langgraph_impl/image_chess_solver.py

import chess
import chess.engine
import tempfile
from PIL import Image

# Path to your Stockfish binary (update if needed)
STOCKFISH_PATH = "/usr/bin/stockfish"

def analyze_position_from_fen(fen: str, time_limit: float = 1.0) -> str:
    """
    Uses Stockfish to analyze the best move from a given FEN string.
    Args:
        fen (str): Forsyth–Edwards Notation of the board.
        time_limit (float): Time to let Stockfish think.
    Returns:
        str: Best move in algebraic notation.
    """
    try:
        board = chess.Board(fen)
        engine = chess.engine.SimpleEngine.popen_uci(STOCKFISH_PATH)
        result = engine.play(board, chess.engine.Limit(time=time_limit))
        engine.quit()
        return board.san(result.move)
    except Exception as e:
        return f"Stockfish error: {e}"

def solve_chess_image(image_path: str) -> str:
    """
    Stub function for image-to-FEN. Replace with actual OCR/vision logic.
    
    Args:
        image_path (str): Path to chessboard image.
    Returns:
        str: Best move or error.
    """
    # Placeholder FEN for development (e.g., black to move, guaranteed mate)
    sample_fen = "6k1/5ppp/8/8/8/8/5PPP/6K1 b - - 0 1"
    
    try:
        print(f"Simulating FEN extraction from image: {image_path}")
        # Replace the above with actual OCR image-to-FEN logic
        best_move = analyze_position_from_fen(sample_fen)
        return f"Detected FEN: {sample_fen}\nBest move for Black: {best_move}"
    except Exception as e:
        return f"Image analysis error: {e}"