"""
Component-based Chess Tokenizer - Optimized for Parameter Efficiency.

This tokenizer decomposes chess moves into reusable components:
- Piece type (P, N, B, R, Q, K)
- Source square (a1-h8)
- Destination square (a1-h8)
- Modifiers (capture, check, castling, etc.)

Example:
    "WPe2e4" → ["P", "e2", "e4"]
    "BNg8f6(x)" → ["N", "g8", "f6", "(x)"]

This reduces vocabulary from ~1682 to ~80 tokens, saving 205K parameters.
"""

from __future__ import annotations

import json
import os
from typing import Dict, List, Optional

from transformers import PreTrainedTokenizer


class ComponentChessTokenizer(PreTrainedTokenizer):
    """
    Component-based tokenizer for chess moves.

    Decomposes moves into: [piece, from_square, to_square, modifiers...]

    Key advantages:
    - 95% smaller vocabulary (1682 → 80 tokens)
    - Saves 205K embedding parameters
    - Better generalization to rare move combinations
    - Compositional understanding of chess structure
    """

    model_input_names = ["input_ids", "attention_mask"]
    vocab_files_names = {"vocab_file": "vocab.json"}

    # Special tokens
    PAD_TOKEN = "[PAD]"
    BOS_TOKEN = "[BOS]"
    EOS_TOKEN = "[EOS]"
    UNK_TOKEN = "[UNK]"
    SEP_TOKEN = "[SEP]"  # Separates components within a move

    # Chess piece types (6 tokens)
    PIECES = ["P", "N", "B", "R", "Q", "K"]

    # All squares on the board (64 tokens)
    FILES = "abcdefgh"
    RANKS = "12345678"

    # Move modifiers (10 tokens)
    MODIFIERS = [
        "(x)",    # capture
        "(+)",    # check
        "(+*)",   # checkmate
        "(o)",    # kingside castling
        "(O)",    # queenside castling
        "=Q",     # promotion to queen
        "=R",     # promotion to rook
        "=B",     # promotion to bishop
        "=N",     # promotion to knight
        "(e.p.)", # en passant
    ]

    def __init__(
        self,
        vocab_file: Optional[str] = None,
        vocab: Optional[Dict[str, int]] = None,
        **kwargs,
    ):
        """Initialize the component chess tokenizer."""
        # Initialize special tokens
        self._pad_token = self.PAD_TOKEN
        self._bos_token = self.BOS_TOKEN
        self._eos_token = self.EOS_TOKEN
        self._unk_token = self.UNK_TOKEN

        # Remove duplicate special-token entries
        kwargs.pop("pad_token", None)
        kwargs.pop("bos_token", None)
        kwargs.pop("eos_token", None)
        kwargs.pop("unk_token", None)

        # Load or create vocabulary
        if vocab is not None:
            self._vocab = vocab
        elif vocab_file is not None and os.path.exists(vocab_file):
            with open(vocab_file, "r", encoding="utf-8") as f:
                self._vocab = json.load(f)
        else:
            self._vocab = self._create_component_vocab()

        # Create reverse mapping
        self._ids_to_tokens = {v: k for k, v in self._vocab.items()}

        # Call parent init
        super().__init__(
            pad_token=self._pad_token,
            bos_token=self._bos_token,
            eos_token=self._eos_token,
            unk_token=self._unk_token,
            **kwargs,
        )

    def _create_component_vocab(self) -> Dict[str, int]:
        """
        Create the component vocabulary.

        Vocabulary structure:
        - Special tokens (5): [PAD], [BOS], [EOS], [UNK], [SEP]
        - Pieces (6): P, N, B, R, Q, K
        - Squares (64): a1, a2, ..., h8
        - Modifiers (10): (x), (+), (+*), (o), (O), =Q, =R, =B, =N, (e.p.)

        Total: 85 tokens (vs 1682 in original tokenizer)
        """
        tokens = [
            self.PAD_TOKEN,
            self.BOS_TOKEN,
            self.EOS_TOKEN,
            self.UNK_TOKEN,
            self.SEP_TOKEN,
        ]

        # Add pieces
        tokens.extend(self.PIECES)

        # Add all squares
        squares = [f + r for f in self.FILES for r in self.RANKS]
        tokens.extend(squares)

        # Add modifiers
        tokens.extend(self.MODIFIERS)

        # Create vocabulary
        vocab = {token: idx for idx, token in enumerate(tokens)}

        return vocab

    @classmethod
    def build_vocab(cls) -> "ComponentChessTokenizer":
        """
        Build tokenizer with component vocabulary.

        No dataset needed - vocabulary is deterministic based on chess rules.
        """
        return cls()

    @property
    def vocab_size(self) -> int:
        """Return the size of the vocabulary."""
        return len(self._vocab)

    def get_vocab(self) -> Dict[str, int]:
        """Return the vocabulary as a dictionary."""
        return dict(self._vocab)

    def _decompose_move(self, move: str) -> List[str]:
        """
        Decompose a move string into components.

        Examples:
            "WPe2e4" → ["P", "e2", "e4"]
            "BNg8f6(x)" → ["N", "g8", "f6", "(x)"]
            "WKe1g1(o)" → ["K", "e1", "g1", "(o)"]
            "BPe7e8=Q(+)" → ["P", "e7", "e8", "=Q", "(+)"]

        Args:
            move: Extended UCI move string (e.g., "WPe2e4")

        Returns:
            List of component tokens
        """
        if not move or move in [self.PAD_TOKEN, self.BOS_TOKEN, self.EOS_TOKEN, self.UNK_TOKEN]:
            return [move]

        components = []

        # Remove color prefix (W/B)
        if move.startswith(('W', 'B')):
            move = move[1:]

        if not move:
            return [self.UNK_TOKEN]

        # Extract piece type
        piece = move[0]
        if piece in self.PIECES:
            components.append(piece)
            move = move[1:]
        else:
            # Invalid piece
            return [self.UNK_TOKEN]

        # Extract squares (from and to)
        # Format: <piece><from_square><to_square>[modifiers]
        # E.g., "Pe2e4", "Ng1f3(x)", "Ke1g1(o)"

        if len(move) < 4:
            # Not enough characters for two squares
            return [self.UNK_TOKEN]

        # Generate valid squares for checking
        valid_squares = [f + r for f in self.FILES for r in self.RANKS]

        # Extract from_square (2 chars)
        from_square = move[0:2]
        if from_square in valid_squares:
            components.append(from_square)
        else:
            return [self.UNK_TOKEN]

        # Extract to_square (2 chars)
        to_square = move[2:4]
        if to_square in valid_squares:
            components.append(to_square)
        else:
            return [self.UNK_TOKEN]

        # Extract modifiers (remaining characters)
        remaining = move[4:]
        if remaining:
            # Parse modifiers: (x), (+), (+*), (o), (O), =Q, =R, =B, =N, (e.p.)
            i = 0
            while i < len(remaining):
                # Check for known modifiers
                found = False
                for modifier in self.MODIFIERS:
                    if remaining[i:].startswith(modifier):
                        components.append(modifier)
                        i += len(modifier)
                        found = True
                        break

                if not found:
                    # Unknown character, skip it
                    i += 1

        return components

    def _tokenize(self, text: str) -> List[str]:
        """
        Tokenize a string of moves into component tokens.

        Args:
            text: Space-separated moves (e.g., "WPe2e4 BPe7e5 WNg1f3")

        Returns:
            List of component tokens
        """
        moves = text.strip().split()
        tokens = []

        for move in moves:
            # Skip special tokens
            if move in [self.PAD_TOKEN, self.BOS_TOKEN, self.EOS_TOKEN, self.UNK_TOKEN]:
                tokens.append(move)
            else:
                # Decompose move into components
                components = self._decompose_move(move)
                tokens.extend(components)

        return tokens

    def _convert_token_to_id(self, token: str) -> int:
        """Convert a token to its ID."""
        return self._vocab.get(token, self._vocab.get(self.UNK_TOKEN, 0))

    def _convert_id_to_token(self, index: int) -> str:
        """Convert an ID to its token."""
        return self._ids_to_tokens.get(index, self.UNK_TOKEN)

    def convert_tokens_to_string(self, tokens: List[str]) -> str:
        """
        Convert component tokens back to move strings.

        This reconstructs moves from components.
        Note: We lose the W/B color prefix, but it's redundant
        (can be inferred from move position).
        """
        # Filter out special tokens
        special = {self.PAD_TOKEN, self.BOS_TOKEN, self.EOS_TOKEN, self.UNK_TOKEN, self.SEP_TOKEN}
        tokens = [t for t in tokens if t not in special]

        # Generate valid squares for checking
        valid_squares = [f + r for f in self.FILES for r in self.RANKS]

        # Reconstruct moves from components
        moves = []
        i = 0
        while i < len(tokens):
            # Expect: piece, from_square, to_square, [modifiers...]
            if i + 2 >= len(tokens):
                break

            piece = tokens[i]
            from_sq = tokens[i + 1]
            to_sq = tokens[i + 2]

            if piece in self.PIECES and from_sq in valid_squares and to_sq in valid_squares:
                move = f"{piece}{from_sq}{to_sq}"
                i += 3

                # Collect modifiers
                while i < len(tokens) and tokens[i] in self.MODIFIERS:
                    move += tokens[i]
                    i += 1

                moves.append(move)
            else:
                # Skip invalid tokens
                i += 1

        return " ".join(moves)

    def save_vocabulary(
        self,
        save_directory: str,
        filename_prefix: Optional[str] = None,
    ) -> tuple:
        """Save the vocabulary to a JSON file."""
        if not os.path.isdir(save_directory):
            os.makedirs(save_directory, exist_ok=True)

        vocab_file = os.path.join(
            save_directory,
            (filename_prefix + "-" if filename_prefix else "") + "vocab.json",
        )

        with open(vocab_file, "w", encoding="utf-8") as f:
            json.dump(self._vocab, f, ensure_ascii=False, indent=2)

        return (vocab_file,)