feat: normalize and validate checkpoint entries in recipes

Add _normalize_checkpoint_entry method to handle legacy and malformed checkpoint data by:
- Converting string entries to structured dict format
- Handling single-element lists/tuples recursively
- Dropping invalid entries with appropriate warnings
- Maintaining backward compatibility while improving data consistency

Add test case to verify string checkpoint conversion works correctly.

py/services/recipe_scanner.py

@@ -441,7 +441,12 @@ class RecipeScanner:
             await self._update_lora_information(recipe_data)
 
             if recipe_data.get('checkpoint'):
-                recipe_data['checkpoint'] = self._enrich_checkpoint_entry(dict(recipe_data['checkpoint']))
+                checkpoint_entry = self._normalize_checkpoint_entry(recipe_data['checkpoint'])
+                if checkpoint_entry:
+                    recipe_data['checkpoint'] = self._enrich_checkpoint_entry(checkpoint_entry)
+                else:
+                    logger.warning("Dropping invalid checkpoint entry in %s", recipe_path)
+                    recipe_data.pop('checkpoint', None)
 
             # Calculate and update fingerprint if missing
             if 'loras' in recipe_data and 'fingerprint' not in recipe_data:
@@ -665,6 +670,29 @@ class RecipeScanner:
             logger.error(f"Error getting base model for lora: {e}")
             return None
 
+    def _normalize_checkpoint_entry(self, checkpoint_raw: Any) -> Optional[Dict[str, Any]]:
+        """Coerce legacy or malformed checkpoint entries into a dict."""
+
+        if isinstance(checkpoint_raw, dict):
+            return dict(checkpoint_raw)
+
+        if isinstance(checkpoint_raw, (list, tuple)) and len(checkpoint_raw) == 1:
+            return self._normalize_checkpoint_entry(checkpoint_raw[0])
+
+        if isinstance(checkpoint_raw, str):
+            name = checkpoint_raw.strip()
+            if not name:
+                return None
+
+            file_name = os.path.splitext(os.path.basename(name))[0]
+            return {
+                "name": name,
+                "file_name": file_name,
+            }
+
+        logger.warning("Unexpected checkpoint payload type %s", type(checkpoint_raw).__name__)
+        return None
+
     def _enrich_checkpoint_entry(self, checkpoint: Dict[str, Any]) -> Dict[str, Any]:
         """Populate convenience fields for a checkpoint entry."""
 

tests/services/test_recipe_scanner.py

@@ -226,6 +226,36 @@ async def test_load_recipe_rewrites_missing_image_path(tmp_path: Path, recipe_sc
     assert persisted["file_path"] == expected_path
 
 
+@pytest.mark.asyncio
+async def test_load_recipe_upgrades_string_checkpoint(tmp_path: Path, recipe_scanner):
+    scanner, _ = recipe_scanner
+    recipes_dir = Path(config.loras_roots[0]) / "recipes"
+    recipes_dir.mkdir(parents=True, exist_ok=True)
+
+    recipe_id = "legacy-checkpoint"
+    image_path = recipes_dir / f"{recipe_id}.webp"
+    recipe_path = recipes_dir / f"{recipe_id}.recipe.json"
+    recipe_path.write_text(
+        json.dumps(
+            {
+                "id": recipe_id,
+                "file_path": str(image_path),
+                "title": "Legacy",
+                "modified": 0.0,
+                "created_date": 0.0,
+                "loras": [],
+                "checkpoint": "sd15.safetensors",
+            }
+        )
+    )
+
+    loaded = await scanner._load_recipe_file(str(recipe_path))
+
+    assert isinstance(loaded["checkpoint"], dict)
+    assert loaded["checkpoint"]["name"] == "sd15.safetensors"
+    assert loaded["checkpoint"]["file_name"] == "sd15"
+
+
 def test_enrich_uses_version_index_when_hash_missing(recipe_scanner):
     scanner, stub = recipe_scanner
     version_id = 77