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mem0ai--mem0/tests/llms/test_openai_structured.py
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chore: import upstream snapshot with attribution
2026-07-13 13:03:45 +08:00

52 lines
1.9 KiB
Python

from unittest.mock import Mock, patch
import pytest
from mem0.configs.llms.openai import OpenAIConfig
from mem0.llms.openai_structured import OpenAIStructuredLLM
@pytest.fixture
def mock_openai_client():
with patch("mem0.llms.openai_structured.OpenAI") as mock_openai:
mock_client = Mock()
mock_openai.return_value = mock_client
yield mock_client
def _mock_parse(mock_client, content="ok"):
mock_response = Mock()
mock_response.choices = [Mock(message=Mock(content=content))]
mock_client.beta.chat.completions.parse.return_value = mock_response
def test_reasoning_model_drops_temperature(mock_openai_client):
"""Reasoning models reject `temperature`; structured output must not send it."""
config = OpenAIConfig(model="o3-mini", reasoning_effort="low")
llm = OpenAIStructuredLLM(config)
_mock_parse(mock_openai_client)
llm.generate_response([{"role": "user", "content": "Hello"}])
call_kwargs = mock_openai_client.beta.chat.completions.parse.call_args[1]
assert "temperature" not in call_kwargs # reasoning models don't accept temperature
assert "max_tokens" not in call_kwargs # also dropped for reasoning models
assert "top_p" not in call_kwargs # also dropped for reasoning models
assert call_kwargs["reasoning_effort"] == "low"
assert call_kwargs["model"] == "o3-mini"
def test_regular_model_sends_sampling_params(mock_openai_client):
"""Regular models still receive the standard sampling params."""
config = OpenAIConfig(model="gpt-4o", temperature=0.3)
llm = OpenAIStructuredLLM(config)
_mock_parse(mock_openai_client)
llm.generate_response([{"role": "user", "content": "Hello"}])
call_kwargs = mock_openai_client.beta.chat.completions.parse.call_args[1]
assert call_kwargs["temperature"] == 0.3
assert "max_tokens" in call_kwargs # standard sampling params still forwarded
assert "top_p" in call_kwargs
assert call_kwargs["model"] == "gpt-4o"