# pyright: reportImportCycles=false
# Lazy (function-local) imports still count as static edges in basedpyright's
# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
# import cycles. Breaking them would require an architectural refactor.
import asyncio
import copy
import logging
import os
import time
from collections import OrderedDict
from typing import Any, Optional, Dict, Tuple, List, Sequence, cast
from .connectivity_guard import (
    OFFLINE_FRIENDLY_MESSAGE,
    is_expected_offline_error,
    is_offline_cooldown_error,
)
from .model_metadata_provider import (
    CivitaiModelMetadataProvider,
    ModelMetadataProviderManager,
)
from .downloader import get_downloader
from .errors import RateLimitError, ResourceNotFoundError
from ..utils.civitai_utils import resolve_license_payload

logger = logging.getLogger(__name__)

# Best-effort cache for creator model counts, keyed by lowercase username.
# Values are (monotonic timestamp, count or None); None results are cached
# too so repeated failures don't hammer the API.
_CREATOR_COUNT_CACHE_TTL_SECONDS = 600
_creator_model_count_cache: Dict[str, Tuple[float, Optional[int]]] = {}


class CivitaiClient:
    _instance = None
    _lock = asyncio.Lock()

    @classmethod
    async def get_instance(cls):
        """Get singleton instance of CivitaiClient"""
        async with cls._lock:
            if cls._instance is None:
                cls._instance = cls()

                # Register this client as a metadata provider
                provider_manager = await ModelMetadataProviderManager.get_instance()
                provider_manager.register_provider(
                    "civitai", CivitaiModelMetadataProvider(cls._instance), True
                )

            return cls._instance

    def __init__(self):
        # Check if already initialized for singleton pattern
        if hasattr(self, "_initialized"):
            return
        self._initialized = True

        self.base_url = "https://civitai.red/api/v1"
        # In-memory cache to avoid redundant get_model_version_info calls
        # within the same import/scan flow. Only successful results are cached.
        # Uses OrderedDict with LRU eviction at MAX_CACHE_ENTRIES to prevent
        # unbounded growth in long-running server processes.
        self._version_info_cache: OrderedDict[
            str, Tuple[Optional[Dict[str, Any]], Optional[str]]
        ] = OrderedDict()
        self._MAX_CACHE_ENTRIES = 500

    def _build_image_info_url(self, image_id: str) -> str:
        return f"{self.base_url}/images?imageId={image_id}&nsfw=X&withMeta=true"

    async def _make_request(
        self,
        method: str,
        url: str,
        *,
        use_auth: bool = False,
        **kwargs,
    ) -> Tuple[bool, Dict[str, Any] | str]:
        """Wrapper around downloader.make_request that surfaces rate limits,
        with retry for transient server errors (5xx, Cloudflare 524, network flakiness)."""

        max_retries = 3
        for attempt in range(max_retries):
            downloader = await get_downloader()
            success, result = await downloader.make_request(
                method,
                url,
                use_auth=use_auth,
                **kwargs,
            )
            if success:
                # RateLimitError is raised below; a successful result is dict or str.
                return True, cast(Dict[str, Any] | str, result)

            if isinstance(result, RateLimitError):
                if result.provider is None:
                    result.provider = "civitai_api"
                raise result

            if is_offline_cooldown_error(result):
                return False, OFFLINE_FRIENDLY_MESSAGE

            # Transient server error — retry with exponential backoff
            if self._is_transient_server_error(str(result)):
                if attempt < max_retries - 1:
                    wait = 2**attempt  # 1s, 2s, 4s
                    logger.info(
                        "Transient error on %s %s, retrying in %ds "
                        "(attempt %d/%d): %s",
                        method,
                        url,
                        wait,
                        attempt + 1,
                        max_retries,
                        result,
                    )
                    await asyncio.sleep(wait)
                    continue
                logger.warning(
                    "All %d retries exhausted for %s %s: %s",
                    max_retries,
                    method,
                    url,
                    result,
                )
                return False, result

            return False, result

        return False, "Unexpected error in _make_request"

    @staticmethod
    def _remove_comfy_metadata(model_version: Optional[Dict[str, Any]]) -> None:
        """Remove Comfy-specific metadata from model version images."""
        if not isinstance(model_version, dict):
            return

        images = model_version.get("images")
        if not isinstance(images, list):
            return

        for image in images:
            if not isinstance(image, dict):
                continue

            meta = image.get("meta")
            if isinstance(meta, dict) and "comfy" in meta:
                meta.pop("comfy", None)

    async def download_file(
        self, url: str, save_dir: str, default_filename: str, progress_callback=None
    ) -> Tuple[bool, str]:
        """Download file with resumable downloads and retry mechanism

        Args:
            url: Download URL
            save_dir: Directory to save the file
            default_filename: Fallback filename if none provided in headers
            progress_callback: Optional async callback function for progress updates (0-100)

        Returns:
            Tuple[bool, str]: (success, save_path or error message)
        """
        downloader = await get_downloader()
        save_path = os.path.join(save_dir, default_filename)

        # Use unified downloader with CivitAI authentication
        success, result = await downloader.download_file(
            url=url,
            save_path=save_path,
            progress_callback=progress_callback,
            use_auth=True,  # Enable CivitAI authentication
            allow_resume=True,
        )

        return success, result

    async def get_model_by_hash(
        self, model_hash: str
    ) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
        try:
            success, version = await self._make_request(
                "GET",
                f"{self.base_url}/model-versions/by-hash/{model_hash}",
                use_auth=True,
            )
            if not success:
                message = str(version)
                if is_expected_offline_error(message):
                    return None, OFFLINE_FRIENDLY_MESSAGE
                if "not found" in message.lower():
                    return None, "Model not found"

                logger.error(
                    "Failed to fetch model info for %s: %s", model_hash[:10], message
                )
                return None, message

            if isinstance(version, dict):
                model_id = version.get("modelId")
                if model_id:
                    model_data = await self._fetch_model_data(model_id)
                    if model_data:
                        self._enrich_version_with_model_data(version, model_data)

                self._remove_comfy_metadata(version)
                return version, None
            else:
                return None, "Invalid response format"
        except RateLimitError:
            raise
        except Exception as exc:
            logger.error("API Error: %s", exc)
            return None, str(exc)

    async def download_preview_image(self, image_url: str, save_path: str):
        try:
            downloader = await get_downloader()
            success, content, headers = await downloader.download_to_memory(
                image_url,
                use_auth=False,  # Preview images don't need auth
            )
            if success:
                # Ensure directory exists
                os.makedirs(os.path.dirname(save_path), exist_ok=True)
                with open(save_path, "wb") as f:
                    f.write(content if isinstance(content, bytes) else content.encode("utf-8"))
                return True
            return False
        except Exception as e:
            if is_expected_offline_error(str(e)):
                logger.debug("Preview download skipped due to offline state.")
                return False
            logger.error(f"Download Error: {str(e)}")
            return False

    @staticmethod
    def _extract_error_message(payload: Any) -> str:
        """Return a human-readable error message from an API payload."""

        def _from_value(value: Any) -> str:
            if isinstance(value, str):
                return value
            if isinstance(value, dict):
                for key in ("message", "error", "detail", "details"):
                    if key in value:
                        candidate = _from_value(value[key])
                        if candidate:
                            return candidate
            if isinstance(value, list):
                for item in value:
                    candidate = _from_value(item)
                    if candidate:
                        return candidate
            return ""

        return _from_value(payload)

    @staticmethod
    def _is_transient_server_error(message: str) -> bool:
        """Return True when the message indicates a transient upstream failure.

        Recognises Cloudflare 524, generic 5xx, and connectivity-level flakiness
        that should not be treated as a permanent failure.
        """
        normalized = message.lower()
        if "status 5" in normalized or "status 524" in normalized:
            return True
        if any(
            keyword in normalized
            for keyword in (
                "connection refused",
                "connection reset",
                "temporary failure",
                "name resolution",
                "connection closed",
            )
        ):
            return True
        return False

    async def get_model_versions(self, model_id: str) -> Optional[Dict[str, Any]]:
        """Get all versions of a model with local availability info"""
        try:
            success, result = await self._make_request(
                "GET",
                f"{self.base_url}/models/{model_id}",
                use_auth=True,
            )
            if success and isinstance(result, dict):
                # Also return model type along with versions
                return {
                    "modelVersions": result.get("modelVersions", []),
                    "type": result.get("type", ""),
                    "name": result.get("name", ""),
                }
            message = self._extract_error_message(result)
            if message and "not found" in message.lower():
                raise ResourceNotFoundError(f"Resource not found for model {model_id}")
            if is_expected_offline_error(message):
                logger.info("Civitai request skipped: %s", OFFLINE_FRIENDLY_MESSAGE)
                return None
            if message:
                if self._is_transient_server_error(message):
                    logger.info(
                        "Transient server error for model %s: %s",
                        model_id,
                        message,
                    )
                    return None
                raise RuntimeError(message)
            return None
        except RateLimitError:
            raise
        except ResourceNotFoundError as exc:
            logger.info("Model %s is no longer available on Civitai: %s", model_id, exc)
            raise
        except Exception as e:
            logger.error("Error fetching model versions: %s", e, exc_info=True)
            raise

    async def get_model_versions_bulk(
        self, model_ids: Sequence[int]
    ) -> Optional[Dict[int, Dict[str, Any]]]:
        """Fetch model metadata for multiple ids using the batch API."""

        deduped: Dict[int, None] = {}
        for raw_id in model_ids:
            try:
                normalized = int(raw_id)
            except (TypeError, ValueError):
                continue
            deduped.setdefault(normalized, None)

        normalized_ids = [str(model_id) for model_id in deduped.keys()]
        if not normalized_ids:
            return {}

        try:
            query = ",".join(normalized_ids)
            success, result = await self._make_request(
                "GET",
                f"{self.base_url}/models",
                use_auth=True,
                params={"ids": query, "nsfw": "true"},
            )
            if not success:
                return None

            items = result.get("items") if isinstance(result, dict) else None
            if not isinstance(items, list):
                return {}

            payload: Dict[int, Dict[str, Any]] = {}
            for item in items:
                if not isinstance(item, dict):
                    continue
                model_id = item.get("id")
                try:
                    normalized_id = int(cast(Any, model_id))
                except (TypeError, ValueError):
                    continue
                payload[normalized_id] = {
                    "modelVersions": item.get("modelVersions", []),
                    "type": item.get("type", ""),
                    "name": item.get("name", ""),
                    "allowNoCredit": item.get("allowNoCredit"),
                    "allowCommercialUse": item.get("allowCommercialUse"),
                    "allowDerivatives": item.get("allowDerivatives"),
                    "allowDifferentLicense": item.get("allowDifferentLicense"),
                }
            return payload
        except RateLimitError:
            raise
        except Exception as exc:
            logger.error(f"Error fetching model versions in bulk: {exc}")
            return None

    async def get_model_version(
        self, model_id: int | None = None, version_id: int | None = None
    ) -> Optional[Dict[str, Any]]:
        """Get specific model version with additional metadata."""
        try:
            if model_id is None and version_id is not None:
                return await self._get_version_by_id_only(version_id)

            if model_id is not None:
                return await self._get_version_with_model_id(model_id, version_id)

            logger.error("Either model_id or version_id must be provided")
            return None

        except RateLimitError:
            raise
        except Exception as e:
            logger.error(f"Error fetching model version: {e}")
            return None

    async def _get_version_by_id_only(self, version_id: int) -> Optional[Dict[str, Any]]:
        version = await self._fetch_version_by_id(version_id)
        if version is None:
            return None

        model_id = version.get("modelId")
        if not model_id:
            logger.error(f"No modelId found in version {version_id}")
            return None

        model_data = await self._fetch_model_data(model_id)
        if model_data:
            self._enrich_version_with_model_data(version, model_data)

        self._remove_comfy_metadata(version)
        return version

    async def _get_version_with_model_id(
        self, model_id: int, version_id: Optional[int]
    ) -> Optional[Dict[str, Any]]:
        model_data = await self._fetch_model_data(model_id)
        if not model_data:
            return None

        target_version = self._select_target_version(model_data, model_id, version_id)

        # If modelVersions is empty (e.g. CivitAI cache lag for newly published
        # models) but a specific version_id is known, fall back to fetching the
        # version directly via the individual model-versions endpoint, then
        # enrich it with the model-level data we already have.
        if target_version is None and version_id is not None:
            logger.info(
                "modelVersions empty for model %s; falling back to direct "
                "version lookup for %s",
                model_id,
                version_id,
            )
            version = await self._fetch_version_by_id(version_id)
            if version:
                self._enrich_version_with_model_data(version, model_data)
                self._remove_comfy_metadata(version)
                return version
            return None

        if target_version is None:
            return None

        target_version_id = target_version.get("id")
        version = (
            await self._fetch_version_by_id(target_version_id)
            if target_version_id
            else None
        )

        if version is None:
            model_hash = self._extract_primary_model_hash(target_version)
            if model_hash:
                version = await self._fetch_version_by_hash(model_hash)
            else:
                logger.warning(
                    f"No primary model hash found for model {model_id} version {target_version_id}"
                )

        if version is None:
            version = self._build_version_from_model_data(
                target_version, model_id, model_data
            )

        self._enrich_version_with_model_data(version, model_data)
        self._remove_comfy_metadata(version)
        return version

    async def _fetch_model_data(self, model_id: int) -> Optional[Dict[str, Any]]:
        success, data = await self._make_request(
            "GET",
            f"{self.base_url}/models/{model_id}",
            use_auth=True,
        )
        if success and isinstance(data, dict):
            return data
        if is_expected_offline_error(data):
            return None
        logger.warning(f"Failed to fetch model data for model {model_id}")
        return None

    async def _fetch_version_by_id(self, version_id: Optional[int]) -> Optional[Dict[str, Any]]:
        if version_id is None:
            return None

        success, version = await self._make_request(
            "GET",
            f"{self.base_url}/model-versions/{version_id}",
            use_auth=True,
        )
        if success and isinstance(version, dict):
            return version
        if is_expected_offline_error(version):
            return None

        logger.warning(f"Failed to fetch version by id {version_id}")
        return None

    async def _fetch_version_by_hash(self, model_hash: Optional[str]) -> Optional[Dict[str, Any]]:
        if not model_hash:
            return None

        success, version = await self._make_request(
            "GET",
            f"{self.base_url}/model-versions/by-hash/{model_hash}",
            use_auth=True,
        )
        if success and isinstance(version, dict):
            return version
        if is_expected_offline_error(version):
            return None

        logger.warning(f"Failed to fetch version by hash {model_hash}")
        return None

    def _select_target_version(
        self, model_data: Dict[str, Any], model_id: int, version_id: Optional[int]
    ) -> Optional[Dict[str, Any]]:
        model_versions = model_data.get("modelVersions", [])
        if not model_versions:
            logger.warning(f"No model versions found for model {model_id}")
            return None

        if version_id is not None:
            target_version = next(
                (item for item in model_versions if item.get("id") == version_id), None
            )
            if target_version is None:
                logger.warning(
                    f"Version {version_id} not found for model {model_id}, defaulting to first version"
                )
                return model_versions[0]
            return target_version

        return model_versions[0]

    def _extract_primary_model_hash(self, version_entry: Dict[str, Any]) -> Optional[str]:
        for file_info in version_entry.get("files", []):
            if file_info.get("type") == "Model" and file_info.get("primary"):
                hashes = file_info.get("hashes", {})
                model_hash = hashes.get("SHA256")
                if model_hash:
                    return model_hash
        return None

    def _build_version_from_model_data(
        self, version_entry: Dict[str, Any], model_id: int, model_data: Dict[str, Any]
    ) -> Dict[str, Any]:
        version = copy.deepcopy(version_entry)
        version.pop("index", None)
        version["modelId"] = model_id
        version["model"] = {
            "name": model_data.get("name"),
            "type": model_data.get("type"),
            "nsfw": model_data.get("nsfw"),
            "poi": model_data.get("poi"),
        }
        return version

    def _enrich_version_with_model_data(self, version: Dict[str, Any], model_data: Dict[str, Any]) -> None:
        model_info = version.get("model")
        if not isinstance(model_info, dict):
            model_info = {}
            version["model"] = model_info

        model_info["description"] = model_data.get("description")
        model_info["tags"] = model_data.get("tags", [])
        version["creator"] = model_data.get("creator")

        license_payload = resolve_license_payload(model_data)
        for field, value in license_payload.items():
            model_info[field] = value

    async def get_model_version_info(
        self, version_id: str
    ) -> Tuple[Optional[Dict[str, Any]], Optional[str]]:
        """Fetch model version metadata from Civitai

        Args:
            version_id: The Civitai model version ID

        Returns:
            Tuple[Optional[Dict], Optional[str]]: A tuple containing:
                - The model version data or None if not found
                - An error message if there was an error, or None on success
        """
        # In-memory cache avoids redundant API calls within the same
        # import/scan flow (e.g. _resolve_base_model_from_checkpoint
        # followed by _resolve_and_populate_checkpoint with the same id).
        if version_id in self._version_info_cache:
            logger.debug("Cache hit for model version info: %s", version_id)
            self._version_info_cache.move_to_end(version_id)  # LRU bump
            return self._version_info_cache[version_id]

        try:
            url = f"{self.base_url}/model-versions/{version_id}"

            logger.debug("Resolving Civitai model version info: %s", url)
            success, result = await self._make_request("GET", url, use_auth=True)

            if success and isinstance(result, dict):
                logger.debug("Successfully fetched model version info for: %s", version_id)
                self._remove_comfy_metadata(result)
                self._version_info_cache[version_id] = (result, None)
                self._version_info_cache.move_to_end(version_id)
                # Evict oldest entry when over capacity
                if len(self._version_info_cache) > self._MAX_CACHE_ENTRIES:
                    self._version_info_cache.popitem(last=False)
                return result, None

            # Handle specific error cases
            if is_expected_offline_error(result):
                return None, OFFLINE_FRIENDLY_MESSAGE
            if "not found" in str(result):
                error_msg = f"Model not found"
                logger.warning(f"Model version not found: {version_id} - {error_msg}")
                return None, error_msg

            # Other error cases
            logger.error(f"Failed to fetch model info for {version_id}: {result}")
            return None, str(result)
        except RateLimitError:
            raise
        except Exception as e:
            error_msg = f"Error fetching model version info: {e}"
            logger.error(error_msg)
            return None, error_msg

    async def get_image_info(
        self, image_id: str, source_url: str | None = None
    ) -> Optional[Dict[str, Any]]:
        """Fetch image information from Civitai API

        Args:
            image_id: The Civitai image ID
            source_url: Original image page URL. Accepted for caller compatibility;
                API requests always target ``civitai.red``.

        Returns:
            Optional[Dict]: The image data or None if not found
        """
        try:
            requested_id = int(image_id)
            url = self._build_image_info_url(image_id)
            success, result = await self._make_request("GET", url, use_auth=True)

            if not success:
                if is_expected_offline_error(result):
                    return None
                if self._is_transient_server_error(str(result)):
                    logger.info(
                        "Transient server error fetching image info for ID %s: %s",
                        image_id,
                        result,
                    )
                    return None
                logger.error(
                    "Failed to fetch image info for ID %s from civitai.red: %s",
                    image_id,
                    result,
                )
                return None

            if isinstance(result, dict) and "items" in result and isinstance(result["items"], list):
                items = result["items"]

                for item in items:
                    if isinstance(item, dict) and item.get("id") == requested_id:
                        logger.debug(
                            "Successfully fetched image info for ID %s from civitai.red",
                            image_id,
                        )
                        return item

                returned_ids = [
                    item.get("id")
                    for item in items
                    if isinstance(item, dict) and "id" in item
                ]

                logger.warning(
                    "CivitAI API returned no matching image for requested ID %s from civitai.red. Returned %d item(s) with IDs: %s. This may indicate the image was deleted, hidden, or there is a database lag.",
                    image_id,
                    len(items),
                    returned_ids,
                )
                return None

            logger.warning("No image found with ID: %s", image_id)
            return None
        except RateLimitError:
            raise
        except ValueError as e:
            error_msg = f"Invalid image ID format: {image_id}"
            logger.error(error_msg)
            return None
        except Exception as e:
            error_msg = f"Error fetching image info: {e}"
            logger.error(error_msg)
            return None

    async def get_model_versions_by_hashes(
        self, hashes: List[str]
    ) -> Optional[List[Dict[str, Any]]]:
        """Fetch full version details for up to 100 SHA256 hashes via the batch endpoint.

        Uses POST /api/v1/model-versions/by-hash which returns full version
        details including ``usageControl`` and ``earlyAccessEndsAt`` that are
        not available from the model-level API.

        Args:
            hashes: List of SHA256 hashes (max 100 per batch; auto-split).

        Returns:
            List of version dicts or None on failure.
        """
        if not hashes:
            return []

        BATCH_SIZE = 100
        all_versions: List[Dict[str, Any]] = []

        for start in range(0, len(hashes), BATCH_SIZE):
            batch = hashes[start : start + BATCH_SIZE]
            try:
                success, result = await self._make_request(
                    "POST",
                    f"{self.base_url}/model-versions/by-hash",
                    use_auth=True,
                    json=batch,
                )
                if not success:
                    logger.warning(
                        "Batch by-hash request failed for %d hashes: %s",
                        len(batch),
                        result,
                    )
                    continue

                if isinstance(result, list):
                    all_versions.extend(cast(Any, result))
                else:
                    logger.debug(
                        "Unexpected by-hash response type: %s", type(result)
                    )
            except RateLimitError:
                raise
            except Exception as exc:  # pragma: no cover - defensive logging
                logger.error(
                    "Error fetching model versions by hashes: %s", exc
                )

        return all_versions if all_versions else None

    async def get_user_models(
        self, username: str, cursor: Optional[str] = None
    ) -> Optional[Dict[str, Any]]:
        """Fetch one page (up to 100 models) for a specific Civitai user.

        Returns ``{"items": [...], "nextCursor": <str|None>}`` on success,
        or None on failure. Pass ``cursor`` (from a previous response's
        ``nextCursor``) to fetch subsequent pages.
        """
        if not username:
            return None

        params: Dict[str, Any] = {
            "username": username,
            "nsfw": "true",
            "limit": 100,
            "sort": "Newest",
            "period": "AllTime",
        }
        if cursor:
            params["cursor"] = cursor

        try:
            success, result = await self._make_request(
                "GET",
                f"{self.base_url}/models",
                use_auth=True,
                params=params,
            )

            if not success:
                if is_expected_offline_error(result):
                    logger.info("User model fetch skipped: %s", OFFLINE_FRIENDLY_MESSAGE)
                    return None
                logger.error("Failed to fetch models for %s: %s", username, result)
                return None

            items = result.get("items") if isinstance(result, dict) else None
            if not isinstance(items, list):
                items = []

            for model in items:
                versions = model.get("modelVersions")
                if not isinstance(versions, list):
                    continue
                for version in versions:
                    self._remove_comfy_metadata(version)

            next_cursor: Optional[str] = None
            metadata = result.get("metadata") if isinstance(result, dict) else None
            if isinstance(metadata, dict):
                raw_cursor = metadata.get("nextCursor")
                if raw_cursor is not None:
                    next_cursor = str(raw_cursor)

            return {"items": items, "nextCursor": next_cursor}
        except RateLimitError:
            raise
        except Exception as exc:  # pragma: no cover - defensive logging
            logger.error("Error fetching models for %s: %s", username, exc)
            return None

    async def get_creator_model_count(self, username: str) -> Optional[int]:
        """Best-effort lookup of a creator's published model count.

        Uses the ``/creators`` endpoint (a contains-match query), picking the
        entry whose username matches exactly (case-insensitive). Returns None
        on any failure; never raises. Results (including None) are cached
        for ``_CREATOR_COUNT_CACHE_TTL_SECONDS``.
        """
        if not username:
            return None

        cache_key = username.lower()
        cached = _creator_model_count_cache.get(cache_key)
        if cached is not None:
            cached_at, cached_count = cached
            if time.monotonic() - cached_at < _CREATOR_COUNT_CACHE_TTL_SECONDS:
                return cached_count

        count: Optional[int] = None
        try:
            success, result = await self._make_request(
                "GET",
                f"{self.base_url}/creators",
                use_auth=True,
                params={"query": username, "limit": 10},
            )

            if success and isinstance(result, dict):
                creators = result.get("items")
                if isinstance(creators, list):
                    for creator in creators:
                        if not isinstance(creator, dict):
                            continue
                        creator_name = creator.get("username")
                        if not isinstance(creator_name, str):
                            continue
                        if creator_name.lower() != cache_key:
                            continue
                        model_count = creator.get("modelCount")
                        if isinstance(model_count, (int, float)) and not isinstance(
                            model_count, bool
                        ):
                            count = int(model_count)
                        break
        except Exception as exc:  # best-effort only, never propagate
            logger.debug(
                "Failed to fetch creator model count for %s: %s", username, exc
            )

        _creator_model_count_cache[cache_key] = (time.monotonic(), count)
        return count