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# solver.py
import sys
import re
import json
import os
import subprocess
from deep_convert import deep_convert
from openai import OpenAI
from dotenv import load_dotenv
def solve_puzzle(index, puzzle, expected_solution, sys_content):
"""
使用 sys_content + puzzle 调用模型，生成 Z3 Python 代码，
运行并比对输出是否与 expected_solution 相同。
"""
load_dotenv()
client = OpenAI(
api_key=os.getenv("GEMINI_API_KEY"),
base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
)
messages = [
{"role": "user", "content": sys_content}, # 先把 sys_content 放进去
{"role": "user", "content": puzzle}, # 再放 puzzle
]
attempts = 0
current_solution = None
while attempts < 3:
attempts += 1
response = client.chat.completions.create(
model="gemini-2.0-flash",
messages=messages,
temperature=0.0,
stream=False
)
content = response.choices[0].message.content
messages.append(response.choices[0].message)
# 提取 code
code_blocks = re.findall(r"```(?:python)?(.*?)```", content, re.DOTALL)
if not code_blocks:
messages.append({"role": "user", "content": "Please write a complete Python code in your response. Try again."})
continue
code_to_run = code_blocks[0].strip()
result = subprocess.run(
[sys.executable, "-c", code_to_run],
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True
)
output = result.stdout.strip()
# print(output)
try:
current_solution = json.loads(output)
except json.JSONDecodeError:
messages.append({"role": "user", "content": "Your output is not valid JSON. Please ensure your code prints the solution as a JSON dictionary."})
continue
if 'rows' in current_solution.keys() and current_solution['rows'] == deep_convert(expected_solution)['rows']:
return {
"index": index,
"success": True,
"solution": current_solution,
"attempts": attempts,
"generatedCode": code_to_run,
"modelResponse": content
}
else:
messages.append({"role": "user", "content": "The solution does not match the expected answer. Please check your categories and constraints and provide the complete code again."})
return {
"index": index,
"success": False,
"solution": current_solution,
"attempts": attempts,
"generatedCode": code_to_run,
"modelResponse": content
}
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