"""
Test cases for the config class, which handles the configuration settings
for the AI and ensures it behaves as a singleton.
"""
import os
from typing import Any
from unittest import mock
from unittest.mock import patch

import pytest
from openai.pagination import SyncPage
from openai.types import Model
from pydantic import SecretStr

from autogpt.app.configurator import GPT_3_MODEL, GPT_4_MODEL, apply_overrides_to_config
from autogpt.config import Config, ConfigBuilder


def test_initial_values(config: Config) -> None:
    """
    Test if the initial values of the config class attributes are set correctly.
    """
    assert config.continuous_mode is False
    assert config.tts_config.speak_mode is False
    assert config.fast_llm == "gpt-3.5-turbo-16k"
    assert config.smart_llm.startswith("gpt-4")


def test_set_continuous_mode(config: Config) -> None:
    """
    Test if the set_continuous_mode() method updates the continuous_mode attribute.
    """
    # Store continuous mode to reset it after the test
    continuous_mode = config.continuous_mode

    config.continuous_mode = True
    assert config.continuous_mode is True

    # Reset continuous mode
    config.continuous_mode = continuous_mode


def test_set_speak_mode(config: Config) -> None:
    """
    Test if the set_speak_mode() method updates the speak_mode attribute.
    """
    # Store speak mode to reset it after the test
    speak_mode = config.tts_config.speak_mode

    config.tts_config.speak_mode = True
    assert config.tts_config.speak_mode is True

    # Reset speak mode
    config.tts_config.speak_mode = speak_mode


def test_set_fast_llm(config: Config) -> None:
    """
    Test if the set_fast_llm() method updates the fast_llm attribute.
    """
    # Store model name to reset it after the test
    fast_llm = config.fast_llm

    config.fast_llm = "gpt-3.5-turbo-test"
    assert config.fast_llm == "gpt-3.5-turbo-test"

    # Reset model name
    config.fast_llm = fast_llm


def test_set_smart_llm(config: Config) -> None:
    """
    Test if the set_smart_llm() method updates the smart_llm attribute.
    """
    # Store model name to reset it after the test
    smart_llm = config.smart_llm

    config.smart_llm = "gpt-4-test"
    assert config.smart_llm == "gpt-4-test"

    # Reset model name
    config.smart_llm = smart_llm


@patch("openai.resources.models.Models.list")
def test_fallback_to_gpt3_if_gpt4_not_available(
    mock_list_models: Any, config: Config
) -> None:
    """
    Test if models update to gpt-3.5-turbo if gpt-4 is not available.
    """
    fast_llm = config.fast_llm
    smart_llm = config.smart_llm

    config.fast_llm = "gpt-4"
    config.smart_llm = "gpt-4"

    mock_list_models.return_value = SyncPage(
        data=[Model(id=GPT_3_MODEL, created=0, object="model", owned_by="AutoGPT")],
        object="Models",  # no idea what this should be, but irrelevant
    )

    apply_overrides_to_config(
        config=config,
        gpt3only=False,
        gpt4only=False,
    )

    assert config.fast_llm == "gpt-3.5-turbo"
    assert config.smart_llm == "gpt-3.5-turbo"

    # Reset config
    config.fast_llm = fast_llm
    config.smart_llm = smart_llm


def test_missing_azure_config(config: Config) -> None:
    assert config.openai_credentials is not None

    config_file = config.app_data_dir / "azure_config.yaml"
    with pytest.raises(FileNotFoundError):
        config.openai_credentials.load_azure_config(config_file)

    config_file.write_text("")
    with pytest.raises(ValueError):
        config.openai_credentials.load_azure_config(config_file)

    assert config.openai_credentials.api_type != "azure"
    assert config.openai_credentials.api_version == ""
    assert config.openai_credentials.azure_model_to_deploy_id_map is None


@pytest.fixture
def config_with_azure(config: Config):
    config_file = config.app_data_dir / "azure_config.yaml"
    config_file.write_text(
        f"""
azure_api_type: azure
azure_api_version: 2023-06-01-preview
azure_endpoint: https://dummy.openai.azure.com
azure_model_map:
    {config.fast_llm}: FAST-LLM_ID
    {config.smart_llm}: SMART-LLM_ID
    {config.embedding_model}: embedding-deployment-id-for-azure
"""
    )
    os.environ["USE_AZURE"] = "True"
    os.environ["AZURE_CONFIG_FILE"] = str(config_file)
    config_with_azure = ConfigBuilder.build_config_from_env(
        project_root=config.project_root
    )
    yield config_with_azure
    del os.environ["USE_AZURE"]
    del os.environ["AZURE_CONFIG_FILE"]


def test_azure_config(config_with_azure: Config) -> None:
    assert (credentials := config_with_azure.openai_credentials) is not None
    assert credentials.api_type == "azure"
    assert credentials.api_version == "2023-06-01-preview"
    assert credentials.azure_endpoint == SecretStr("https://dummy.openai.azure.com")
    assert credentials.azure_model_to_deploy_id_map == {
        config_with_azure.fast_llm: "FAST-LLM_ID",
        config_with_azure.smart_llm: "SMART-LLM_ID",
        config_with_azure.embedding_model: "embedding-deployment-id-for-azure",
    }

    fast_llm = config_with_azure.fast_llm
    smart_llm = config_with_azure.smart_llm
    assert (
        credentials.get_model_access_kwargs(config_with_azure.fast_llm)["model"]
        == "FAST-LLM_ID"
    )
    assert (
        credentials.get_model_access_kwargs(config_with_azure.smart_llm)["model"]
        == "SMART-LLM_ID"
    )

    # Emulate --gpt4only
    config_with_azure.fast_llm = smart_llm
    assert (
        credentials.get_model_access_kwargs(config_with_azure.fast_llm)["model"]
        == "SMART-LLM_ID"
    )
    assert (
        credentials.get_model_access_kwargs(config_with_azure.smart_llm)["model"]
        == "SMART-LLM_ID"
    )

    # Emulate --gpt3only
    config_with_azure.fast_llm = config_with_azure.smart_llm = fast_llm
    assert (
        credentials.get_model_access_kwargs(config_with_azure.fast_llm)["model"]
        == "FAST-LLM_ID"
    )
    assert (
        credentials.get_model_access_kwargs(config_with_azure.smart_llm)["model"]
        == "FAST-LLM_ID"
    )


def test_create_config_gpt4only(config: Config) -> None:
    with mock.patch("autogpt.llm.api_manager.ApiManager.get_models") as mock_get_models:
        mock_get_models.return_value = [
            Model(id=GPT_4_MODEL, created=0, object="model", owned_by="AutoGPT")
        ]
        apply_overrides_to_config(
            config=config,
            gpt4only=True,
        )
        assert config.fast_llm == GPT_4_MODEL
        assert config.smart_llm == GPT_4_MODEL


def test_create_config_gpt3only(config: Config) -> None:
    with mock.patch("autogpt.llm.api_manager.ApiManager.get_models") as mock_get_models:
        mock_get_models.return_value = [{"id": GPT_3_MODEL}]
        apply_overrides_to_config(
            config=config,
            gpt3only=True,
        )
        assert config.fast_llm == GPT_3_MODEL
        assert config.smart_llm == GPT_3_MODEL