Architecture firm marketing aide - Expansion

README.md

@@ -16,7 +16,7 @@ preload_from_hub:
   - Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Down ltx-2-19b-lora-camera-control-jib-down.safetensors
   - Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Up ltx-2-19b-lora-camera-control-jib-up.safetensors
   - Lightricks/LTX-2-19b-LoRA-Camera-Control-Static ltx-2-19b-lora-camera-control-static.safetensors
-  - Lightricks/LTX-2.3 ltx-2.3-22b-distilled-lora-384.safetensors,ltx-2.3-spatial-upscaler-x2-1.1.safetensors
+  - Lightricks/LTX-2.3 ltx-2.3-22b-distilled-lora-384.safetensors,ltx-2.3-spatial-upscaler-x2-1.0.safetensors
   - Lightricks/LTX-2.3-22b-IC-LoRA-Union-Control ltx-2.3-22b-ic-lora-union-control-ref0.5.safetensors
   - google/gemma-3-12b-it-qat-q4_0-unquantized gemma-3-12b-it/model-00001-of-00005.safetensors,gemma-3-12b-it/model-00002-of-00005.safetensors,gemma-3-12b-it/model-00003-of-00005.safetensors,gemma-3-12b-it/model-00004-of-00005.safetensors,gemma-3-12b-it/model-00005-of-00005.safetensors,gemma-3-12b-it/model.safetensors.index.json,gemma-3-12b-it/preprocessor_config.json,gemma-3-12b-it/tokenizer.model
 ---

models.py

@@ -34,9 +34,7 @@ MODEL_REGISTRY: dict[str, ModelEntry] = {
     # Main LTX 2.3 transformer + LoRAs + upscalers
     "ltx-2.3-22b-distilled.safetensors": ModelEntry("Lightricks/LTX-2.3", comfy_type="checkpoints"),
     "ltx-2.3-22b-dev.safetensors": ModelEntry("Lightricks/LTX-2.3", comfy_type="checkpoints"),
-    # v1.0 was deleted upstream on 2026-08-10; workflow.RETIRED_MODEL_RENAMES
-    # rewrites the templates' references to this name.
-    "ltx-2.3-spatial-upscaler-x2-1.1.safetensors": ModelEntry(
+    "ltx-2.3-spatial-upscaler-x2-1.0.safetensors": ModelEntry(
         "Lightricks/LTX-2.3", comfy_type="latent_upscale_models"
     ),
     "ltx-2.3-22b-distilled-lora-384.safetensors": ModelEntry(

tests/conftest.py

@@ -132,7 +132,7 @@ def fake_hf_cache(tmp_path: pathlib.Path) -> pathlib.Path:
     layouts = {
         "models--Lightricks--LTX-2.3": [
             "ltx-2.3-22b-distilled.safetensors",
-            "ltx-2.3-spatial-upscaler-x2-1.1.safetensors",
+            "ltx-2.3-spatial-upscaler-x2-1.0.safetensors",
             "ltx-2.3-22b-distilled-lora-384.safetensors",
         ],
         "models--google--gemma-3-12b-it-qat-q4_0-unquantized": [

tests/test_models.py

@@ -29,23 +29,6 @@ def test_walk_workflow_for_models_finds_t2v_loaders():
     assert any("gemma" in name.lower() for name in needed)
 
 
-def test_model_registry_has_no_retired_filenames():
-    """A registry key that 404s on the Hub makes every generation abort mid-graph."""
-    assert "ltx-2.3-spatial-upscaler-x2-1.0.safetensors" not in models.MODEL_REGISTRY
-    assert "ltx-2.3-spatial-upscaler-x2-1.1.safetensors" in models.MODEL_REGISTRY
-    entry = models.MODEL_REGISTRY["ltx-2.3-spatial-upscaler-x2-1.1.safetensors"]
-    assert entry.repo_id == "Lightricks/LTX-2.3"
-    assert entry.comfy_type == "latent_upscale_models"
-
-
-def test_walk_workflow_for_models_requests_current_upscaler_for_every_mode():
-    """The download pass must fetch the upscaler the workflow actually loads."""
-    for mode in workflow.VALID_MODES:
-        needed = models.walk_workflow_for_models(workflow.load_template(mode))
-        assert "ltx-2.3-spatial-upscaler-x2-1.1.safetensors" in needed
-        assert "ltx-2.3-spatial-upscaler-x2-1.0.safetensors" not in needed
-
-
 def test_ensure_models_creates_symlinks_local(tmp_path, monkeypatch, fake_hf_cache):
     """In local mode, ensure_models creates symlinks from comfy/models -> HF cache."""
     monkeypatch.setenv("HF_HUB_CACHE", str(fake_hf_cache))

tests/test_workflow.py

@@ -1,7 +1,5 @@
 """Unit tests for workflow.py — pure functions over JSON dicts."""
 
-import json
-
 import pytest
 
 import workflow
@@ -59,23 +57,6 @@ def test_validate_rejects_orphan_link():
         workflow.validate(wf)
 
 
-def test_load_template_remaps_retired_upscaler_filename():
-    """Lightricks deleted the x2 spatial upscaler v1.0; templates still name it."""
-    for mode in workflow.VALID_MODES:
-        wf = workflow.load_template(mode)
-        assert wf["101"]["inputs"]["model_name"] == "ltx-2.3-spatial-upscaler-x2-1.1.safetensors", (
-            f"{mode} still loads a retired upscaler"
-        )
-
-
-def test_load_template_leaves_no_retired_filenames_in_any_mode():
-    """No retired model filename may reach the workflow handed to PromptExecutor."""
-    for mode in workflow.VALID_MODES:
-        serialized = json.dumps(workflow.load_template(mode))
-        for retired in ("ltx-2.3-spatial-upscaler-x2-1.0.safetensors",):
-            assert retired not in serialized, f"{mode} references retired {retired}"
-
-
 def test_set_input_handles_dict_widgets_values():
     """VHS_* nodes carry dict-style widgets_values; set_input must support str keys."""
     wf = workflow.load_template("a2v")

workflow.py

@@ -16,38 +16,13 @@ WORKFLOWS_DIR = pathlib.Path(__file__).parent / "workflows"
 
 VALID_MODES: tuple[str, ...] = ("t2v", "a2v", "i2v", "lipsync", "keyframe", "style")
 
-# Model files the upstream HF repos have deleted, mapped to their replacements.
-# The templates are machine-generated by tools/extract_modes.py from the user's
-# master ComfyUI export, so patching the JSON would be undone on the next
-# re-export — the remap has to live in code. load_template is the only reader of
-# workflows/*.json, which puts it upstream of both consumers: the dict handed to
-# PromptExecutor and models.walk_workflow_for_models' download pass.
-RETIRED_MODEL_RENAMES: dict[str, str] = {
-    # Lightricks deleted x2 spatial upscaler v1.0 on 2026-08-10 (v1.1 is the
-    # long-video hotfix). Loading the retired name 404s and aborts the graph
-    # right after sampling, leaving the user with an empty output.
-    "ltx-2.3-spatial-upscaler-x2-1.0.safetensors": "ltx-2.3-spatial-upscaler-x2-1.1.safetensors",
-}
-
-
-def _rename_retired_models(value: Any) -> Any:
-    """Return *value* with every retired model filename swapped for its successor."""
-    if isinstance(value, str):
-        return RETIRED_MODEL_RENAMES.get(value, value)
-    if isinstance(value, dict):
-        return {k: _rename_retired_models(v) for k, v in value.items()}
-    if isinstance(value, list):
-        return [_rename_retired_models(v) for v in value]
-    return value
-
 
 def load_template(mode: str) -> dict[str, Any]:
     """Load a fresh, independent copy of the named mode's API workflow template."""
     if mode not in VALID_MODES:
         raise ValueError(f"unknown mode {mode!r}; expected one of {VALID_MODES}")
     path = WORKFLOWS_DIR / f"{mode}.json"
-    template = copy.deepcopy(json.loads(path.read_text()))
-    return _rename_retired_models(template)
+    return copy.deepcopy(json.loads(path.read_text()))
 
 
 def set_input(workflow: dict[str, Any], node_id: int | str, field: str, value: Any) -> None: