wehub-resource-sync
56 lines
2.1 KiB
Python
56 lines
2.1 KiB
Python
"""Thought 模型 — Agent 思考流持久化。
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遵循 Edict Architecture §4 Thought JSON Schema。
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支持 streaming partial thoughts 和 dashboard 实时展示。
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"""
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import uuid
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from datetime import datetime, timezone
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from sqlalchemy import Column, DateTime, Float, Index, Integer, String, Text, Boolean
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from sqlalchemy.dialects.postgresql import UUID
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from ..db import Base
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class Thought(Base):
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"""Agent 思考记录。"""
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__tablename__ = "thoughts"
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thought_id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
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trace_id = Column(String(32), nullable=False, index=True, comment="关联任务ID")
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agent = Column(String(32), nullable=False, index=True, comment="Agent 标识")
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step = Column(Integer, nullable=False, default=0, comment="思考步骤序号")
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type = Column(
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String(32),
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nullable=False,
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default="reasoning",
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comment="思考类型: reasoning|query|action_intent|summary",
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)
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source = Column(String(16), default="llm", comment="来源: llm|tool|human")
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content = Column(Text, nullable=False, default="", comment="思考内容")
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tokens = Column(Integer, default=0, comment="消耗 token 数")
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confidence = Column(Float, default=0.0, comment="置信度 0-1")
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sensitive = Column(Boolean, default=False, comment="是否敏感内容")
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timestamp = Column(DateTime(timezone=True), default=lambda: datetime.now(timezone.utc), nullable=False)
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__table_args__ = (
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Index("ix_thoughts_trace_agent", "trace_id", "agent"),
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Index("ix_thoughts_timestamp", "timestamp"),
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)
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def to_dict(self) -> dict:
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return {
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"thought_id": str(self.thought_id),
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"trace_id": self.trace_id,
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"agent": self.agent,
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"step": self.step,
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"type": self.type,
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"source": self.source,
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"content": self.content,
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"tokens": self.tokens,
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"confidence": self.confidence,
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"sensitive": self.sensitive,
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"timestamp": self.timestamp.isoformat() if self.timestamp else "",
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}
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