From 44c6984f7397917bdabd2c86f7a1786b51e9bf2d Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Fri, 3 Jul 2026 11:58:24 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 .../training/diffusion_training_service.py    |  4 +--
 studio/backend/routes/training.py             |  1 -
 .../backend/tests/test_diffusion_training.py  | 28 ++++++++++++++-----
 3 files changed, 22 insertions(+), 11 deletions(-)

diff --git a/studio/backend/core/training/diffusion_training_service.py b/studio/backend/core/training/diffusion_training_service.py
index 0f57f4d4ca..fb1527b8bf 100644
--- a/studio/backend/core/training/diffusion_training_service.py
+++ b/studio/backend/core/training/diffusion_training_service.py
@@ -77,9 +77,7 @@ def list_diffusion_runs(limit: int = 20) -> list[dict]:
     """Summaries of persisted diffusion runs, newest first. The heavy per-run payload
     (metric logs, config) stays in the file; fetch it via ``get_diffusion_run``."""
     try:
-        files = sorted(
-            _runs_dir().glob("*.json"), key = lambda p: p.stat().st_mtime, reverse = True
-        )
+        files = sorted(_runs_dir().glob("*.json"), key = lambda p: p.stat().st_mtime, reverse = True)
     except Exception:  # noqa: BLE001 -- unreadable dir -> no history
         return []
     out: list[dict] = []
diff --git a/studio/backend/routes/training.py b/studio/backend/routes/training.py
index a25983dcc3..1a85089439 100644
--- a/studio/backend/routes/training.py
+++ b/studio/backend/routes/training.py
@@ -1285,7 +1285,6 @@ async def list_diffusion_training_runs(
     """Previous diffusion training runs (terminal), newest first, from the persisted
     per-run records. Summaries only; fetch one run for its config + metric logs."""
     from core.training.diffusion_training_service import list_diffusion_runs
-
     return DiffusionTrainingRunsResponse(
         runs = [DiffusionTrainingRunSummary(**r) for r in list_diffusion_runs(limit = limit)]
     )
diff --git a/studio/backend/tests/test_diffusion_training.py b/studio/backend/tests/test_diffusion_training.py
index ad43cf85f0..c9bb62335a 100644
--- a/studio/backend/tests/test_diffusion_training.py
+++ b/studio/backend/tests/test_diffusion_training.py
@@ -670,7 +670,9 @@ def test_run_record_no_save_stop_marks_unsaved(_isolated_runs_dir):
     def _cancel_target(*, event_queue, stop_queue, config):
         event_queue.put({"type": "model_load_completed"})
         stop_queue.get(timeout = 5.0)
-        event_queue.put({"type": "complete", "output_dir": None, "lora_path": None, "stopped": True})
+        event_queue.put(
+            {"type": "complete", "output_dir": None, "lora_path": None, "stopped": True}
+        )
 
     svc = DiffusionTrainingService(ctx = _FakeCtx(), target = _cancel_target)
     job_id = svc.start(dict(_CFG))
@@ -692,14 +694,26 @@ def test_runs_endpoints_list_and_detail(client, _isolated_runs_dir):
     import os
 
     a = {
-        "job_id": "a" * 32, "status": "completed", "adapter": "first", "saved": True,
-        "step": 10, "total_steps": 10, "avg_loss": 0.4,
-        "config": {"train_steps": 10}, "metric_history": {"steps": [1], "loss": [0.4], "lr": [1e-4], "grad_norm": [0.2]},
+        "job_id": "a" * 32,
+        "status": "completed",
+        "adapter": "first",
+        "saved": True,
+        "step": 10,
+        "total_steps": 10,
+        "avg_loss": 0.4,
+        "config": {"train_steps": 10},
+        "metric_history": {"steps": [1], "loss": [0.4], "lr": [1e-4], "grad_norm": [0.2]},
     }
     b = {
-        "job_id": "b" * 32, "status": "stopped", "adapter": "second", "saved": False,
-        "step": 3, "total_steps": 10, "avg_loss": 0.6,
-        "config": {"train_steps": 10}, "metric_history": {"steps": [1], "loss": [0.6], "lr": [1e-4], "grad_norm": [0.3]},
+        "job_id": "b" * 32,
+        "status": "stopped",
+        "adapter": "second",
+        "saved": False,
+        "step": 3,
+        "total_steps": 10,
+        "avg_loss": 0.6,
+        "config": {"train_steps": 10},
+        "metric_history": {"steps": [1], "loss": [0.6], "lr": [1e-4], "grad_norm": [0.3]},
     }
     pa = _isolated_runs_dir / f"{a['job_id']}.json"
     pb = _isolated_runs_dir / f"{b['job_id']}.json"