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internbootcamp/bootcamp/minesweeper/minesweeper.py

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+"""# 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
+
+**Objective**: Clear a rectangular grid of hidden cells without detonating any mines. Cells contain either mines or numbers indicating adjacent mines.
+
+**Grid Setup**:
+1. The grid consists of hidden cells, some containing mines (randomly placed).
+2. Non-mine cells reveal a number when uncovered, representing the total mines in the 8 adjacent cells (vertically, horizontally, and diagonally).
+
+**Gameplay**:
+1. **Uncover a Cell**: Click/select a cell to reveal its content:
+   - If it contains a mine, the game ends (loss).
+   - If it shows a number, use this to deduce nearby mine locations.
+   - If it shows **0** (no adjacent mines), all adjacent cells automatically uncover recursively until numbered cells are reached.
+
+2. **Flagging Mines**: Right-click/mark a cell to flag it as a suspected mine (prevents accidental uncovering). Flags help track potential mines but do not affect gameplay logic otherwise.
+
+**Win Condition**:
+- All non-mine cells are uncovered, and all mines are correctly flagged.
+
+**Logic Rules**:
+- Numbers on the grid are **static hints**, not live updates. Flagging a mine does not change existing numbers.
+- Use the numbers to infer mine positions: e.g., a cell labeled \"3\" must have exactly 3 mines in its 8 neighboring cells.
+
+**Loss Condition**:
+- Uncovering any cell containing a mine.
+
+
+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
+import ast
+
+class Minesweeperbootcamp(Basebootcamp):
+    def __init__(self, rows=8, cols=8, mines_count=10):
+        if mines_count > rows * cols:
+            raise ValueError("Number of mines cannot exceed grid size.")
+        self.rows = rows
+        self.cols = cols
+        self.mines_count = mines_count
+    
+    def case_generator(self):
+        all_cells = [(i, j) for i in range(self.rows) for j in range(self.cols)]
+        if self.mines_count > len(all_cells):
+            raise ValueError("mines_count exceeds valid cells count.")
+        mines = random.sample(all_cells, self.mines_count)
+        mines_list = [list(coord) for coord in mines]
+        return {
+            'rows': self.rows,
+            'cols': self.cols,
+            'mines': mines_list
+        }
+    
+    @staticmethod
+    def prompt_func(question_case):
+        rows = question_case['rows']
+        cols = question_case['cols']
+        mines_count = len(question_case['mines'])
+        mines_set = set(tuple(coord) for coord in question_case['mines'])
+        
+        grid_info = []
+        for i in range(rows):
+            for j in range(cols):
+                count = 0
+                for dx in (-1, 0, 1):
+                    for dy in (-1, 0, 1):
+                        if dx == 0 and dy == 0:
+                            continue
+                        x, y = i + dx, j + dy
+                        if 0 <= x < rows and 0 <= y < cols and (x, y) in mines_set:
+                            count += 1
+                grid_info.append((i, j, count))
+        
+        prompt = (
+            f"You are playing Minesweeper on a {rows}x{cols} grid with {mines_count} mines.\n"
+            "Each number below represents the count of adjacent mines for a cell. "
+            "Find all the mine locations and provide them in the specified format.\n\n"
+            "Revealed cells (format: row, column: count):\n"
+        )
+        for i, j, num in grid_info:
+            prompt += f"- ({i}, {j}): {num}\n"
+        prompt += (
+            "\nYour answer must be a list of mine coordinates formatted as [[row1, col1], [row2, col2], ...]. "
+            "Place your final answer between [answer] and [/answer]."
+        )
+        return prompt
+    
+    @staticmethod
+    def extract_output(output):
+        pattern = r'\[answer\](.*?)\[/answer\]'
+        matches = re.findall(pattern, output, re.DOTALL)
+        if not matches:
+            return None
+        last_match = matches[-1].strip()
+        try:
+            solution = ast.literal_eval(last_match)
+            if (isinstance(solution, list) and 
+                all(isinstance(coord, list) and len(coord) == 2 for coord in solution)):
+                return solution
+            return None
+        except (SyntaxError, ValueError):
+            return None
+    
+    @classmethod
+    def _verify_correction(cls, solution, identity):
+        if not isinstance(solution, list):
+            return False
+        try:
+            solution_set = {tuple(coord) for coord in solution}
+        except TypeError:
+            return False
+        mines = identity.get('mines', [])
+        mines_set = {tuple(mine) for mine in mines}
+        if len(solution_set) != len(mines_set):
+            return False
+        rows, cols = identity['rows'], identity['cols']
+        for (r, c) in solution_set:
+            if not (0 <= r < rows and 0 <= c < cols):
+                return False
+        return solution_set == mines_set