ci: run unit tests + ruff lint on every push

.github/workflows/ci.yml

@@ -0,0 +1,31 @@
+name: CI
+
+on:
+  push:
+  pull_request:
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: false  # ComfyUI submodule not needed for L1+L3 tests
+
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Install runtime + dev deps
+        run: |
+          pip install -U pip
+          pip install -r requirements.txt
+
+      - name: Run unit + integration tests (no GPU)
+        run: |
+          python -m pytest tests/ -v -m "not gpu"
+
+      - name: Lint
+        run: |
+          ruff check .
+          ruff format --check .

app.py

@@ -1,21 +1,26 @@
 # app.py
 """LTX 2.3 All-in-One — Gradio entry point."""
+
 from __future__ import annotations
 
 import os
 import pathlib
 import sys
+import time
+from typing import Any
 
 import gradio as gr
 
+import backend as backend_module
 import modes
 import ui
-
+import workflow as wf_module
 
 # ---------------------------------------------------------------------------
 # Bootstrap — runs once on cold start.
 # ---------------------------------------------------------------------------
 
+
 def _on_spaces() -> bool:
     return bool(os.environ.get("SPACES_ZERO_GPU"))
 
@@ -39,6 +44,7 @@ CUSTOM_NODES_PINNED: list[tuple[str, str]] = [
 
 def _git_clone(url: str, dst: pathlib.Path, ref: str) -> None:
     import subprocess
+
     subprocess.check_call(["git", "clone", "--depth", "1", "--branch", ref, url, str(dst)])
 
 
@@ -54,6 +60,7 @@ def _bootstrap() -> None:
             _git_clone(node_url, comfy_dir / "custom_nodes" / name, ref=node_ref)
         # Install custom node deps
         import subprocess
+
         for cn in (comfy_dir / "custom_nodes").iterdir():
             req = cn / "requirements.txt"
             if req.exists():
@@ -106,7 +113,7 @@ def build_app() -> gr.Blocks:
 
 def _render_sidebar() -> None:
     gr.Markdown("### Modes")
-    for name, mode in modes.MODE_REGISTRY.items():
+    for mode in modes.MODE_REGISTRY.values():
         gr.Markdown(f"- {mode.icon} {mode.label}")
     gr.Markdown("---\n### Models")
     gr.Button("Unload all models", variant="secondary")
@@ -115,7 +122,7 @@ def _render_sidebar() -> None:
 def _render_mode_panels() -> dict[str, dict]:
     """Render one form per mode. Returns the component handles keyed by mode."""
     handles: dict[str, dict] = {}
-    with gr.Tabs() as tabs:
+    with gr.Tabs():
         for name, mode in modes.MODE_REGISTRY.items():
             with gr.Tab(label=f"{mode.icon} {mode.label}"):
                 handles[name] = _render_one_mode(name)
@@ -124,12 +131,13 @@ def _render_mode_panels() -> dict[str, dict]:
 
 def _render_one_mode(name: str) -> dict:
     """Render a per-mode form. Returns component handles for the generate handler."""
-    mode = modes.MODE_REGISTRY[name]
     handles: dict = {"mode": name}
 
     with gr.Row():
         with gr.Column(scale=2):
-            handles["prompt"] = gr.Textbox(label="Prompt", lines=4, placeholder="Describe the shot...")
+            handles["prompt"] = gr.Textbox(
+                label="Prompt", lines=4, placeholder="Describe the shot..."
+            )
 
             # Mode-specific media inputs
             if name == "i2v":
@@ -168,12 +176,6 @@ def _render_one_mode(name: str) -> dict:
     return handles
 
 
-import time
-from typing import Any
-
-import workflow as wf_module
-import backend as backend_module
-
 _BACKEND: backend_module.ComfyUILibraryBackend | None = None
 
 
@@ -202,10 +204,22 @@ async def _on_generate(mode_name: str, **inputs: Any):
         "fps": int(inputs.get("fps", 24)),
         "seed": int(inputs.get("seed", 42)),
     }
-    for k in ("image", "audio", "first_frame", "last_frame", "input_video",
-              "camera_lora", "camera_strength",
-              "detailer_on", "detailer_strength",
-              "ic_lora", "ic_strength", "pose_on", "audio_cfg", "image_strength"):
+    for k in (
+        "image",
+        "audio",
+        "first_frame",
+        "last_frame",
+        "input_video",
+        "camera_lora",
+        "camera_strength",
+        "detailer_on",
+        "detailer_strength",
+        "ic_lora",
+        "ic_strength",
+        "pose_on",
+        "audio_cfg",
+        "image_strength",
+    ):
         if k in inputs:
             params[k] = inputs[k]
 
@@ -227,7 +241,8 @@ async def _on_generate(mode_name: str, **inputs: Any):
                 stage_label=f"Downloading {event.filename}",
                 step=int(event.mb_done),
                 total_steps=int(max(event.mb_total, 1)),
-                elapsed_s=elapsed, eta_s=0,
+                elapsed_s=elapsed,
+                eta_s=0,
             )
             yield status, gr.update()
         elif isinstance(event, backend_module.ProgressEvent):
@@ -242,7 +257,8 @@ async def _on_generate(mode_name: str, **inputs: Any):
                 stage_label=stage.label,
                 step=event.step,
                 total_steps=event.total_steps,
-                elapsed_s=elapsed, eta_s=eta,
+                elapsed_s=elapsed,
+                eta_s=eta,
             )
             yield status, gr.update()
         elif isinstance(event, backend_module.OutputEvent):
@@ -251,8 +267,8 @@ async def _on_generate(mode_name: str, **inputs: Any):
             error_html = (
                 f'<div class="status-card status-error">'
                 f'  <div class="status-row"><span class="status-stage">Error · {event.category}</span></div>'
-                f'  <div>{event.message}</div>'
-                f'</div>'
+                f"  <div>{event.message}</div>"
+                f"</div>"
             )
             yield error_html, gr.update()
 
@@ -292,10 +308,14 @@ def _collect_inputs_for_mode(mode_name: str, h: dict) -> list:
     elif mode_name == "style":
         base.append(h["input_video"])
     base.append(h["negative_prompt"])
-    base.extend([
-        h["lora"].camera_lora, h["lora"].camera_strength,
-        h["lora"].detailer_on, h["lora"].detailer_strength,
-    ])
+    base.extend(
+        [
+            h["lora"].camera_lora,
+            h["lora"].camera_strength,
+            h["lora"].detailer_on,
+            h["lora"].detailer_strength,
+        ]
+    )
     if h["lora"].ic_lora is not None:
         base.extend([h["lora"].ic_lora, h["lora"].ic_strength])
     if h["lora"].pose_on is not None:
@@ -307,7 +327,7 @@ def _make_handler(mode_name: str, h: dict):
     keys = _input_keys_for_mode(mode_name, h)
 
     async def handler(*values):
-        kwargs = dict(zip(keys, values))
+        kwargs = dict(zip(keys, values, strict=False))
         async for output in _on_generate(mode_name, **kwargs):
             yield output
 

backend.py

@@ -3,6 +3,7 @@
 Single-process, single-implementation. The @spaces.GPU decorator is the only
 divergence between local and HF Spaces deployment.
 """
+
 from __future__ import annotations
 
 import asyncio
@@ -13,7 +14,7 @@ import threading
 import traceback as tb_mod
 from collections.abc import AsyncIterator, Iterable
 from dataclasses import dataclass, field
-from typing import Any, Optional
+from typing import Any
 
 import models
 
@@ -36,7 +37,7 @@ class ProgressEvent:
 @dataclass
 class OutputEvent:
     video_path: str
-    audio_path: Optional[str] = None
+    audio_path: str | None = None
     meta: dict = field(default_factory=dict)
 
 
@@ -44,7 +45,7 @@ class OutputEvent:
 class ErrorEvent:
     category: str  # "oom" | "zerogpu_timeout" | "execution" | "interrupt" | "download"
     message: str
-    stage: Optional[int] = None
+    stage: int | None = None
     traceback: str = ""
 
 
@@ -113,13 +114,18 @@ class ComfyUILibraryBackend:
             asyncio.run_coroutine_threadsafe(queue.put(event), loop)
 
         def _hook(value: int, total: int, _preview=None) -> None:
-            _push(ProgressEvent(
-                stage=0, stage_label="diffusion",
-                step=int(value), total_steps=int(total),
-            ))
+            _push(
+                ProgressEvent(
+                    stage=0,
+                    stage_label="diffusion",
+                    step=int(value),
+                    total_steps=int(total),
+                )
+            )
 
         def _worker() -> None:
             import comfy.utils
+
             saved_hook = getattr(comfy.utils, "PROGRESS_BAR_HOOK", None)
             try:
                 # Use the public setter; it writes the same global the
@@ -137,11 +143,13 @@ class ComfyUILibraryBackend:
                 video_path = _first_video_path(outputs) or ""
                 _push(OutputEvent(video_path=video_path))
             except Exception as exc:
-                _push(ErrorEvent(
-                    category=_classify(exc),
-                    message=str(exc),
-                    traceback=tb_mod.format_exc(),
-                ))
+                _push(
+                    ErrorEvent(
+                        category=_classify(exc),
+                        message=str(exc),
+                        traceback=tb_mod.format_exc(),
+                    )
+                )
             finally:
                 comfy.utils.set_progress_bar_global_hook(saved_hook)
                 _free_memory()
@@ -149,6 +157,7 @@ class ComfyUILibraryBackend:
 
         if _on_spaces():
             import spaces
+
             execute = spaces.GPU(duration=gpu_duration)(_worker)
             thread = threading.Thread(target=execute, daemon=True)
         else:
@@ -165,6 +174,7 @@ class ComfyUILibraryBackend:
         """Cancel the currently running workflow (if any)."""
         try:
             import comfy.model_management as mm
+
             mm.interrupt_current_processing()
         except Exception:
             pass
@@ -183,24 +193,27 @@ def _free_memory() -> None:
     """Free VRAM after a workflow finishes (success or failure)."""
     try:
         import comfy.model_management as mm
+
         mm.unload_all_models()
     except Exception:
         pass
     try:
         import torch
+
         if torch.backends.mps.is_available():
             torch.mps.empty_cache()
     except Exception:
         pass
     try:
         import torch
+
         if torch.cuda.is_available():
             torch.cuda.empty_cache()
     except Exception:
         pass
 
 
-def _first_video_path(outputs: Iterable) -> Optional[str]:
+def _first_video_path(outputs: Iterable) -> str | None:
     """Find the first .mp4 path emitted by VHS_VideoCombine in PromptExecutor outputs."""
     for output in outputs:
         if not isinstance(output, dict):

models.py

@@ -3,6 +3,7 @@
 Lookups are by filename only — the same filename in two different repos is not
 supported. If that ever happens we'll qualify by ComfyUI loader-type.
 """
+
 from __future__ import annotations
 
 import logging
@@ -25,12 +26,8 @@ class ModelEntry:
 
 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"
-    ),
+    "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"),
     "ltx-2.3-spatial-upscaler-x2-1.0.safetensors": ModelEntry(
         "Lightricks/LTX-2.3", comfy_type="upscale_models"
     ),
@@ -62,12 +59,8 @@ MODEL_REGISTRY: dict[str, ModelEntry] = {
         subfolder="gemma-3-12b-it",
     ),
     # Kijai's LTX 2.3 ComfyUI assets
-    "LTX23_video_vae_bf16.safetensors": ModelEntry(
-        "Kijai/LTX2.3_comfy", comfy_type="vae"
-    ),
-    "LTX23_audio_vae_bf16.safetensors": ModelEntry(
-        "Kijai/LTX2.3_comfy", comfy_type="vae"
-    ),
+    "LTX23_video_vae_bf16.safetensors": ModelEntry("Kijai/LTX2.3_comfy", comfy_type="vae"),
+    "LTX23_audio_vae_bf16.safetensors": ModelEntry("Kijai/LTX2.3_comfy", comfy_type="vae"),
     "ltx-2.3_text_projection_bf16.safetensors": ModelEntry(
         "Kijai/LTX2.3_comfy", comfy_type="text_encoders"
     ),
@@ -133,8 +126,10 @@ def walk_workflow_for_models(workflow: dict) -> set[str]:
         widgets = node.get("widgets_values") or []
         for value in _flatten_widget_values(widgets):
             if isinstance(value, str) and (
-                value.endswith(".safetensors") or value.endswith(".gguf")
-                or value == "tokenizer.model" or value.endswith(".json")
+                value.endswith(".safetensors")
+                or value.endswith(".gguf")
+                or value == "tokenizer.model"
+                or value.endswith(".json")
             ):
                 needed.add(value)
     return needed
@@ -246,6 +241,7 @@ def ensure_models(filenames: set[str]) -> Iterator[DownloadEvent]:
 def ensure_models_for_mode(mode: str) -> Iterator[DownloadEvent]:
     """Convenience: walk a mode's workflow and ensure all referenced models exist."""
     import workflow as workflow_module  # local import to avoid cycle at import time
+
     wf = workflow_module.load_template(mode)
     needed = walk_workflow_for_models(wf)
     yield from ensure_models(needed)

modes.py

@@ -14,6 +14,7 @@ backend.py.
 Tasks 11 (T2V + I2V) and 12 (A2V + Lipsync + Keyframe + Style) populate
 MODE_REGISTRY. This task only sets up the dataclass and the empty container.
 """
+
 from __future__ import annotations
 
 from collections.abc import Callable
@@ -64,12 +65,12 @@ MODE_REGISTRY: dict[str, Mode] = {}
 # in models.py once camera-LoRA selection lands. Deferred for now.
 # ---------------------------------------------------------------------------
 
-T2V_NODE_PROMPT = 5536            # CLIPTextEncode positive — wv[0] = prompt
-T2V_NODE_NEG_PROMPT = 5537        # CLIPTextEncode negative — wv[0] = negative prompt
-T2V_NODE_WIDTH = 5383             # INTConstant "Width" — wv[0]
-T2V_NODE_HEIGHT = 5382            # INTConstant "Height" — wv[0]
-T2V_NODE_FPS = 5445               # INTConstant "FPS" — wv[0]
-T2V_NODE_CLIP_LENGTH = 196        # mxSlider "Clip Length ( in seconds )" — wv[0]
+T2V_NODE_PROMPT = 5536  # CLIPTextEncode positive — wv[0] = prompt
+T2V_NODE_NEG_PROMPT = 5537  # CLIPTextEncode negative — wv[0] = negative prompt
+T2V_NODE_WIDTH = 5383  # INTConstant "Width" — wv[0]
+T2V_NODE_HEIGHT = 5382  # INTConstant "Height" — wv[0]
+T2V_NODE_FPS = 5445  # INTConstant "FPS" — wv[0]
+T2V_NODE_CLIP_LENGTH = 196  # mxSlider "Clip Length ( in seconds )" — wv[0]
 
 I2V_NODE_PROMPT = 5536
 I2V_NODE_NEG_PROMPT = 5537
@@ -77,7 +78,7 @@ I2V_NODE_WIDTH = 5383
 I2V_NODE_HEIGHT = 5382
 I2V_NODE_FPS = 5445
 I2V_NODE_CLIP_LENGTH = 196
-I2V_NODE_IMAGE = 149              # LoadImage "Load Image1" — wv[0] = filename
+I2V_NODE_IMAGE = 149  # LoadImage "Load Image1" — wv[0] = filename
 
 # Mode-specific media nodes — captured from workflows/{a2v,lipsync,keyframe,style}.json
 # on 2026-04-30. All four templates contain the same node ids for these inputs (the
@@ -97,27 +98,27 @@ A2V_NODE_WIDTH = 5383
 A2V_NODE_HEIGHT = 5382
 A2V_NODE_FPS = 5445
 A2V_NODE_CLIP_LENGTH = 196
-A2V_NODE_AUDIO = 5400             # VHS_LoadAudioUpload — dict wv keyed by "audio"
+A2V_NODE_AUDIO = 5400  # VHS_LoadAudioUpload — dict wv keyed by "audio"
 
 LIPSYNC_NODE_PROMPT = 5536
 LIPSYNC_NODE_NEG_PROMPT = 5537
 LIPSYNC_NODE_FPS = 5445
 LIPSYNC_NODE_CLIP_LENGTH = 196
-LIPSYNC_NODE_IMAGE = 149          # LoadImage "Load Image1" — wv[0] = filename
-LIPSYNC_NODE_AUDIO = 5400         # VHS_LoadAudioUpload — dict wv keyed by "audio"
+LIPSYNC_NODE_IMAGE = 149  # LoadImage "Load Image1" — wv[0] = filename
+LIPSYNC_NODE_AUDIO = 5400  # VHS_LoadAudioUpload — dict wv keyed by "audio"
 
 KEYFRAME_NODE_PROMPT = 5536
 KEYFRAME_NODE_NEG_PROMPT = 5537
 KEYFRAME_NODE_FPS = 5445
 KEYFRAME_NODE_CLIP_LENGTH = 196
-KEYFRAME_NODE_FIRST_FRAME = 149   # LoadImage "Load Image1" — wv[0] = filename
-KEYFRAME_NODE_LAST_FRAME = 5437   # LoadImage "Load Image2" — wv[0] = filename
+KEYFRAME_NODE_FIRST_FRAME = 149  # LoadImage "Load Image1" — wv[0] = filename
+KEYFRAME_NODE_LAST_FRAME = 5437  # LoadImage "Load Image2" — wv[0] = filename
 
 STYLE_NODE_PROMPT = 5536
 STYLE_NODE_NEG_PROMPT = 5537
 STYLE_NODE_FPS = 5445
 STYLE_NODE_CLIP_LENGTH = 196
-STYLE_NODE_INPUT_VIDEO = 5444     # VHS_LoadVideo — dict wv keyed by "video"
+STYLE_NODE_INPUT_VIDEO = 5444  # VHS_LoadVideo — dict wv keyed by "video"
 
 
 def _frames_to_seconds(frames: int, fps: int) -> int:

pyproject.toml

@@ -7,6 +7,7 @@ markers = [
 [tool.ruff]
 line-length = 100
 target-version = "py311"
+exclude = ["comfyui/", ".venv/"]
 
 [tool.ruff.lint]
 select = ["E", "F", "I", "B", "UP"]

tests/conftest.py

@@ -1,4 +1,5 @@
 """Shared pytest fixtures and CLI flags."""
+
 import json
 import os
 import pathlib
@@ -11,7 +12,8 @@ REPO_ROOT = pathlib.Path(__file__).resolve().parent.parent
 DEFAULT_MASTER_WORKFLOW = pathlib.Path(
     os.environ.get(
         "LTX23_MASTER_WORKFLOW",
-        pathlib.Path.home() / "Projects/comfyui/user/default/workflows"
+        pathlib.Path.home()
+        / "Projects/comfyui/user/default/workflows"
         / "1. LTX 2.3 All-In-One 260406-05.json",
     )
 )
@@ -26,9 +28,7 @@ def pytest_addoption(parser: pytest.Parser) -> None:
     )
 
 
-def pytest_collection_modifyitems(
-    config: pytest.Config, items: list[pytest.Item]
-) -> None:
+def pytest_collection_modifyitems(config: pytest.Config, items: list[pytest.Item]) -> None:
     if not config.getoption("--gpu"):
         skip_gpu = pytest.mark.skip(reason="GPU smoke tests skipped (use --gpu)")
         for item in items:

tests/test_backend.py

@@ -1,4 +1,5 @@
 """Backend tests — most are smoke / structural since the real work is GPU."""
+
 import backend
 
 

tests/test_extract_modes.py

@@ -1,4 +1,5 @@
 """Tests for the workflow-mode extractor."""
+
 import json
 import subprocess
 import sys

tests/test_models.py

@@ -1,12 +1,13 @@
 """Unit tests for models.py — MODEL_REGISTRY and ensure_models_for_mode."""
-import pathlib
 
 import models
 import workflow
 
 
 def test_model_registry_resolves_known_files():
-    assert models.MODEL_REGISTRY["ltx-2.3-22b-distilled.safetensors"].repo_id == "Lightricks/LTX-2.3"
+    assert (
+        models.MODEL_REGISTRY["ltx-2.3-22b-distilled.safetensors"].repo_id == "Lightricks/LTX-2.3"
+    )
     assert models.MODEL_REGISTRY["ltx-2.3-22b-distilled.safetensors"].subfolder == ""
 
 
@@ -22,9 +23,7 @@ def test_walk_workflow_for_models_finds_t2v_loaders():
     needed = models.walk_workflow_for_models(wf)
     # T2V needs at minimum a transformer (distilled, dev fp8, or GGUF Q4) and a gemma encoder
     assert any(
-        name.endswith(".gguf")
-        or "distilled.safetensors" in name
-        or "transformer_only" in name
+        name.endswith(".gguf") or "distilled.safetensors" in name or "transformer_only" in name
         for name in needed
     )
     assert any("gemma" in name.lower() for name in needed)
@@ -38,6 +37,7 @@ def test_ensure_models_creates_symlinks_local(tmp_path, monkeypatch, fake_hf_cac
     # Force the HF Hub call to fail so the fallback path (cache_dir.rglob) is exercised.
     def _raise(*_args, **_kwargs):
         raise RuntimeError("offline test: forcing fallback to cache scan")
+
     monkeypatch.setattr(models, "hf_hub_download", _raise)
 
     comfy_models = tmp_path / "comfyui" / "models"
@@ -47,23 +47,27 @@ def test_ensure_models_creates_symlinks_local(tmp_path, monkeypatch, fake_hf_cac
         "ltx-2.3-22b-distilled.safetensors",
         "model-00001-of-00005.safetensors",
     }
-    events = list(models.ensure_models(needed))
+    list(models.ensure_models(needed))
 
     # Each requested file should now have a symlink in comfyui/models/<type>/
     assert (comfy_models / "checkpoints" / "ltx-2.3-22b-distilled.safetensors").is_symlink()
-    assert (comfy_models / "text_encoders" / "gemma-3-12b-it"
-            / "model-00001-of-00005.safetensors").is_symlink()
+    assert (
+        comfy_models / "text_encoders" / "gemma-3-12b-it" / "model-00001-of-00005.safetensors"
+    ).is_symlink()
 
 
-def test_ensure_models_skips_unregistered_files_with_warning(tmp_path, monkeypatch, fake_hf_cache, caplog):
+def test_ensure_models_skips_unregistered_files_with_warning(
+    tmp_path, monkeypatch, fake_hf_cache, caplog
+):
     """Files not in MODEL_REGISTRY are skipped (with warning), not raised."""
     import logging
+
     monkeypatch.setenv("HF_HUB_CACHE", str(fake_hf_cache))
     monkeypatch.setattr(models, "_on_spaces", lambda: False)
     monkeypatch.setattr(models, "_comfy_models_dir", lambda: tmp_path / "comfyui" / "models")
 
     with caplog.at_level(logging.WARNING):
-        events = list(models.ensure_models({"nonexistent_phantom_file.safetensors"}))
+        list(models.ensure_models({"nonexistent_phantom_file.safetensors"}))
 
     # Should not raise, should log a warning, should yield no events for the missing entry.
     assert any("nonexistent_phantom_file" in record.message for record in caplog.records)

tests/test_modes.py

@@ -1,4 +1,5 @@
 """Unit tests for modes.py — MODE_REGISTRY and parameterize_fn correctness."""
+
 import pytest
 
 import modes
@@ -23,7 +24,7 @@ def test_t2v_parameterize_produces_valid_patches(canonical_inputs):
     patches = mode.parameterize_fn(inputs)
 
     # All patches must be (node_id: int, widget_index: int, value: Any)
-    for node_id, widget_index, value in patches:
+    for node_id, widget_index, _value in patches:
         assert isinstance(node_id, int)
         assert isinstance(widget_index, int)
 
@@ -88,7 +89,12 @@ def test_style_parameterize_passes_input_video(canonical_inputs):
 def test_mode_registry_has_all_six_keys():
     """All six modes are in the registry now."""
     assert set(modes.MODE_REGISTRY.keys()) == {
-        "t2v", "a2v", "i2v", "lipsync", "keyframe", "style",
+        "t2v",
+        "a2v",
+        "i2v",
+        "lipsync",
+        "keyframe",
+        "style",
     }
 
 

tests/test_workflow.py

@@ -1,4 +1,5 @@
 """Unit tests for workflow.py — pure functions over JSON dicts."""
+
 import pytest
 
 import workflow

tools/extract_modes.py

@@ -12,6 +12,7 @@ Group title -> output filename mapping:
     05 -> keyframe.json
     06 -> style.json
 """
+
 from __future__ import annotations
 
 import argparse
@@ -94,7 +95,7 @@ def extract_mode(master: dict, mode_prefix: str) -> dict:
         "id": f"ltx23-aio-{mode_prefix}",
         "revision": 0,
         "last_node_id": max(kept_ids, default=0),
-        "last_link_id": max((l[0] for l in links), default=0),
+        "last_link_id": max((link[0] for link in links), default=0),
         "nodes": nodes,
         "links": links,
         "groups": groups,

tools/refresh_models.py

@@ -1,4 +1,5 @@
 """Materialize all LTX 2.3 model files for every mode by walking each template."""
+
 from __future__ import annotations
 
 import pathlib

ui.py

@@ -1,7 +1,10 @@
 # ui.py
 """Reusable Gradio components shared across modes."""
+
 from __future__ import annotations
 
+from dataclasses import dataclass
+
 import gradio as gr
 
 
@@ -48,11 +51,11 @@ def render_status(
         f'  <div class="status-row">'
         f'    <span class="status-stage">Stage {stage_index} · {stage_label}</span>'
         f'    <span class="status-meta">Step {step}/{total_steps} · '
-        f'      {_fmt_secs(elapsed_s)} elapsed · ~{_fmt_secs(eta_s)} remaining</span>'
-        f'  </div>'
+        f"      {_fmt_secs(elapsed_s)} elapsed · ~{_fmt_secs(eta_s)} remaining</span>"
+        f"  </div>"
         f'  <div class="status-bar"><div class="status-fill" style="width:{pct}%"></div></div>'
         f'  <div class="status-mem">{memory_text}</div>'
-        f'</div>'
+        f"</div>"
     )
 
 
@@ -63,12 +66,15 @@ def _fmt_secs(secs: float) -> str:
     return f"{secs // 60}m {secs % 60}s"
 
 
-from dataclasses import dataclass
-
-
 CAMERA_LORAS: list[str] = [
-    "none", "static", "dolly-in", "dolly-out", "dolly-left", "dolly-right",
-    "jib-up", "jib-down",
+    "none",
+    "static",
+    "dolly-in",
+    "dolly-out",
+    "dolly-left",
+    "dolly-right",
+    "jib-up",
+    "jib-down",
 ]
 
 IC_LORAS_BY_MODE: dict[str, list[str]] = {
@@ -101,19 +107,29 @@ def lora_chrome(mode: str) -> LoRAComponents:
     with gr.Group():
         gr.Markdown("**📷 Camera Movement**")
         camera_lora = gr.Dropdown(
-            choices=CAMERA_LORAS, value="none", label="Camera",
+            choices=CAMERA_LORAS,
+            value="none",
+            label="Camera",
             info="Mutually exclusive — pick one camera direction or none.",
         )
         camera_strength = gr.Slider(
-            minimum=0.0, maximum=1.5, value=0.8, step=0.05,
-            label="Camera strength", visible=True,
+            minimum=0.0,
+            maximum=1.5,
+            value=0.8,
+            step=0.05,
+            label="Camera strength",
+            visible=True,
         )
 
     with gr.Group():
         gr.Markdown("**✨ Detailer**")
         detailer_on = gr.Checkbox(label="Apply IC-LoRA-Detailer", value=False)
         detailer_strength = gr.Slider(
-            minimum=0.0, maximum=1.0, value=0.5, step=0.05, label="Detailer strength",
+            minimum=0.0,
+            maximum=1.0,
+            value=0.5,
+            step=0.05,
+            label="Detailer strength",
         )
 
     ic_lora = ic_strength = pose_on = None
@@ -127,7 +143,11 @@ def lora_chrome(mode: str) -> LoRAComponents:
                 label="IC-LoRA",
             )
             ic_strength = gr.Slider(
-                minimum=0.0, maximum=1.0, value=0.5, step=0.05, label="IC strength",
+                minimum=0.0,
+                maximum=1.0,
+                value=0.5,
+                step=0.05,
+                label="IC strength",
             )
 
     if mode in ("i2v", "lipsync"):

workflow.py

@@ -1,4 +1,5 @@
 """Pure functions over LTX 2.3 mode workflow JSON templates."""
+
 from __future__ import annotations
 
 import copy