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| from tools.base_tool import BaseTool | |
| from PIL import Image | |
| import requests | |
| from io import BytesIO | |
| class ImageToChessBoardFENTool(BaseTool): | |
| name = "image_to_chess_fen" | |
| description = "Extracts the FEN representation of a chess board from an image." | |
| inputs = { | |
| "image_url": { | |
| "type": "string", | |
| "description": "The URL of the chessboard image.", | |
| } | |
| } | |
| output_type = "string" | |
| def forward(self, image_url: str) -> str: | |
| try: | |
| response = requests.get(image_url) | |
| response.raise_for_status() | |
| image = Image.open(BytesIO(response.content)).convert("RGB") | |
| except Exception as e: | |
| return f"Failed to load image: {e}" | |
| # This is a placeholder implementation. | |
| # You should replace it with an actual model or logic that processes the image and returns the FEN. | |
| fen = self._mock_fen_extraction(image) | |
| return fen | |
| def _mock_fen_extraction(self, image): | |
| # Replace this logic with your actual FEN model prediction if available. | |
| return "r1bqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1" |