"""DistributedWorker — task lifecycle management and backend routing.

Routes delegated tasks to appropriate execution backends:

- agentic_loop: local multi-step execution via Timmy's agentic loop
- kimi: heavy research tasks dispatched via Gitea kimi-ready issues
- paperclip: task submission to the Paperclip API

Task lifecycle: queued → running → completed | failed

Failure handling: auto-retry up to MAX_RETRIES, then mark failed.
"""

from __future__ import annotations

import asyncio
import logging
import threading
import uuid
from dataclasses import dataclass, field
from datetime import UTC, datetime
from typing import Any, ClassVar

logger = logging.getLogger(__name__)

MAX_RETRIES = 2


# ---------------------------------------------------------------------------
# Task record
# ---------------------------------------------------------------------------


@dataclass
class DelegatedTask:
    """Record of one delegated task and its execution state."""

    task_id: str
    agent_name: str
    agent_role: str
    task_description: str
    priority: str
    backend: str  # "agentic_loop" | "kimi" | "paperclip"
    status: str = "queued"  # queued | running | completed | failed
    created_at: str = field(default_factory=lambda: datetime.now(UTC).isoformat())
    result: dict[str, Any] | None = None
    error: str | None = None
    retries: int = 0


# ---------------------------------------------------------------------------
# Worker
# ---------------------------------------------------------------------------


class DistributedWorker:
    """Routes and tracks delegated task execution across multiple backends.

    All methods are class-methods; DistributedWorker is a singleton-style
    service — no instantiation needed.

    Usage::

        from brain.worker import DistributedWorker

        task_id = DistributedWorker.submit("researcher", "research", "summarise X")
        status  = DistributedWorker.get_status(task_id)
    """

    _tasks: ClassVar[dict[str, DelegatedTask]] = {}
    _lock: ClassVar[threading.Lock] = threading.Lock()

    @classmethod
    def submit(
        cls,
        agent_name: str,
        agent_role: str,
        task_description: str,
        priority: str = "normal",
    ) -> str:
        """Submit a task for execution. Returns task_id immediately.

        The task is registered as 'queued' and a daemon thread begins
        execution in the background. Use get_status(task_id) to poll.
        """
        task_id = uuid.uuid4().hex[:8]
        backend = cls._select_backend(agent_role, task_description)

        record = DelegatedTask(
            task_id=task_id,
            agent_name=agent_name,
            agent_role=agent_role,
            task_description=task_description,
            priority=priority,
            backend=backend,
        )

        with cls._lock:
            cls._tasks[task_id] = record

        thread = threading.Thread(
            target=cls._run_task,
            args=(record,),
            daemon=True,
            name=f"worker-{task_id}",
        )
        thread.start()

        logger.info(
            "Task %s queued: %s → %.60s (backend=%s, priority=%s)",
            task_id,
            agent_name,
            task_description,
            backend,
            priority,
        )
        return task_id

    @classmethod
    def get_status(cls, task_id: str) -> dict[str, Any]:
        """Return current status of a task by ID."""
        record = cls._tasks.get(task_id)
        if record is None:
            return {"found": False, "task_id": task_id}
        return {
            "found": True,
            "task_id": record.task_id,
            "agent": record.agent_name,
            "role": record.agent_role,
            "status": record.status,
            "backend": record.backend,
            "priority": record.priority,
            "created_at": record.created_at,
            "retries": record.retries,
            "result": record.result,
            "error": record.error,
        }

    @classmethod
    def list_tasks(cls) -> list[dict[str, Any]]:
        """Return a summary list of all tracked tasks."""
        with cls._lock:
            return [
                {
                    "task_id": t.task_id,
                    "agent": t.agent_name,
                    "status": t.status,
                    "backend": t.backend,
                    "created_at": t.created_at,
                }
                for t in cls._tasks.values()
            ]

    @classmethod
    def clear(cls) -> None:
        """Clear the task registry (for tests)."""
        with cls._lock:
            cls._tasks.clear()

    # ------------------------------------------------------------------
    # Backend selection
    # ------------------------------------------------------------------

    @classmethod
    def _select_backend(cls, agent_role: str, task_description: str) -> str:
        """Choose the execution backend for a given agent role and task.

        Priority:
        1. kimi  — research role + Gitea enabled + task exceeds local capacity
        2. paperclip — paperclip API key is configured
        3. agentic_loop — local fallback (always available)
        """
        try:
            from config import settings
            from timmy.kimi_delegation import exceeds_local_capacity

            if (
                agent_role == "research"
                and getattr(settings, "gitea_enabled", False)
                and getattr(settings, "gitea_token", "")
                and exceeds_local_capacity(task_description)
            ):
                return "kimi"

            if getattr(settings, "paperclip_api_key", ""):
                return "paperclip"

        except Exception as exc:
            logger.debug("Backend selection error — defaulting to agentic_loop: %s", exc)

        return "agentic_loop"

    # ------------------------------------------------------------------
    # Task execution
    # ------------------------------------------------------------------

    @classmethod
    def _run_task(cls, record: DelegatedTask) -> None:
        """Execute a task with retry logic. Runs inside a daemon thread."""
        record.status = "running"

        for attempt in range(MAX_RETRIES + 1):
            try:
                if attempt > 0:
                    logger.info(
                        "Retrying task %s (attempt %d/%d)",
                        record.task_id,
                        attempt + 1,
                        MAX_RETRIES + 1,
                    )
                    record.retries = attempt

                result = cls._dispatch(record)
                record.status = "completed"
                record.result = result
                logger.info(
                    "Task %s completed via %s",
                    record.task_id,
                    record.backend,
                )
                return

            except Exception as exc:
                logger.warning(
                    "Task %s attempt %d failed: %s",
                    record.task_id,
                    attempt + 1,
                    exc,
                )
                if attempt == MAX_RETRIES:
                    record.status = "failed"
                    record.error = str(exc)
                    logger.error(
                        "Task %s exhausted %d retries. Final error: %s",
                        record.task_id,
                        MAX_RETRIES,
                        exc,
                    )

    @classmethod
    def _dispatch(cls, record: DelegatedTask) -> dict[str, Any]:
        """Route to the selected backend. Raises on failure."""
        if record.backend == "kimi":
            return asyncio.run(cls._execute_kimi(record))
        if record.backend == "paperclip":
            return asyncio.run(cls._execute_paperclip(record))
        return asyncio.run(cls._execute_agentic_loop(record))

    @classmethod
    async def _execute_kimi(cls, record: DelegatedTask) -> dict[str, Any]:
        """Create a kimi-ready Gitea issue for the task.

        Kimi picks up the issue via the kimi-ready label and executes it.
        """
        from timmy.kimi_delegation import create_kimi_research_issue

        result = await create_kimi_research_issue(
            task=record.task_description[:120],
            context=f"Delegated by agent '{record.agent_name}' via delegate_task.",
            question=record.task_description,
            priority=record.priority,
        )
        if not result.get("success"):
            raise RuntimeError(f"Kimi issue creation failed: {result.get('error')}")
        return result

    @classmethod
    async def _execute_paperclip(cls, record: DelegatedTask) -> dict[str, Any]:
        """Submit the task to the Paperclip API."""
        import httpx

        from timmy.paperclip import PaperclipClient

        client = PaperclipClient()
        async with httpx.AsyncClient(timeout=client.timeout) as http:
            resp = await http.post(
                f"{client.base_url}/api/tasks",
                headers={"Authorization": f"Bearer {client.api_key}"},
                json={
                    "kind": record.agent_role,
                    "agent_id": client.agent_id,
                    "company_id": client.company_id,
                    "priority": record.priority,
                    "context": {"task": record.task_description},
                },
            )

        if resp.status_code in (200, 201):
            data = resp.json()
            logger.info(
                "Task %s submitted to Paperclip (paperclip_id=%s)",
                record.task_id,
                data.get("id"),
            )
            return {
                "success": True,
                "paperclip_task_id": data.get("id"),
                "backend": "paperclip",
            }
        raise RuntimeError(f"Paperclip API error {resp.status_code}: {resp.text[:200]}")

    @classmethod
    async def _execute_agentic_loop(cls, record: DelegatedTask) -> dict[str, Any]:
        """Execute the task via Timmy's local agentic loop."""
        from timmy.agentic_loop import run_agentic_loop

        result = await run_agentic_loop(record.task_description)
        return {
            "success": result.status != "failed",
            "agentic_task_id": result.task_id,
            "summary": result.summary,
            "status": result.status,
            "backend": "agentic_loop",
        }