imagerepo/app/utils/image_importer.py

# app/utils/image_importer.py

from __future__ import annotations

from datetime import datetime
from pathlib import Path
import hashlib
import json
import mimetypes
import os
import re
import shutil
import subprocess
import tempfile
import time
import uuid

from PIL import Image, ImageOps
import exifread
import imagehash

from pyunpack import Archive

from app import db
from app.models import ImageRecord, Tag, ArchiveRecord

FFMPEG_THUMB_TIMEOUT = int(os.environ.get("THUMBS_FFMPEG_TIMEOUT", "60"))  # seconds
FFMPEG_TRANSCODE_TIMEOUT = int(os.environ.get("FFMPEG_TRANSCODE_TIMEOUT", "600"))  # 10 min default
Image.MAX_IMAGE_PIXELS = int(os.environ.get("PIL_MAX_IMAGE_PIXELS", "178956970"))
ARCHIVE_NUM_WIDTH = int(os.environ.get("ARCHIVE_NUM_WIDTH", "4"))


# =============================================================================
# Configuration & Constants
# =============================================================================

THUMB_SIZE = (400, 400)

# Media and archive extensions we handle
IMAGE_EXTS = (".jpg", ".jpeg", ".jfif", ".png", ".gif", ".bmp", ".tiff", ".webp")
VIDEO_EXTS = (".mp4", ".mov", ".avi", ".mkv", ".webm", ".m4v", ".wmv", ".flv")
VIDEO_EXTS_NEED_TRANSCODE = (".mov", ".avi", ".mkv", ".webm", ".m4v", ".wmv", ".flv")  # Non-MP4 formats
ALLOWED_MEDIA_EXTS = IMAGE_EXTS + VIDEO_EXTS
ALLOWED_ARCHIVE_EXTS = (
    ".zip", ".rar", ".cbr", ".7z",
    ".tar", ".tar.gz", ".tgz", ".tar.bz2", ".tbz2", ".tar.xz", ".txz"
)

# Import filter settings (loaded from file or env)
IMPORT_SETTINGS_PATH = "/import/settings.json"
IMPORT_STATS_PATH = "/import/stats.json"


def load_import_settings() -> dict:
    """
    Load import filter settings from database, with file and environment fallbacks.
    Priority: DB settings > file settings > environment variables
    """
    # Start with environment defaults
    defaults = {
        "min_width": int(os.environ.get("IMPORT_MIN_WIDTH", "0")),
        "min_height": int(os.environ.get("IMPORT_MIN_HEIGHT", "0")),
        "skip_transparent": os.environ.get("IMPORT_SKIP_TRANSPARENT", "false").lower() == "true",
        "transparency_threshold": float(os.environ.get("IMPORT_TRANSPARENCY_THRESHOLD", "0.9")),
        "skip_single_color": os.environ.get("IMPORT_SKIP_SINGLE_COLOR", "true").lower() == "true",
        "single_color_threshold": float(os.environ.get("IMPORT_SINGLE_COLOR_THRESHOLD", "0.95")),
        "single_color_tolerance": int(os.environ.get("IMPORT_SINGLE_COLOR_TOLERANCE", "30")),
        "phash_threshold": int(os.environ.get("IMPORT_PHASH_THRESHOLD", "10")),  # Default for 256-bit
        "supersede_smaller": os.environ.get("IMPORT_SUPERSEDE_SMALLER", "true").lower() == "true",
    }

    # Try to load from file (legacy support)
    try:
        if os.path.exists(IMPORT_SETTINGS_PATH):
            with open(IMPORT_SETTINGS_PATH, "r") as f:
                file_settings = json.load(f)
                defaults.update(file_settings)
    except Exception as e:
        print(f"[WARN] Failed to load import settings from file: {e}")

    # Try to load from database (preferred)
    try:
        from app.utils.version_migration import get_import_settings
        db_settings = get_import_settings()
        # Only override if DB has non-default values
        for key, value in db_settings.items():
            if value is not None:
                defaults[key] = value
    except Exception as e:
        print(f"[WARN] Failed to load import settings from DB: {e}")

    return defaults


def save_import_stats(stats: dict) -> None:
    """Save import statistics to file."""
    try:
        with open(IMPORT_STATS_PATH, "w") as f:
            json.dump(stats, f, indent=2)
    except Exception as e:
        print(f"[WARN] Failed to save import stats: {e}")


def is_mostly_transparent(file_path: str, threshold: float = 0.9) -> bool:
    """
    Check if an image is mostly transparent (> threshold % of pixels are transparent).
    Returns False for images without alpha channel.
    """
    try:
        with Image.open(file_path) as img:
            if img.mode not in ("RGBA", "LA", "P"):
                return False

            # Convert palette images with transparency
            if img.mode == "P" and "transparency" in img.info:
                img = img.convert("RGBA")
            elif img.mode == "LA":
                img = img.convert("RGBA")
            elif img.mode != "RGBA":
                return False

            # Get alpha channel and count transparent pixels
            alpha = img.split()[-1]
            total_pixels = alpha.size[0] * alpha.size[1]
            # Count pixels where alpha < 128 (more than 50% transparent)
            transparent_count = sum(1 for p in alpha.getdata() if p < 128)
            transparency_ratio = transparent_count / total_pixels
            return transparency_ratio > threshold
    except Exception as e:
        print(f"[WARN] Failed to check transparency for {file_path}: {e}")
        return False


def is_mostly_single_color(file_path: str, threshold: float = 0.95, tolerance: int = 30) -> bool:
    """
    Check if an image is mostly a single color (> threshold % of pixels are similar).
    Uses color distance tolerance to group similar colors.

    Args:
        file_path: Path to the image file
        threshold: Percentage of pixels that must be similar (0.0-1.0, default 0.95 = 95%)
        tolerance: Maximum color distance to be considered "same" color (0-255 per channel, default 30)

    Returns:
        True if the image is mostly a single solid color
    """
    try:
        with Image.open(file_path) as img:
            # Convert to RGB for consistent color comparison
            if img.mode in ("RGBA", "LA"):
                # For images with alpha, only consider non-transparent pixels
                img_rgba = img.convert("RGBA") if img.mode != "RGBA" else img
                pixels = list(img_rgba.getdata())
                # Filter out mostly transparent pixels (alpha < 128)
                opaque_pixels = [(r, g, b) for r, g, b, a in pixels if a >= 128]
                if len(opaque_pixels) == 0:
                    return True  # Fully transparent = effectively single color
                pixels = opaque_pixels
            elif img.mode == "P":
                img = img.convert("RGB")
                pixels = list(img.getdata())
            elif img.mode == "L":
                # Grayscale - convert to RGB tuples
                pixels = [(p, p, p) for p in img.getdata()]
            else:
                if img.mode != "RGB":
                    img = img.convert("RGB")
                pixels = list(img.getdata())

            if len(pixels) == 0:
                return True

            # Sample pixels for performance on large images
            total_pixels = len(pixels)
            if total_pixels > 10000:
                # Sample evenly distributed pixels
                step = total_pixels // 10000
                pixels = pixels[::step]

            # Find the dominant color (most common pixel or average of sampled area)
            # Use the pixel at center as reference
            center_idx = len(pixels) // 2
            ref_color = pixels[center_idx]

            # Count pixels within tolerance of reference color
            similar_count = 0
            for pixel in pixels:
                if isinstance(pixel, int):
                    pixel = (pixel, pixel, pixel)
                # Calculate color distance (simple RGB distance)
                dist = abs(pixel[0] - ref_color[0]) + abs(pixel[1] - ref_color[1]) + abs(pixel[2] - ref_color[2])
                if dist <= tolerance * 3:  # tolerance per channel * 3 channels
                    similar_count += 1

            similarity_ratio = similar_count / len(pixels)
            return similarity_ratio > threshold

    except Exception as e:
        print(f"[WARN] Failed to check single color for {file_path}: {e}")
        return False


def supersede_image(old_record: "ImageRecord", new_filepath: str, new_thumb_path: str,
                    new_hash: str, new_phash, new_metadata: dict, new_filename: str) -> "ImageRecord":
    """
    Replace a smaller image with a larger version, preserving tags and metadata.

    Args:
        old_record: The existing ImageRecord to supersede
        new_filepath: Path to the new larger image file
        new_thumb_path: Path to the new thumbnail
        new_hash: SHA256 hash of the new file
        new_phash: Perceptual hash of the new image
        new_metadata: Metadata dict for the new image
        new_filename: Original filename of the new image

    Returns:
        The updated ImageRecord
    """
    # Store old file paths for cleanup
    old_filepath = old_record.filepath
    old_thumb_path = old_record.thumb_path

    print(f"[SUPERSEDE] Replacing {old_record.filename} ({old_record.width}x{old_record.height}) "
          f"with {new_filename} ({new_metadata['width']}x{new_metadata['height']})")

    # Update record with new file info
    old_record.filename = new_filename
    old_record.filepath = new_filepath
    old_record.thumb_path = new_thumb_path
    old_record.hash = new_hash
    old_record.perceptual_hash = str(new_phash) if new_phash else None
    old_record.file_size = new_metadata["file_size"]
    old_record.width = new_metadata["width"]
    old_record.height = new_metadata["height"]
    old_record.format = new_metadata["format"]
    # Keep the earlier taken_at date (prefer original date)
    if new_metadata.get("taken_at") and old_record.taken_at:
        if new_metadata["taken_at"] < old_record.taken_at:
            old_record.taken_at = new_metadata["taken_at"]
    elif new_metadata.get("taken_at") and not old_record.taken_at:
        old_record.taken_at = new_metadata["taken_at"]
    # Don't update imported_at - keep original import time

    # Delete old files
    try:
        if old_filepath and os.path.exists(old_filepath):
            os.remove(old_filepath)
            print(f"[SUPERSEDE] Deleted old file: {old_filepath}")
    except Exception as e:
        print(f"[WARN] Failed to delete old file {old_filepath}: {e}")

    try:
        if old_thumb_path and os.path.exists(old_thumb_path):
            os.remove(old_thumb_path)
            print(f"[SUPERSEDE] Deleted old thumbnail: {old_thumb_path}")
    except Exception as e:
        print(f"[WARN] Failed to delete old thumbnail {old_thumb_path}: {e}")

    return old_record


# Regex for multi-part detection
RAR_PART_RE    = re.compile(r"\.part(\d+)\.rar$", re.IGNORECASE)
SEVENZ_PART_RE = re.compile(r"\.7z\.(\d{3})$", re.IGNORECASE)
OLD_RAR_VOL_RE = re.compile(r"\.r\d{2}$", re.IGNORECASE)  # .r00, .r01, ...

# Environment configuration (optional)
ENV_TMPDIR = "ARCHIVE_TMPDIR"          # where to extract archives (default: system tmp)
ENV_MINFREE = "ARCHIVE_MIN_FREE_GB"    # min free GB required to start extraction (float; 0 = disabled)


# =============================================================================
# Utilities: Temp space management & free-space guard
# =============================================================================

def get_tmp_base() -> Path:
    """Return the base temp directory for archive extraction."""
    return Path(os.environ.get(ENV_TMPDIR, tempfile.gettempdir())).resolve()


def cleanup_stale_tempdirs(prefix: str = "extract_") -> None:
    """Delete any leftover extraction directories from previous crashes."""
    base = get_tmp_base()
    base.mkdir(parents=True, exist_ok=True)
    for entry in base.glob(f"{prefix}*"):
        if entry.is_dir():
            try:
                shutil.rmtree(entry, ignore_errors=True)
            except Exception:
                pass


def ensure_free_space_or_raise(path: Path, min_free_gb: float) -> None:
    """Raise if there is not enough free space at path."""
    if min_free_gb <= 0:
        return
    total, used, free = shutil.disk_usage(str(path))
    free_gb = free / (1024 ** 3)
    if free_gb < min_free_gb:
        raise RuntimeError(
            f"Insufficient free space at {path}: {free_gb:.1f} GB free "
            f"(required >= {min_free_gb:.1f} GB)."
        )


# =============================================================================
# Utilities: External extractors with resilient fallback
# =============================================================================

class ExtractError(Exception):
    """Raised when archive extraction fails with all strategies."""


def _run_cmd(cmd: list[str]) -> tuple[int, str, str]:
    p = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
    return p.returncode, p.stdout, p.stderr


def extract_with_unar(archive_path: str, out_dir: str) -> None:
    os.makedirs(out_dir, exist_ok=True)
    rc, out, err = _run_cmd(["unar", "-o", out_dir, archive_path])
    if rc != 0:
        raise ExtractError(f"unar failed (rc={rc})\nSTDOUT:\n{out}\nSTDERR:\n{err}")


def extract_with_7z(archive_path: str, out_dir: str) -> None:
    os.makedirs(out_dir, exist_ok=True)
    rc, out, err = _run_cmd(["7z", "x", "-y", f"-o{out_dir}", archive_path])
    if rc != 0:
        raise ExtractError(f"7z failed (rc={rc})\nSTDOUT:\n{out}\nSTDERR:\n{err}")


def looks_password_protected_with_lsar(archive_path: str) -> bool:
    """Best-effort pre-check for 'Encrypted/Password' in lsar output."""
    try:
        rc, out, err = _run_cmd(["lsar", archive_path])
        txt = (out + "\n" + err).lower()
        return ("encrypted" in txt) or ("password" in txt)
    except Exception:
        return False


def extract_archive_resilient(archive_path: str, out_dir: str) -> None:
    """
    Prefer unar for RAR/CBR (RAR5-friendly); fallback to 7z.
    For other formats, try 7z first then unar.
    Surfaces stderr so logs show CRC/password/permissions issues.
    """
    lower = archive_path.lower()
    errors = []

    # Optional password hint to skip early
    if lower.endswith((".rar", ".cbr")) and looks_password_protected_with_lsar(archive_path):
        raise ExtractError("Archive appears password-protected; skipping (no password provided).")

    if lower.endswith((".rar", ".cbr")):
        order = (extract_with_unar, extract_with_7z)
    else:
        order = (extract_with_7z, extract_with_unar)

    for fn in order:
        try:
            fn(archive_path, out_dir)
            return
        except ExtractError as e:
            errors.append(str(e))

    raise ExtractError("Both extractors failed:\n" + "\n---\n".join(errors))


# =============================================================================
# Core: Import task & archive processing
# =============================================================================

def import_images_task(source_dir: str, dest_dir: str) -> str:
    """
    Walk the import tree, process archives first (only first volumes),
    then media files. Batches DB commits for efficiency.
    """
    # Cleanup any stale extraction dirs from previous runs/crashes
    cleanup_stale_tempdirs()

    # Load import filter settings
    settings = load_import_settings()
    min_width = settings.get("min_width", 0)
    min_height = settings.get("min_height", 0)
    skip_transparent = settings.get("skip_transparent", False)
    transparency_threshold = settings.get("transparency_threshold", 0.9)
    skip_single_color = settings.get("skip_single_color", True)
    single_color_threshold = settings.get("single_color_threshold", 0.95)
    single_color_tolerance = settings.get("single_color_tolerance", 30)
    phash_threshold = settings.get("phash_threshold", 2)
    supersede_smaller = settings.get("supersede_smaller", True)

    print(f"[INFO] Import settings: min_width={min_width}, min_height={min_height}, "
          f"skip_transparent={skip_transparent}, transparency_threshold={transparency_threshold}, "
          f"skip_single_color={skip_single_color}, single_color_threshold={single_color_threshold}, "
          f"phash_threshold={phash_threshold}, supersede_smaller={supersede_smaller}")

    # Statistics tracking
    stats = {
        "total_processed": 0,
        "total_imported": 0,
        "total_superseded": 0,
        "filtered_by_dimension": 0,
        "filtered_by_transparency": 0,
        "filtered_by_single_color": 0,
        "filtered_by_duplicate": 0,
    }

    imported: list[str] = []
    batch_size = 10
    batch_counter = 0

    # Preload existing pHashes to avoid N+1 lookups
    # Format: (phash, width, height, image_id) for supersede functionality
    existing_phashes = [
        (imagehash.hex_to_hash(img.perceptual_hash), img.width, img.height, img.id)
        for img in ImageRecord.query.filter(ImageRecord.perceptual_hash != None).all()
    ]

    # Ensure thumbs base exists
    (Path(dest_dir) / "thumbs").mkdir(parents=True, exist_ok=True)

    # Optional free-space guard
    min_free = float(os.environ.get(ENV_MINFREE, "0") or "0")
    try:
        ensure_free_space_or_raise(get_tmp_base(), min_free)
    except Exception as e:
        print(f"[WARN] Free-space check failed: {e}")

    for artist_dir in os.listdir(source_dir):
        artist_path = os.path.join(source_dir, artist_dir)
        if not os.path.isdir(artist_path):
            continue

        for root, _, files in os.walk(artist_path):
            for file in files:
                full_path = os.path.join(root, file)
                lower = file.lower()

                # Archives first
                if lower.endswith(ALLOWED_ARCHIVE_EXTS):
                    if not is_first_volume(full_path):
                        print(f"[SKIP] Not first archive volume: {file}")
                        continue
                    try:
                        count = process_archive(
                            archive_path=full_path,
                            dest_dir=dest_dir,
                            artist=artist_dir,
                            existing_phashes=existing_phashes,
                            settings=settings,
                            stats=stats
                        )
                        imported.append(f"[archive]{file}:{count}")
                    except Exception as e:
                        print(f"[WARN] Failed processing archive {file}: {e}")
                    continue

                # Non-archive media
                if not lower.endswith(ALLOWED_MEDIA_EXTS):
                    continue

                stats["total_processed"] += 1

                # Apply dimension filter
                if min_width > 0 or min_height > 0:
                    md = extract_metadata(full_path)
                    if md.get("width") and md.get("height"):
                        if md["width"] < min_width or md["height"] < min_height:
                            print(f"[SKIP] Too small ({md['width']}x{md['height']}): {file}")
                            stats["filtered_by_dimension"] += 1
                            continue

                # Apply transparency filter
                if skip_transparent and lower.endswith((".png", ".gif", ".webp")):
                    if is_mostly_transparent(full_path, transparency_threshold):
                        print(f"[SKIP] Mostly transparent: {file}")
                        stats["filtered_by_transparency"] += 1
                        continue

                # Apply single-color filter (skip images that are mostly one solid color)
                if skip_single_color and lower.endswith((".png", ".jpg", ".jpeg", ".gif", ".webp", ".bmp")):
                    if is_mostly_single_color(full_path, single_color_threshold, single_color_tolerance):
                        print(f"[SKIP] Mostly single color: {file}")
                        stats["filtered_by_single_color"] += 1
                        continue

                added, phash, _rec, superseded = import_single_file(
                    src_path=full_path,
                    dest_dir=dest_dir,
                    artist=artist_dir,
                    existing_phashes=existing_phashes,
                    phash_threshold=phash_threshold,
                    supersede_smaller=supersede_smaller
                )
                if added:
                    imported.append(file)
                    if superseded:
                        stats["total_superseded"] += 1
                    else:
                        stats["total_imported"] += 1
                elif _rec is None and phash is None:
                    # Was a duplicate
                    stats["filtered_by_duplicate"] += 1

                # Add new image's phash to the tracking list (for fresh imports only, not supersedes)
                if phash and _rec and not superseded:
                    existing_phashes.append((phash, _rec.width, _rec.height, _rec.id))

                batch_counter += 1
                if batch_counter >= batch_size:
                    db.session.commit()
                    print(f"[INFO] Committed batch of {batch_size} items.")
                    batch_counter = 0
                    if "sqlite" in db.engine.url.drivername:
                        time.sleep(1)

    if batch_counter > 0:
        db.session.commit()
        print(f"[INFO] Committed final batch of {batch_counter} items.")

    # Save stats
    save_import_stats(stats)

    summary = (f"Imported {stats['total_imported']} items, superseded {stats['total_superseded']} smaller versions. "
               f"Filtered: {stats['filtered_by_dimension']} by size, {stats['filtered_by_transparency']} by transparency, "
               f"{stats['filtered_by_single_color']} by single color, {stats['filtered_by_duplicate']} duplicates.")
    print(f"[INFO] {summary}")
    return summary


def process_archive(archive_path, dest_dir, artist, existing_phashes, settings=None, stats=None):
    """
    Extracts archive to temp dir, imports/tag existing images, and records ArchiveRecord.
    Creates an archive:* tag ONLY if at least one image was imported or tagged.
    Returns number of items imported or tagged.
    """
    if settings is None:
        settings = load_import_settings()
    if stats is None:
        stats = {"total_processed": 0, "total_imported": 0, "total_superseded": 0,
                 "filtered_by_dimension": 0, "filtered_by_transparency": 0,
                 "filtered_by_single_color": 0, "filtered_by_duplicate": 0}

    min_width = settings.get("min_width", 0)
    min_height = settings.get("min_height", 0)
    skip_transparent = settings.get("skip_transparent", False)
    transparency_threshold = settings.get("transparency_threshold", 0.9)
    skip_single_color = settings.get("skip_single_color", True)
    single_color_threshold = settings.get("single_color_threshold", 0.95)
    single_color_tolerance = settings.get("single_color_tolerance", 30)
    phash_threshold = settings.get("phash_threshold", 2)
    supersede_smaller = settings.get("supersede_smaller", True)

    archive_size = os.path.getsize(archive_path)
    archive_hash = calculate_hash(archive_path)

    # Skip if this exact archive file was already processed (hash-based)
    existing_archive = ArchiveRecord.query.filter_by(hash=archive_hash).first()
    if existing_archive:
        print(f"[SKIP] Archive already imported: {archive_path}")
        return 0

    tmpdir = tempfile.mkdtemp(prefix="extract_")
    touched_records = []   # ImageRecord objects we imported or matched
    imported_or_tagged = 0
    created_tag = None

    try:
        # Extract using pyunpack
        Archive(archive_path).extractall(tmpdir)

        # Import / collect all media
        for root, _, files in os.walk(tmpdir):
            for file in files:
                lower = file.lower()
                if not lower.endswith(ALLOWED_MEDIA_EXTS):
                    continue
                src_path = os.path.join(root, file)
                stats["total_processed"] += 1

                # Apply dimension filter
                if min_width > 0 or min_height > 0:
                    md = extract_metadata(src_path)
                    if md.get("width") and md.get("height"):
                        if md["width"] < min_width or md["height"] < min_height:
                            print(f"[SKIP] Too small ({md['width']}x{md['height']}): {file}")
                            stats["filtered_by_dimension"] += 1
                            continue

                # Apply transparency filter
                if skip_transparent and lower.endswith((".png", ".gif", ".webp")):
                    if is_mostly_transparent(src_path, transparency_threshold):
                        print(f"[SKIP] Mostly transparent: {file}")
                        stats["filtered_by_transparency"] += 1
                        continue

                # Apply single-color filter
                if skip_single_color and lower.endswith((".png", ".jpg", ".jpeg", ".gif", ".webp", ".bmp")):
                    if is_mostly_single_color(src_path, single_color_threshold, single_color_tolerance):
                        print(f"[SKIP] Mostly single color: {file}")
                        stats["filtered_by_single_color"] += 1
                        continue

                added, _phash, rec, superseded = import_single_file(
                    src_path=src_path,
                    dest_dir=dest_dir,
                    artist=artist,  # still used for auto artist:<name> tag
                    existing_phashes=existing_phashes,
                    commit=False,
                    phash_threshold=phash_threshold,
                    supersede_smaller=supersede_smaller
                )
                if rec is not None:
                    touched_records.append(rec)
                    if added:
                        imported_or_tagged += 1
                        if superseded:
                            stats["total_superseded"] += 1
                        else:
                            stats["total_imported"] += 1
                elif rec is None and _phash is None:
                    stats["filtered_by_duplicate"] += 1

        # Only now: create/attach the archive tag if we actually touched images
        if touched_records:
            # Incremental name like 'archive:{artist}/0001'
            tag_name = compute_next_archive_tag_name(artist)
            created_tag = Tag.query.filter_by(name=tag_name).first()
            if not created_tag:
                created_tag = Tag(name=tag_name, kind='archive')
                db.session.add(created_tag)
                db.session.flush()

            newly_tagged = 0
            for rec in touched_records:
                if created_tag not in rec.tags:
                    rec.tags.append(created_tag)
                    newly_tagged += 1
            imported_or_tagged += newly_tagged

        # Record this archive as processed (tag may be None if no media)
        arch = ArchiveRecord(
            filename=archive_path,
            file_size=archive_size,
            hash=archive_hash,
            artist=artist,
            tag=created_tag
        )
        db.session.add(arch)
        db.session.commit()

        print(f"[INFO] Archive processed: {archive_path} items={imported_or_tagged}")
        return imported_or_tagged

    finally:
        shutil.rmtree(tmpdir, ignore_errors=True)


# =============================================================================
# Core: Single-file import path (content-addressed storage)
# =============================================================================

def build_hashed_dest_path(target_dir: str, original_name: str, content_hash: str) -> str:
    """
    Always produce a content-addressed destination:
    <target>/<name_without_ext>__<hash[:10]><ext>
    If that path already exists, append a numeric suffix.
    """
    base, ext = os.path.splitext(original_name)
    candidate = os.path.join(target_dir, f"{base}__{content_hash[:10]}{ext}")
    if not os.path.exists(candidate):
        return candidate

    # Rare: collision (e.g., concurrent import) → add counter
    i = 2
    while True:
        candidate = os.path.join(target_dir, f"{base}__{content_hash[:10]}_{i}{ext}")
        if not os.path.exists(candidate):
            return candidate
        i += 1


def import_single_file(src_path: str, dest_dir: str, artist: str, existing_phashes,
                       commit: bool = True, phash_threshold: int = 2, supersede_smaller: bool = True):
    """
    Import a single media file. If an equivalent file already exists, return that
    record so callers can tag it (no duplicate import).

    If a smaller visually-similar image exists and supersede_smaller is True,
    the smaller image will be replaced with the larger one (preserving tags).

    Also enriches metadata from Gallery-DL sidecar JSON files if present.

    Returns (added: bool, phash_or_None, record_or_None, superseded: bool).
    The superseded flag indicates if an existing smaller image was replaced.
    """
    original_name = os.path.basename(src_path)
    print(f"[INFO] Processing: {src_path}")
    file_size = os.path.getsize(src_path)

    # Compute content hash first (authoritative de-dup + used in filepath)
    file_hash = calculate_hash(src_path)
    existing = ImageRecord.query.filter_by(hash=file_hash).first()
    if existing:
        print(f"[SKIP] Duplicate by hash: {original_name}")
        # Even for duplicates, try to enrich with sidecar metadata
        _enrich_existing_record(existing, src_path)
        return (False, None, existing, False)

    # Optional info: same name+size (but different content) → we still import with hashed name
    existing_ns = ImageRecord.query.filter_by(filename=original_name, file_size=file_size).first()
    if existing_ns:
        print(f"[INFO] Same name+size exists but different hash; storing with hashed name: {original_name}")

    # Metadata & pHash similarity
    metadata = extract_metadata(src_path)
    if not metadata["width"] or not metadata["height"]:
        print(f"[SKIP] Missing dimension data for {original_name}")
        return (False, None, None, False)

    phash = calculate_perceptual_hash(src_path)

    # Check for similar images
    superseded = False
    if phash and phash_threshold > 0:
        relationship, similar_id = find_similar_image(
            phash, metadata["width"], metadata["height"], existing_phashes, threshold=phash_threshold
        )

        if relationship == "larger_exists":
            print(f"[SKIP] {original_name} is visually similar to an existing larger image (threshold={phash_threshold}).")
            return (False, phash, None, False)

        elif relationship == "smaller_exists" and supersede_smaller and similar_id:
            # Found a smaller version - supersede it
            old_record = ImageRecord.query.get(similar_id)
            if old_record:
                # Enrich metadata from Gallery-DL sidecar JSON if present
                enriched = _get_enriched_metadata(src_path, metadata)
                metadata["taken_at"] = enriched.get("taken_at") or metadata["taken_at"]

                # Copy new file to destination
                target_dir = os.path.join(dest_dir, artist)
                os.makedirs(target_dir, exist_ok=True)
                dest_path = build_hashed_dest_path(target_dir, original_name, file_hash)
                shutil.copy2(src_path, dest_path)

                # Generate new thumbnail
                try:
                    if dest_path.lower().endswith((".mp4", ".mov")):
                        thumb_path = generate_video_thumbnail_mirrored(dest_path)
                    else:
                        thumb_path = generate_thumbnail(dest_path)
                except Exception as e:
                    print(f"[WARN] Failed to generate thumbnail for {original_name}: {e}")
                    thumb_path = None

                # Supersede the old record (preserves tags)
                record = supersede_image(
                    old_record, dest_path, thumb_path, file_hash, phash, metadata, original_name
                )

                # Apply any new tags from sidecar
                _apply_enriched_tags(record, enriched)

                if commit:
                    db.session.commit()

                # Update existing_phashes list with new dimensions
                for i, (ph, w, h, img_id) in enumerate(existing_phashes):
                    if img_id == similar_id:
                        existing_phashes[i] = (phash, metadata["width"], metadata["height"], img_id)
                        break

                return (True, phash, record, True)  # superseded=True

    # No similar image found (or supersede disabled) - normal import
    # Enrich metadata from Gallery-DL sidecar JSON if present
    enriched = _get_enriched_metadata(src_path, metadata)

    # Copy into /images/<artist>/<base>__<hash[:10]><ext>
    target_dir = os.path.join(dest_dir, artist)
    os.makedirs(target_dir, exist_ok=True)
    dest_path = build_hashed_dest_path(target_dir, original_name, file_hash)
    shutil.copy2(src_path, dest_path)

    # Thumbnails (mirrored for both images and videos)
    try:
        if dest_path.lower().endswith((".mp4", ".mov")):
            thumb_path = generate_video_thumbnail_mirrored(dest_path)
        else:
            thumb_path = generate_thumbnail(dest_path)
    except Exception as e:
        print(f"[WARN] Failed to generate thumbnail for {original_name}: {e}")
        thumb_path = None

    # Create DB record (keep display name as original; filepath is content-addressed)
    # Use enriched taken_at (earliest date wins)
    record = ImageRecord(
        filename=original_name,
        filepath=dest_path,
        thumb_path=thumb_path,
        hash=file_hash,
        perceptual_hash=str(phash) if phash else None,
        file_size=metadata["file_size"],
        width=metadata["width"],
        height=metadata["height"],
        format=metadata["format"],
        camera_model=metadata["camera_model"],
        taken_at=enriched.get("taken_at") or metadata["taken_at"],
        imported_at=datetime.utcnow()
    )

    # Auto-tag with artist:<name> (treat artist as a tag only)
    if artist:
        artist_tag_name = f"artist:{artist}"
        artist_tag = Tag.query.filter_by(name=artist_tag_name).first()
        if not artist_tag:
            artist_tag = Tag(name=artist_tag_name, kind="artist")
            db.session.add(artist_tag)
            db.session.flush()
        if artist_tag not in record.tags:
            record.tags.append(artist_tag)

    # Add tags from Gallery-DL metadata (source:platform, post:platform:artist:id)
    _apply_enriched_tags(record, enriched)

    db.session.add(record)
    if commit:
        db.session.commit()
    return (True, phash, record, False)  # superseded=False (new import)


def _get_enriched_metadata(src_path: str, existing_metadata: dict) -> dict:
    """
    Get enriched metadata from Gallery-DL sidecar JSON.
    Returns empty dict if no sidecar found.
    """
    try:
        from app.utils.metadata_enrichment import enrich_from_sidecar
        return enrich_from_sidecar(src_path, existing_metadata)
    except ImportError:
        return {}
    except Exception as e:
        print(f"[WARN] Failed to enrich metadata for {src_path}: {e}")
        return {}


def _apply_enriched_tags(record: ImageRecord, enriched: dict) -> None:
    """
    Apply tags from enriched metadata to an ImageRecord.
    Creates tags if they don't exist.
    """
    if not enriched or "tags" not in enriched:
        return

    for tag_info in enriched.get("tags", []):
        tag_name = tag_info.get("name")
        tag_kind = tag_info.get("kind")
        if not tag_name:
            continue

        tag = Tag.query.filter_by(name=tag_name).first()
        if not tag:
            tag = Tag(name=tag_name, kind=tag_kind)
            db.session.add(tag)
            db.session.flush()

        if tag not in record.tags:
            record.tags.append(tag)
            print(f"[INFO] Added tag: {tag_name}")


def _enrich_existing_record(record: ImageRecord, src_path: str) -> None:
    """
    Enrich an existing record with metadata from sidecar JSON.
    Used when a duplicate is found - we still want to merge metadata.

    - Updates taken_at if sidecar date is earlier
    - Adds source/post tags if not already present
    """
    try:
        from app.utils.metadata_enrichment import enrich_from_sidecar, resolve_date_conflict

        enriched = enrich_from_sidecar(src_path, {"taken_at": record.taken_at})
        if not enriched.get("raw_metadata"):
            return  # No sidecar found

        # Update date if sidecar has an earlier date
        new_date = resolve_date_conflict(record.taken_at, enriched.get("taken_at"))
        if new_date != record.taken_at:
            print(f"[INFO] Updating taken_at for {record.filename}: {record.taken_at} -> {new_date}")
            record.taken_at = new_date

        # Add any new tags
        _apply_enriched_tags(record, enriched)

    except Exception as e:
        print(f"[WARN] Failed to enrich existing record: {e}")


# =============================================================================
# Helpers: Thumbnails, metadata, hashing, similarity
# =============================================================================

def generate_thumbnail(
    image_path,
    size=(400, 400),
    overwrite=False,
    prefer_jpeg=False,      # False = auto-pick PNG for alpha images; True = always JPEG
    jpeg_bg=(0, 0, 0),      # background used when flattening to JPEG
):
    """
    Save thumbnails mirrored under /images/thumbs/<...>.
    If prefer_jpeg is False (default), transparent images save as PNG, others as JPEG.
    If prefer_jpeg is True, all thumbs are JPEG with transparency flattened to `jpeg_bg`.

    For images with extreme aspect ratios (very tall like comic strips, or very wide),
    crops to the center region before thumbnailing to produce better quality previews.

    Returns the absolute path to the thumbnail.
    """
    images_root = Path("/images").resolve()
    image_path = Path(image_path).resolve()

    try:
        rel_path = image_path.relative_to(images_root)
    except ValueError:
        raise ValueError(f"{image_path} is not under {images_root}")

    # Base path under /images/thumbs with same subfolders/filename (we may change the suffix)
    thumb_base = (images_root / "thumbs" / rel_path).with_suffix("")  # drop original suffix for control

    # Decide output extension/format
    with Image.open(image_path) as img:
        img = ImageOps.exif_transpose(img)  # honor camera rotation

        # Handle extreme aspect ratios by cropping to a more balanced region
        # This prevents very tall/wide images from becoming tiny slivers
        w, h = img.size
        aspect_ratio = w / h if h > 0 else 1

        # If aspect ratio is extreme (< 0.5 means very tall, > 2.0 means very wide)
        # crop to a more balanced region before thumbnailing
        if aspect_ratio < 0.5:
            # Very tall image (like comic strip) - crop from top portion
            # Take a region that's closer to square, from the top
            crop_height = min(h, w * 2)  # At most 2:1 tall
            img = img.crop((0, 0, w, crop_height))
        elif aspect_ratio > 2.0:
            # Very wide image - crop from center
            crop_width = min(w, h * 2)  # At most 2:1 wide
            left = (w - crop_width) // 2
            img = img.crop((left, 0, left + crop_width, h))

        # Use LANCZOS resampling for high-quality downscaling
        img.thumbnail(size, Image.Resampling.LANCZOS)

        has_alpha = _has_alpha(img)

        if prefer_jpeg:
            # Force JPEG for consistency
            out_path = thumb_base.with_suffix(".jpg")
            out_path.parent.mkdir(parents=True, exist_ok=True)
            if not overwrite and out_path.exists():
                return str(out_path)
            img_rgb = _flatten_to_rgb(img, bg=jpeg_bg)
            img_rgb.save(out_path, format="JPEG", quality=85, optimize=True, progressive=True)
            return str(out_path)
        else:
            # Auto-pick: PNG for alpha, JPEG otherwise
            if has_alpha:
                out_path = thumb_base.with_suffix(".png")
                out_path.parent.mkdir(parents=True, exist_ok=True)
                if not overwrite and out_path.exists():
                    return str(out_path)
                # Keep transparency if present
                # Convert palette to RGBA for reliable PNG writing
                if img.mode == "P":
                    img = img.convert("RGBA")
                img.save(out_path, format="PNG", optimize=True)
                return str(out_path)
            else:
                out_path = thumb_base.with_suffix(".jpg")
                out_path.parent.mkdir(parents=True, exist_ok=True)
                if not overwrite and out_path.exists():
                    return str(out_path)
                if img.mode != "RGB":
                    img = img.convert("RGB")
                img.save(out_path, format="JPEG", quality=85, optimize=True, progressive=True)
                return str(out_path)

def generate_video_thumbnail(video_path: str, output_path: str, time_position: str = "00:00:01") -> str | None:
    """
    Extract a single JPG frame from a video using ffmpeg and write it to output_path.
    Returns output_path on success, or None on failure.
    """
    try:
        os.makedirs(os.path.dirname(output_path), exist_ok=True)
        cmd = [
            "ffmpeg", "-y",
            "-ss", time_position,
            "-i", str(video_path),
            "-vframes", "1",
            "-vf", f"scale={THUMB_SIZE[0]}:-1",
            str(output_path),
        ]
        subprocess.run(cmd, check=True, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, timeout=FFMPEG_THUMB_TIMEOUT)
        return output_path
    except subprocess.CalledProcessError as e:
        print(f"[WARN] Failed to extract video thumbnail for {video_path}: {e}")
        return None


def generate_video_thumbnail_mirrored(video_path: str, time_position: str = "00:00:01") -> str | None:
    """
    Mirror the stored (hashed) video path under /images/thumbs/... and save as .jpg.
    """
    images_root = Path("/images").resolve()
    video_path_p = Path(video_path).resolve()
    rel_path = video_path_p.relative_to(images_root)  # raises if not under /images
    thumb_path = (images_root / "thumbs" / rel_path).with_suffix(".jpg")
    return generate_video_thumbnail(str(video_path_p), str(thumb_path), time_position=time_position)


def transcode_video_to_mp4(input_path: str, output_path: str = None) -> str | None:
    """
    Transcode a video to H.264 MP4 for universal browser playback.

    Args:
        input_path: Path to source video file
        output_path: Optional destination path. If None, replaces extension with .mp4
                     in a temp location.

    Returns:
        Path to transcoded MP4 file on success, None on failure.
    """
    input_p = Path(input_path)

    # Determine output path
    if output_path is None:
        # Create temp file with .mp4 extension
        output_path = str(input_p.with_suffix(".mp4"))
        if output_path == input_path:
            # Already .mp4, use temp suffix
            output_path = str(input_p.with_suffix(".transcoded.mp4"))

    try:
        os.makedirs(os.path.dirname(output_path), exist_ok=True)

        # FFmpeg command for H.264/AAC transcoding with good browser compatibility
        # -movflags +faststart: Enables progressive playback (moov atom at start)
        # -preset medium: Balance between speed and compression
        # -crf 23: Good quality (lower = better, 18-28 typical range)
        # -c:v libx264: H.264 video codec
        # -c:a aac: AAC audio codec
        # -pix_fmt yuv420p: Pixel format for maximum compatibility
        cmd = [
            "ffmpeg", "-y",
            "-i", str(input_path),
            "-c:v", "libx264",
            "-preset", "medium",
            "-crf", "23",
            "-pix_fmt", "yuv420p",
            "-c:a", "aac",
            "-b:a", "128k",
            "-movflags", "+faststart",
            str(output_path),
        ]

        print(f"[INFO] Transcoding video: {input_path} -> {output_path}")
        result = subprocess.run(
            cmd,
            check=True,
            stdout=subprocess.PIPE,
            stderr=subprocess.PIPE,
            timeout=FFMPEG_TRANSCODE_TIMEOUT
        )
        print(f"[INFO] Transcoding complete: {output_path}")
        return output_path

    except subprocess.TimeoutExpired:
        print(f"[WARN] Video transcode timed out after {FFMPEG_TRANSCODE_TIMEOUT}s: {input_path}")
        # Clean up partial output
        if os.path.exists(output_path):
            os.remove(output_path)
        return None
    except subprocess.CalledProcessError as e:
        print(f"[WARN] Failed to transcode video {input_path}: {e}")
        if e.stderr:
            print(f"[WARN] FFmpeg stderr: {e.stderr.decode('utf-8', errors='ignore')[:500]}")
        # Clean up partial output
        if os.path.exists(output_path):
            os.remove(output_path)
        return None
    except Exception as e:
        print(f"[WARN] Unexpected error transcoding video {input_path}: {e}")
        if os.path.exists(output_path):
            os.remove(output_path)
        return None


def needs_transcode(file_path: str) -> bool:
    """Check if a video file needs transcoding to MP4."""
    ext = Path(file_path).suffix.lower()
    return ext in VIDEO_EXTS_NEED_TRANSCODE


def calculate_hash(file_path: str) -> str:
    hash_func = hashlib.sha256()
    with open(file_path, "rb") as f:
        for chunk in iter(lambda: f.read(1024 * 1024), b""):  # 1MB chunks work well for big files
            hash_func.update(chunk)
    return hash_func.hexdigest()


def calculate_perceptual_hash(file_path: str, hash_size: int = 16):
    """
    Calculate a perceptual hash for an image.

    Args:
        file_path: Path to the image file
        hash_size: Size of the hash grid (default 16 for 256-bit hash)
                   hash_size=8 gives 64-bit, hash_size=16 gives 256-bit

    Returns:
        ImageHash object or None if hashing fails (e.g., for videos)
    """
    try:
        with Image.open(file_path) as img:
            return imagehash.phash(img, hash_size=hash_size)
    except Exception:
        # videos or unreadable images land here (phash not applicable)
        return None


def find_similar_image(phash, width: int, height: int, existing_phashes, threshold: int = 10):
    """
    Find visually similar images and determine relationship.

    Args:
        phash: Perceptual hash of the new image
        width: Width of the new image
        height: Height of the new image
        existing_phashes: List of (phash, width, height, image_id) tuples for existing images
        threshold: Maximum Hamming distance to consider images similar
                   Default is 10 for 256-bit hashes (was 2 for 64-bit)

    Returns:
        tuple: (relationship, image_id) where relationship is one of:
            - None: No similar image found
            - "larger_exists": A larger or equal similar image exists (skip new image)
            - "smaller_exists": A smaller similar image exists (supersede it)
        image_id is the ID of the matching image, or None
    """
    for existing_phash, ew, eh, image_id in existing_phashes:
        try:
            distance = phash - existing_phash
            if distance <= threshold:
                # Similar image found - check size relationship
                if ew >= width and eh >= height:
                    # Existing is larger or equal - skip new image
                    return ("larger_exists", image_id)
                elif width > ew or height > eh:
                    # New image is larger - supersede the existing one
                    return ("smaller_exists", image_id)
        except Exception as e:
            print(f"[WARN] Failed pHash comparison: {e}")
    return (None, None)


def is_similar_image(phash, width: int, height: int, existing_phashes, threshold: int = 10) -> bool:
    """
    Check if an image is visually similar to any existing larger image.

    Legacy wrapper for find_similar_image - returns True only if a larger version exists.
    """
    relationship, _ = find_similar_image(phash, width, height, existing_phashes, threshold)
    return relationship == "larger_exists"


def extract_metadata(file_path: str) -> dict:
    metadata = {
        "file_size": None,
        "width": None,
        "height": None,
        "format": None,
        "camera_model": None,
        "taken_at": None
    }

    metadata["file_size"] = os.path.getsize(file_path)
    ext = os.path.splitext(file_path)[1].lower()

    # Get file modification time as fallback for taken_at
    try:
        file_mtime = datetime.fromtimestamp(os.path.getmtime(file_path))
    except Exception:
        file_mtime = None

    # Video: use ffprobe
    if ext in (".mp4", ".mov"):
        try:
            cmd = [
                "ffprobe", "-v", "error",
                "-select_streams", "v:0",
                "-show_entries", "stream=width,height",
                "-of", "json", file_path
            ]
            result = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.DEVNULL, text=True, check=False)
            data = json.loads(result.stdout or "{}")
            stream = data.get("streams", [{}])[0]
            metadata["width"] = stream.get("width")
            metadata["height"] = stream.get("height")
            metadata["format"] = ext.lstrip(".")
            # Use file mtime for videos since they don't have EXIF
            metadata["taken_at"] = file_mtime
        except Exception as e:
            print(f"[WARN] Failed to extract video metadata: {file_path} – {e}")
        return metadata

    # Image: PIL + EXIF (best-effort)
    try:
        with Image.open(file_path) as img:
            metadata["width"], metadata["height"] = img.size
            metadata["format"] = (img.format or "").lower()
    except Exception as e:
        mime_type, _ = mimetypes.guess_type(file_path)
        print(f"[WARN] Failed to read image metadata: {file_path} ({e}) ext={ext} mime={mime_type}")

    try:
        with open(file_path, "rb") as f:
            tags = exifread.process_file(f, stop_tag="UNDEF", details=False)
        if "EXIF DateTimeOriginal" in tags:
            metadata["taken_at"] = datetime.strptime(str(tags["EXIF DateTimeOriginal"]), "%Y:%m:%d %H:%M:%S")
        if "Image Model" in tags:
            metadata["camera_model"] = str(tags["Image Model"])
    except Exception:
        pass

    # Fallback to file modification time if no EXIF date
    if metadata["taken_at"] is None:
        metadata["taken_at"] = file_mtime

    return metadata

def _has_alpha(img: Image.Image) -> bool:
    """Return True if the image has any transparency channel."""
    if img.mode in ("RGBA", "LA"):
        return True
    if img.mode == "P" and "transparency" in img.info:
        return True
    return False

def _flatten_to_rgb(img: Image.Image, bg=(0, 0, 0)) -> Image.Image:
    """
    Flatten an RGBA/LA/Palette-with-alpha image onto a solid background,
    returning an RGB image suitable for saving as JPEG.
    """
    # Normalize to RGBA so we can use the alpha channel as a mask
    if img.mode == "P":
        img = img.convert("RGBA")
    if img.mode in ("RGBA", "LA"):
        # Ensure we have an explicit alpha channel as last band
        if img.mode == "LA":
            img = img.convert("RGBA")
        alpha = img.split()[-1]  # A channel
        bg_img = Image.new("RGB", img.size, bg)
        bg_img.paste(img, mask=alpha)
        return bg_img
    # No alpha, just convert to RGB
    return img.convert("RGB")


# =============================================================================
# Helpers: Multi-part detection
# =============================================================================

def is_first_volume(path: str) -> bool:
    """
    Determine if 'path' is the first volume of a multi-part archive.
    We only attempt extraction from the first volume.
    """
    name = os.path.basename(path).lower()

    # RAR: .partN.rar (only N==1 is first)
    m = RAR_PART_RE.search(name)
    if m:
        n = m.group(1)
        return n in ("1", "01", "001")

    # RAR old-style: first is .rar, subsequent are .r00, .r01...
    if name.endswith(".rar"):
        return True
    if OLD_RAR_VOL_RE.search(name):
        return False

    # CBR is typically a single-volume RAR
    if name.endswith(".cbr"):
        return True

    # 7z multi-part: .7z.001 is first
    m = SEVENZ_PART_RE.search(name)
    if m:
        n = m.group(1)
        return n in ("1", "01", "001")
    if name.endswith(".7z"):
        return True  # single-volume 7z

    # ZIP and tarballs: treat as single-volume (we don't include .z01 in our allowlist)
    if name.endswith((".zip", ".tar", ".tar.gz", ".tgz", ".tar.bz2", ".tbz2", ".tar.xz", ".txz")):
        return True

    return True

def compute_next_archive_tag_name(artist: str, width: int = ARCHIVE_NUM_WIDTH) -> str:
    """
    Return a unique incremental tag name like: 'archive:{artist}/0001', '0002', ...
    - Looks only at Tag(kind='archive') with names starting 'archive:{artist}/'
    - Finds max numeric suffix and returns next number (zero-padded).
    - Ensures no collision even if tags were renamed.
    """
    prefix = f"archive:{artist}/"
    # Pull existing tag names for this artist/prefix
    rows = (Tag.query
              .with_entities(Tag.name)
              .filter(Tag.kind == 'archive',
                      Tag.name.like(prefix + '%'))
              .all())

    max_n = 0
    for (name,) in rows:
        tail = name[len(prefix):]
        if tail.isdigit():
            try:
                n = int(tail)
                if n > max_n:
                    max_n = n
            except Exception:
                pass

    # Propose next number and make sure it doesn't already exist
    n = max_n + 1
    while True:
        candidate = f"{prefix}{str(n).zfill(width)}"
        if not Tag.query.filter_by(name=candidate).first():
            return candidate
        n += 1

def compute_next_archive_tag_name(artist: str, width: int = ARCHIVE_NUM_WIDTH) -> str:
    """
    Return a unique incremental tag name like: 'archive:{artist}/0001', '0002', ...
    - Looks only at Tag(kind='archive') with names starting 'archive:{artist}/'
    - Finds max numeric suffix and returns next number (zero-padded).
    - Ensures no collision even if tags were renamed.
    """
    prefix = f"archive:{artist}/"
    # Pull existing tag names for this artist/prefix
    rows = (Tag.query
              .with_entities(Tag.name)
              .filter(Tag.kind == 'archive',
                      Tag.name.like(prefix + '%'))
              .all())

    max_n = 0
    for (name,) in rows:
        tail = name[len(prefix):]
        if tail.isdigit():
            try:
                n = int(tail)
                if n > max_n:
                    max_n = n
            except Exception:
                pass

    # Propose next number and make sure it doesn't already exist
    n = max_n + 1
    while True:
        candidate = f"{prefix}{str(n).zfill(width)}"
        if not Tag.query.filter_by(name=candidate).first():
            return candidate
        n += 1