from unittest import mock

import pytest
from crewai.agent import Agent
from crewai.crew import Crew
from crewai.task import Task
from crewai.tasks.task_output import TaskOutput
from crewai.utilities.evaluators.crew_evaluator_handler import (
    CrewEvaluator,
    TaskEvaluationPydanticOutput,
)


class InternalCrewEvaluator:
    @pytest.fixture
    def crew_planner(self):
        agent = Agent(role="Agent 1", goal="Goal 1", backstory="Backstory 1")
        task = Task(
            description="Task 1",
            expected_output="Output 1",
            agent=agent,
        )
        crew = Crew(agents=[agent], tasks=[task])

        return CrewEvaluator(crew, openai_model_name="gpt-4o-mini")

    def test_setup_for_evaluating(self, crew_planner):
        crew_planner._setup_for_evaluating()
        assert crew_planner.crew.tasks[0].callback == crew_planner.evaluate

    def test_set_iteration(self, crew_planner):
        crew_planner.set_iteration(1)
        assert crew_planner.iteration == 1

    def test_evaluator_agent(self, crew_planner):
        agent = crew_planner._evaluator_agent()
        assert agent.role == "Task Execution Evaluator"
        assert (
            agent.goal
            == "Your goal is to evaluate the performance of the agents in the crew based on the tasks they have performed using score from 1 to 10 evaluating on completion, quality, and overall performance."
        )
        assert (
            agent.backstory
            == "Evaluator agent for crew evaluation with precise capabilities to evaluate the performance of the agents in the crew based on the tasks they have performed"
        )
        assert agent.verbose is False
        assert agent.llm.model == "gpt-4o-mini"

    def test_evaluation_task(self, crew_planner):
        evaluator_agent = Agent(
            role="Evaluator Agent",
            goal="Evaluate the performance of the agents in the crew",
            backstory="Master in Evaluation",
        )
        task_to_evaluate = Task(
            description="Task 1",
            expected_output="Output 1",
            agent=Agent(role="Agent 1", goal="Goal 1", backstory="Backstory 1"),
        )
        task_output = "Task Output 1"
        task = crew_planner._evaluation_task(
            evaluator_agent, task_to_evaluate, task_output
        )

        assert task.description.startswith(
            "Based on the task description and the expected output, compare and evaluate the performance of the agents in the crew based on the Task Output they have performed using score from 1 to 10 evaluating on completion, quality, and overall performance."
        )

        assert task.agent == evaluator_agent
        assert (
            task.description
            == "Based on the task description and the expected output, compare and evaluate "
            "the performance of the agents in the crew based on the Task Output they have "
            "performed using score from 1 to 10 evaluating on completion, quality, and overall "
            "performance.task_description: Task 1 task_expected_output: Output 1 "
            "agent: Agent 1 agent_goal: Goal 1 Task Output: Task Output 1"
        )

    @mock.patch("crewai.utilities.evaluators.crew_evaluator_handler.Console")
    @mock.patch("crewai.utilities.evaluators.crew_evaluator_handler.Table")
    def test_print_crew_evaluation_result(self, table, console, crew_planner):
        # Set up task scores and execution times
        crew_planner.tasks_scores = {
            1: [10, 9, 8],
            2: [9, 8, 7],
        }
        crew_planner.run_execution_times = {
            1: [24, 45, 66],
            2: [55, 33, 67],
        }

        # Mock agents and assign them to tasks
        crew_planner.crew.agents = [
            mock.Mock(role="Agent 1"),
            mock.Mock(role="Agent 2"),
        ]
        crew_planner.crew.tasks = [
            mock.Mock(
                agent=crew_planner.crew.agents[0], processed_by_agents=["Agent 1"]
            ),
            mock.Mock(
                agent=crew_planner.crew.agents[1], processed_by_agents=["Agent 2"]
            ),
        ]

        # Run the method
        crew_planner.print_crew_evaluation_result()

        # Verify that the table is created with the appropriate structure and rows
        table.assert_has_calls(
            [
                mock.call(
                    title="Tasks Scores \n (1-10 Higher is better)", box=mock.ANY
                ),  # Title and styling
                mock.call().add_column("Tasks/Crew/Agents", style="cyan"),  # Columns
                mock.call().add_column("Run 1", justify="center"),
                mock.call().add_column("Run 2", justify="center"),
                mock.call().add_column("Avg. Total", justify="center"),
                mock.call().add_column("Agents", style="green"),
                # Verify rows for tasks with agents
                mock.call().add_row("Task 1", "10.0", "9.0", "9.5", "- Agent 1"),
                mock.call().add_row("", "", "", "", "", ""),  # Blank row between tasks
                mock.call().add_row("Task 2", "9.0", "8.0", "8.5", "- Agent 2"),
                # Add crew averages and execution times
                mock.call().add_row("Crew", "9.00", "8.00", "8.5", ""),
                mock.call().add_row("Execution Time (s)", "135", "155", "145", ""),
            ]
        )

        # Ensure the console prints the table
        console.assert_has_calls([mock.call(), mock.call().print(table())])

    def test_evaluate(self, crew_planner):
        task_output = TaskOutput(
            description="Task 1", agent=str(crew_planner.crew.agents[0])
        )

        with mock.patch.object(Task, "execute_sync") as execute:
            execute().pydantic = TaskEvaluationPydanticOutput(quality=9.5)
            crew_planner.evaluate(task_output)
            assert crew_planner.tasks_scores[0] == [9.5]