"""Persistence models for the standalone position-collaboration workspace.

This deliberately does **not** reuse ``roundtable_drafts`` or
``roundtable_jobs``. A session captures the selected business chain and the
confirmed task intent; every chain seat then has one durable node record.
LangGraph threads remain the execution source, while these tables also retain
database-owned recovery copies of conversations and text deliverables so the
workspace survives replacement of container-local checkpoint/output volumes.
"""

from __future__ import annotations

from datetime import UTC, datetime

from sqlalchemy import ForeignKey, Integer, String, UniqueConstraint
from sqlalchemy.orm import Mapped, mapped_column

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


class PositionRoundtableSessionRow(Base):
    __tablename__ = "position_roundtable_sessions"

    id: Mapped[str] = mapped_column(String(64), primary_key=True)
    # Phase one uses normal account isolation. A future membership / role ACL
    # can be added without changing the session or thread identifiers.
    user_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
    external_task_id: Mapped[str | None] = mapped_column(String(128), nullable=True, index=True)
    task_snapshot: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    chain_id: Mapped[str | None] = mapped_column(String(64), nullable=True, index=True)
    chain_snapshot: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    intent_thread_id: Mapped[str | None] = mapped_column(String(128), nullable=True)
    intent_snapshot: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    # Database-owned recovery copy for the complete Step-1 conversation.  The
    # normal LangGraph checkpoint remains the execution source, while this
    # snapshot lets the position workspace recover after a checkpoint volume
    # or container-local store has been replaced.
    intent_conversation: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    # The two built-in closing agents own normal LangGraph threads too.  Keep
    # their ids on the position session so a refresh can continue the same
    # report/planning dialogue instead of silently starting a fresh context.
    summary_thread_id: Mapped[str | None] = mapped_column(String(128), nullable=True)
    summary_snapshot: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    summary_conversation: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    action_plan_thread_id: Mapped[str | None] = mapped_column(String(128), nullable=True)
    action_plan_snapshot: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    action_plan_conversation: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    # intent_pending -> active -> completed / archived. The router owns legal
    # transitions; the DB keeps it as a concise, portable string.
    status: Mapped[str] = mapped_column(String(32), nullable=False, default="intent_pending", index=True)
    created_at: Mapped[datetime] = mapped_column(
        BeijingDateTime(), nullable=False, default=lambda: datetime.now(UTC)
    )
    updated_at: Mapped[datetime] = mapped_column(
        BeijingDateTime(),
        nullable=False,
        default=lambda: datetime.now(UTC),
        onupdate=lambda: datetime.now(UTC),
    )


class PositionRoundtableNodeRow(Base):
    __tablename__ = "position_roundtable_nodes"
    __table_args__ = (
        UniqueConstraint("session_id", "node_key", name="uq_position_roundtable_nodes_session_key"),
    )

    id: Mapped[str] = mapped_column(String(64), primary_key=True)
    session_id: Mapped[str] = mapped_column(
        String(64),
        ForeignKey("position_roundtable_sessions.id", ondelete="CASCADE"),
        nullable=False,
        index=True,
    )
    # Stable inside one frozen chain snapshot; e.g. ``stage-1-seat-2-agent``.
    node_key: Mapped[str] = mapped_column(String(256), nullable=False)
    stage_index: Mapped[int] = mapped_column(Integer, nullable=False)
    seat_index: Mapped[int] = mapped_column(Integer, nullable=False)
    agent_id: Mapped[str] = mapped_column(String(128), nullable=False, index=True)
    position_id: Mapped[str | None] = mapped_column(String(64), nullable=True, index=True)
    # The LangGraph/checkpoint store remains the execution source for messages.
    thread_id: Mapped[str | None] = mapped_column(String(128), nullable=True, unique=True)
    # locked / ready / running / done / stale / rejected / error
    status: Mapped[str] = mapped_column(String(32), nullable=False, default="locked", index=True)
    latest_answer: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    artifact_manifest: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    # A complete, JSON-serialisable copy of the node chat plus its composer
    # draft.  It is intentionally colocated with the node so deleting a
    # position Session removes every recovery snapshot through the FK cascade.
    conversation_snapshot: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    revision: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
    upstream_revision: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    rejection_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0, server_default="0")
    last_rejection: Mapped[str | None] = mapped_column(PortableLongText, nullable=True)
    invalidated_by: Mapped[str | None] = mapped_column(String(256), nullable=True)
    created_at: Mapped[datetime] = mapped_column(
        BeijingDateTime(), nullable=False, default=lambda: datetime.now(UTC)
    )
    updated_at: Mapped[datetime] = mapped_column(
        BeijingDateTime(),
        nullable=False,
        default=lambda: datetime.now(UTC),
        onupdate=lambda: datetime.now(UTC),
    )