my-project-public

repository

loading code, commits, and activity

repositories

loading repo index

#1	import os
#2	from unittest.mock import Mock, patch
#3
#4	import pytest
#5
#6	from mem0.configs.llms.openai import OpenAIConfig
#7	from mem0.llms.openai import OpenAILLM
#8
#9
#10	@pytest.fixture
#11	def mock_openai_client():
#12	with patch("mem0.llms.openai.OpenAI") as mock_openai:
#13	mock_client = Mock()
#14	mock_openai.return_value = mock_client
#15	yield mock_client
#16
#17
#18	def test_openai_llm_base_url():
#19	# case1: default config: with openai official base url
#20	config = OpenAIConfig(model="gpt-4.1-nano-2025-04-14", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key")
#21	llm = OpenAILLM(config)
#22	# Note: openai client will parse the raw base_url into a URL object, which will have a trailing slash
#23	assert str(llm.client.base_url) == "https://api.openai.com/v1/"
#24
#25	# case2: with env variable OPENAI_API_BASE
#26	provider_base_url = "https://api.provider.com/v1"
#27	os.environ["OPENAI_BASE_URL"] = provider_base_url
#28	config = OpenAIConfig(model="gpt-4.1-nano-2025-04-14", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key")
#29	llm = OpenAILLM(config)
#30	# Note: openai client will parse the raw base_url into a URL object, which will have a trailing slash
#31	assert str(llm.client.base_url) == provider_base_url + "/"
#32
#33	# case3: with config.openai_base_url
#34	config_base_url = "https://api.config.com/v1"
#35	config = OpenAIConfig(
#36	model="gpt-4.1-nano-2025-04-14", temperature=0.7, max_tokens=100, top_p=1.0, api_key="api_key", openai_base_url=config_base_url
#37	)
#38	llm = OpenAILLM(config)
#39	# Note: openai client will parse the raw base_url into a URL object, which will have a trailing slash
#40	assert str(llm.client.base_url) == config_base_url + "/"
#41
#42
#43	def test_generate_response_without_tools(mock_openai_client):
#44	config = OpenAIConfig(model="gpt-4.1-nano-2025-04-14", temperature=0.7, max_tokens=100, top_p=1.0)
#45	llm = OpenAILLM(config)
#46	messages = [
#47	{"role": "system", "content": "You are a helpful assistant."},
#48	{"role": "user", "content": "Hello, how are you?"},
#49	]
#50
#51	mock_response = Mock()
#52	mock_response.choices = [Mock(message=Mock(content="I'm doing well, thank you for asking!"))]
#53	mock_openai_client.chat.completions.create.return_value = mock_response
#54
#55	response = llm.generate_response(messages)
#56
#57	mock_openai_client.chat.completions.create.assert_called_once_with(
#58	model="gpt-4.1-nano-2025-04-14", messages=messages, temperature=0.7, max_tokens=100, top_p=1.0, store=False
#59	)
#60	assert response == "I'm doing well, thank you for asking!"
#61
#62
#63	def test_generate_response_with_tools(mock_openai_client):
#64	config = OpenAIConfig(model="gpt-4.1-nano-2025-04-14", temperature=0.7, max_tokens=100, top_p=1.0)
#65	llm = OpenAILLM(config)
#66	messages = [
#67	{"role": "system", "content": "You are a helpful assistant."},
#68	{"role": "user", "content": "Add a new memory: Today is a sunny day."},
#69	]
#70	tools = [
#71	{
#72	"type": "function",
#73	"function": {
#74	"name": "add_memory",
#75	"description": "Add a memory",
#76	"parameters": {
#77	"type": "object",
#78	"properties": {"data": {"type": "string", "description": "Data to add to memory"}},
#79	"required": ["data"],
#80	},
#81	},
#82	}
#83	]
#84
#85	mock_response = Mock()
#86	mock_message = Mock()
#87	mock_message.content = "I've added the memory for you."
#88
#89	mock_tool_call = Mock()
#90	mock_tool_call.function.name = "add_memory"
#91	mock_tool_call.function.arguments = '{"data": "Today is a sunny day."}'
#92
#93	mock_message.tool_calls = [mock_tool_call]
#94	mock_response.choices = [Mock(message=mock_message)]
#95	mock_openai_client.chat.completions.create.return_value = mock_response
#96
#97	response = llm.generate_response(messages, tools=tools)
#98
#99	mock_openai_client.chat.completions.create.assert_called_once_with(
#100	model="gpt-4.1-nano-2025-04-14", messages=messages, temperature=0.7, max_tokens=100, top_p=1.0, tools=tools, tool_choice="auto", store=False
#101	)
#102
#103	assert response["content"] == "I've added the memory for you."
#104	assert len(response["tool_calls"]) == 1
#105	assert response["tool_calls"][0]["name"] == "add_memory"
#106	assert response["tool_calls"][0]["arguments"] == {"data": "Today is a sunny day."}
#107
#108
#109	def test_response_callback_invocation(mock_openai_client):
#110	# Setup mock callback
#111	mock_callback = Mock()
#112
#113	config = OpenAIConfig(model="gpt-4.1-nano-2025-04-14", response_callback=mock_callback)
#114	llm = OpenAILLM(config)
#115	messages = [{"role": "user", "content": "Test callback"}]
#116
#117	# Mock response
#118	mock_response = Mock()
#119	mock_response.choices = [Mock(message=Mock(content="Response"))]
#120	mock_openai_client.chat.completions.create.return_value = mock_response
#121
#122	# Call method
#123	llm.generate_response(messages)
#124
#125	# Verify callback called with correct arguments
#126	mock_callback.assert_called_once()
#127	args = mock_callback.call_args[0]
#128	assert args[0] is llm # llm_instance
#129	assert args[1] == mock_response # raw_response
#130	assert "messages" in args[2] # params
#131
#132
#133	def test_no_response_callback(mock_openai_client):
#134	config = OpenAIConfig(model="gpt-4.1-nano-2025-04-14")
#135	llm = OpenAILLM(config)
#136	messages = [{"role": "user", "content": "Test no callback"}]
#137
#138	# Mock response
#139	mock_response = Mock()
#140	mock_response.choices = [Mock(message=Mock(content="Response"))]
#141	mock_openai_client.chat.completions.create.return_value = mock_response
#142
#143	# Should complete without calling any callback
#144	response = llm.generate_response(messages)
#145	assert response == "Response"
#146
#147	# Verify no callback is set
#148	assert llm.config.response_callback is None
#149
#150
#151	def test_callback_exception_handling(mock_openai_client):
#152	# Callback that raises exception
#153	def faulty_callback(*args):
#154	raise ValueError("Callback error")
#155
#156	config = OpenAIConfig(model="gpt-4.1-nano-2025-04-14", response_callback=faulty_callback)
#157	llm = OpenAILLM(config)
#158	messages = [{"role": "user", "content": "Test exception"}]
#159
#160	# Mock response
#161	mock_response = Mock()
#162	mock_response.choices = [Mock(message=Mock(content="Expected response"))]
#163	mock_openai_client.chat.completions.create.return_value = mock_response
#164
#165	# Should complete without raising
#166	response = llm.generate_response(messages)
#167	assert response == "Expected response"
#168
#169	# Verify callback was called (even though it raised an exception)
#170	assert llm.config.response_callback is faulty_callback
#171
#172
#173	def test_callback_with_tools(mock_openai_client):
#174	mock_callback = Mock()
#175	config = OpenAIConfig(model="gpt-4.1-nano-2025-04-14", response_callback=mock_callback)
#176	llm = OpenAILLM(config)
#177	messages = [{"role": "user", "content": "Test tools"}]
#178	tools = [
#179	{
#180	"type": "function",
#181	"function": {
#182	"name": "test_tool",
#183	"description": "A test tool",
#184	"parameters": {
#185	"type": "object",
#186	"properties": {"param1": {"type": "string"}},
#187	"required": ["param1"],
#188	},
#189	}
#190	}
#191	]
#192
#193	# Mock tool response
#194	mock_response = Mock()
#195	mock_message = Mock()
#196	mock_message.content = "Tool response"
#197	mock_tool_call = Mock()
#198	mock_tool_call.function.name = "test_tool"
#199	mock_tool_call.function.arguments = '{"param1": "value1"}'
#200	mock_message.tool_calls = [mock_tool_call]
#201	mock_response.choices = [Mock(message=mock_message)]
#202	mock_openai_client.chat.completions.create.return_value = mock_response
#203
#204	llm.generate_response(messages, tools=tools)
#205
#206	# Verify callback called with tool response
#207	mock_callback.assert_called_once()
#208	# Check that tool_calls exists in the message
#209	assert hasattr(mock_callback.call_args[0][1].choices[0].message, 'tool_calls')
#210

z6Mkq5mY3JWtxoxUobWcfNHm7AkRubgSWEZTkBVqZXJviFZ5/my-project-public