"""Workflow-aware render dispatch service.

C2: extends the legacy dispatch_render path with WorkflowDefinition support.

If an OutputType has workflow_definition_id set:
  - Loads the WorkflowDefinition
  - Calls dispatch_workflow() to build + submit a Celery Canvas
  - Creates a WorkflowRun record tracking the submission

If no workflow_definition_id is set, falls back to the existing direct
task-dispatch logic in app.services.render_dispatcher (legacy path).
"""
from __future__ import annotations

import logging

logger = logging.getLogger(__name__)


def dispatch_render_with_workflow(order_line_id: str) -> dict:
    """Dispatch a render for the given order line.

    Checks whether the associated OutputType has a WorkflowDefinition linked.
    If yes, uses the Celery Canvas workflow builder.
    If no, falls back to the legacy direct-dispatch logic.

    This function is synchronous (Celery-task-safe).
    """
    from sqlalchemy import create_engine, select
    from sqlalchemy.orm import Session, selectinload

    from app.config import settings
    from app.domains.orders.models import OrderLine
    from app.domains.rendering.models import OutputType, WorkflowDefinition
    from app.domains.rendering.workflow_config_utils import (
        extract_runtime_workflow,
        get_workflow_execution_mode,
    )
    from app.domains.rendering.workflow_executor import prepare_workflow_context
    from app.domains.rendering.workflow_graph_runtime import (
        execute_graph_workflow,
        find_unsupported_graph_nodes,
    )
    from app.domains.rendering.workflow_run_service import create_workflow_run, mark_workflow_run_failed

    engine = create_engine(
        settings.database_url.replace("+asyncpg", ""),
        pool_pre_ping=True,
    )

    with Session(engine) as session:
        # Load order line with its output_type
        line = session.execute(
            select(OrderLine)
            .where(OrderLine.id == order_line_id)
            .options(selectinload(OrderLine.output_type))
        ).scalar_one_or_none()

        if not line:
            raise ValueError(f"OrderLine {order_line_id} not found")

        output_type: OutputType | None = line.output_type

        if output_type is None or output_type.workflow_definition_id is None:
            # Legacy path — no workflow definition linked
            logger.info(
                "order_line %s: no workflow_definition_id, using legacy dispatch",
                order_line_id,
            )
            return _legacy_dispatch(order_line_id)

        # Load the linked WorkflowDefinition
        wf_def: WorkflowDefinition | None = session.execute(
            select(WorkflowDefinition).where(
                WorkflowDefinition.id == output_type.workflow_definition_id,
                WorkflowDefinition.is_active.is_(True),
            )
        ).scalar_one_or_none()

        if wf_def is None:
            logger.warning(
                "order_line %s: workflow_definition_id %s not found or inactive, "
                "falling back to legacy dispatch",
                order_line_id,
                output_type.workflow_definition_id,
            )
            return _legacy_dispatch(order_line_id)

        execution_mode = get_workflow_execution_mode(wf_def.config, default="legacy")

        if execution_mode == "graph":
            try:
                workflow_context = prepare_workflow_context(
                    wf_def.config,
                    context_id=order_line_id,
                    execution_mode="graph",
                )
            except Exception as exc:
                logger.warning(
                    "order_line %s: workflow_definition_id %s failed graph runtime preparation (%s), "
                    "falling back to legacy dispatch",
                    order_line_id,
                    wf_def.id,
                    exc,
                )
                return _legacy_dispatch(order_line_id)

            unsupported_nodes = find_unsupported_graph_nodes(workflow_context)
            if unsupported_nodes:
                logger.warning(
                    "order_line %s: workflow_definition_id %s contains graph-unsupported nodes %s, "
                    "falling back to legacy dispatch",
                    order_line_id,
                    wf_def.id,
                    unsupported_nodes,
                )
                return _legacy_dispatch(order_line_id)

            run = None
            try:
                run = create_workflow_run(
                    session,
                    workflow_def_id=wf_def.id,
                    order_line_id=line.id,
                    workflow_context=workflow_context,
                )
                session.commit()
            except Exception as exc:
                session.rollback()
                logger.warning(
                    "order_line %s: failed to create graph workflow run for workflow_definition_id %s (%s), "
                    "falling back to legacy dispatch",
                    order_line_id,
                    wf_def.id,
                    exc,
                )
                return _legacy_dispatch(order_line_id)

            try:
                dispatch_result = execute_graph_workflow(session, workflow_context)
                session.commit()
            except Exception as exc:
                if run is not None:
                    mark_workflow_run_failed(run, str(exc))
                    session.commit()
                logger.exception(
                    "order_line %s: graph workflow execution via definition %s failed, falling back to legacy dispatch",
                    order_line_id,
                    wf_def.id,
                )
                fallback_result = _legacy_dispatch(order_line_id)
                fallback_result["fallback_from"] = "workflow_graph"
                if run is not None:
                    fallback_result["workflow_run_id"] = str(run.id)
                return fallback_result

            return {
                "backend": "workflow_graph",
                "execution_mode": "graph",
                "workflow_run_id": str(run.id),
                "celery_task_id": dispatch_result.task_ids[0] if dispatch_result.task_ids else None,
                "task_ids": dispatch_result.task_ids,
            }

        if execution_mode == "shadow":
            logger.warning(
                "order_line %s: workflow_definition_id %s requested shadow mode, "
                "falling back to legacy dispatch until duplicate-safe shadow execution exists",
                order_line_id,
                wf_def.id,
            )
            return _legacy_dispatch(order_line_id)

        workflow_type, params = extract_runtime_workflow(wf_def.config)
        if workflow_type is None or workflow_type == "custom":
            logger.warning(
                "order_line %s: workflow_definition_id %s has no supported preset runtime, "
                "falling back to legacy dispatch",
                order_line_id,
                wf_def.id,
            )
            return _legacy_dispatch(order_line_id)

        logger.info(
            "order_line %s: dispatching via WorkflowDefinition %s (type=%s)",
            order_line_id,
            wf_def.id,
            workflow_type,
        )

        try:
            workflow_context = prepare_workflow_context(
                wf_def.config,
                context_id=order_line_id,
                execution_mode="legacy",
            )
        except Exception as exc:
            logger.warning(
                "order_line %s: workflow_definition_id %s failed runtime preparation (%s), "
                "falling back to legacy dispatch",
                order_line_id,
                wf_def.id,
                exc,
            )
            return _legacy_dispatch(order_line_id)

        # For turntable workflows: resolve step_path + output_dir from the order line at runtime
        if workflow_type == "turntable" and ("step_path" not in params or "output_dir" not in params):
            from app.domains.products.models import CadFile as _CadFile
            from pathlib import Path as _Path
            from app.config import settings as _cfg
            _product = line.product if hasattr(line, "product") else None
            if _product is None:
                from sqlalchemy.orm import selectinload as _si
                from app.domains.orders.models import OrderLine as _OL
                _line_full = session.execute(
                    select(_OL).where(_OL.id == line.id).options(_si(_OL.product))
                ).scalar_one_or_none()
                _product = _line_full.product if _line_full else None
            if _product and _product.cad_file_id:
                _cad = session.execute(
                    select(_CadFile).where(_CadFile.id == _product.cad_file_id)
                ).scalar_one_or_none()
                if _cad and _cad.stored_path:
                    params.setdefault("step_path", _cad.stored_path)
                    params.setdefault(
                        "output_dir",
                        str(_Path(_cfg.upload_dir) / "renders" / str(line.id)),
                    )

        run = None
        try:
            run = create_workflow_run(
                session,
                workflow_def_id=wf_def.id,
                order_line_id=line.id,
                workflow_context=workflow_context,
            )
            session.commit()
        except Exception as exc:
            session.rollback()
            logger.warning(
                "order_line %s: failed to create workflow run for workflow_definition_id %s (%s), "
                "falling back to legacy dispatch",
                order_line_id,
                wf_def.id,
                exc,
            )
            return _legacy_dispatch(order_line_id)

        from app.domains.rendering.workflow_builder import dispatch_workflow

        try:
            celery_task_id = dispatch_workflow(workflow_type, order_line_id, params)
            run.celery_task_id = celery_task_id
            session.commit()
        except Exception as exc:
            session.rollback()
            session.add(run)
            mark_workflow_run_failed(run, str(exc))
            session.commit()
            logger.exception(
                "order_line %s: workflow dispatch via definition %s failed, falling back to legacy dispatch",
                order_line_id,
                wf_def.id,
            )
            return _legacy_dispatch(order_line_id)

        return {
            "backend": "workflow",
            "workflow_type": workflow_type,
            "execution_mode": "legacy",
            "workflow_run_id": str(run.id),
            "celery_task_id": celery_task_id,
        }


def _legacy_dispatch(order_line_id: str) -> dict:
    """Queue render_order_line_task (the working Celery render implementation)."""
    from app.tasks.step_tasks import render_order_line_task
    render_order_line_task.delay(order_line_id)
    return {"backend": "celery", "queued": True}