"""
LLM 软规则审查器
使用 LLM 进行代码安全审查
"""

import os
import json
from typing import Optional, List
from dataclasses import dataclass
from dotenv import load_dotenv

from llm.client import get_client, LLMClientError, ENV_PATH
from llm.prompts import SAFETY_REVIEW_SYSTEM, SAFETY_REVIEW_USER


@dataclass
class LLMReviewResult:
    """LLM 审查结果"""
    passed: bool
    reason: str
    raw_response: Optional[str] = None


class LLMReviewer:
    """
    LLM 安全审查器
    
    使用大模型对代码进行语义级别的安全审查
    """
    
    def __init__(self):
        load_dotenv(ENV_PATH)
        self.model_name = os.getenv("GENERATION_MODEL_NAME")
    
    def review(
        self,
        user_input: str,
        execution_plan: str,
        code: str,
        warnings: Optional[List[str]] = None
    ) -> LLMReviewResult:
        """
        审查代码安全性
        
        Args:
            user_input: 用户原始需求
            execution_plan: 执行计划
            code: 待审查的代码
            warnings: 静态检查产生的警告列表
            
        Returns:
            LLMReviewResult: 审查结果
        """
        try:
            client = get_client()
            
            # 构建警告信息
            warning_text = ""
            if warnings and len(warnings) > 0:
                warning_text = "\n\n【静态检查警告】请重点审查以下内容：\n" + "\n".join(f"- {w}" for w in warnings)
            
            messages = [
                {"role": "system", "content": SAFETY_REVIEW_SYSTEM},
                {"role": "user", "content": SAFETY_REVIEW_USER.format(
                    user_input=user_input,
                    execution_plan=execution_plan,
                    code=code
                ) + warning_text}
            ]
            
            response = client.chat(
                messages=messages,
                model=self.model_name,
                temperature=0.1,
                max_tokens=512,
                timeout=120
            )
            
            return self._parse_response(response)
            
        except LLMClientError as e:
            # LLM 调用失败，保守起见判定为不通过
            return LLMReviewResult(
                passed=False,
                reason=f"安全审查失败（{str(e)}），出于安全考虑拒绝执行"
            )
        except Exception as e:
            return LLMReviewResult(
                passed=False,
                reason=f"安全审查异常（{str(e)}），出于安全考虑拒绝执行"
            )
    
    def _parse_response(self, response: str) -> LLMReviewResult:
        """解析 LLM 响应"""
        try:
            # 提取 JSON
            json_str = self._extract_json(response)
            data = json.loads(json_str)
            
            passed = data.get("pass", False)
            reason = data.get("reason", "未提供原因")
            
            # 确保 passed 是布尔值
            if isinstance(passed, str):
                passed = passed.lower() in ('true', 'yes', '1', 'pass')
            
            return LLMReviewResult(
                passed=bool(passed),
                reason=reason,
                raw_response=response
            )
            
        except (json.JSONDecodeError, ValueError, TypeError):
            # 解析失败，保守判定
            return LLMReviewResult(
                passed=False,
                reason=f"审查结果解析失败，出于安全考虑拒绝执行",
                raw_response=response
            )
    
    def _extract_json(self, text: str) -> str:
        """从文本中提取 JSON"""
        start = text.find('{')
        end = text.rfind('}')
        
        if start != -1 and end != -1 and end > start:
            return text[start:end + 1]
        
        return text


def review_code_safety(
    user_input: str,
    execution_plan: str,
    code: str,
    warnings: Optional[List[str]] = None
) -> LLMReviewResult:
    """便捷函数：审查代码安全性"""
    reviewer = LLMReviewer()
    return reviewer.review(user_input, execution_plan, code, warnings)