"""Unit tests for PromptEvaluator.evaluate()."""
from __future__ import annotations

from unittest.mock import MagicMock

import pytest

from prometheus.application.evaluator import PromptEvaluator
from prometheus.domain.entities import EvalResult, Prompt, SyntheticExample, Trajectory
from prometheus.domain.ports import JudgePort, LLMPort


class TestPromptEvaluatorEvaluate:
    """Tests for the evaluate() pipeline: execute → judge → trajectories."""

    @pytest.fixture
    def executor(self) -> MagicMock:
        return MagicMock(spec=LLMPort)

    @pytest.fixture
    def judge(self) -> MagicMock:
        return MagicMock(spec=JudgePort)

    @pytest.fixture
    def evaluator(self, executor: MagicMock, judge: MagicMock) -> PromptEvaluator:
        return PromptEvaluator(executor=executor, judge=judge)

    def test_happy_path_builds_correct_trajectories(
        self,
        evaluator: PromptEvaluator,
        executor: MagicMock,
        judge: MagicMock,
    ) -> None:
        prompt = Prompt(text="Answer the question.")
        examples = [
            SyntheticExample(input_text="What is 2+2?", id=0),
            SyntheticExample(input_text="Capital of France?", id=1),
        ]
        executor.execute.side_effect = ["4", "Paris"]
        judge.judge_batch.return_value = [
            (0.9, "Correct."),
            (0.8, "Mostly correct."),
        ]

        result = evaluator.evaluate(prompt, examples, "math and geography")

        assert isinstance(result, EvalResult)
        assert result.scores == [0.9, 0.8]
        assert result.feedbacks == ["Correct.", "Mostly correct."]
        assert len(result.trajectories) == 2
        assert result.trajectories[0].input_text == "What is 2+2?"
        assert result.trajectories[0].output_text == "4"
        assert result.trajectories[0].score == 0.9
        assert result.trajectories[0].feedback == "Correct."
        assert result.trajectories[0].prompt_used == "Answer the question."
        assert result.trajectories[1].prompt_used == "Answer the question."

    def test_empty_minibatch_returns_empty_result(
        self,
        evaluator: PromptEvaluator,
        executor: MagicMock,
        judge: MagicMock,
    ) -> None:
        prompt = Prompt(text="test")
        result = evaluator.evaluate(prompt, [], "task")

        assert result.scores == []
        assert result.feedbacks == []
        assert result.trajectories == []
        executor.execute.assert_not_called()
        # judge_batch is called with empty pairs list
        judge.judge_batch.assert_called_once_with("task", [])

    def test_executor_called_with_correct_prompt(
        self,
        evaluator: PromptEvaluator,
        executor: MagicMock,
        judge: MagicMock,
    ) -> None:
        prompt = Prompt(text="Summarize this.")
        examples = [SyntheticExample(input_text="Long text here", id=0)]
        executor.execute.return_value = "Summary."
        judge.judge_batch.return_value = [(0.7, "Good summary.")]

        evaluator.evaluate(prompt, examples, "summarization")

        executor.execute.assert_called_once_with(prompt, "Long text here")

    def test_trajectories_prompt_used_matches_input_prompt(
        self,
        evaluator: PromptEvaluator,
        executor: MagicMock,
        judge: MagicMock,
    ) -> None:
        prompt = Prompt(text="Translate to French.")
        examples = [SyntheticExample(input_text="Hello", id=0)]
        executor.execute.return_value = "Bonjour"
        judge.judge_batch.return_value = [(1.0, "Perfect.")]

        result = evaluator.evaluate(prompt, examples, "translation")

        assert result.trajectories[0].prompt_used == "Translate to French."

    def test_scores_feedbacks_trajectories_lists_sized_correctly(
        self,
        evaluator: PromptEvaluator,
        executor: MagicMock,
        judge: MagicMock,
    ) -> None:
        prompt = Prompt(text="test prompt")
        examples = [SyntheticExample(input_text=f"q{i}", id=i) for i in range(4)]
        executor.execute.side_effect = [f"a{i}" for i in range(4)]
        judge.judge_batch.return_value = [
            (0.1 * i, f"fb{i}") for i in range(4)
        ]

        result = evaluator.evaluate(prompt, examples, "task")

        assert len(result.scores) == 4
        assert len(result.feedbacks) == 4
        assert len(result.trajectories) == 4