Will Miao
19abf7ed03
Distinguish same-version quantized models (e.g. GGUF Q4_K_M vs Q8_0) on cards, which previously showed only the identical CivitAI version name. Detection is content-based and stored as a three-state sidecar field (absent = unchecked, "" = checked-unavailable, value = canonical name), mirroring the autov3 pipeline: - GGUF: minimal pure-struct header parser reads general.file_type - safetensors: dominant tensor dtype F8_* -> FP8 - CivitAI files[].metadata.fp == "fp8" fills in as a fallback only - A one-time backfill service covers existing libraries; each file costs only a few-hundred-byte header read The footer renders the badge after the version name (suppressed in grouped mode), gated by a new show_quantization_on_card setting that follows the show_version_on_card toggle pattern.
338 lines
12 KiB
Python
338 lines
12 KiB
Python
"""Tests for QuantizationBackfillService."""
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from __future__ import annotations
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import io
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import json
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import struct
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from pathlib import Path
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from typing import Any, Dict, Iterator, List, Optional
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import pytest
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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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from py.services.quantization_backfill_service import QuantizationBackfillService
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@pytest.fixture(autouse=True)
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def reset_backfill_singleton() -> Iterator[None]:
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"""Reset the service singleton so every test starts from a fresh instance."""
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QuantizationBackfillService._instance = None
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yield
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QuantizationBackfillService._instance = None
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def _entry(file_path: str, sha256: str, quantization: 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': '',
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'quantization': quantization,
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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[str, str, str]] = []
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async def update_quantization_for_model(self, model_type: str, file_path: str, quantization: str) -> bool:
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self.update_calls.append((model_type, file_path, quantization))
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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['quantization'] = quantization
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self._persistent_cache.update_single_model(model_type, new_item, old_item)
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entry['quantization'] = quantization
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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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def _write_gguf(tmp_path: Path, name: str, file_type: int) -> str:
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"""Write a minimal GGUF file whose general.file_type is ``file_type``."""
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blob = io.BytesIO()
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blob.write(b"GGUF")
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blob.write(struct.pack("<I", 3)) # version
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blob.write(struct.pack("<Q", 0)) # tensor_count
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blob.write(struct.pack("<Q", 1)) # metadata_kv_count
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key = b"general.file_type"
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blob.write(struct.pack("<Q", len(key)))
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blob.write(key)
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blob.write(struct.pack("<I", 4)) # UINT32
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blob.write(struct.pack("<I", file_type))
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path = tmp_path / name
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path.write_bytes(blob.getvalue())
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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', quantization=''),
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_entry(valued, 'hash-valued', quantization='Q4_K_M'),
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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 QuantizationBackfillService.get_instance().backfill(scanner) # pyright: ignore[reportArgumentType]
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# Non-model files yield no detectable quantization, 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_quantization('dummy') == []
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persisted = store.load_cache('dummy')
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assert persisted is not None
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items = {item['file_path']: item for item in persisted.raw_data}
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assert items[path_a]['quantization'] == ''
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assert items[path_b]['quantization'] == ''
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# Checked-unavailable and valued rows are never recomputed or touched.
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assert items[checked]['quantization'] == ''
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assert items[valued]['quantization'] == 'Q4_K_M'
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async def test_backfill_detects_gguf_quantization(tmp_path: Path, monkeypatch) -> None:
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store = _make_store(tmp_path, monkeypatch)
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path = _write_gguf(tmp_path, 'model.gguf', 15) # MOSTLY_Q4_K_M
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entries = [_entry(path, 'hash-gguf')]
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store.save_cache('dummy', entries, {'hash-gguf': [path]}, [])
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scanner = RecordingScanner('dummy', store, entries)
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updated = await QuantizationBackfillService.get_instance().backfill(scanner) # pyright: ignore[reportArgumentType]
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assert updated == 1
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assert scanner.update_calls == [('dummy', path, 'Q4_K_M')]
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persisted = store.load_cache('dummy')
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assert persisted is not None
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items = {item['file_path']: item for item in persisted.raw_data}
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assert items[path]['quantization'] == 'Q4_K_M'
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assert store.get_models_missing_quantization('dummy') == []
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async def test_backfill_falls_back_to_civitai_fp8_from_sidecar(tmp_path: Path, monkeypatch) -> None:
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"""Content detection is inconclusive for a non-model file; the Civitai
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fp8 flag of the SHA256-matching file fills the gap."""
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store = _make_store(tmp_path, monkeypatch)
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path = _write_file(tmp_path, 'ckpt.txt')
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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"}, "metadata": {"fp": "fp16"}},
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{"name": "ckpt.safetensors", "hashes": {"SHA256": "HASH-CKPT"}, "metadata": {"fp": "fp8"}},
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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 QuantizationBackfillService.get_instance().backfill(scanner) # pyright: ignore[reportArgumentType]
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assert updated == 1
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assert scanner.update_calls == [('dummy', path, 'FP8')]
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persisted = store.load_cache('dummy')
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assert persisted is not None
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items = {item['file_path']: item for item in persisted.raw_data}
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assert items[path]['quantization'] == 'FP8'
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assert store.get_models_missing_quantization('dummy') == []
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async def test_backfill_content_detection_beats_civitai_fp16(tmp_path: Path, monkeypatch) -> None:
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"""A detected GGUF quantization wins over Civitai metadata."""
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store = _make_store(tmp_path, monkeypatch)
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path = _write_gguf(tmp_path, 'model.gguf', 7) # MOSTLY_Q8_0
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sidecar = tmp_path / 'model.metadata.json'
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sidecar.write_text(
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json.dumps({
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"sha256": "hash-gguf",
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"civitai": {
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"files": [
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{"name": "model.gguf", "hashes": {"SHA256": "hash-gguf"}, "metadata": {"fp": "fp8"}},
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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-gguf')], {'hash-gguf': [path]}, [])
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scanner = RecordingScanner('dummy', store, [_entry(path, 'hash-gguf')])
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updated = await QuantizationBackfillService.get_instance().backfill(scanner) # pyright: ignore[reportArgumentType]
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assert updated == 1
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assert scanner.update_calls == [('dummy', path, 'Q8_0')]
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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 QuantizationBackfillService.get_instance().backfill(scanner) # pyright: ignore[reportArgumentType]
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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_quantization('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 = QuantizationBackfillService.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 # pyright: ignore[reportArgumentType]
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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_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_quantization_for_model(self, model_type: str, file_path: str, quantization: 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 QuantizationBackfillService.get_instance().backfill(scanner) # pyright: ignore[reportArgumentType]
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assert updated == 0
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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 = QuantizationBackfillService.get_instance()
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assert await service.backfill(scanner) == 1 # pyright: ignore[reportArgumentType]
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# A re-run has nothing left to do.
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assert await service.backfill(scanner) == 0 # pyright: ignore[reportArgumentType]
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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_quantization_backfill`) end to end."""
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store = _make_store(tmp_path, monkeypatch)
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path_a = _write_gguf(tmp_path, 'alpha.gguf', 15)
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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: # pyright: ignore[reportMissingSuperCall]
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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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self._cache_version = 0
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await RealScanner()._run_quantization_backfill()
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assert store.get_models_missing_quantization('dummy') == []
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persisted = store.load_cache('dummy')
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assert persisted is not None
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items = {item['file_path']: item for item in persisted.raw_data}
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assert items[path_a]['quantization'] == 'Q4_K_M'
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assert items[path_b]['quantization'] == ''
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