Codex
96 lines
5.2 KiB
Python
96 lines
5.2 KiB
Python
"""
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智能体模型
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"""
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from sqlalchemy import Column, String, Text, Float, Integer, Boolean, JSON, Index
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from app.base_model import BaseModel
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class Agent(BaseModel):
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"""
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智能体定义
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智能体是一个能够自主决策、调用工具、多轮推理的 AI 实体
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支持两种模式：
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- autonomous: 自主规划模式 - Agent 自动拆解任务并执行
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- dialog_flow: 对话流模式 - 按预定义流程与用户交互
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"""
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__tablename__ = "ai_agent"
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application_id = Column(String(21), nullable=True, index=True, comment="所属应用ID（逻辑外键关联core_application）")
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is_global = Column(Boolean, default=False, comment="是否在子应用中可见")
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name = Column(String(100), nullable=False, comment="智能体名称")
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code = Column(String(100), unique=True, nullable=False, comment="智能体编码")
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description = Column(Text, default="", comment="智能体描述")
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avatar = Column(String(500), default="", comment="头像 URL")
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mode = Column(String(20), default="autonomous", comment="运行模式: autonomous/dialog_flow")
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status = Column(String(20), default="draft", comment="状态: draft/published/disabled")
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persona = Column(JSON, default=dict, comment="人设配置")
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system_prompt = Column(Text, default="", comment="系统提示词")
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model_id = Column(String(21), nullable=True, index=True, comment="默认模型ID（逻辑外键关联ai_llm_model）")
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temperature = Column(Float, default=0.7, comment="温度参数（0-2）")
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top_p = Column(Float, default=1.0, comment="top_p 参数")
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max_tokens = Column(Integer, default=4096, comment="最大输出 Token")
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max_iterations = Column(Integer, default=10, comment="最大推理轮数")
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welcome_message = Column(Text, default="", comment="开场白")
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suggested_questions = Column(JSON, default=list, comment="推荐问题列表")
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workflow_id = Column(String(21), nullable=True, index=True, comment="关联工作流ID（逻辑外键关联ai_workflow）")
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enable_memory = Column(Boolean, default=False, comment="是否启用对话记忆")
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memory_window = Column(Integer, default=10, comment="记忆窗口大小（最近 N 轮对话）")
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enable_streaming = Column(Boolean, default=True, comment="是否启用流式输出（自主规划模式）")
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knowledge_base_ids = Column(JSON, default=list, comment="关联的知识库ID列表")
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knowledge_config = Column(JSON, default=dict, comment="知识库检索配置(top_k/score_threshold/retrieval_mode等)")
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is_public = Column(Boolean, default=False, comment="是否公开")
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conversation_count = Column(Integer, default=0, comment="对话数量")
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message_count = Column(Integer, default=0, comment="消息数量")
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total_tokens = Column(Integer, default=0, comment="总 Token 消耗")
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class AgentConversation(BaseModel):
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"""
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智能体对话
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"""
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__tablename__ = "ai_agent_conversation"
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agent_id = Column(String(21), nullable=False, index=True, comment="智能体ID（逻辑外键关联ai_agent）")
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user_id = Column(String(21), nullable=True, index=True, comment="用户ID（逻辑外键关联core_user）")
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title = Column(String(200), default="", comment="对话标题")
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summary = Column(Text, default="", comment="对话摘要")
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workflow_run_id = Column(String(21), nullable=True, comment="工作流运行实例ID（逻辑外键关联ai_workflow_run）")
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waiting_node_id = Column(String(100), default="", comment="等待输入的节点 ID")
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extra_data = Column(JSON, default=dict, comment="元数据")
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message_count = Column(Integer, default=0, comment="消息数量")
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total_tokens = Column(Integer, default=0, comment="总 Token 消耗")
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__table_args__ = (
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Index("ix_ai_agent_conversation_agent_user", "agent_id", "user_id"),
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)
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class AgentMessage(BaseModel):
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"""
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智能体消息
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记录对话中的每条消息，包括用户消息、助手回复、工具调用等
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"""
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__tablename__ = "ai_agent_message"
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conversation_id = Column(String(21), nullable=False, index=True, comment="对话ID（逻辑外键关联ai_agent_conversation）")
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role = Column(String(20), nullable=False, comment="角色: user/assistant/tool/system")
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content = Column(Text, default="", comment="消息内容")
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attachments = Column(JSON, default=list, comment="附件列表 [{id, type, name, url, mime_type, size}]")
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status = Column(String(20), default="completed", comment="状态: pending/completed/failed")
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reasoning_steps = Column(JSON, default=list, comment="推理步骤")
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tool_calls = Column(JSON, default=list, comment="工具调用记录")
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prompt_tokens = Column(Integer, default=0, comment="提示 Token")
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completion_tokens = Column(Integer, default=0, comment="生成 Token")
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total_tokens = Column(Integer, default=0, comment="总 Token")
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elapsed_time = Column(Integer, default=0, comment="耗时（毫秒）")
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error_message = Column(Text, default="", comment="错误信息")
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feedback = Column(String(20), default="", comment="用户反馈（like/dislike）")
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feedback_content = Column(Text, default="", comment="反馈内容")
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__table_args__ = (
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Index("ix_ai_agent_message_conversation_role", "conversation_id", "role"),
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)
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