Maia 3：一个用 2.5 亿局人类棋谱训练的开源象棋引擎，Elo 1800 且能本地跑

# 克隆仓库
git clone https://github.com/cssmaia/maia-chess.git
cd maia-chess

# 安装依赖（建议用 conda 或 venv）
python -m venv maia_env
source maia_env/bin/activate
pip install -r requirements.txt
pip install python-chess  # 用于棋局交互

import chess
import chess.pgn
from maia_chess import MaiaModel  # 假设仓库提供此接口

# 加载 Maia 3 模型（首次运行会下载权重，约数 GB）
model = MaiaModel.load("maia-3")

# 创建一个棋局
board = chess.Board()

# 获取 Maia 3 对当前局面的走法预测
# 返回的是走法概率分布，而非单一最优走法
predictions = model.predict_moves(board)

# 打印前 5 个最可能的走法及其概率
for move, prob in predictions.top_k(5):
    print(f"走法: {move.uci()}, 概率: {prob:.2%}")

# 示例输出（开局位置）:
# 走法: e2e4, 概率: 38.50%
# 走法: d2d4, 概率: 28.20%
# 赝法: g1f3, 概率: 12.10%
# 走法: c2c4, 概率: 8.40%
# 走法: b1c3, 概率: 4.30%

import chess

board = chess.Board()
model = MaiaModel.load("maia-3")

# 你执白，Maia 执黑
while not board.is_game_over():
    if board.turn == chess.WHITE:
        # 人类走法——这里用输入模拟，实际可接入 GUI
        legal_moves = list(board.legal_moves)
        print(f"当前局面: {board.fen()}")
        print(f"合法走法: {[m.uci() for m in legal_moves[:10]]}")
        human_move = input("你的走法(UCI格式，如 e2e4): ")
        board.push_uci(human_move)
    else:
        # Maia 3 走法——从预测分布中采样，而非取最高概率
        # 采样让它更像人类：人类不会每次都走"最可能"的那步
        maia_move = model.sample_move(board)
        print(f"Maia 走了: {maia_move.uci()}")
        board.push(maia_move)

print(f"对局结束: {board.result()}")

import chess.pgn
import io

# 你的某局 PGN 记录
pgn_text = """
[Event "Casual Game"]
[White "You"]
[Black "Opponent"]
1. e4 e5 2. Nf3 Nc6 3. Bb5 a6 4. Ba4 Nf6 5. O-O Be7 6. Re1 b5 7. Bb3 d6 8. c3 O-O
"""

game = chess.pgn.read_game(io.StringIO(pgn_text))
board = game.board()

deviations = []  # 记录你的走法与 Maia 预测的差异

for move in game.mainline_moves():
    if board.turn == chess.WHITE:  # 假设你执白
        predictions = model.predict_moves(board)
        your_move_prob = predictions.get_prob(move)
        top_move = predictions.top_k(1)[0]
        deviations.append({
            "fen": board.fen(),
            "your_move": move.uci(),
            "your_prob": your_move_prob,
            "maia_top_move": top_move[0].uci(),
            "maia_top_prob": top_move[1],
        })
    board.push(move)

# 找出你偏离"人类主流"最多的几步
deviations.sort(key=lambda d: d["your_prob"])
for d in deviations[:3]:
    print(f"局面 {d['fen'][:30]}...")
    print(f"  你走了 {d['your_move']} (Maia预测概率 {d['your_prob']:.2%})")
    print(f"  人类最常走 {d['maia_top_move']} (概率 {d['maia_top_prob']:.2%})")