"""ORM model for thread metadata."""

from __future__ import annotations

from datetime import UTC, datetime

from sqlalchemy import Index, String
from sqlalchemy.orm import Mapped, mapped_column

from deerflow.persistence.base import Base
from deerflow.persistence.types import BeijingDateTime, PortableJSON


class ThreadMetaRow(Base):
    __tablename__ = "threads_meta"
    __table_args__ = (
        Index("ix_threads_meta_created_user", "created_at", "user_id"),
        Index("ix_threads_meta_user_created", "user_id", "created_at"),
        # Task deep-link history is globally shared and therefore cannot use
        # the normal ``user_id`` scope.  Keep its high-cardinality lookup
        # fields out of ``metadata_json`` so task entry never has to scan and
        # Python-filter every thread in the installation.
        Index("ix_threads_meta_task_agent_updated", "task_id", "agent_id", "updated_at", "thread_id"),
        Index("ix_threads_meta_task_action_agent_updated", "task_id", "action_id", "agent_id", "updated_at", "thread_id"),
        # The ordinary recent-chat path has an owner filter and the same
        # updated-at ordering.  This prevents a full table sort there too.
        Index("ix_threads_meta_user_updated", "user_id", "updated_at", "thread_id"),
    )

    thread_id: Mapped[str] = mapped_column(String(64), primary_key=True)
    assistant_id: Mapped[str | None] = mapped_column(String(128), index=True)
    user_id: Mapped[str | None] = mapped_column(String(64), index=True)
    # Indexed projections of the corresponding metadata values.  The JSON
    # blob remains authoritative and supports arbitrary metadata filters;
    # these columns exist solely for the task-workspace hot path.
    task_id: Mapped[str | None] = mapped_column(String(128), nullable=True)
    agent_id: Mapped[str | None] = mapped_column(String(128), nullable=True)
    action_id: Mapped[str | None] = mapped_column(String(128), nullable=True)
    display_name: Mapped[str | None] = mapped_column(String(256))
    status: Mapped[str] = mapped_column(String(20), default="idle")
    metadata_json: Mapped[dict] = mapped_column(PortableJSON(), default=dict)
    created_at: Mapped[datetime] = mapped_column(BeijingDateTime(), default=lambda: datetime.now(UTC))
    updated_at: Mapped[datetime] = mapped_column(BeijingDateTime(), default=lambda: datetime.now(UTC), onupdate=lambda: datetime.now(UTC))