#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
-------------------------------------------------------------------------
This file is part of the RAGSDK project.
Copyright (c) 2025 Huawei Technologies Co.,Ltd.

RAGSDK is licensed under Mulan PSL v2.
You can use this software according to the terms and conditions of the Mulan PSL v2.
You may obtain a copy of Mulan PSL v2 at:

         http://license.coscl.org.cn/MulanPSL2

THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, WITHOUT WARRANTIES OF ANY KIND,
EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT,
MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE.
See the Mulan PSL v2 for more details.
-------------------------------------------------------------------------
"""


import unittest
from unittest.mock import Mock, patch
from mx_rag.graphrag.qa_base_model import QABaseModel, GenerationEvaluationStrategy
from mx_rag.utils.common import Lang


class TestQABaseModel(unittest.TestCase):
    def setUp(self):
        """Set up a mock LLM and QABaseModel instance."""
        self.mock_llm = Mock()
        self.mock_llm_config = Mock()
        self.qa_model = QABaseModel(self.mock_llm, self.mock_llm_config, metric="generation")

    def test_init(self):
        """Test initialization of QABaseModel."""
        self.assertEqual(self.qa_model.llm, self.mock_llm)
        self.assertEqual(self.qa_model.llm_config, self.mock_llm_config)
        self.assertEqual(self.qa_model.metric, "generation")
        self.assertIsInstance(self.qa_model.evaluation_strategy, GenerationEvaluationStrategy)

    @patch.object(QABaseModel, "_plain_generate")
    def test_generate(self, mock_plain_generate):
        """Test the generate method."""
        mock_plain_generate.return_value = ["response1", "response2"]
        questions = ["question1", "question2"]

        result = self.qa_model.generate(questions)

        mock_plain_generate.assert_called_once_with(questions)
        self.assertEqual(result, ["response1", "response2"])

    @patch.object(GenerationEvaluationStrategy, "evaluate")
    def test_evaluate(self, mock_evaluate):
        """Test the evaluate method."""
        mock_evaluate.return_value = ["evaluation1", "evaluation2"]
        questions = ["question1", "question2"]
        answers = ["answer1", "answer2"]
        responses = ["response1", "response2"]

        result = self.qa_model.evaluate(questions, answers, responses, Lang.EN)

        mock_evaluate.assert_called_once_with(questions, answers, responses, Lang.EN)
        self.assertEqual(result, ["evaluation1", "evaluation2"])

    def test_select_evaluation_strategy(self):
        """Test the _select_evaluation_strategy method."""
        strategy = self.qa_model._select_evaluation_strategy()
        self.assertIsInstance(strategy, GenerationEvaluationStrategy)

        # Test unsupported metric
        self.qa_model.metric = "unsupported_metric"
        strategy = self.qa_model._select_evaluation_strategy()
        self.assertIsNone(strategy)

    @patch("mx_rag.graphrag.qa_base_model.LLM_PLAIN_TEMPLATE", "{question}")
    def test_plain_generate(self):
        """Test the _plain_generate method."""
        self.mock_llm.chat.side_effect = ["response1", "response2"]
        questions = ["question1", "question2"]

        result = self.qa_model._plain_generate(questions)

        expected_prompts = ["question1", "question2"]
        self.mock_llm.chat.assert_any_call(
            expected_prompts[0],
            [
                {
                    "role": "system",
                    "content": "You are a helpful AI assistant that answers questions as simply as possible."
                }
            ],
            llm_config=self.mock_llm_config
        )
        self.mock_llm.chat.assert_any_call(
            expected_prompts[1],
            [
                {
                    "role": "system",
                    "content": "You are a helpful AI assistant that answers questions as simply as possible."
                }
            ],
            llm_config=self.mock_llm_config
        )
        self.assertEqual(result, ["response1", "response2"])