"""Test Vertex AI API wrapper.
In order to run this test, you need to install VertexAI SDK (that is is the private
preview)  and be whitelisted to list the models themselves:
In order to run this test, you need to install VertexAI SDK 
pip install google-cloud-aiplatform>=1.25.0

Your end-user credentials would be used to make the calls (make sure you've run 
`gcloud auth login` first).
"""
from unittest.mock import Mock, patch

import pytest

from langchain.chat_models import ChatVertexAI
from langchain.chat_models.vertexai import _MessagePair, _parse_chat_history
from langchain.schema.messages import AIMessage, HumanMessage, SystemMessage


def test_vertexai_single_call() -> None:
    model = ChatVertexAI()
    message = HumanMessage(content="Hello")
    response = model([message])
    assert isinstance(response, AIMessage)
    assert isinstance(response.content, str)
    assert model._llm_type == "vertexai"
    assert model.model_name == model.client._model_id


def test_vertexai_single_call_with_context() -> None:
    model = ChatVertexAI()
    raw_context = (
        "My name is Ned. You are my personal assistant. My favorite movies "
        "are Lord of the Rings and Hobbit."
    )
    question = (
        "Hello, could you recommend a good movie for me to watch this evening, please?"
    )
    context = SystemMessage(content=raw_context)
    message = HumanMessage(content=question)
    response = model([context, message])
    assert isinstance(response, AIMessage)
    assert isinstance(response.content, str)


def test_parse_chat_history_correct() -> None:
    text_context = (
        "My name is Ned. You are my personal assistant. My "
        "favorite movies are Lord of the Rings and Hobbit."
    )
    context = SystemMessage(content=text_context)
    text_question = (
        "Hello, could you recommend a good movie for me to watch this evening, please?"
    )
    question = HumanMessage(content=text_question)
    text_answer = (
        "Sure, You might enjoy The Lord of the Rings: The Fellowship of the Ring "
        "(2001): This is the first movie in the Lord of the Rings trilogy."
    )
    answer = AIMessage(content=text_answer)
    history = _parse_chat_history([context, question, answer, question, answer])
    assert history.system_message == context
    assert len(history.history) == 2
    assert history.history[0] == _MessagePair(question=question, answer=answer)


def test_parse_chat_history_wrong_sequence() -> None:
    text_question = (
        "Hello, could you recommend a good movie for me to watch this evening, please?"
    )
    question = HumanMessage(content=text_question)
    with pytest.raises(ValueError) as exc_info:
        _ = _parse_chat_history([question, question])
    assert (
        str(exc_info.value)
        == "A human message should follow a bot one, got human, human."
    )


def test_vertexai_single_call_failes_no_message() -> None:
    chat = ChatVertexAI()
    with pytest.raises(ValueError) as exc_info:
        _ = chat([])
    assert (
        str(exc_info.value)
        == "You should provide at least one message to start the chat!"
    )


def test_vertexai_args_passed() -> None:
    response_text = "Goodbye"
    user_prompt = "Hello"
    prompt_params = {
        "max_output_tokens": 1,
        "temperature": 10000.0,
        "top_k": 10,
        "top_p": 0.5,
    }

    # Mock the library to ensure the args are passed correctly
    with patch(
        "vertexai.language_models._language_models.ChatSession.send_message"
    ) as send_message:
        mock_response = Mock(text=response_text)
        send_message.return_value = mock_response

        model = ChatVertexAI(**prompt_params)
        message = HumanMessage(content=user_prompt)
        response = model([message])

        assert response.content == response_text
        send_message.assert_called_once_with(
            user_prompt,
            **prompt_params,
        )
