app.py

import gradio as gr
from io import StringIO
from model import DecoderTransformer, Tokenizer
from huggingface_hub import hf_hub_download
import torch
import chess
import chess.svg
import chess.pgn
from svglib.svglib import svg2rlg
from reportlab.graphics import renderPM
from PIL import Image
import os
from uuid import uuid4


vocab_size = 36
n_embed = 384
context_size = 256
n_layer = 6
n_head = 6
dropout = 0.2

device = 'cpu'

model_id = "philipp-zettl/chessPT"

model_path = hf_hub_download(repo_id=model_id, filename="chessPT-v0.5.pth")
tokenizer_path = hf_hub_download(repo_id=model_id, filename="tokenizer-v0.5.json")

model = DecoderTransformer(vocab_size, n_embed, context_size, n_layer, n_head, dropout)
model.load_state_dict(torch.load(model_path, map_location=torch.device('cpu')))
model.to(device)
tokenizer = Tokenizer.from_pretrained(tokenizer_path)

invalid_move_plot = Image.open('./invalid_move.png')

def gen_image_from_svg(img, filename):
    with open(filename + '.svg', 'w') as f:
        f.write(img)
    drawing = svg2rlg(filename + '.svg')
    renderPM.drawToFile(drawing, f"{filename}.png", fmt="PNG")
    plot = Image.open(f'{filename}.png')

    os.remove(f'{filename}.png')
    os.remove(f'{filename}.svg')
    return plot


def get_board(pgn):
    pgn_str = StringIO(pgn)
    try:
        game = chess.pgn.read_game(pgn_str)
        board = game.board()
        for move in game.mainline_moves():
            board.push(move)
    except Exception as e:
        if 'illegal san' in str(e):
            return None
    return board

def gen_board_image(pgn):
    board = get_board(pgn)
    return chess.svg.board(board)
    
def gen_move(pgn):
    model_input = torch.tensor(tokenizer.encode(pgn), dtype=torch.long, device=device).view((1, len(pgn)))
    is_invalid = True
    board = get_board(pgn)
    while is_invalid:
        new_pgn = tokenizer.decode(model.generate(model_input, max_new_tokens=4, context_size=context_size, temperature=0.2)[0].tolist())
        try:
            print(f'checking {new_pgn}')
            mv = new_pgn[len(pgn):].split(' ')[0]
            new_pgn = pgn.rstrip() + f' {mv}'
            is_invalid = get_board(new_pgn) is None
        except Exception:
            is_invalid = True
            print(f'For {pgn} invalid "{new_pgn[len(pgn):].split(" ")[0]}" {new_pgn}')
            #print(mov in board.legal_moves)
    return new_pgn


def generate(prompt):
    model_input = torch.tensor(tokenizer.encode(prompt), dtype=torch.long, device=device).view((1, len(prompt)))
    pgn = tokenizer.decode(model.generate(model_input, max_new_tokens=4, context_size=context_size, temperature=0.2)[0].tolist())
    img = gen_board_image(pgn)
    filename = f'./moves-{str(uuid4())}'
    plot = gen_image_from_svg(img, filename)
    return pgn, plot


with gr.Blocks() as demo:
    gr.Markdown("""
    # ChessPT
    Welcome to ChessPT.

    The **C**hess-**P**re-trained-**T**ransformer.

    The rules are simple: 
    - "Interactive": Play a game against the model
    - "Next turn prediction": provide a PGN string of your current game, the model will predict the next token
    """)
    def manual():
        with gr.Tab("Next turn prediction"):
            prompt = gr.Text(label="PGN")
            output = gr.Text(label="Next turn", interactive=False)
            img = gr.Image()
            submit = gr.Button("Submit")
            submit.click(generate, [prompt], [output, img])
        
            gr.Examples(
                [
                    ["1. e4", ],
                    ["1. e4 g6 2."],
                ],
                inputs=[prompt],
                outputs=[output, img],
                fn=generate
            )
    def interactive():           
        with gr.Tab("Interactive"):
            color = gr.Dropdown(["white", "black"], value='white', label="Chose a color")
            start_button = gr.Button("Start Game")

            def start_game(c):
                pgn = '1. '
                if c == 'black':
                    pgn = gen_move(pgn)
                img = gen_board_image(pgn)
                fn = 'foo'
                return gen_image_from_svg(img, fn), pgn, 1

            state = gr.Text(label='PGN', value='', interactive=False)
            game = gr.Image()
            move_counter = gr.State(value=1)
            start_button.click(
                start_game,
                inputs=[color],
                outputs=[game, state, move_counter]
            )

            next_move = gr.Text(label='Next move')
            gen_next_move_button = gr.Button("Submit")

            def gen_next_move(pgn, new_move, move_ctr, c):
                pgn += (' ' if c == 'black' else '') + new_move.strip() + ' '
                if c == 'black':
                    move_ctr += 1
                    pgn = f'{pgn.rstrip()} {move_ctr}. '
                print(f'gen for {pgn}')
                pgn = gen_move(pgn)
                print(f'got {pgn}')
                img = gen_board_image(pgn)
                if c == 'white':
                    move_ctr += 1
                    pgn = f'{pgn.rstrip()} {move_ctr}. '
                return gen_image_from_svg(img, 'foo-bar'), pgn, move_ctr

            gen_next_move_button.click(
                gen_next_move,
                inputs=[state, next_move, move_counter, color],
                outputs=[game, state, move_counter]
            )
    interactive()
    manual()
demo.launch()