"""
Story 写入提交后的统一异步调度：插图、章节物化、可选 memory compaction。

enqueue 失败不回滚已提交数据，仅记录日志；依赖后续触发或重试收敛。
"""

from __future__ import annotations

from dataclasses import dataclass, field
from datetime import datetime, timezone
import threading
from typing import Any, cast

import redis

from app.core.config import settings
from app.core.logging import get_logger
from app.core.memory_compaction_schedule import schedule_memory_compaction_run

logger = get_logger(__name__)
_redis_client: redis.Redis | None = None
_redis_lock = threading.Lock()


def _story_image_enqueue_key(story_id: str) -> str:
    return f"enqueue:story-image:{story_id}"


def _get_redis() -> redis.Redis:
    """进程内复用单个 Redis 客户端，避免重复创建连接池。"""
    global _redis_client
    if _redis_client is None:
        with _redis_lock:
            if _redis_client is None:
                _redis_client = redis.from_url(
                    settings.redis_url, decode_responses=True
                )
    return _redis_client


@dataclass
class PostCommitResult:
    enqueued_story_image_count: int = 0
    enqueued_chapter_recompose_count: int = 0
    compaction_scheduled: bool = False
    errors: list[str] = field(default_factory=list)


def enqueue_story_post_commit_effects(
    *,
    user_id: str,
    story_ids: set[str],
    chapter_ids: set[str],
    trigger_source: str,
    need_image: bool = True,
    need_recompose: bool = True,
    need_compaction: bool = False,
    compaction_extra: dict[str, Any] | None = None,
) -> PostCommitResult:
    """
    story_ids 为空则跳过 image；chapter_ids 为空则跳过 recompose。
    need_compaction=True 时仅按 user_id 调度 compaction（不依赖 story/chapter 集合）。
    """
    result = PostCommitResult()
    r = _get_redis()
    ttl = int(settings.story_image_enqueue_dedup_ttl)

    if need_image and story_ids:
        from app.tasks.story_image_tasks import (
            generate_story_image as gen_story_image_task,
        )

        for sid in sorted(story_ids):
            key = _story_image_enqueue_key(sid)
            try:
                if not r.set(key, "1", nx=True, ex=ttl):
                    logger.debug(
                        "story_image enqueue skipped (dedup): story={} trigger={}",
                        sid,
                        trigger_source,
                    )
                    continue
            except Exception as exc:
                logger.warning(
                    "story_image enqueue dedup redis failed, allowing enqueue: "
                    "story={} err={}",
                    sid,
                    exc,
                )
            try:
                cast(Any, gen_story_image_task).delay(sid)
                result.enqueued_story_image_count += 1
            except Exception as exc:
                logger.warning(
                    "generate_story_image.delay failed story={} trigger={}: {}",
                    sid,
                    trigger_source,
                    exc,
                )
                result.errors.append(f"generate_story_image:{sid}:{exc}")
                try:
                    r.delete(key)
                except Exception:
                    pass

    if need_recompose and chapter_ids:
        from app.tasks.chapter_compose_tasks import (
            recompose_chapter as recompose_chapter_task,
        )

        cd = int(settings.recompose_chapter_delay_seconds)
        for cid in sorted(chapter_ids):
            try:
                cast(Any, recompose_chapter_task).apply_async(
                    args=[cid], countdown=max(0, cd)
                )
                result.enqueued_chapter_recompose_count += 1
            except Exception as exc:
                logger.warning(
                    "recompose_chapter.apply_async failed chapter={} trigger={}: {}",
                    cid,
                    trigger_source,
                    exc,
                )
                result.errors.append(f"recompose_chapter:{cid}:{exc}")

    if need_compaction:
        try:
            ctx: dict[str, Any] = {
                "trigger_source": trigger_source,
                "trigger_time": datetime.now(timezone.utc).isoformat(),
                "story_ids": sorted(story_ids),
                "chapter_ids": sorted(chapter_ids),
            }
            if compaction_extra:
                ctx.update(compaction_extra)
            schedule_memory_compaction_run(user_id, ctx)
            result.compaction_scheduled = True
        except Exception as exc:
            logger.warning(
                "schedule_memory_compaction_run failed user_id={} trigger={}: {}",
                user_id,
                trigger_source,
                exc,
            )
            result.errors.append(f"compaction:{exc}")

    return result