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https://github.com/willmiao/ComfyUI-Lora-Manager.git
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feat(metadata): add CivitAI AutoV3 hash support across all storage layers
- Three-state autov3 field (not-checked / checked-unavailable / 12-hex value) in .metadata.json sidecars, in-memory ModelHashIndex, and SQLite (models.autov3 column + autov3_index table) with column-presence migration - Background self-terminating backfill for legacy rows: per-model-type concurrency guard, executor-offloaded I/O, Civitai-first resolution (SHA256-matched version file) falling back to the embedded safetensors header hash - Civitai-first propagation on metadata refresh, scan, and download paths; reject the empty-string SHA256 placeholder and strip OneTrainer 0x prefix - List API hash filters and hash index lookups accept 12-char AutoV3 - Cap safetensors header reads at 64 MiB to prevent crafted-file allocation - Prevent stale AutoV3 mappings on file replacement while preserving them on same-file re-registration (lazy-hash completion)
This commit is contained in:
Will Miao
350
tests/services/test_autov3_backfill_service.py
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350
tests/services/test_autov3_backfill_service.py
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"""Tests for Autov3BackfillService."""
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from __future__ import annotations
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import json
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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import pytest
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from py.services.autov3_backfill_service import Autov3BackfillService
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from py.services.model_cache import ModelCache
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from py.services.model_hash_index import ModelHashIndex
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from py.services.model_scanner import ModelScanner
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from py.services.persistent_model_cache import DEFAULT_LICENSE_FLAGS, PersistentModelCache
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@pytest.fixture(autouse=True)
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def reset_backfill_singleton() -> None:
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"""Reset the service singleton so every test starts from a fresh instance."""
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Autov3BackfillService._instance = None
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yield
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Autov3BackfillService._instance = None
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def _entry(file_path: str, sha256: str, autov3: Optional[str] = None) -> Dict[str, Any]:
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return {
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'file_path': file_path,
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'file_name': Path(file_path).stem,
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'model_name': Path(file_path).stem,
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'folder': '',
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'size': 1,
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'modified': 1.0,
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'sha256': sha256,
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'autov3': autov3,
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'base_model': '',
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'preview_url': '',
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'preview_nsfw_level': 0,
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'from_civitai': True,
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'favorite': False,
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'notes': '',
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'usage_tips': '',
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'metadata_source': None,
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'exclude': False,
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'db_checked': False,
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'last_checked_at': 0.0,
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'tags': [],
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'civitai': None,
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'civitai_deleted': False,
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'skip_metadata_refresh': False,
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'license_flags': DEFAULT_LICENSE_FLAGS,
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'hash_status': 'completed',
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'hf_url': '',
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}
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class RecordingScanner:
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"""Duck-typed scanner double persisting updates to a real cache."""
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def __init__(
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self,
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model_type: str,
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persistent_cache: PersistentModelCache,
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entries: List[Dict[str, Any]],
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) -> None:
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self.model_type = model_type
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self._persistent_cache = persistent_cache
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self.entries: Dict[str, Dict[str, Any]] = {entry['file_path']: entry for entry in entries}
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self.update_calls: List[tuple] = []
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async def update_autov3_for_model(self, model_type: str, file_path: str, autov3: str) -> bool:
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self.update_calls.append((model_type, file_path, autov3))
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entry = self.entries.get(file_path)
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if entry is None:
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return False
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old_item = dict(entry)
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new_item = dict(entry)
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new_item['autov3'] = autov3
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self._persistent_cache.update_single_model(model_type, new_item, old_item)
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entry['autov3'] = autov3
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return True
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def _make_store(tmp_path: Path, monkeypatch, name: str = 'cache.sqlite') -> PersistentModelCache:
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monkeypatch.setenv('LORA_MANAGER_DISABLE_PERSISTENT_CACHE', '0')
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return PersistentModelCache(db_path=str(tmp_path / name))
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def _write_file(tmp_path: Path, name: str) -> str:
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path = tmp_path / name
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path.write_text(name, encoding='utf-8')
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return path.as_posix()
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async def test_backfill_updates_models_and_self_terminates(tmp_path: Path, monkeypatch) -> None:
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store = _make_store(tmp_path, monkeypatch)
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path_a = _write_file(tmp_path, 'a.txt')
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path_b = _write_file(tmp_path, 'b.txt')
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checked = (tmp_path / 'checked.txt').as_posix()
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valued = (tmp_path / 'valued.txt').as_posix()
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entries = [
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_entry(path_a, 'hash-a'),
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_entry(path_b, 'hash-b'),
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_entry(checked, 'hash-checked', autov3=''),
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_entry(valued, 'hash-valued', autov3='a1b2c3d4e5f6'),
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]
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store.save_cache(
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'dummy',
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entries,
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{e['sha256']: [e['file_path']] for e in entries},
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[],
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)
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scanner = RecordingScanner('dummy', store, entries)
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updated = await Autov3BackfillService.get_instance().backfill(scanner)
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# Non-safetensors files yield no embedded hash, so both are marked ''.
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assert updated == 2
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assert set(scanner.update_calls) == {('dummy', path_a, ''), ('dummy', path_b, '')}
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# Self-terminating: the driving query now finds no remaining rows.
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assert store.get_models_missing_autov3('dummy') == []
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persisted = store.load_cache('dummy')
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items = {item['file_path']: item for item in persisted.raw_data}
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assert items[path_a]['autov3'] == ''
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assert items[path_b]['autov3'] == ''
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# Checked-unavailable and valued rows are never recomputed or touched.
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assert items[checked]['autov3'] == ''
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assert items[valued]['autov3'] == 'a1b2c3d4e5f6'
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async def test_backfill_skips_missing_files_without_marking(tmp_path: Path, monkeypatch) -> None:
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store = _make_store(tmp_path, monkeypatch)
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existing = _write_file(tmp_path, 'existing.txt')
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missing = (tmp_path / 'missing.txt').as_posix()
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entries = [_entry(existing, 'hash-existing'), _entry(missing, 'hash-missing')]
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store.save_cache(
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'dummy',
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entries,
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{'hash-existing': [existing], 'hash-missing': [missing]},
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[],
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)
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scanner = RecordingScanner('dummy', store, entries)
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updated = await Autov3BackfillService.get_instance().backfill(scanner)
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assert updated == 1
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assert scanner.update_calls == [('dummy', existing, '')]
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# The missing row was not marked, so it still appears in the query.
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assert store.get_models_missing_autov3('dummy') == [missing]
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async def test_backfill_returns_zero_when_same_type_already_running(tmp_path: Path, monkeypatch) -> None:
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store = _make_store(tmp_path, monkeypatch)
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scanner = RecordingScanner('dummy', store, [])
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service = Autov3BackfillService.get_instance()
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service._running_types = {'dummy'}
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try:
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assert await service.backfill(scanner) == 0
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finally:
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service._running_types = set()
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assert scanner.update_calls == []
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async def test_backfill_runs_concurrently_for_different_model_types(tmp_path: Path, monkeypatch) -> None:
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"""Scanners initialize in parallel (lora_manager.py), so a backfill for one
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model type must not skip another type's backfill."""
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store = _make_store(tmp_path, monkeypatch)
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lora_file = _write_file(tmp_path, 'lora.txt')
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ckpt_file = _write_file(tmp_path, 'ckpt.txt')
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store.save_cache(
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'lora',
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[_entry(lora_file, 'hash-lora')],
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{'hash-lora': [lora_file]},
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[],
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)
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store.save_cache(
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'checkpoint',
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[_entry(ckpt_file, 'hash-ckpt')],
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{'hash-ckpt': [ckpt_file]},
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[],
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)
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lora_scanner = RecordingScanner('lora', store, [_entry(lora_file, 'hash-lora')])
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ckpt_scanner = RecordingScanner('checkpoint', store, [_entry(ckpt_file, 'hash-ckpt')])
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service = Autov3BackfillService.get_instance()
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service._running_types = {'checkpoint'} # Simulate a checkpoint backfill in flight
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try:
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# The lora backfill must still run while checkpoint is in progress.
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assert await service.backfill(lora_scanner) == 1
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assert lora_scanner.update_calls == [('lora', lora_file, '')]
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finally:
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service._running_types = set()
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async def test_backfill_never_raises_on_failure(tmp_path: Path, monkeypatch) -> None:
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store = _make_store(tmp_path, monkeypatch)
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existing = _write_file(tmp_path, 'boom.txt')
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class RaisingScanner(RecordingScanner):
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async def update_autov3_for_model(self, model_type: str, file_path: str, autov3: str) -> bool:
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raise RuntimeError('boom')
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entries = [_entry(existing, 'hash-boom')]
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store.save_cache('dummy', entries, {'hash-boom': [existing]}, [])
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scanner = RaisingScanner('dummy', store, entries)
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updated = await Autov3BackfillService.get_instance().backfill(scanner)
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assert updated == 0
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async def test_backfill_uses_default_cache_when_scanner_has_none(tmp_path: Path, monkeypatch) -> None:
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store = _make_store(tmp_path, monkeypatch)
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existing = _write_file(tmp_path, 'model.txt')
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entries = [_entry(existing, 'hash-x')]
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store.save_cache('dummy', entries, {'hash-x': [existing]}, [])
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from py.services import persistent_model_cache as pmc_module
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monkeypatch.setattr(pmc_module, 'get_persistent_cache', lambda: store)
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class BareScanner:
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model_type = 'dummy'
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async def update_autov3_for_model(self, model_type: str, file_path: str, autov3: str) -> bool:
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entry = next(e for e in entries if e['file_path'] == file_path)
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old_item = dict(entry)
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new_item = dict(entry)
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new_item['autov3'] = autov3
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store.update_single_model(model_type, new_item, old_item)
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return True
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updated = await Autov3BackfillService.get_instance().backfill(BareScanner())
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assert updated == 1
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assert store.get_models_missing_autov3('dummy') == []
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async def test_backfill_idempotent_second_run_is_noop(tmp_path: Path, monkeypatch) -> None:
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store = _make_store(tmp_path, monkeypatch)
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existing = _write_file(tmp_path, 'idem.txt')
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entries = [_entry(existing, 'hash-idem')]
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store.save_cache('dummy', entries, {'hash-idem': [existing]}, [])
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scanner = RecordingScanner('dummy', store, entries)
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service = Autov3BackfillService.get_instance()
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assert await service.backfill(scanner) == 1
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# A re-run has nothing left to do.
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assert await service.backfill(scanner) == 0
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assert len(scanner.update_calls) == 1
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async def test_backfill_end_to_end_through_scanner_lazy_import(tmp_path: Path, monkeypatch) -> None:
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"""Drive the scanner's lazy-import trigger (`_run_autov3_backfill`) end to end."""
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store = _make_store(tmp_path, monkeypatch)
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path_a = _write_file(tmp_path, 'alpha.txt')
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path_b = _write_file(tmp_path, 'beta.txt')
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entries = [_entry(path_a, 'hash-alpha'), _entry(path_b, 'hash-beta')]
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store.save_cache(
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'dummy',
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entries,
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{'hash-alpha': [path_a], 'hash-beta': [path_b]},
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[],
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)
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class RealScanner(ModelScanner):
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def __init__(self) -> None:
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self.model_type = 'dummy'
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self._persistent_cache = store
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self._cache = ModelCache(raw_data=[dict(e) for e in entries], folders=[])
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self._hash_index = ModelHashIndex()
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await RealScanner()._run_autov3_backfill()
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assert store.get_models_missing_autov3('dummy') == []
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persisted = store.load_cache('dummy')
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items = {item['file_path']: item for item in persisted.raw_data}
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assert items[path_a]['autov3'] == ''
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assert items[path_b]['autov3'] == ''
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async def test_backfill_prefers_civitai_autov3_from_sidecar(tmp_path: Path, monkeypatch) -> None:
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"""Backfill uses the Civitai AutoV3 for the SHA256-matching file when the
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sidecar carries Civitai metadata, even if the file itself has no embedded
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header hash (the checkpoint case)."""
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store = _make_store(tmp_path, monkeypatch)
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path = _write_file(tmp_path, 'ckpt.txt') # non-safetensors: no header hash
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sidecar = tmp_path / 'ckpt.metadata.json'
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sidecar.write_text(
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json.dumps({
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"sha256": "hash-ckpt",
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"civitai": {
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"files": [
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{"name": "other.safetensors", "hashes": {"SHA256": "zzz999"}},
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{"name": "ckpt.safetensors", "hashes": {"SHA256": "HASH-CKPT", "AutoV3": "ABCDEF1234567890"}},
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]
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},
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}),
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encoding='utf-8',
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)
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store.save_cache('dummy', [_entry(path, 'hash-ckpt')], {'hash-ckpt': [path]}, [])
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scanner = RecordingScanner('dummy', store, [_entry(path, 'hash-ckpt')])
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updated = await Autov3BackfillService.get_instance().backfill(scanner)
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assert updated == 1
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assert scanner.update_calls == [('dummy', path, 'abcdef123456')]
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persisted = store.load_cache('dummy')
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items = {item['file_path']: item for item in persisted.raw_data}
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assert items[path]['autov3'] == 'abcdef123456'
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# Self-terminating: the row is marked and the driving query empties.
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assert store.get_models_missing_autov3('dummy') == []
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async def test_backfill_falls_back_to_header_when_sidecar_has_no_match(tmp_path: Path, monkeypatch) -> None:
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"""When the sidecar's Civitai files do not contain a SHA256 match, the
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backfill falls back to the embedded header hash ('' for non-safetensors)."""
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store = _make_store(tmp_path, monkeypatch)
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path = _write_file(tmp_path, 'plain.txt')
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sidecar = tmp_path / 'plain.metadata.json'
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sidecar.write_text(
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json.dumps({
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"sha256": "hash-plain",
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"civitai": {"files": [{"name": "other.safetensors", "hashes": {"SHA256": "zzz999", "AutoV3": "ABCDEF123456"}}]},
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}),
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encoding='utf-8',
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)
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store.save_cache('dummy', [_entry(path, 'hash-plain')], {'hash-plain': [path]}, [])
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scanner = RecordingScanner('dummy', store, [_entry(path, 'hash-plain')])
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updated = await Autov3BackfillService.get_instance().backfill(scanner)
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assert updated == 1
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assert scanner.update_calls == [('dummy', path, '')]
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