"""# 谜题训练场开发任务 ## 任务概述 你是一位资深程序员,我需要你帮我实现一个特定谜题的训练场环境类。这个类继承自`Basebootcamp`,用于生成谜题实例并验证解答。 ## 背景说明 我正在开发一系列谜题训练场,每个训练场对应一个特定类型的谜题。训练场类命名为`{PuzzleName}bootcamp`,其中`PuzzleName`是谜题的名称。 每个训练场类主要提供两个核心功能: 1. 生成该谜题类型的问题实例 2. 验证用户对问题的回答是否正确 ## 技术接口规范 ### 类方法实现要求 ```python class {PuzzleName}bootcamp(Basebootcamp): def __init__(self, **params): \"\"\" 请你自定义params,以保存该puzzle相关的参数,例如网格大小等,参数配有默认值 \"\"\" pass def case_generator(self): \"\"\" 生成谜题实例,提示:为保证谜题有解,可以先生成结果再对结果处理得到谜题 返回:一个可JSON序列化的字典(避免包含set等无法通过json.dumps处理的数据结构) \"\"\" pass @staticmethod def prompt_func(question_case) -> str: \"\"\" 将case_generator生成的谜题实例转换为文本形式的问题,问题中包含问题背景、对谜题规则的介绍、具体要解决的谜题实例、期望最终答案的格式, 例如:你是xxxx,请你解答yyyy,规则如下:yyyy,最终答案放置在:zzzzz 参数: question_case: 由case_generator生成的谜题实例 返回: str: 格式化的问题字符串 注意: 1. 需考虑问题的格式,以便后续能正确提取 2. 问题描述中应包含期望的答案格式说明,以便后续能正确提取,为了避免抽取时匹配出干扰项,请要求模型将答案放在特定标签,如[answer] [/answer]内 \"\"\" pass @staticmethod def extract_output(output): \"\"\" 从LLM的回复中提取符合格式要求的答案,如有多个,请抽取最后一个,避免使用re.search等只抽取第一个结果的方式。 参数: output: LLM的完整输出(包含原始问题和回答) 返回: 提取的答案,若未找到符合格式的答案则返回None \"\"\" pass @classmethod def _verify_correction(cls, solution, identity): \"\"\" 验证提取的答案是否正确,注意一个问题可以能有多个解,按照谜题规则进行检验,不要直接匹配可能的答案。 参数: solution: extract_output提取的答案 identity: case_generator生成的谜题实例 返回: bool: 答案是否正确 \"\"\" pass ``` ### 验证评分方法(基类已实现) ```python @classmethod def verify_score(cls, model_output, identity:dict, format_score=0.1) -> float: \"\"\" 验证输出结果并评分。 参数: model_output: 模型的完整输出 identity: 谜题实例(由case_generator生成) format_score: 答案格式正确时的基础分数 返回: float: 评分结果(0-1之间) \"\"\" score = 0. try: extract_solution = cls.extract_output(model_output) if extract_solution is None: return score else: score = format_score # 格式正确时的基础分数 if cls._verify_correction(extract_solution, identity): score = 1. # 答案完全正确时的满分 except Exception as e: # 处理异常情况 pass return score ``` ### 使用示例 ```python # 初始化谜题训练场 bootcamp = Puzzlebootcamp() # 生成谜题实例 case = bootcamp.case_generator() # 将谜题转换为文本问题 prompt = Puzzlebootcamp.prompt_func(case) # 获取LLM对问题的解答 response = get_response(prompt, \"LLM\") # 从完整对话中提取答案 extracted_output = Puzzlebootcamp.extract_output(prompt + response) # 验证答案并评分 score = Puzzlebootcamp.verify_score(extracted_output, case) ``` ## 你的任务 请根据以下谜题描述(谜题描述可能不完整,请先结合你的知识澄清规则),实现一个完整的谜题训练场类: ### 谜题描述 **Kakuro Puzzle Rules:** 1. **Grid Structure**: - The puzzle is played on a grid of white (empty) and black (clue) cells. - **Clue cells** (black) contain hints for solving adjacent white cells. Each clue has two components: - **Rightward (→)**: Sum of digits in the horizontal sequence of white cells to its right. - **Downward (↓)**: Sum of digits in the vertical sequence of white cells below it. 2. **Digit Placement**: - Fill white cells with digits **1–9**. - A digit **cannot repeat** within the same horizontal or vertical sequence (referred to as a \"run\"). 3. **Run Constraints**: - Each run is defined by a clue cell. For example, a rightward clue of \"12 in 3 cells\" means the three adjacent horizontal cells must sum to 12, with no repeated digits. - A white cell can belong to both a horizontal and vertical run simultaneously. Its digit must satisfy **both clues**. 4. **Key Principles**: - **Uniqueness**: All digits in a single run must be distinct. - **No Zeros**: Digits must be between 1 and 9. - **Interconnected Solutions**: Solving one run provides constraints for intersecting runs. **Objective**: Fill all white cells to satisfy all horizontal and vertical clues without violating the rules. 请完成上述谜题的训练场环境类实现,包括所有必要的方法。 """ from bootcamp import Basebootcamp import random import re from ast import literal_eval class Kakurobootcamp(Basebootcamp): def __init__(self, rows=3, cols=3): self.rows = rows self.cols = cols def case_generator(self): # 生成横向序列的数对 a, b = self._generate_unique_pair() sum_r = a + b # 生成纵向序列的数对 c, d = self._generate_unique_pair() sum_d = c + d # 构建网格结构 grid = [[{'type': 'black', 'right': (sum_r, 2), 'down': (sum_d, 2)} if (row == 0 and col == 0) else {'type': 'white'} if ((row == 0 and col in (1, 2)) or (col == 0 and row in (1, 2))) else {'type': 'black'} for col in range(self.cols)] for row in range(self.rows)] solution = { "(0, 1)": a, "(0, 2)": b, "(1, 0)": c, "(2, 0)": d } return { 'grid': grid, 'solution': solution } def _generate_unique_pair(self): while True: a = random.randint(1, 9) b = random.randint(1, 9) if a != b: return a, b @staticmethod def prompt_func(question_case) -> str: clues = [] grid = question_case['grid'] for row_idx, row in enumerate(grid): for col_idx, cell in enumerate(row): if cell['type'] == 'black': parts = [] if 'right' in cell: sum_r, len_r = cell['right'] parts.append(f"右侧的 {len_r} 个白色格子之和为 {sum_r}") if 'down' in cell: sum_d, len_d = cell['down'] parts.append(f"下方的 {len_d} 个白色格子之和为 {sum_d}") if parts: clues.append(f"位于 ({row_idx}, {col_idx}) 的黑色格子:" + ",".join(parts)) clues_text = "\n".join(clues) white_coords = [] for row_idx, row in enumerate(grid): for col_idx, cell in enumerate(row): if cell['type'] == 'white': white_coords.append(f"({row_idx}, {col_idx})") white_coords_text = ", ".join(white_coords) prompt = f"""你是Kakuro谜题解答者,请根据以下线索填充所有白色格子,确保每个横向或纵向的序列满足和的条件,且同一序列中的数字不重复。每个格子只能填1-9的整数。 谜题线索: {clues_text} 需要填充的白色格子位于以下坐标:{white_coords_text}。 请将你的答案以字典形式放在[answer]和[/answer]之间,键为坐标字符串,如"(行,列)",值为对应的整数。例如: [answer] {{"(0,1)": 3, "(0,2)": 4, "(1,0)":5, "(2,0)":2}} [/answer] 请确保所有白色格子都被正确填写,且没有多余或缺少的项。""" return prompt @staticmethod def extract_output(output): answer_blocks = re.findall(r'\[answer\](.*?)\[/answer\]', output, re.DOTALL) if not answer_blocks: return None last_block = answer_blocks[-1].strip() try: answer_dict = literal_eval(last_block) if not isinstance(answer_dict, dict): return None converted = {} for coord_str, value in answer_dict.items(): coord_str = coord_str.strip('()') row, col = map(int, coord_str.split(',')) converted[(row, col)] = value return converted except: return None @classmethod def _verify_correction(cls, solution, identity): if not solution: return False grid = identity['grid'] solution = solution.copy() # Check all coordinates in solution are valid white cells for coord in solution: row, col = coord if row < 0 or col < 0 or row >= len(grid) or col >= len(grid[0]): return False cell = grid[row][col] if cell.get('type') != 'white': return False value = solution[coord] if not (1 <= value <= 9): return False # Check all clues for row_idx in range(len(grid)): for col_idx in range(len(grid[row_idx])): cell = grid[row_idx][col_idx] if cell.get('type') != 'black': continue # Check right clue if 'right' in cell: sum_r, len_r = cell['right'] run_coords = [] current_col = col_idx + 1 while current_col < len(grid[row_idx]) and grid[row_idx][current_col].get('type') == 'white': run_coords.append((row_idx, current_col)) current_col += 1 if len(run_coords) != len_r: return False # Check all coords are in solution for coord in run_coords: if coord not in solution: return False values = [solution[coord] for coord in run_coords] if sum(values) != sum_r or len(set(values)) != len_r: return False # Check down clue if 'down' in cell: sum_d, len_d = cell['down'] run_coords = [] current_row = row_idx + 1 while current_row < len(grid) and grid[current_row][col_idx].get('type') == 'white': run_coords.append((current_row, col_idx)) current_row += 1 if len(run_coords) != len_d: return False for coord in run_coords: if coord not in solution: return False values = [solution[coord] for coord in run_coords] if sum(values) != sum_d or len(set(values)) != len_d: return False return True