_item["id"]
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assert result_item["memory"] == expected_item["memory"]
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assert result_item["user_id"] == expected_item["user_id"]
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if enable_graph:
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assert "relations" in result
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assert result["relations"] == expected_result["relations"]
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else:
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assert "relations" not in result
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memory_instance.vector_store.list.assert_called_once_with(filters={"user_id": "test_user"}, top_k=100)
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if enable_graph:
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memory_instance.graph.get_all.assert_called_once_with({"user_id": "test_user"}, 100)
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def test_no_telemetry_vector_store_when_disabled():
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"""VectorStoreFactory should only be called once (for user data) when telemetry is disabled."""
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with (
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patch("mem0.memory.main.MEM0_TELEMETRY", False),
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patch("mem0.utils.factory.EmbedderFactory") as mock_embedder,
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patch("mem0.memory.main.VectorStoreFactory") as mock_vector_store,
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patch("mem0.utils.factory.LlmFactory") as mock_llm,
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patch("mem0.memory.telemetry.capture_event"),
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):
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mock_embedder.create.return_value = Mock()
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mock_vector_store.create.return_value = Mock()
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mock_llm.create.return_value = Mock()
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config = MemoryConfig(version="v1.1")
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Memory(config)
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# VectorStoreFactory.create should be called exactly once — for user data only, not telemetry
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assert mock_vector_store.create.call_count == 1
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def test_telemetry_vector_store_created_when_enabled():
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"""VectorStoreFactory should be called twice (user data + telemetry) when telemetry is enabled."""
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with (
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patch("mem0.memory.main.MEM0_TELEMETRY", True),
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patch("mem0.utils.factory.EmbedderFactory") as mock_embedder,
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patch("mem0.memory.main.VectorStoreFactory") as mock_vector_store,
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patch("mem0.utils.factory.LlmFactory") as mock_llm,
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patch("mem0.memory.telemetry.capture_event"),
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):
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mock_embedder.create.return_value = Mock()
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mock_vector_store.create.return_value = Mock()
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mock_llm.create.return_value = Mock()
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config = MemoryConfig(version="v1.1")
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Memory(config)
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# VectorStoreFactory.create should be called twice — user data + telemetry
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assert mock_vector_store.create.call_count == 2
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