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from __future__ import annotations

import ast
import csv
import json
from pathlib import Path
import random
from typing import TYPE_CHECKING

from uw_programmatic.base_machine import UWBaseMachine

if TYPE_CHECKING:
    from griptape.tools import BaseTool


class UWMachine(UWBaseMachine):
    """State machine with GOAP"""

    @property
    def tools(self) -> dict[str, BaseTool]:
        return {}

    def start_machine(self) -> None:
        """Starts the machine."""
        # Clear input history.
        # Clear csv file
        self.send("enter_first_state")

    def on_event_gather_parameters(self, event_: dict) -> None:
        event_source = event_["type"]
        event_value = event_["value"]
        match event_source:
            case "user_input":
                parameters = event_value
                self.page_range = parameters["page_range"]
                self.question_number = parameters["question_number"]
                self.taxonomy = parameters["taxonomy"]
                self.current_question_count = 0
                self.give_up_count = 0
                self.send("next_state")
            case _:
                err_msg = f"Unexpected Transition Event ID: {event_value}."
                raise ValueError(err_msg)

    def on_enter_evaluate_q_count(self) -> None:
        # Check if the number of questions has incremented
        if len(self.question_list) <= self.current_question_count:
            self.give_up_count += 1
        else:
            self.current_question_count = len(self.question_list)
            self.give_up_count = 0
        if self.give_up_count == 3:
            self.send("finish_state")
            return
        if len(self.question_list) >= self.question_number:
            self.send("finish_state")  # go to output questions
        else:
            self.send("next_state")  # go to need more questions

    def on_event_evaluate_q_count(self, event_: dict) -> None:
        pass

    def on_enter_need_more_q(self) -> None:
        # Create the entire workflow to create another question.
        self.get_questions_workflow().run()

    def on_event_need_more_q(self, event_: dict) -> None:
        event_source = event_["type"]
        event_value = event_["value"]
        match event_source:
            case "griptape_event":
                event_type = event_value["type"]
                match event_type:
                    case "FinishStructureRunEvent":
                        structure_id = event_value["structure_id"]
                        match structure_id:
                            case "create_question_workflow":
                                values = event_value["output_task_output"]["value"]
                                questions = [
                                    ast.literal_eval(question["value"])
                                    for question in values
                                ]
                                self.most_recent_questions = (
                                    questions  # This is a ListArtifact I'm pretty sure
                                )
                                self.send("next_state")
                    case _:
                        print(f"Error:{event_} ")
            case _:
                print(f"Unexpected: {event_}")

    def on_enter_assess_generated_q(self) -> None:
        # TODO: Should it append it to the list already and remove duplicates? or not?
        # TODO: Merge incoming lists
        merged_list = [*self.question_list, *self.most_recent_questions]
        prompt = f"{merged_list}"
        self.get_structure("similarity_auditor").run(prompt)

    def on_event_assess_generated_q(self, event_: dict) -> None:
        event_source = event_["type"]
        event_value = event_["value"]
        match event_source:
            case "griptape_event":
                event_type = event_value["type"]
                match event_type:
                    case "FinishStructureRunEvent":
                        structure_id = event_value["structure_id"]
                        match structure_id:
                            case "similarity_auditor":
                                new_question_list = event_value["output_task_output"][
                                    "value"
                                ]
                                try:
                                    new_question_list = json.loads(
                                        new_question_list
                                    )  # This must be in that JSON format
                                except:
                                    new_question_list = self.question_list
                                self.question_list = new_question_list
                                self.send("next_state")  # move on

    def on_enter_output_q(self) -> None:
        with Path(Path.cwd().joinpath("outputs/professor_guide.csv")).open(
            "w", newline=""
        ) as file:
            writer = csv.writer(file)
            for question in range(len(self.question_list)):
                new_row = ["MC", "", 1]
                try:
                    new_row.append(self.question_list[question]["Question"])
                    wrong_answers = list(self.question_list[question]["Wrong Answers"])
                    column = random.randint(1, len(wrong_answers) + 1)
                    new_row.append(column)
                    for i in range(1, len(wrong_answers) + 2):
                        if i == column:
                            new_row.append(self.question_list[question]["Answer"])
                        else:
                            wrong_answer = wrong_answers.pop()
                            if not wrong_answer:
                                wrong_answer = ""
                            new_row.append(wrong_answer)
                    new_row.append(self.question_list[question]["Page"])
                    new_row.append(self.question_list[question]["Taxonomy"])
                    writer.writerow(new_row)
                except KeyError:
                    new_row.append(self.question_list["Question"])
                    wrong_answers = list(self.question_list["Wrong Answers"])
                    column = random.randint(1, len(wrong_answers) + 1)
                    new_row.append(column)
                    for i in range(1, len(wrong_answers) + 2):
                        if i == column:
                            new_row.append(self.question_list["Answer"])
                        else:
                            new_row.append(wrong_answers.pop())
                    new_row.append(self.question_list["Page"])
                    new_row.append(self.question_list["Taxonomy"])
                    writer.writerow(new_row)
            if self.give_up_count == 3:
                writer.writerow("Failed to generate more questions.")
        self.send("next_state")

    def on_event_output_q(self, event_: dict) -> None:
        pass

    def on_exit_output_q(self) -> None:
        # Reset the state machine values
        self.question_list = []
        self.most_recent_questions = []

    if __name__ == "__main__":

        question_list = [
            {
                "Page": "1-2",
                "Taxonomy": "Knowledge",
                "Question": "What is Python?",
                "Answer": "A programming language",
                "Wrong Answers": ["A snake", "A car brand", "A fruit"],
            },
            {
                "Page": "3-4",
                "Taxonomy": "Comprehension",
                "Question": "What does HTML stand for?",
                "Answer": "HyperText Markup Language",
                "Wrong Answers": [
                    "High Text Machine Language",
                    "Hyperlink Text Mode Language",
                    "None of the above",
                ],
            },
        ]

        with Path(Path.cwd().joinpath("outputs/professor_guide.csv")).open(
            "w", newline=""
        ) as file:
            writer = csv.writer(file)
            for question in range(len(question_list)):
                # TODO: Shuffle answers according to row, keep correct answer in random section. Answer column is a number.
                new_row = [question_list[question]["Question"]]
                wrong_answers = list(question_list[question]["Wrong Answers"])
                column = random.randint(1, len(wrong_answers) + 1)
                new_row.append(column)
                for i in range(1, len(wrong_answers) + 2):
                    if i == column:
                        new_row.append(question_list[question]["Answer"])
                    else:
                        new_row.append(wrong_answers.pop())
                new_row.append(question_list[question]["Page"])
                new_row.append(question_list[question]["Taxonomy"])
                writer.writerow(new_row)