import os

import httpx
import pytest
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler

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


@pytest.fixture()
def env_config():
    os.environ["OPENAI_API_KEY"] = "test_api_key"
    os.environ["OPENAI_API_BASE"] = "https://api.openai.com/v1/engines/"
    yield
    os.environ.pop("OPENAI_API_KEY")


@pytest.fixture
def config(env_config):
    config = BaseLlmConfig(
        temperature=0.7,
        max_tokens=50,
        top_p=0.8,
        stream=False,
        system_prompt="System prompt",
        model="gpt-4o-mini",
        http_client_proxies=None,
        http_async_client_proxies=None,
    )
    yield config


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_token_usage(config, mocker):
    test_config = BaseLlmConfig(
        temperature=config.temperature,
        max_tokens=config.max_tokens,
        top_p=config.top_p,
        stream=config.stream,
        system_prompt=config.system_prompt,
        model=config.model,
        token_usage=True,
    )
    mocked_get_answer = mocker.patch(
        "embedchain.llm.openai.OpenAILlm._get_answer",
        return_value=("Test answer", {"prompt_tokens": 1, "completion_tokens": 2}),
    )

    llm = OpenAILlm(test_config)
    answer, token_info = llm.get_llm_model_answer("Test query")

    assert answer == "Test answer"
    assert token_info == {
        "prompt_tokens": 1,
        "completion_tokens": 2,
        "total_tokens": 3,
        "total_cost": 1.35e-06,
        "cost_currency": "USD",
    }
    mocked_get_answer.assert_called_once_with("Test query", test_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"],
        base_url=os.environ["OPENAI_API_BASE"],
        http_client=None,
        http_async_client=None,
    )


def test_get_llm_model_answer_with_special_headers(config, mocker):
    config.default_headers = {"test": "test"}
    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"],
        base_url=os.environ["OPENAI_API_BASE"],
        default_headers={"test": "test"},
        http_client=None,
        http_async_client=None,
    )


def test_get_llm_model_answer_with_model_kwargs(config, mocker):
    config.model_kwargs = {"response_format": {"type": "json_object"}}
    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={"response_format": {"type": "json_object"}},
        top_p=config.top_p,
        api_key=os.environ["OPENAI_API_KEY"],
        base_url=os.environ["OPENAI_API_BASE"],
        http_client=None,
        http_async_client=None,
    )


@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"],
        base_url=os.environ["OPENAI_API_BASE"],
        http_client=None,
        http_async_client=None,
    )
    mocked_convert_to_openai_tool.assert_called_once_with({"test": "test"})
    mocked_json_output_tools_parser.assert_called_once()

    assert answer == expected


def test_get_llm_model_answer_with_http_client_proxies(env_config, mocker):
    mocked_openai_chat = mocker.patch("embedchain.llm.openai.ChatOpenAI")
    mock_http_client = mocker.Mock(spec=httpx.Client)
    mock_http_client_instance = mocker.Mock(spec=httpx.Client)
    mock_http_client.return_value = mock_http_client_instance

    mocker.patch("httpx.Client", new=mock_http_client)

    config = BaseLlmConfig(
        temperature=0.7,
        max_tokens=50,
        top_p=0.8,
        stream=False,
        system_prompt="System prompt",
        model="gpt-4o-mini",
        http_client_proxies="http://testproxy.dejavu.net:8000",
    )

    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"],
        base_url=os.environ["OPENAI_API_BASE"],
        http_client=mock_http_client_instance,
        http_async_client=None,
    )
    mock_http_client.assert_called_once_with(proxies="http://testproxy.dejavu.net:8000")


def test_get_llm_model_answer_with_http_async_client_proxies(env_config, mocker):
    mocked_openai_chat = mocker.patch("embedchain.llm.openai.ChatOpenAI")
    mock_http_async_client = mocker.Mock(spec=httpx.AsyncClient)
    mock_http_async_client_instance = mocker.Mock(spec=httpx.AsyncClient)
    mock_http_async_client.return_value = mock_http_async_client_instance

    mocker.patch("httpx.AsyncClient", new=mock_http_async_client)

    config = BaseLlmConfig(
        temperature=0.7,
        max_tokens=50,
        top_p=0.8,
        stream=False,
        system_prompt="System prompt",
        model="gpt-4o-mini",
        http_async_client_proxies={"http://": "http://testproxy.dejavu.net:8000"},
    )

    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"],
        base_url=os.environ["OPENAI_API_BASE"],
        http_client=None,
        http_async_client=mock_http_async_client_instance,
    )
    mock_http_async_client.assert_called_once_with(proxies={"http://": "http://testproxy.dejavu.net:8000"})
