fix: Reprocess example images with missing folders, improve error handling, and add new tests. Fixes #760

tests/services/test_issue_760_repro.py

@@ -0,0 +1,101 @@
+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"]