from langchain.chat_models.base import BaseChatModel
from langchain_community.chat_models.fake import FakeListChatModel

from gpt_engineer.core.ai import AI


def mock_create_chat_model(self) -> BaseChatModel:
    return FakeListChatModel(responses=["response1", "response2", "response3"])


def test_start(monkeypatch):
    monkeypatch.setattr(AI, "_create_chat_model", mock_create_chat_model)

    ai = AI("gpt-4")

    # act
    response_messages = ai.start("system prompt", "user prompt", step_name="step name")

    # assert
    assert response_messages[-1].content == "response1"


def test_next(monkeypatch):
    # arrange
    monkeypatch.setattr(AI, "_create_chat_model", mock_create_chat_model)

    ai = AI("gpt-4")
    response_messages = ai.start("system prompt", "user prompt", step_name="step name")

    # act
    response_messages = ai.next(
        response_messages, "next user prompt", step_name="step name"
    )

    # assert
    assert response_messages[-1].content == "response2"


def test_token_logging(monkeypatch):
    # arrange
    monkeypatch.setattr(AI, "_create_chat_model", mock_create_chat_model)

    ai = AI("gpt-4")

    # act
    response_messages = ai.start("system prompt", "user prompt", step_name="step name")
    usageCostAfterStart = ai.token_usage_log.usage_cost()
    ai.next(response_messages, "next user prompt", step_name="step name")
    usageCostAfterNext = ai.token_usage_log.usage_cost()

    # assert
    assert usageCostAfterStart > 0
    assert usageCostAfterNext > usageCostAfterStart