144 lines
5.0 KiB
Python
144 lines
5.0 KiB
Python
import os
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import pytest
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from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
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from embedchain.config import BaseLlmConfig
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from embedchain.llm.openai import OpenAILlm
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@pytest.fixture
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def config():
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os.environ["OPENAI_API_KEY"] = "test_api_key"
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os.environ["OPENAI_API_BASE"] = "https://api.openai.com/v1/engines/"
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config = BaseLlmConfig(
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temperature=0.7, max_tokens=50, top_p=0.8, stream=False, system_prompt="System prompt", model="gpt-3.5-turbo"
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)
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yield config
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os.environ.pop("OPENAI_API_KEY")
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def test_get_llm_model_answer(config, mocker):
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mocked_get_answer = mocker.patch("embedchain.llm.openai.OpenAILlm._get_answer", return_value="Test answer")
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llm = OpenAILlm(config)
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answer = llm.get_llm_model_answer("Test query")
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assert answer == "Test answer"
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mocked_get_answer.assert_called_once_with("Test query", config)
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def test_get_llm_model_answer_with_system_prompt(config, mocker):
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config.system_prompt = "Custom system prompt"
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mocked_get_answer = mocker.patch("embedchain.llm.openai.OpenAILlm._get_answer", return_value="Test answer")
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llm = OpenAILlm(config)
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answer = llm.get_llm_model_answer("Test query")
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assert answer == "Test answer"
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mocked_get_answer.assert_called_once_with("Test query", config)
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def test_get_llm_model_answer_empty_prompt(config, mocker):
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mocked_get_answer = mocker.patch("embedchain.llm.openai.OpenAILlm._get_answer", return_value="Test answer")
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llm = OpenAILlm(config)
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answer = llm.get_llm_model_answer("")
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assert answer == "Test answer"
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mocked_get_answer.assert_called_once_with("", config)
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def test_get_llm_model_answer_with_streaming(config, mocker):
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config.stream = True
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mocked_openai_chat = mocker.patch("embedchain.llm.openai.ChatOpenAI")
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llm = OpenAILlm(config)
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llm.get_llm_model_answer("Test query")
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mocked_openai_chat.assert_called_once()
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callbacks = [callback[1]["callbacks"] for callback in mocked_openai_chat.call_args_list]
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assert any(isinstance(callback[0], StreamingStdOutCallbackHandler) for callback in callbacks)
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def test_get_llm_model_answer_without_system_prompt(config, mocker):
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config.system_prompt = None
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mocked_openai_chat = mocker.patch("embedchain.llm.openai.ChatOpenAI")
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llm = OpenAILlm(config)
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llm.get_llm_model_answer("Test query")
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mocked_openai_chat.assert_called_once_with(
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model=config.model,
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temperature=config.temperature,
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max_tokens=config.max_tokens,
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model_kwargs={"top_p": config.top_p},
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api_key=os.environ["OPENAI_API_KEY"],
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base_url=os.environ["OPENAI_API_BASE"],
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)
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def test_get_llm_model_answer_with_special_headers(config, mocker):
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config.default_headers = {"test": "test"}
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mocked_openai_chat = mocker.patch("embedchain.llm.openai.ChatOpenAI")
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llm = OpenAILlm(config)
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llm.get_llm_model_answer("Test query")
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mocked_openai_chat.assert_called_once_with(
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model=config.model,
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temperature=config.temperature,
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max_tokens=config.max_tokens,
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model_kwargs={"top_p": config.top_p},
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api_key=os.environ["OPENAI_API_KEY"],
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base_url=os.environ["OPENAI_API_BASE"],
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default_headers={"test": "test"},
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)
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def test_get_llm_model_answer_with_model_kwargs(config, mocker):
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config.model_kwargs = {"response_format": {"type": "json_object"}}
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mocked_openai_chat = mocker.patch("embedchain.llm.openai.ChatOpenAI")
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llm = OpenAILlm(config)
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llm.get_llm_model_answer("Test query")
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mocked_openai_chat.assert_called_once_with(
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model=config.model,
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temperature=config.temperature,
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max_tokens=config.max_tokens,
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model_kwargs={"top_p": config.top_p, "response_format": {"type": "json_object"}},
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api_key=os.environ["OPENAI_API_KEY"],
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base_url=os.environ["OPENAI_API_BASE"],
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)
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@pytest.mark.parametrize(
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"mock_return, expected",
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[
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([{"test": "test"}], '{"test": "test"}'),
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([], "Input could not be mapped to the function!"),
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],
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)
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def test_get_llm_model_answer_with_tools(config, mocker, mock_return, expected):
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mocked_openai_chat = mocker.patch("embedchain.llm.openai.ChatOpenAI")
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mocked_convert_to_openai_tool = mocker.patch("langchain_core.utils.function_calling.convert_to_openai_tool")
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mocked_json_output_tools_parser = mocker.patch("langchain.output_parsers.openai_tools.JsonOutputToolsParser")
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mocked_openai_chat.return_value.bind.return_value.pipe.return_value.invoke.return_value = mock_return
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llm = OpenAILlm(config, tools={"test": "test"})
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answer = llm.get_llm_model_answer("Test query")
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mocked_openai_chat.assert_called_once_with(
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model=config.model,
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temperature=config.temperature,
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max_tokens=config.max_tokens,
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model_kwargs={"top_p": config.top_p},
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api_key=os.environ["OPENAI_API_KEY"],
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base_url=os.environ["OPENAI_API_BASE"],
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)
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mocked_convert_to_openai_tool.assert_called_once_with({"test": "test"})
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mocked_json_output_tools_parser.assert_called_once()
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assert answer == expected
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