"""
Exam backend functions for AI Examiner Agent.
"""

import json
import random
import os
from datetime import datetime
from typing import TypedDict, Literal

TOPICS = [
    "Tokenization and text preprocessing",
    "Word embeddings (Word2Vec, GloVe, FastText)",
    "Recurrent neural networks (RNN, LSTM, GRU)",
    "Attention mechanism and Transformers",
    "BERT and pre-trained language models",
    "Named Entity Recognition (NER)",
    "Sentiment analysis",
    "Machine translation",
    "Text classification",
    "Language model evaluation metrics (BLEU, ROUGE, Perplexity)",
]

STUDENTS = [
    {"name": "Stanislav Androshchuk", "email": "Stanislav.Androshchuk.mKNSSh.2025@lpnu.ua"},
    {"name": "Oleksandr Babilia", "email": "Oleksandr.Babilia.mKNSSh.2025@lpnu.ua"},
    {"name": "Vitalii Bahrynets", "email": "Vitalii.Bahrynets.mKNSSh.2025@lpnu.ua"},
    {"name": "Dmytro Betsa", "email": "Dmytro.Betsa.mKNSSh.2025@lpnu.ua"},
    {"name": "Kateryna Bilyk", "email": "Kateryna.Bilyk.mKNSSh.2025@lpnu.ua"},
    {"name": "Iryna Boiko", "email": "Iryna.Boiko.mKNSSh.2025@lpnu.ua"},
    {"name": "Ihor Boklach", "email": "Ihor.Boklach.mKNSSh.2025@lpnu.ua"},
    {"name": "Bohdan Boretskyi", "email": "Bohdan.Boretskyi.mKNSSh.2025@lpnu.ua"},
    {"name": "Yaroslav Borys", "email": "Yaroslav.Borys.mKNSSh.2025@lpnu.ua"},
    {"name": "Denys Brativnyk", "email": "Denys.Brativnyk.mKNSSh.2025@lpnu.ua"},
    {"name": "Oleksandr Vlasiuk", "email": "Oleksandr.Vlasiuk.mKNSSh.2025@lpnu.ua"},
    {"name": "Oleksandr Voznyi", "email": "Oleksandr.Voznyi.mKNSSh.2025@lpnu.ua"},
    {"name": "Khrystyna Dolynska", "email": "Khrystyna.Dolynska.mKNSSh.2025@lpnu.ua"},
    {"name": "Viktor Zharkivskyi", "email": "Viktor.Zharkivskyi.mKNSSh.2025@lpnu.ua"},
    {"name": "Olena Kalenchuk", "email": "Olena.Kalenchuk.mKNSSh.2025@lpnu.ua"},
    {"name": "Dmytro Kostinskyi", "email": "Dmytro.Kostinskyi.mKNSSh.2025@lpnu.ua"},
    {"name": "Anastasiia Kudybovska", "email": "Anastasiia.Kudybovska.mKNSSh.2025@lpnu.ua"},
    {"name": "Vladyslav Kuchynskyi", "email": "Vladyslav.Kuchynskyi.mKNSSh.2025@lpnu.ua"},
    {"name": "Olena Litovska", "email": "Olena.Litovska.mKNSSh.2025@lpnu.ua"},
    {"name": "Oleh Lozovyi", "email": "Oleh.Lozovyi.mKNSSh.2025@lpnu.ua"},
    {"name": "Roman Maior", "email": "Roman.Maior.mKNSSh.2025@lpnu.ua"},
    {"name": "Yevhen Makarenko", "email": "Yevhen.Makarenko.mKNSSh.2025@lpnu.ua"},
    {"name": "Serhii Matsyshyn", "email": "Serhii.Matsyshyn.mKNSSh.2025@lpnu.ua"},
    {"name": "Maksym Myna", "email": "Maksym.Myna.mKNSSh.2025@lpnu.ua"},
    {"name": "Artem Mikanov", "email": "Artem.Mikanov.mKNSSh.2025@lpnu.ua"},
    {"name": "Vitalii Mil", "email": "Vitalii.Mil.mKNSSh.2025@lpnu.ua"},
    {"name": "Vladyslav Miniailo", "email": "Vladyslav.Miniailo.mKNSSh.2025@lpnu.ua"},
    {"name": "Vladyslav Moiseienko", "email": "Vladyslav.Moiseienko.mKNSSh.2025@lpnu.ua"},
    {"name": "Tymofii Nasobko", "email": "Tymofii.Nasobko.mKNSSh.2025@lpnu.ua"},
    {"name": "Arsenii Ohar", "email": "Arsenii.Ohar.mKNSSh.2025@lpnu.ua"},
    {"name": "Marta Oliinyk", "email": "Marta.Oliinyk.mKNSSh.2025@lpnu.ua"},
    {"name": "Oleksii Oliinyk", "email": "Oleksii.Oliinyk.mKNSSh.2025@lpnu.ua"},
    {"name": "Roman Omelchuk", "email": "Roman.Omelchuk.mKNSSh.2025@lpnu.ua"},
    {"name": "Maksym Orlianskyi", "email": "Maksym.Orlianskyi.mKNSSh.2025@lpnu.ua"},
    {"name": "Alina Pavliv", "email": "Alina.Pavliv.mKNSSh.2025@lpnu.ua"},
    {"name": "Andrii Pytel", "email": "Andrii.Pytel.mKNSSh.2025@lpnu.ua"},
    {"name": "Oleksii Postovyi", "email": "Oleksii.Postovyi.mKNSSh.2025@lpnu.ua"},
    {"name": "Myroslav Pronyshyn", "email": "Myroslav.Pronyshyn.mKNSSh.2025@lpnu.ua"},
    {"name": "Yurii Pukhta", "email": "Yurii.Pukhta.mKNSSh.2025@lpnu.ua"},
    {"name": "Denys Ratushniak", "email": "Denys.Ratushniak.mKNSSh.2025@lpnu.ua"},
    {"name": "Nazar Savitskyi", "email": "Nazar.Savitskyi.mKNSSh.2025@lpnu.ua"},
    {"name": "Oleksandr Siryk", "email": "Oleksandr.Siryk.mKNSSh.2025@lpnu.ua"},
    {"name": "Petro Slobodian", "email": "Petro.Slobodian.mKNSSh.2025@lpnu.ua"},
    {"name": "Artem Somar", "email": "Artem.Somar.mKNSSh.2025@lpnu.ua"},
    {"name": "Vladyslav Spivakov", "email": "Vladyslav.Spivakov.mKNSSh.2025@lpnu.ua"},
    {"name": "Pavlo Stetsiuk", "email": "Pavlo.Stetsiuk.mKNSSh.2025@lpnu.ua"},
    {"name": "Vladyslav Taraban", "email": "Vladyslav.Taraban.mKNSSh.2025@lpnu.ua"},
    {"name": "Andrii Tarasov", "email": "Andrii.Tarasov.mKNSSh.2025@lpnu.ua"},
    {"name": "Illia Feloniuk", "email": "Illia.Feloniuk.mKNSSh.2025@lpnu.ua"},
    {"name": "Sviatoslav Shainoha", "email": "Sviatoslav.Shainoha.mKNSSh.2025@lpnu.ua"},
    {"name": "Sviatoslav Shylkov", "email": "Sviatoslav.Shylkov.mKNSSh.2025@lpnu.ua"},
    {"name": "Vitalii Yuzvyn", "email": "Vitalii.Yuzvyn.mKNSSh.2025@lpnu.ua"},
    {"name": "Vladyslav Yakymchuk", "email": "Vladyslav.Yakymchuk.mKNSSh.2025@lpnu.ua"},
    # demo
    {"name": "Test", "email": "test@test.com"},
]

DB_FILE = "exam_db.json"


def _load_db() -> dict:
    if os.path.exists(DB_FILE):
        with open(DB_FILE, "r", encoding="utf-8") as f:
            return json.load(f)
    return {"exams": []}


def _save_db(db: dict) -> None:
    with open(DB_FILE, "w", encoding="utf-8") as f:
        json.dump(db, f, ensure_ascii=False, indent=2)


def start_exam(email: str, name: str) -> list[str]:
    student = next(
        (s for s in STUDENTS if s["email"].lower() == email.strip().lower()),
        None,
    )
    if student is None:
        raise ValueError(
            f"Student with email '{email}' not found. Please check your email address."
        )

    topics = random.sample(TOPICS, k=random.randint(2, 3))

    db = _load_db()
    db["exams"].append({
        "email": email,
        "name": name,
        "started_at": datetime.now().isoformat(),
        "topics": topics,
        "score": None,
        "finished_at": None,
    })
    _save_db(db)
    print(f"[DB] Exam started for {name} <{email}>. Topics: {topics}")
    return topics


_topic_queue: list[str] = []


def set_topic_queue(topics: list[str]) -> None:
    global _topic_queue
    _topic_queue = list(topics)


def get_next_topic() -> str:
    if _topic_queue:
        return _topic_queue.pop(0)
    return ""


class Message(TypedDict):
    role: Literal["system", "user", "tool_call"]
    content: str
    datetime: str


def end_exam(email: str, score: float, history: list[Message]) -> None:
    db = _load_db()
    for exam in reversed(db["exams"]):
        if exam["email"].lower() == email.lower() and exam["score"] is None:
            exam["score"] = score
            exam["finished_at"] = datetime.now().isoformat()
            exam["history"] = history
            break
    _save_db(db)
    print(f"[DB] Exam finished for {email}. Score: {score}/10")