e39829fc4e
批次1: 项目结构 + SQLite 存储层 + 数据模型 批次2: REST API (http.server) 批次3: LLM 编译器 (支持 OpenAI/Anthropic) 批次4: RestrictedPython 规则执行器 批次5: 规则匹配器 + LLM Callback 兜底 批次6: 冲突检测器 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
71 lines
1.8 KiB
Python
71 lines
1.8 KiB
Python
"""Data models for rule engine - pure Python implementation."""
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from dataclasses import dataclass, field
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from datetime import datetime
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from typing import Optional, Dict, Any
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@dataclass
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class CreateRuleRequest:
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"""创建规则的请求模型。"""
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name: str
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condition_template: str
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description: Optional[str] = None
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priority: int = 0
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facts_schema: Optional[Dict] = None
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@dataclass
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class Rule:
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"""规则模型。"""
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id: str
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name: str
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condition_template: str
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code: str
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description: Optional[str] = None
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priority: int = 0
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version: int = 1
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created_at: Optional[datetime] = None
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updated_at: Optional[datetime] = None
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is_active: bool = True
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def to_dict(self) -> Dict[str, Any]:
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return {
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"id": self.id,
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"name": self.name,
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"description": self.description,
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"condition_template": self.condition_template,
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"code": self.code,
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"priority": self.priority,
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"version": self.version,
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"created_at": self.created_at.isoformat() if self.created_at else None,
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"updated_at": self.updated_at.isoformat() if self.updated_at else None,
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"is_active": self.is_active
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}
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@dataclass
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class RuleExecution:
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"""规则执行记录模型。"""
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id: str
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rule_id: str
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facts: Dict
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result: Optional[Dict] = None
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matched: bool = False
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executed_at: Optional[datetime] = None
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@dataclass
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class EvaluateRequest:
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"""校验事实的请求模型。"""
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facts: Dict
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rule_id: Optional[str] = None # 指定规则ID，为空则匹配所有
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@dataclass
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class EvaluateResponse:
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"""校验事实的响应模型。"""
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matched: bool
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rule_id: Optional[str] = None
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result: Optional[Dict] = None
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conflict_warning: Optional[str] = None
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