refactor(upscale): drop LoRA support per spec

CLAUDE.md and docs/superpowers/specs marked LoRA on the Upscale refinement
pass as out-of-scope for v1, but the UI + handler still exposed it. In
practice the upscale flow is RealESRGAN x2 -> 5 step Z-Image-Turbo img2img
at 0.33 denoising — a window so tight that style LoRAs (Toon5, DarkGhibly,
etc.) have almost no purchase on the output. Worse, users expect "Use a
LoRA" to actually do something visible.

Remove:
- LoRA checkbox / file / strength group from ui.build_upscale_tab
- lora_enabled/lora_path/lora_strength params + _coerce_lora call in
app.on_upscale_generate
- The lora_enabled.change visibility wiring in build_app
- applied_lora wrapper + lora/lora_strength meta fields in
modes.call_upscale

Test coverage:
- Update existing call_upscale tests to drop the no-longer-accepted
lora_path / lora_strength params.
- Add test_build_upscale_tab_has_no_lora_components to lock the UI
surface against regression.

The lora module + the T2I/ControlNet LoRA paths are untouched.

app.py

@@ -206,26 +206,14 @@ def on_upscale_generate(
     refine_steps,
     refine_denoise,
     seed,
-    lora_enabled,
-    lora_path,
-    lora_strength,
     progress=gr.Progress(track_tqdm=True),  # noqa: B008
 ):
-    if not lora_enabled:
-        lora_path = None
-    try:
-        lora_p = _coerce_lora(lora_path)
-    except lora_mod.LoRAValidationError as e:
-        raise gr.Error(str(e)) from e
-
     params = dict(
         prompt=prompt or "masterpiece, 8k",
         input_image=input_image,
         refine_steps=int(refine_steps),
         refine_denoise=float(refine_denoise),
         seed=_maybe_random_seed(int(seed)),
-        lora_path=lora_p,
-        lora_strength=float(lora_strength),
         esrgan_model_path=_esrgan_path(),
     )
     image, meta = backend.generate_with_retry(get_backend(), mode="upscale", params=params)
@@ -344,17 +332,9 @@ def build_app() -> gr.Blocks:
                         u["refine_steps"],
                         u["refine_denoise"],
                         u["seed"],
-                        u["lora_enabled"],
-                        u["lora_path"],
-                        u["lora_strength"],
                     ],
                     outputs=[u["output_image"], u["output_meta"]],
                 )
-                u["lora_enabled"].change(
-                    fn=lambda v: gr.Group(visible=v),
-                    inputs=[u["lora_enabled"]],
-                    outputs=[u["lora_group"]],
-                )
     return demo
 
 

modes.py

@@ -185,8 +185,7 @@ def call_upscale(pipe: Any, params: dict[str, Any]) -> tuple[Image.Image, dict[s
         seed=int(params.get("seed", 0)),
     )
 
-    with lora.applied_lora(pipe, params.get("lora_path"), params.get("lora_strength", 0.0)):
-        image = pipe(**kwargs)
+    image = pipe(**kwargs)
 
     meta = dict(
         mode="upscale",
@@ -196,7 +195,5 @@ def call_upscale(pipe: Any, params: dict[str, Any]) -> tuple[Image.Image, dict[s
         seed=kwargs["seed"],
         width=upscaled.size[0],
         height=upscaled.size[1],
-        lora=str(params.get("lora_path")) if params.get("lora_path") else None,
-        lora_strength=params.get("lora_strength", 0.0),
     )
     return image, meta

tests/test_modes.py

@@ -182,8 +182,6 @@ def test_upscale_runs_realesrgan_then_pipeline(fake_pipe, monkeypatch):
             refine_steps=5,
             refine_denoise=0.33,
             seed=42,
-            lora_path=None,
-            lora_strength=0.0,
             esrgan_model_path="/fake/path/RealESRGAN_x4plus.pth",
         ),
     )
@@ -220,8 +218,6 @@ def test_upscale_crops_to_multiple_of_16(fake_pipe, monkeypatch):
             refine_steps=5,
             refine_denoise=0.33,
             seed=0,
-            lora_path=None,
-            lora_strength=0.0,
             esrgan_model_path="/fake/path/RealESRGAN_x4plus.pth",
         ),
     )
@@ -244,8 +240,6 @@ def test_upscale_rejects_missing_image(fake_pipe):
                 refine_steps=5,
                 refine_denoise=0.33,
                 seed=0,
-                lora_path=None,
-                lora_strength=0.0,
                 esrgan_model_path="/fake.pth",
             ),
         )

tests/test_ui.py

@@ -105,12 +105,16 @@ def test_build_upscale_tab_returns_components():
         "refine_steps",
         "refine_denoise",
         "seed",
-        "lora_enabled",
-        "lora_group",
-        "lora_path",
-        "lora_strength",
         "generate_btn",
         "output_image",
         "output_meta",
     }
     assert expected.issubset(components.keys())
+
+
+def test_build_upscale_tab_has_no_lora_components():
+    """LoRA is intentionally not wired on Upscale — the refinement pass uses
+    too low a denoising window for style LoRAs to meaningfully apply."""
+    components = ui.build_upscale_tab()
+    for key in ("lora_enabled", "lora_group", "lora_path", "lora_strength"):
+        assert key not in components

ui.py

@@ -262,23 +262,6 @@ def build_upscale_tab() -> dict[str, gr.components.Component]:
                     info=TOOLTIPS["refine_denoise"],
                 )
 
-            lora_enabled = gr.Checkbox(label="Use a LoRA (compatible with Z-Image-Turbo)", value=False)
-            with gr.Group(visible=False) as lora_group:
-                lora_path = gr.File(
-                    label="LoRA file",
-                    file_types=[".safetensors"],
-                    type="filepath",
-                    elem_classes=["zis-lora-file"],
-                )
-                lora_strength = gr.Slider(
-                    0.0,
-                    1.5,
-                    value=0.8,
-                    step=0.05,
-                    label="LoRA strength",
-                    info=TOOLTIPS["lora_strength"],
-                )
-
             with gr.Accordion("Advanced", open=False):
                 seed = gr.Number(value=0, precision=0, label="Seed", info=TOOLTIPS["seed"])
 
@@ -302,10 +285,6 @@ def build_upscale_tab() -> dict[str, gr.components.Component]:
         refine_steps=refine_steps,
         refine_denoise=refine_denoise,
         seed=seed,
-        lora_enabled=lora_enabled,
-        lora_group=lora_group,
-        lora_path=lora_path,
-        lora_strength=lora_strength,
         generate_btn=generate_btn,
         output_image=output_image,
         output_meta=output_meta,