"""Test chat model integration."""
from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
from langchain_core.pydantic_v1 import SecretStr
from pytest import CaptureFixture

from langchain_google_genai.chat_models import (
    ChatGoogleGenerativeAI,
    _parse_chat_history,
)


def test_integration_initialization() -> None:
    """Test chat model initialization."""
    ChatGoogleGenerativeAI(
        model="gemini-nano",
        google_api_key="...",
        top_k=2,
        top_p=1,
        temperature=0.7,
        n=2,
    )
    ChatGoogleGenerativeAI(
        model="gemini-nano",
        google_api_key="...",
        top_k=2,
        top_p=1,
        temperature=0.7,
        candidate_count=2,
    )


def test_api_key_is_string() -> None:
    chat = ChatGoogleGenerativeAI(model="gemini-nano", google_api_key="secret-api-key")
    assert isinstance(chat.google_api_key, SecretStr)


def test_api_key_masked_when_passed_via_constructor(capsys: CaptureFixture) -> None:
    chat = ChatGoogleGenerativeAI(model="gemini-nano", google_api_key="secret-api-key")
    print(chat.google_api_key, end="")
    captured = capsys.readouterr()

    assert captured.out == "**********"


def test_parse_history() -> None:
    system_input = "You're supposed to answer math questions."
    text_question1, text_answer1 = "How much is 2+2?", "4"
    text_question2 = "How much is 3+3?"
    system_message = SystemMessage(content=system_input)
    message1 = HumanMessage(content=text_question1)
    message2 = AIMessage(content=text_answer1)
    message3 = HumanMessage(content=text_question2)
    messages = [system_message, message1, message2, message3]
    history = _parse_chat_history(messages, convert_system_message_to_human=True)
    assert len(history) == 3
    assert history[0] == {
        "role": "user",
        "parts": [{"text": system_input}, {"text": text_question1}],
    }
    assert history[1] == {"role": "model", "parts": [{"text": text_answer1}]}