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https://github.com/InternLM/InternBootcamp.git
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178 lines
No EOL
7.5 KiB
Python
Executable file
178 lines
No EOL
7.5 KiB
Python
Executable file
import re
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import json
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import random
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from internbootcamp.bootcamp.base import Basebootcamp
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from internbootcamp.libs.starbattle.get_grid import generate_star_battle_grid
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from internbootcamp.libs.starbattle.dfs_solver_cn import print_grid_in_kor
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class Starbattlebootcamp(Basebootcamp):
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def __init__(self, size=5):
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self.size = size
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def generator(self):
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self.grid, self.star_positions = generate_star_battle_grid(self.size)
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return self.grid
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def case_generator(self, size:tuple = (8,8), expect_camp_number:int = 8, random_rate:float = 0.1 , seed:int = None):
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grid = self.generator()
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return {
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"input_grid": grid
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}
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def prompt_func(self, identity) -> str:
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"""
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Process the input_data and return the processed prompt.
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Args:
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question_ori: The question to be processed.
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Returns:
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str: The processed prompt.
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"""
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statements = [f"""### 核心职责:
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1. 规则分析:
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- 解码并理解所提供的谜题规则
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- 创建一个系统化的规则实施方法
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- 识别潜在的规则相互作用或依赖关系
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2. 解决方案开发:
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- 有条理地将规则应用于谜题场景
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- 开发分步解决策略
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- 在整个解题过程中保持准确性
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3. 质量保证:
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- 反复检查解决方案的有效性
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- 确保遵守所有规定规则
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- 根据初始条件验证最终结果
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### 谜题参数:
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1. 网格结构: 游戏区域由不同的区域(分区)组成,每个区域包含多个方格。
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2. 星星放置指南:
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- 星星必须均匀分布,每行每列1个星星
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- 每个分区需要恰好1个星星
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- 星星必须保持分离(不能相邻,包括对角线)
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3. 输入格式:
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- 采用字母指定区域的矩阵表示
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- 每个独特字母代表一个不同的分区
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- 示例: A区域包括所有标记为'A'的方格
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4. 解决方案格式:
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- 基于坐标的报告系统
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- 格式: [区域字母]:(行坐标,列坐标)
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- 每个区域根据需要列出多个坐标
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###Question
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初始网格为:\n {print_grid_in_kor(identity['input_grid'])}
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""",
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f"""star battle是一种逻辑解谜游戏，其规则简单，解题过程富有挑战性。
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游戏规则 很简单。
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按如下要求在格子上放置星星：
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- 任意两颗星星不能在横向、纵向或对角上相邻。
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- 每行、每列及每个区域上需放置1颗星星。
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网格由矩阵表示，每个字母表示该位置所在区域的ID
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请完成该star battle，初始网格为:\n {print_grid_in_kor(identity['input_grid'])}"""]
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instruction_following = """Please note that the coordinate system used in this task starts from (1, 1). This means:
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1. The first row and first column are both numbered 1, not 0.
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2. In any coordinate (x, y), x represents the row number, and y represents the column number, with both x and y having a minimum value of 1.
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3. When processing coordinate data, ensure all calculations and logic are based on (1, 1) as the starting point to avoid errors caused by misunderstandings of the coordinate system.
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Let's think step by step and output the final answer with an example json formatting for a 5x5 board:
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Final-answer: ```json
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{'A': [(row_a, col_a)],'B': [(row_b, col_b)],'C': [(row_c, col_c)],'D': [(row_d, col_d)],'E': [(row_e, col_e)]}
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```"""
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prompt = statements[random.randint(0,len(statements)-1)] + '\n' + instruction_following
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return prompt
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@staticmethod
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def extract_output(output):
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"""
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Extract the output from the solution.
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Args:
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output: Model output to be processed.
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Returns:
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The processed output.
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"""
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pattern = pattern = r'```json\s*(\{[\s\S]*?\})\s*```'
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matches = re.findall(pattern, output)
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# Final-answer:{'A': [(3, 1)],
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# 'B': [(1, 4)],
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# 'C': [(2, 3)],
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# 'D': [(5, 2)],
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# 'E': [(4, 5)]}
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if matches:
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# 获取 JSON 字符串
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json_str = matches[-1]
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# print('match?', json_str)
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# print('solution generated? first lines', output[:200])
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# print('solution generated? last lines', output[-200:])
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# 替换单引号为双引号，将元组表示改为列表表示
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json_str = json_str.replace("'", '"').replace("(", "[").replace(")", "]")
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try:
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# 解析 JSON 字符串为 Python 字典
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result_dict = json.loads(json_str)
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return result_dict
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except json.JSONDecodeError as e:
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return json_str
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else:
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return None
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@classmethod
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def _verify_correction(cls, solution, identuty:dict)->bool:
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"""
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Verify the correction of the solution.
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"""
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input_grid = json.loads(identuty['input_grid']) if type(identuty['input_grid']) == str else identuty['input_grid']
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n = identuty.pop('n', 1)
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# Check each star is in the correct region
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for region, coords in solution.items():
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for (row, col) in coords:
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if row < 1 or row > len(input_grid) or col < 1 or col > len(input_grid[0]):
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return False
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if input_grid[row-1][col-1] != region:
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return False
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# Check each region has exactly n stars
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for region, coords in solution.items():
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if len(coords) != n:
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return False
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# Collect all stars and check row/column counts
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all_stars = [coord for coords in solution.values() for coord in coords]
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rows = {}
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cols = {}
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for (r, c) in all_stars:
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rows[r] = rows.get(r, 0) + 1
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cols[c] = cols.get(c, 0) + 1
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if any(v != n for v in rows.values()) or any(v != n for v in cols.values()):
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return False
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# Check adjacency
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for i in range(len(all_stars)):
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for j in range(i+1, len(all_stars)):
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r1, c1 = all_stars[i]
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r2, c2 = all_stars[j]
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if abs(r1 - r2) <= 1 and abs(c1 - c2) <= 1:
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return False
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return True
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if __name__ == '__main__':
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model_output = """ at (5,7).\n\nThus, Row 4 has no possible squares for a star.\n\nThis suggests that it's impossible to place stars in this configuration without violating the rules.\n\n### Conclusion\n\nAfter several iterations and attempts to place stars in each zone while adhering to the rules, it appears that there's an inherent conflict that prevents a valid solution. Specifically, Row 4 consistently lacks a suitable square for a star without violating the adjacency or zone constraints.\n\nTherefore, the puzzle, as presented, does not have a valid solution under the given rules.\n\nHowever, if we assume that there might have been a misunderstanding or a typo in the grid layout or zone definitions, we could revisit the initial assumptions. But based on the provided information and thorough analysis, it's concluded that the puzzle is unsolvable.\n\n**Final Answer**:\n\n```json\n{}\n```"""
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identity = {"input_grid": [["E", "E", "F", "F", "F", "F", "F"], ["E", "E", "D", "D", "F", "F", "F"], ["E", "E", "A", "A", "F", "F", "F"], ["E", "A", "A", "A", "F", "F", "G"], ["E", "A", "A", "A", "G", "G", "G"], ["B", "B", "B", "A", "A", "A", "C"], ["B", "B", "B", "B", "A", "A", "C"]]}
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score = StarBattlebootcamp.verify_score(model_output=model_output, identity=identity)
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print(score) |