Studio: apply ruff-format kwarg spacing to the diffusion review changes

studio/backend/routes/models.py

@@ -3223,6 +3223,7 @@ def _arch_to_task(arch: Optional[str], name_hints: tuple[Optional[str], ...] = (
         # GGUF (which the loader also cannot resolve) stays in the unsupported bucket rather than
         # advertising a GGUF that would 400 on load.
         from core.inference.video_families import detect_video_family
+
         fam = detect_video_family("", override = a)
         if fam is None:
             for hint in name_hints:
@@ -3250,9 +3251,7 @@ def _repo_gguf_task(repo_info) -> Optional[str]:
         for path in _iter_gguf_paths(Path(repo_info.repo_path)):
             if _is_mmproj_filename(path.name):
                 continue
-            task = _arch_to_task(
-                _gguf_architecture(str(path)), name_hints = (repo_id, path.name)
-            )
+            task = _arch_to_task(_gguf_architecture(str(path)), name_hints = (repo_id, path.name))
             if task is not None:
                 return task
     except Exception:
@@ -3274,15 +3273,11 @@ def _local_model_task(model: "LocalModelInfo") -> Optional[str]:
         try:
             p = Path(path)
             if p.suffix.lower() == ".gguf" and p.is_file():
-                return _arch_to_task(
-                    _gguf_architecture(str(p)), name_hints = _id_hints + (p.name,)
-                )
+                return _arch_to_task(_gguf_architecture(str(p)), name_hints = _id_hints + (p.name,))
             for f in _iter_gguf_paths(p):
                 if _is_mmproj_filename(f.name):
                     continue
-                task = _arch_to_task(
-                    _gguf_architecture(str(f)), name_hints = _id_hints + (f.name,)
-                )
+                task = _arch_to_task(_gguf_architecture(str(f)), name_hints = _id_hints + (f.name,))
                 if task is not None:
                     return task
         except Exception:
@@ -3298,7 +3293,11 @@ def _local_model_task(model: "LocalModelInfo") -> Optional[str]:
             from core.inference.video import _is_trusted_video_repo
             from core.inference.video_families import detect_video_family
             for needle in (model.model_id, model.display_name, model.id):
-                if needle and detect_video_family(needle) is not None and _is_trusted_video_repo(path):
+                if (
+                    needle
+                    and detect_video_family(needle) is not None
+                    and _is_trusted_video_repo(path)
+                ):
                     return _VIDEO_GEN_TASK
         except Exception:
             pass

studio/backend/routes/training.py

@@ -2120,9 +2120,7 @@ async def import_diffusion_dataset_example(
             # above would treat that partial result as complete on the next retry (imported=0)
             # and strand the user with a truncated dataset (there is no dataset-delete flow).
             # Staged as a hidden sibling on the same filesystem so promotion is an atomic rename.
-            staging = Path(
-                tempfile.mkdtemp(dir = folder.parent, prefix = f".{folder.name}.import-")
-            )
+            staging = Path(tempfile.mkdtemp(dir = folder.parent, prefix = f".{folder.name}.import-"))
             try:
                 try:
                     if entry["loader"] == "imagefolder_jsonl":

studio/backend/tests/test_diffusion_backend.py

@@ -1244,9 +1244,7 @@ def test_resolve_base_repo_drops_untrusted_card_tag(monkeypatch):
     fam = detect_family("unsloth/FLUX.1-dev-GGUF")
     # A malicious card tag is ignored -> the family default base is used instead.
     monkeypatch.setattr(dmod, "_hf_base_model", lambda repo_id, hf_token: "attacker/evil-pipeline")
-    assert (
-        _resolve_base_repo("attacker/flux.1-evil-GGUF", None, fam, None) == fam.base_repo
-    )
+    assert _resolve_base_repo("attacker/flux.1-evil-GGUF", None, fam, None) == fam.base_repo
     # A trusted (allowlisted) card tag is still honoured, so variant resolution is not regressed.
     monkeypatch.setattr(
         dmod, "_hf_base_model", lambda repo_id, hf_token: "black-forest-labs/FLUX.1-dev"

studio/backend/tests/test_gpu_selection.py

@@ -936,9 +936,7 @@ class TestRouteErrors(unittest.TestCase):
                 "ModelConfig",
                 SimpleNamespace(from_identifier = lambda **_kwargs: model_config),
             ),
-            patch.object(
-                inference_route, "_guard_chat_load_against_training", return_value = None
-            ),
+            patch.object(inference_route, "_guard_chat_load_against_training", return_value = None),
             patch.object(inference_route.asyncio, "to_thread", new = _inline_to_thread),
             patch.object(inference_route, "_hf_offline_if_dns_dead", nullcontext),
             patch.object(arb, "acquire_for", lambda owner: acquired.append(owner)),

studio/backend/tests/test_middleware.py

@@ -176,9 +176,7 @@ class TestMaxBodyMiddleware:
         )
 
         path = "/api/train/diffusion/dataset"
-        assert any(
-            path.startswith(p) for p in main_module._BODY_UPLOAD_PASSTHROUGH_PREFIXES
-        )
+        assert any(path.startswith(p) for p in main_module._BODY_UPLOAD_PASSTHROUGH_PREFIXES)
         cap = main_module._get_upload_passthrough_request_max_bytes(path)
         assert cap == upload_request_limit_bytes()  # DB-aware cap + multipart overhead
         assert cap > default_request_body_limit_bytes()  # not the plain default body cap
@@ -196,9 +194,7 @@ class TestMaxBodyMiddleware:
             "/v1/messages",
             "/v1/chat/completions",
         ):
-            assert any(
-                path.startswith(p) for p in main_module._BODY_PROTECTED_PREFIXES
-            ), path
+            assert any(path.startswith(p) for p in main_module._BODY_PROTECTED_PREFIXES), path
 
     def test_upload_passthrough_rejects_declared_body_over_dedicated_cap(self, main_module):
         app = _make_protected_app(