react-agent-chess.py

import chess
import chess.engine
from langchain.agents import load_tools
from langchain.agents import initialize_agent
from langchain.agents import AgentType
from langchain.llms import OpenAI
from config import OPENAI_API_KEY, SERPAPI_API_KEY
import os

os.environ['OPENAI_API_KEY'] = OPENAI_API_KEY
os.environ['SERPAPI_API_KEY'] = SERPAPI_API_KEY

llm = OpenAI(temperature=0)

tools = load_tools(["serpapi"], llm=llm)

agent_executor = initialize_agent(tools,
                                  llm,
                                  agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
                                  verbose=True)

# Initialize a chess board and the chess engine
engine = chess.engine.SimpleEngine.popen_uci("/opt/homebrew/Cellar/stockfish/16/bin/stockfish")


def play_game():
    moves = []  # Variable to store the list of moves
    board = chess.Board()

    def get_agent_move(board):
        feedback = ""
        while True:

            prompt = f"Current board: {board}\nMove history: {moves}\nChoose the next move for black in UCI format. The available legal moves are {list(board.legal_moves)}. The move you select should be among the legal moves in UCI format like this:'Move.from_uci('g7g5')' {feedback}"

            response = agent_executor.invoke({"input": prompt})

            next_move = response["output"][-6:-2]

            try:
                move = chess.Move.from_uci(next_move)

                if move in board.legal_moves:
                    return move
                else:
                    feedback = f"Agent's generated move {move} is not valid currently."
            except:
                feedback = "Failed to parse the Agent's generated move. Retrying..."

    while not board.is_game_over():
        if board.turn:  # True for white's turn, False for black's turn
            result = engine.play(board, chess.engine.Limit(time=2.0))
            board.push(result.move)
            moves.append(result.move.uci())  # Store UCI move in the list
        else:
            move = get_agent_move(board)
            board.push(move)
            moves.append(move.uci())  # Store UCI move in the list
        print(board)
        print("\n\n")

    # Check the result of the game
    winner = ""
    if board.is_checkmate():
        if board.turn:
            winner = "Black"
        else:
            winner = "White"
    elif board.is_stalemate() or board.is_insufficient_material() or board.is_seventyfive_moves() or board.is_fivefold_repetition() or board.is_variant_draw():
        winner = "Draw"

    # Return the result
    if winner == "Black":
        return "Agent wins by checkmate."
    elif winner == "White":
        return "Stockfish wins by checkmate."
    else:
        return "The game is a draw."

# Number of games to play
n_games = 10

# Initialize a dictionary to store the results
results = {"GPT-4 wins": 0, "Stockfish wins": 0, "Draw": 0}

# Run the game n times
for i in range(n_games):
    print(f"Starting game {i+1}...")
    result = play_game()
    print(result)

    # Update the results dictionary based on the outcome of the game
    if "Agent wins" in result:
        results["GPT-4 wins"] += 1
    elif "Stockfish wins" in result:
        results["Stockfish wins"] += 1
    else:
        results["Draw"] += 1

    print(f"Game {i+1} finished.\n\n")

# Print the final results
print("Final results after playing", n_games, "games:")
print("Agent won:", results["Agent wins"], "games")
print("Stockfish won:", results["Stockfish wins"], "games")
print("Draw:", results["Draw"], "games")