initial application

app.py

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+import os
+import gradio as gr
+import random
+import chess
+import chess.svg
+from transformers import AutoModelForSequenceClassification, AutoTokenizer, AutoConfig, pipeline
+
+token = os.environ['auth_token']
+
+tokenizer = AutoTokenizer.from_pretrained('jrahn/chessv3', use_auth_token=token)
+model = AutoModelForSequenceClassification.from_pretrained('jrahn/chessv3', use_auth_token=token)
+pipe = pipeline(task="text-classification", model=model, tokenizer=tokenizer)
+
+empty_field = '0'
+board_split = ' | '
+nums = {str(n): empty_field * n for n in range(1, 9)}
+nums_rev = {v:k for k,v in reversed(nums.items())}
+
+board = chess.Board()
+
+def encode_fen(fen):
+    # decompress fen representation
+    # prepare for sub-word tokenization
+    fen_board, fen_rest = fen.split(' ', 1)
+    for n in nums:
+        fen_board = fen_board.replace(n, nums[n])
+    fen_board = '+' + fen_board
+    fen_board = fen_board.replace('/', ' +')
+    return board_split.join([fen_board, fen_rest])
+
+def decode_fen_repr(fen_repr):
+    fen_board, fen_rest = fen_repr.split(board_split, 1)
+    for n in nums_rev:
+        fen_board = fen_board.replace(n, nums_rev[n])
+    fen_board = fen_board.replace(' +', '/')
+    fen_board = fen_board.replace('+', '')
+    return ' '.join([fen_board, fen_rest])
+
+def predict_move(fen, top_k=3):
+    fen_prep = encode_fen(fen)
+    preds = pipe(fen_prep, top_k=top_k)
+    weights = [p['score'] for p in preds]
+    p = random.choices(preds, weights=weights)[0]
+    # discard illegal moves (https://python-chess.readthedocs.io/en/latest/core.html#chess.Board.legal_moves), then select top_k
+    return p['label']
+
+def play_yolochess(inp_color, inp_notation, inp_move, inp_custom_fen, state):
+    global board
+    if inp_custom_fen:
+        board = chess.Board(fen=inp_custom_fen)
+    if (inp_color == 'white' and board.turn == chess.BLACK) or (inp_color == 'black' and board.turn == chess.WHITE):
+        move = predict_move(board.fen())
+        board.push_uci(move)
+    else:
+        if inp_move:
+            if inp_notation == 'UCI':
+                board.push_uci(inp_move)
+            if inp_notation == 'SAN':
+                board.push_san(inp_move)
+    with open('board.svg', 'w') as f:
+        f.write(str(chess.svg.board(board)))
+    print(state)
+    return 'board.svg', board.fen()
+
+iface = gr.Interface(
+    fn=play_yolochess, 
+    inputs=[
+        gr.Radio(["white", "black"], value="white", label='human player color'),
+        gr.Radio(["SAN", "UCI"], value="SAN", label='move notation'),
+        gr.Textbox(label='human player move'),
+        gr.Textbox(placeholder=board.fen(), label='starting position FEN'),
+        "state"
+    ], 
+    outputs=[
+        gr.Image(label='position'),
+        "state"
+    ],
+    title='Play YoloChess - Policy Network v0.3',
+    allow_flagging="never",
+)
+iface.launch()

requirements.txt

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+chess==1.9.2