mem0/tests/llm/test_openai.py

import os

import pytest
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler

from embedchain.config import BaseLlmConfig
from embedchain.llm.openai import OpenAILlm


@pytest.fixture
def config():
    os.environ["OPENAI_API_KEY"] = "test_api_key"
    config = BaseLlmConfig(
        temperature=0.7, max_tokens=50, top_p=0.8, stream=False, system_prompt="System prompt", model="gpt-3.5-turbo"
    )
    yield config
    os.environ.pop("OPENAI_API_KEY")


def test_get_llm_model_answer(config, mocker):
    mocked_get_answer = mocker.patch("embedchain.llm.openai.OpenAILlm._get_answer", return_value="Test answer")

    llm = OpenAILlm(config)
    answer = llm.get_llm_model_answer("Test query")

    assert answer == "Test answer"
    mocked_get_answer.assert_called_once_with("Test query", config)


def test_get_llm_model_answer_with_system_prompt(config, mocker):
    config.system_prompt = "Custom system prompt"
    mocked_get_answer = mocker.patch("embedchain.llm.openai.OpenAILlm._get_answer", return_value="Test answer")

    llm = OpenAILlm(config)
    answer = llm.get_llm_model_answer("Test query")

    assert answer == "Test answer"
    mocked_get_answer.assert_called_once_with("Test query", config)


def test_get_llm_model_answer_empty_prompt(config, mocker):
    mocked_get_answer = mocker.patch("embedchain.llm.openai.OpenAILlm._get_answer", return_value="Test answer")

    llm = OpenAILlm(config)
    answer = llm.get_llm_model_answer("")

    assert answer == "Test answer"
    mocked_get_answer.assert_called_once_with("", config)


def test_get_llm_model_answer_with_streaming(config, mocker):
    config.stream = True
    mocked_openai_chat = mocker.patch("embedchain.llm.openai.ChatOpenAI")

    llm = OpenAILlm(config)
    llm.get_llm_model_answer("Test query")

    mocked_openai_chat.assert_called_once()
    callbacks = [callback[1]["callbacks"] for callback in mocked_openai_chat.call_args_list]
    assert any(isinstance(callback[0], StreamingStdOutCallbackHandler) for callback in callbacks)


def test_get_llm_model_answer_without_system_prompt(config, mocker):
    config.system_prompt = None
    mocked_openai_chat = mocker.patch("embedchain.llm.openai.ChatOpenAI")

    llm = OpenAILlm(config)
    llm.get_llm_model_answer("Test query")

    mocked_openai_chat.assert_called_once_with(
        model=config.model,
        temperature=config.temperature,
        max_tokens=config.max_tokens,
        model_kwargs={"top_p": config.top_p},
        api_key=os.environ["OPENAI_API_KEY"],
    )


@pytest.mark.parametrize(
    "mock_return, expected",
    [
        ([{"test": "test"}], '{"test": "test"}'),
        ([], "Input could not be mapped to the function!"),
    ],
)
def test_get_llm_model_answer_with_tools(config, mocker, mock_return, expected):
    mocked_openai_chat = mocker.patch("embedchain.llm.openai.ChatOpenAI")
    mocked_convert_to_openai_tool = mocker.patch("langchain_core.utils.function_calling.convert_to_openai_tool")
    mocked_json_output_tools_parser = mocker.patch("langchain.output_parsers.openai_tools.JsonOutputToolsParser")
    mocked_openai_chat.return_value.bind.return_value.pipe.return_value.invoke.return_value = mock_return

    llm = OpenAILlm(config, tools={"test": "test"})
    answer = llm.get_llm_model_answer("Test query")

    mocked_openai_chat.assert_called_once_with(
        model=config.model,
        temperature=config.temperature,
        max_tokens=config.max_tokens,
        model_kwargs={"top_p": config.top_p},
        api_key=os.environ["OPENAI_API_KEY"],
    )
    mocked_convert_to_openai_tool.assert_called_once_with({"test": "test"})
    mocked_json_output_tools_parser.assert_called_once()

    assert answer == expected