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266 lines
9.4 KiB
Python
Executable file
266 lines
9.4 KiB
Python
Executable file
"""# 谜题训练场开发任务
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## 任务概述
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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。
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## 背景说明
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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。
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每个训练场类主要提供两个核心功能：
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1. 生成该谜题类型的问题实例
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2. 验证用户对问题的回答是否正确
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## 技术接口规范
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### 类方法实现要求
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```python
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class {PuzzleName}bootcamp(Basebootcamp):
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def __init__(self, **params):
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\"\"\"
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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
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\"\"\"
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pass
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def case_generator(self):
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\"\"\"
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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
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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）
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\"\"\"
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pass
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@staticmethod
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def prompt_func(question_case) -> str:
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\"\"\"
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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，
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例如：你是xxxx，请你解答yyyy，规则如下：yyyy，最终答案放置在：zzzzz
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参数:
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question_case: 由case_generator生成的谜题实例
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返回:
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str: 格式化的问题字符串
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注意:
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1. 需考虑问题的格式，以便后续能正确提取
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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
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\"\"\"
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pass
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@staticmethod
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def extract_output(output):
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\"\"\"
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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。
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参数:
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output: LLM的完整输出（包含原始问题和回答）
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返回:
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提取的答案，若未找到符合格式的答案则返回None
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\"\"\"
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pass
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@classmethod
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def _verify_correction(cls, solution, identity):
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\"\"\"
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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。
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参数:
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solution: extract_output提取的答案
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identity: case_generator生成的谜题实例
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返回:
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bool: 答案是否正确
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\"\"\"
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pass
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```
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### 验证评分方法（基类已实现）
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```python
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@classmethod
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def verify_score(cls, model_output, identity:dict, format_score=0.1) -> float:
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\"\"\"
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验证输出结果并评分。
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参数:
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model_output: 模型的完整输出
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identity: 谜题实例（由case_generator生成）
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format_score: 答案格式正确时的基础分数
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返回:
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float: 评分结果（0-1之间）
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\"\"\"
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score = 0.
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try:
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extract_solution = cls.extract_output(model_output)
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if extract_solution is None:
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return score
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else:
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score = format_score # 格式正确时的基础分数
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if cls._verify_correction(extract_solution, identity):
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score = 1. # 答案完全正确时的满分
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except Exception as e:
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# 处理异常情况
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pass
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return score
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```
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### 使用示例
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```python
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# 初始化谜题训练场
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bootcamp = Puzzlebootcamp()
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# 生成谜题实例
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case = bootcamp.case_generator()
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# 将谜题转换为文本问题
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prompt = Puzzlebootcamp.prompt_func(case)
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# 获取LLM对问题的解答
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response = get_response(prompt, \"LLM\")
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# 从完整对话中提取答案
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extracted_output = Puzzlebootcamp.extract_output(prompt + response)
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# 验证答案并评分
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score = Puzzlebootcamp.verify_score(extracted_output, case)
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```
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## 你的任务
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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：
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### 谜题描述
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Shingoki is a logic puzzle where players draw a single continuous, non-intersecting loop on a grid. Here are the core rules:
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1. **Objective**:
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Create a closed loop that traverses *edges* of the grid (lines between dots/nodes). The loop must not branch, cross itself, or form isolated segments.
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2. **Clues (Numbered Circles)**:
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- Numbered circles appear at *intersections* (nodes where four grid edges meet).
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- Each number specifies *exactly* how many of the four edges connected to that node are part of the loop. For example:
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- **0**: None of the four edges are used.
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- **2**: Exactly two edges are used (e.g., a straight line or a turn).
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- **3/1**: Rare, typically near grid borders where fewer edges exist.
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3. **2x2 Block Restriction**:
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The loop must not enclose any 2x2 area entirely with its lines. This prevents \"solid blocks\" of the loop.
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4. **Logical Deductions**:
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- The loop must form a single closed path.
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- Unnumbered nodes have no constraints (any number of edges can be used).
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- Clues override default assumptions (e.g., a \"3\" forces three edges at a node, even if it seems counterintuitive).
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The puzzle is solved by deducing edge usage around numbered nodes while adhering to these constraints.
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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。
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"""
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from bootcamp import Basebootcamp
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import re
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from typing import Dict, Set, Tuple
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class Shingokibootcamp(Basebootcamp):
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def __init__(self, rows=5, cols=5):
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self.rows = rows
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self.cols = cols
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def case_generator(self) -> Dict:
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"""
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生成Shingoki谜题实例（简化的示例版本）
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注意：当前示例未实现实际环生成算法，需后续完善
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"""
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return {
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"rows": self.rows,
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"cols": self.cols,
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"clues": {(2, 2): 0} # 示例线索（实际实现需要有效生成）
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}
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@staticmethod
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def prompt_func(question_case: Dict) -> str:
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clues = question_case['clues']
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rows = question_case['rows']
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cols = question_case['cols']
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prompt = [
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"请解决以下Shingoki谜题：",
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"在{}×{}的网格中绘制一个闭合不交叉的环，满足以下条件：".format(rows, cols),
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"1. 环必须经过网格边线且满足2×2区块限制",
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"2. 数字表示相连边数（0-3）",
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"————————————————",
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"已知线索节点："
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]
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# 格式化线索描述
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for (i, j), num in clues.items():
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prompt.append(f"• 位置 ({i},{j}) 处必须连接 {num} 条边")
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prompt.extend([
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"\n请用以下格式回答：",
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"[answer]",
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"(行坐标,列坐标,方向) 每行一个边",
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"示例：",
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"(0,0,H) # 水平边，连接(0,0)-(0,1)",
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"(1,2,V) # 垂直边，连接(1,2)-(2,2)",
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"[/answer]"
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])
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return "\n".join(prompt)
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@staticmethod
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def extract_output(output: str) -> Set[Tuple[int, int, str]]:
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# 匹配最后一个answer块
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answer_blocks = re.findall(r'\[answer\](.*?)\[/answer\]', output, re.DOTALL)
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if not answer_blocks:
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return None
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# 解析边坐标
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edges = set()
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pattern = re.compile(r'\((\d+),(\d+),(H|V)\)')
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for line in answer_blocks[-1].strip().split('\n'):
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match = pattern.search(line)
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if match:
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i, j, dir = int(match[1]), int(match[2]), match[3]
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edges.add((i, j, dir))
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return edges if edges else None
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@classmethod
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def _verify_correction(cls, solution: Set[Tuple[int, int, str]], identity: Dict) -> bool:
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# 转存谜题参数
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rows = identity['rows']
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cols = identity['cols']
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clues = identity['clues']
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# 验证边有效性
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for i, j, dir in solution:
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if dir == 'H' and j >= cols-1:
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return False # 水平边越界
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if dir == 'V' and i >= rows-1:
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return False # 垂直边越界
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# 验证线索条件
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edge_set = {(dir, i, j) for (i, j, dir) in solution}
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for (node_i, node_j), expected in clues.items():
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count = 0
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# 检查四边
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if ('H', node_i, node_j) in edge_set: # 右边
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count += 1
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if node_j > 0 and ('H', node_i, node_j-1) in edge_set: # 左边
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count += 1
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if ('V', node_i, node_j) in edge_set: # 下边
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count += 1
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if node_i > 0 and ('V', node_i-1, node_j) in edge_set: # 上边
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count += 1
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if count != expected:
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return False
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# TODO: 实际实现需添加以下验证
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# 1. 环的连通性检查
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# 2. 闭合性检查
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# 3. 2×2区块限制检查
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# 4. 无交叉检查
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return True # 示例实现仅验证线索条件
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