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Fix failing tests (#3162)

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This commit is contained in:
Parshva Daftari
2025-07-25 00:58:45 +05:30
committed by GitHub
parent 37ee3c5eb2
commit 4433666117
11 changed files with 144 additions and 169 deletions
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81
tests/test_memory_integration.py
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@@ -5,7 +5,7 @@ from mem0.memory.main import Memory
def test_memory_configuration_without_env_vars():
"""Test Memory configuration with mock config instead of environment variables"""
# Mock configuration without relying on environment variables
mock_config = {
"llm": {
@@ -14,60 +14,62 @@ def test_memory_configuration_without_env_vars():
"model": "gpt-4",
"temperature": 0.1,
"max_tokens": 1500,
}
},
},
"vector_store": {
"provider": "chroma",
"config": {
"collection_name": "test_collection",
"path": "./test_db",
}
},
},
"embedder": {
"provider": "openai",
"config": {
"model": "text-embedding-ada-002",
}
}
},
},
}
# Test messages similar to the main.py file
test_messages = [
{"role": "user", "content": "Hi, I'm Alex. I'm a vegetarian and I'm allergic to nuts."},
{"role": "assistant", "content": "Hello Alex! I've noted that you're a vegetarian and have a nut allergy. I'll keep this in mind for any food-related recommendations or discussions."}
{
"role": "assistant",
"content": "Hello Alex! I've noted that you're a vegetarian and have a nut allergy. I'll keep this in mind for any food-related recommendations or discussions.",
},
]
# Mock the Memory class methods to avoid actual API calls
with patch.object(Memory, '__init__', return_value=None):
with patch.object(Memory, 'from_config') as mock_from_config:
with patch.object(Memory, 'add') as mock_add:
with patch.object(Memory, 'get_all') as mock_get_all:
with patch.object(Memory, "__init__", return_value=None):
with patch.object(Memory, "from_config") as mock_from_config:
with patch.object(Memory, "add") as mock_add:
with patch.object(Memory, "get_all") as mock_get_all:
# Configure mocks
mock_memory_instance = MagicMock()
mock_from_config.return_value = mock_memory_instance
mock_add.return_value = {
"results": [
{"id": "1", "text": "Alex is a vegetarian"},
{"id": "2", "text": "Alex is allergic to nuts"}
{"id": "2", "text": "Alex is allergic to nuts"},
]
}
mock_get_all.return_value = [
{"id": "1", "text": "Alex is a vegetarian", "metadata": {"category": "dietary_preferences"}},
{"id": "2", "text": "Alex is allergic to nuts", "metadata": {"category": "allergies"}}
{"id": "2", "text": "Alex is allergic to nuts", "metadata": {"category": "allergies"}},
]
# Test the workflow
mem = Memory.from_config(config_dict=mock_config)
assert mem is not None
# Test adding memories
result = mock_add(test_messages, user_id="alice", metadata={"category": "book_recommendations"})
assert "results" in result
assert len(result["results"]) == 2
# Test retrieving memories
all_memories = mock_get_all(user_id="alice")
assert len(all_memories) == 2
@@ -77,7 +79,7 @@ def test_memory_configuration_without_env_vars():
def test_azure_config_structure():
"""Test that Azure configuration structure is properly formatted"""
# Test Azure configuration structure (without actual credentials)
azure_config = {
"llm": {
@@ -91,8 +93,8 @@ def test_azure_config_structure():
"api_version": "2023-12-01-preview",
"azure_endpoint": "https://test.openai.azure.com/",
"api_key": "test-key",
}
}
},
},
},
"vector_store": {
"provider": "azure_ai_search",
@@ -101,7 +103,7 @@ def test_azure_config_structure():
"api_key": "test-key",
"collection_name": "test-collection",
"embedding_model_dims": 1536,
}
},
},
"embedder": {
"provider": "azure_openai",
@@ -113,46 +115,49 @@ def test_azure_config_structure():
"azure_deployment": "test-embedding-deployment",
"azure_endpoint": "https://test.openai.azure.com/",
"api_key": "test-key",
}
}
}
},
},
},
}
# Validate configuration structure
assert "llm" in azure_config
assert "vector_store" in azure_config
assert "embedder" in azure_config
# Validate Azure-specific configurations
assert azure_config["llm"]["provider"] == "azure_openai"
assert "azure_kwargs" in azure_config["llm"]["config"]
assert "azure_deployment" in azure_config["llm"]["config"]["azure_kwargs"]
assert azure_config["vector_store"]["provider"] == "azure_ai_search"
assert "service_name" in azure_config["vector_store"]["config"]
assert azure_config["embedder"]["provider"] == "azure_openai"
assert "azure_kwargs" in azure_config["embedder"]["config"]
def test_memory_messages_format():
"""Test that memory messages are properly formatted"""
# Test message format from main.py
messages = [
{"role": "user", "content": "Hi, I'm Alex. I'm a vegetarian and I'm allergic to nuts."},
{"role": "assistant", "content": "Hello Alex! I've noted that you're a vegetarian and have a nut allergy. I'll keep this in mind for any food-related recommendations or discussions."}
{
"role": "assistant",
"content": "Hello Alex! I've noted that you're a vegetarian and have a nut allergy. I'll keep this in mind for any food-related recommendations or discussions.",
},
]
# Validate message structure
assert len(messages) == 2
assert all("role" in msg for msg in messages)
assert all("content" in msg for msg in messages)
# Validate roles
assert messages[0]["role"] == "user"
assert messages[1]["role"] == "assistant"
# Validate content
assert "vegetarian" in messages[0]["content"].lower()
assert "allergic to nuts" in messages[0]["content"].lower()
@@ -162,12 +167,12 @@ def test_memory_messages_format():
def test_safe_update_prompt_constant():
"""Test the SAFE_UPDATE_PROMPT constant from main.py"""
SAFE_UPDATE_PROMPT = """
Based on the user's latest messages, what new preference can be inferred?
Reply only in this json_object format:
"""
# Validate prompt structure
assert isinstance(SAFE_UPDATE_PROMPT, str)
assert "user's latest messages" in SAFE_UPDATE_PROMPT