58 lines
2.7 KiB
Python
58 lines
2.7 KiB
Python
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"""
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Agent 执行日志模型 — 结构化记录每次 Agent 执行的完整信息
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用于知识自进化系统的数据基础
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"""
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from sqlalchemy import Column, String, Text, Integer, DateTime, JSON, Float, Boolean
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from sqlalchemy.dialects.mysql import CHAR
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from app.core.database import Base
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import uuid
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from datetime import datetime
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class AgentExecutionLog(Base):
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"""Agent 每次执行的完整结构化日志"""
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__tablename__ = "agent_execution_logs"
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id = Column(CHAR(36), primary_key=True, default=lambda: str(uuid.uuid4()), comment="日志ID")
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agent_id = Column(String(36), nullable=True, index=True, comment="Agent ID")
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agent_name = Column(String(200), nullable=True, comment="Agent 名称")
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goal_id = Column(String(36), nullable=True, index=True, comment="关联 Goal ID")
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task_id = Column(String(36), nullable=True, index=True, comment="关联 Task ID")
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user_id = Column(String(36), nullable=True, index=True, comment="用户 ID")
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session_id = Column(String(100), nullable=True, comment="会话标识")
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# 输入/输出
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input_text = Column(Text, nullable=True, comment="用户输入文本")
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output_text = Column(Text, nullable=True, comment="Agent 输出文本")
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output_truncated = Column(Boolean, default=False, comment="输出是否被截断")
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# 执行结果
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success = Column(Boolean, default=True, comment="是否成功")
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error_message = Column(Text, nullable=True, comment="错误信息")
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# 性能指标
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latency_ms = Column(Integer, nullable=True, comment="总耗时(ms)")
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iterations_used = Column(Integer, default=0, comment="ReAct 迭代次数")
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tool_calls_made = Column(Integer, default=0, comment="工具调用总次数")
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# 结构化明细（JSON）
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tool_chain = Column(JSON, nullable=True, comment="工具调用链: [{tool_name, input, output, duration_ms}]")
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llm_calls = Column(JSON, nullable=True, comment="LLM调用明细: [{model, prompt_tokens, completion_tokens, latency_ms}]")
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steps = Column(JSON, nullable=True, comment="执行步骤详情（精简版）")
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# 模型信息
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model = Column(String(100), nullable=True, comment="使用的模型")
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provider = Column(String(50), nullable=True, comment="模型提供商")
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# 用户反馈（后续补充）
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user_rating = Column(Integer, nullable=True, comment="用户评分(1-5)")
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user_feedback = Column(Text, nullable=True, comment="用户反馈文本")
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# 知识提取标记
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knowledge_extracted = Column(Boolean, default=False, comment="是否已提取知识")
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created_at = Column(DateTime, default=datetime.now, comment="创建时间")
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def __repr__(self):
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return f"<AgentExecutionLog(id={self.id}, agent={self.agent_name}, success={self.success})>"
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