Files
ComfyUI-Lora-Manager/tests/services/test_issue_760_repro.py

102 lines
3.8 KiB
Python

import asyncio
import json
import pytest
from pathlib import Path
from py.services.settings_manager import get_settings_manager
from py.utils import example_images_download_manager as download_module
class RecordingWebSocketManager:
def __init__(self) -> None:
self.payloads: list[dict] = []
async def broadcast(self, payload: dict) -> None:
self.payloads.append(payload)
class StubScanner:
def __init__(self, models: list[dict]) -> None:
self.raw_data = models
async def get_cached_data(self):
class Cache:
def __init__(self, data): self.raw_data = data
return Cache(self.raw_data)
@pytest.mark.asyncio
async def test_reprocessing_triggered_when_folder_missing(monkeypatch, tmp_path):
# Setup paths
images_root = tmp_path / "examples"
images_root.mkdir()
settings_manager = get_settings_manager()
monkeypatch.setitem(settings_manager.settings, "example_images_path", str(images_root))
monkeypatch.setitem(settings_manager.settings, "libraries", {"default": {}})
monkeypatch.setitem(settings_manager.settings, "active_library", "default")
model_hash = "f" * 64
model_name = "Issue 760 Model"
# Create a progress file where this model is already processed
progress_file = images_root / ".download_progress.json"
progress_file.write_text(json.dumps({
"processed_models": [model_hash],
"failed_models": []
}))
# But the model folder is missing! (repro condition)
model_data = {
"sha256": model_hash,
"model_name": model_name,
"file_path": str(tmp_path / "model.safetensors"),
"file_name": "model.safetensors",
"civitai": {"images": [{"url": "https://example.com/img.png"}]}
}
scanner = StubScanner([model_data])
async def mock_get_lora_scanner():
return scanner
monkeypatch.setattr(download_module.ServiceRegistry, "get_lora_scanner", mock_get_lora_scanner)
# Mock downloader and processor to avoid actual network/file ops
async def fake_get_downloader():
class MockDownloader:
async def download_to_memory(self, *args, **kwargs):
return True, b"data", {"content-type": "image/png"}
return MockDownloader()
monkeypatch.setattr(download_module, "get_downloader", fake_get_downloader)
process_called = False
async def fake_process_local_examples(*args):
nonlocal process_called
process_called = True
return False # Fallback to remote
monkeypatch.setattr(download_module.ExampleImagesProcessor, "process_local_examples", fake_process_local_examples)
async def fake_download_model_images(*args):
# Create the directory so it's "fixed"
model_dir = args[3]
Path(model_dir).mkdir(parents=True, exist_ok=True)
(Path(model_dir) / "image_0.png").write_text("fixed")
return True, False, []
monkeypatch.setattr(download_module.ExampleImagesProcessor, "download_model_images_with_tracking", fake_download_model_images)
# Run the manager
ws_manager = RecordingWebSocketManager()
manager = download_module.DownloadManager(ws_manager=ws_manager)
result = await manager.start_download({"model_types": ["lora"], "delay": 0})
assert result["success"] is True
# Wait for completion
if manager._download_task:
await asyncio.wait_for(manager._download_task, timeout=2)
# Verify reprocessing was triggered
assert model_hash in manager._progress["reprocessed_models"]
assert model_hash in manager._progress["processed_models"] # Should be back in processed
# Verify the progress was saved (discarding reprocessed in memory, but summary logged)
saved_progress = json.loads(progress_file.read_text())
assert model_hash in saved_progress["processed_models"]