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my-project-public — gitlawb

#1	from unittest.mock import Mock, patch
#2
#3	import pytest
#4
#5	from mem0.configs.llms.lmstudio import LMStudioConfig
#6	from mem0.llms.lmstudio import LMStudioLLM
#7
#8
#9	@pytest.fixture
#10	def mock_lm_studio_client():
#11	with patch("mem0.llms.lmstudio.OpenAI") as mock_openai: # Corrected path
#12	mock_client = Mock()
#13	mock_client.chat.completions.create.return_value = Mock(
#14	choices=[Mock(message=Mock(content="I'm doing well, thank you for asking!"))]
#15	)
#16	mock_openai.return_value = mock_client
#17	yield mock_client
#18
#19
#20	def test_generate_response_without_tools(mock_lm_studio_client):
#21	config = LMStudioConfig(
#22	model="lmstudio-community/Meta-Llama-3.1-8B-Instruct-GGUF/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf",
#23	temperature=0.7,
#24	max_tokens=100,
#25	top_p=1.0,
#26	)
#27	llm = LMStudioLLM(config)
#28	messages = [
#29	{"role": "system", "content": "You are a helpful assistant."},
#30	{"role": "user", "content": "Hello, how are you?"},
#31	]
#32
#33	response = llm.generate_response(messages)
#34
#35	mock_lm_studio_client.chat.completions.create.assert_called_once_with(
#36	model="lmstudio-community/Meta-Llama-3.1-8B-Instruct-GGUF/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf",
#37	messages=messages,
#38	temperature=0.7,
#39	max_tokens=100,
#40	top_p=1.0,
#41	response_format={"type": "json_object"},
#42	)
#43
#44	assert response == "I'm doing well, thank you for asking!"
#45
#46
#47	def test_generate_response_specifying_response_format(mock_lm_studio_client):
#48	config = LMStudioConfig(
#49	model="lmstudio-community/Meta-Llama-3.1-8B-Instruct-GGUF/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf",
#50	temperature=0.7,
#51	max_tokens=100,
#52	top_p=1.0,
#53	lmstudio_response_format={"type": "json_schema"}, # Specifying the response format in config
#54	)
#55	llm = LMStudioLLM(config)
#56	messages = [
#57	{"role": "system", "content": "You are a helpful assistant."},
#58	{"role": "user", "content": "Hello, how are you?"},
#59	]
#60
#61	response = llm.generate_response(messages)
#62
#63	mock_lm_studio_client.chat.completions.create.assert_called_once_with(
#64	model="lmstudio-community/Meta-Llama-3.1-8B-Instruct-GGUF/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf",
#65	messages=messages,
#66	temperature=0.7,
#67	max_tokens=100,
#68	top_p=1.0,
#69	response_format={"type": "json_schema"},
#70	)
#71
#72	assert response == "I'm doing well, thank you for asking!"
#73

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