import random
import uuid

from ielts_be.configs.constants import GPTModels, TemperatureSettings
from ielts_be.helpers import ExercisesHelper
from ielts_be.services import ILLMService


class ParagraphMatch:

    def __init__(self, llm: ILLMService):
        self._llm = llm

    async def gen_paragraph_match_exercise(self, text: str, quantity: int, start_id: int):
        paragraphs = ExercisesHelper.assign_letters_to_paragraphs(text)
        messages = [
            {
                "role": "system",
                "content": (
                    'You are a helpful assistant designed to output JSON on this format: '
                    '{"headings": [ {"heading": "first paragraph heading"}, {"heading": "second paragraph heading"}]}'
                )
            },
            {
                "role": "user",
                "content": (
                    'For every paragraph of the list generate a minimum 5 word heading for it. '
                    f'The paragraphs are these: {str(paragraphs)}'
                )

            }
        ]

        response = await self._llm.prediction(
            GPTModels.GPT_4_O, messages, ["headings"], TemperatureSettings.GEN_QUESTION_TEMPERATURE
        )
        headings = response["headings"]

        options = []
        for i, paragraph in enumerate(paragraphs, start=0):
            paragraph["heading"] = headings[i]["heading"]
            options.append({
                "id": paragraph["letter"],
                "sentence": paragraph["paragraph"]
            })

        random.shuffle(paragraphs)
        sentences = []
        for i, paragraph in enumerate(paragraphs, start=start_id):
            sentences.append({
                "id": i,
                "sentence": paragraph["heading"],
                "solution": paragraph["letter"]
            })

        return {
            "id": str(uuid.uuid4()),
            "allowRepetition": False,
            "options": options,
            "prompt": "Choose the correct heading for paragraphs from the list of headings below.",
            "sentences": sentences[:quantity],
            "type": "matchSentences"
        }