"""内部评测：按 App 一致路径回放用户轮次（segment + orchestrator + memoir 队列）。"""

from __future__ import annotations

import secrets
import uuid

from sqlalchemy.ext.asyncio import AsyncSession

from app.core.db import utc_now
from app.core.logging import get_logger
from app.core.security import hash_password
from app.features.auth import repo as auth_repo
from app.features.conversation.models import Conversation
from app.features.conversation.service import ConversationService
from app.features.conversation.ws.pipeline import (
    background_runner,
    process_user_message,
)
from app.features.evaluation.errors import (
    EvaluationBadRequestError,
    EvaluationNotFoundError,
)
from app.features.evaluation.user_export_fixtures import read_user_export_fixture
from app.features.quota.service import QuotaService
from app.features.user.models import User

logger = get_logger(__name__)


class ReplayConversationService:
    def __init__(self, db: AsyncSession, quota_service: QuotaService) -> None:
        self._db = db
        self._quota = quota_service

    async def create_eval_sandbox(self) -> tuple[str, str, str, str]:
        """新建仅用于评测的临时用户（唯一伪手机号）+ 新会话。"""
        user_id = str(uuid.uuid4())
        phone: str | None = None
        for _ in range(8):
            candidate = f"eval_{secrets.token_hex(10)}"
            existing = await auth_repo.get_user_by_phone(candidate, self._db)
            if not existing:
                phone = candidate
                break
        if not phone:
            raise EvaluationBadRequestError("could not allocate eval phone")

        user = User(
            id=user_id,
            phone=phone,
            password_hash=hash_password(secrets.token_urlsafe(24)),
            nickname="评测临时用户",
            subscription_type="free",
            created_at=utc_now(),
        )
        await auth_repo.create_user(user, self._db)
        await self._db.commit()
        await self._db.refresh(user)

        conversation_id = str(uuid.uuid4())
        conv_service = ConversationService(self._db, self._quota)
        conv, err = await conv_service.ensure_ws_connection(conversation_id, user_id)
        if err or not conv:
            raise EvaluationBadRequestError(err or "failed to create conversation")

        logger.info(
            "eval sandbox user_id={} phone={} conversation_id={}",
            user_id,
            phone,
            conversation_id,
        )
        return user_id, conversation_id, phone, user.nickname

    async def bootstrap_conversation(self, user_id: str) -> str:
        uid = (user_id or "").strip()
        if not uid:
            raise EvaluationBadRequestError("user_id is required")
        user = await self._db.get(User, uid)
        if not user:
            raise EvaluationBadRequestError("user not found")
        conversation_id = str(uuid.uuid4())
        conv_service = ConversationService(self._db, self._quota)
        conv, err = await conv_service.ensure_ws_connection(conversation_id, uid)
        if err or not conv:
            raise EvaluationBadRequestError(err or "failed to create conversation")
        logger.info(
            "eval replay bootstrap conversation_id={} user_id={}",
            conversation_id,
            uid,
        )
        return conversation_id

    async def replay_fixture(
        self,
        *,
        conversation_id: str,
        fixture_filename: str,
        flush_memoir_after: bool,
        skip_tts: bool,
    ) -> tuple[int, list[str], list[str]]:
        try:
            turns, _ = read_user_export_fixture(fixture_filename)
        except ValueError as e:
            raise EvaluationBadRequestError(str(e)) from e
        except FileNotFoundError:
            raise EvaluationNotFoundError("fixture not found") from None
        utterances = [u.strip() for u, _ in turns if (u or "").strip()]
        if not utterances:
            raise EvaluationBadRequestError("fixture produced no user utterances")
        n, segment_ids = await self.replay_utterances(
            conversation_id=conversation_id,
            utterances=utterances,
            flush_memoir_after=flush_memoir_after,
            skip_tts=skip_tts,
        )
        return n, utterances, segment_ids

    async def replay_utterances(
        self,
        *,
        conversation_id: str,
        utterances: list[str],
        flush_memoir_after: bool,
        skip_tts: bool,
    ) -> tuple[int, list[str]]:
        cid = (conversation_id or "").strip()
        if not cid:
            raise EvaluationBadRequestError("conversation_id is required")
        conv = await self._db.get(Conversation, cid)
        if not conv or conv.deleted_at is not None:
            raise EvaluationNotFoundError("conversation not found")
        user = await self._db.get(User, conv.user_id)
        if not user:
            raise EvaluationBadRequestError("user not found for conversation")

        conv_service = ConversationService(self._db, self._quota)
        count = 0
        segment_ids: list[str] = []
        for raw in utterances:
            text = (raw or "").strip()
            if not text:
                continue
            segment = await conv_service.create_user_segment(conv, conv.user_id, text)
            segment_ids.append(segment.id)
            ts = segment.created_at or conv.last_message_at
            await background_runner.queue_message(
                conv.user_id,
                segment.id,
                text_char_count=len(text),
            )
            await process_user_message(
                conversation_id=cid,
                user_message=text,
                conversation=conv,
                segment=segment,
                db=self._db,
                user=user,
                user_message_timestamp=ts,
                force_skip_tts=skip_tts,
            )
            count += 1

        if flush_memoir_after and conv.user_id:
            await background_runner.flush_pending(conv.user_id)

        logger.info(
            "eval replay done conversation_id={} turns={} flush={} skip_tts={}",
            cid,
            count,
            flush_memoir_after,
            skip_tts,
        )
        return count, segment_ids