mirror of
https://github.com/bytedance/deer-flow.git
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rayhpeng
e3179cd54d
Phase 2-B: run persistence + event storage + token tracking. - ORM models: RunRow (with token fields), ThreadMetaRow, RunEventRow - RunRepository implements RunStore ABC via SQLAlchemy ORM - ThreadMetaRepository with owner access control - DbRunEventStore with trace content truncation and cursor pagination - JsonlRunEventStore with per-run files and seq recovery from disk - RunJournal (BaseCallbackHandler) captures LLM/tool/lifecycle events, accumulates token usage by caller type, buffers and flushes to store - RunManager now accepts optional RunStore for persistent backing - Worker creates RunJournal, writes human_message, injects callbacks - Gateway deps use factory functions (RunRepository when DB available) - New endpoints: messages, run messages, run events, token-usage - ThreadCreateRequest gains assistant_id field - 92 tests pass (33 new), zero regressions Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
24 lines
934 B
Python
24 lines
934 B
Python
"""ORM model for thread metadata."""
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from __future__ import annotations
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from datetime import UTC, datetime
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from sqlalchemy import JSON, String
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from sqlalchemy.orm import Mapped, mapped_column
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from deerflow.persistence.base import Base
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class ThreadMetaRow(Base):
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__tablename__ = "threads_meta"
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thread_id: Mapped[str] = mapped_column(String(64), primary_key=True)
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assistant_id: Mapped[str | None] = mapped_column(String(128), index=True)
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owner_id: Mapped[str | None] = mapped_column(String(64), index=True)
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display_name: Mapped[str | None] = mapped_column(String(256))
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status: Mapped[str] = mapped_column(String(20), default="idle")
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metadata_json: Mapped[dict] = mapped_column(JSON, default=dict)
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created_at: Mapped[datetime] = mapped_column(default=lambda: datetime.now(UTC))
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updated_at: Mapped[datetime] = mapped_column(default=lambda: datetime.now(UTC), onupdate=lambda: datetime.now(UTC))
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