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"""LTX 2.3 All-in-One — Gradio entry point."""
from __future__ import annotations
import os
import pathlib
import random
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"))
COMFYUI_REPO = "https://github.com/comfyanonymous/ComfyUI.git"
COMFYUI_COMMIT = os.environ.get(
"LTX23_AIO_COMFYUI_COMMIT",
"eb0686bbb60c83e44c3a3e4f7defd0f589cfef10",
)
CUSTOM_NODES_PINNED: list[tuple[str, str]] = [
("https://github.com/Lightricks/ComfyUI-LTXVideo.git", "main"),
("https://github.com/kijai/ComfyUI-KJNodes.git", "main"),
("https://github.com/rgthree/rgthree-comfy.git", "main"),
("https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite.git", "main"),
("https://github.com/pythongosssss/ComfyUI-Custom-Scripts.git", "main"),
]
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)])
def _bootstrap() -> None:
on_spaces = _on_spaces()
comfy_dir = pathlib.Path("/data/comfyui" if on_spaces else "comfyui")
if on_spaces and not comfy_dir.exists():
print(f"[bootstrap] cold start on Spaces; cloning ComfyUI to {comfy_dir}", flush=True)
comfy_dir.parent.mkdir(parents=True, exist_ok=True)
_git_clone(COMFYUI_REPO, comfy_dir, ref=COMFYUI_COMMIT)
for node_url, node_ref in CUSTOM_NODES_PINNED:
name = node_url.rstrip(".git").rsplit("/", 1)[-1]
_git_clone(node_url, comfy_dir / "custom_nodes" / name, ref=node_ref)
import subprocess
# ComfyUI core requirements + each custom node's requirements
for req_path in [
comfy_dir / "requirements.txt",
*(cn / "requirements.txt" for cn in (comfy_dir / "custom_nodes").iterdir()),
]:
if req_path.exists():
print(f"[bootstrap] pip install -r {req_path}", flush=True)
subprocess.check_call(
[sys.executable, "-m", "pip", "install", "--quiet", "-r", str(req_path)]
)
if str(comfy_dir) not in sys.path:
sys.path.insert(0, str(comfy_dir))
os.environ.setdefault(
"COMFY_MODELS_DIR",
str(pathlib.Path("/data/models") if on_spaces else (comfy_dir / "models")),
)
# Stage placeholder input files so the workflow's hard-referenced loaders
# (LoadImage/VHS_Load*) don't error at runtime even when the active mode
# doesn't actually use the file. Real user uploads are placed alongside via
# `_stage_to_comfy_input` later.
seed_dir = pathlib.Path(__file__).parent / "assets" / "seed_inputs"
inputs_dir = comfy_dir / "input"
inputs_dir.mkdir(parents=True, exist_ok=True)
if seed_dir.exists():
import shutil
for src in seed_dir.iterdir():
if not src.is_file():
continue
dst = inputs_dir / src.name
if not dst.exists():
try:
shutil.copy2(src, dst)
except OSError as exc:
print(f"[bootstrap] could not seed {src.name}: {exc}", flush=True)
_bootstrap()
# ---------------------------------------------------------------------------
# Styling: hide the default top tab strip (sidebar drives selection),
# add status-card styling, plus responsive breakpoints (≤1024px tablet,
# ≤700px mobile).
# ---------------------------------------------------------------------------
_CUSTOM_CSS = """
/* Hide the top tab strip from view, but keep it in the DOM and clickable so
the sidebar buttons can drive selection via programmatic click. */
.aio-tabs > .tab-nav,
.aio-tabs > div:first-child[role="tablist"],
.aio-tabs > div:first-child:has([role="tab"]) {
position: absolute !important;
left: -99999px !important;
top: -99999px !important;
height: 0 !important;
overflow: hidden !important;
visibility: visible !important;
pointer-events: auto !important;
}
/* Sidebar nav buttons */
.aio-mode-btn { width: 100%; text-align: left; margin: 2px 0; }
.aio-mode-btn-active { background: rgba(110,168,254,0.15) !important; border-left: 3px solid #6ea8fe !important; }
/* Sidebar headings */
.aio-sidebar-heading { font-size: 12px; text-transform: uppercase; letter-spacing: 0.05em; opacity: 0.6; margin-top: 16px !important; margin-bottom: 4px !important; }
/* Status banner */
.status-card { padding: 14px 16px; border-radius: 10px; background: rgba(255,255,255,0.04); border: 1px solid rgba(255,255,255,0.08); }
.status-row { display: flex; gap: 14px; align-items: center; margin-bottom: 8px; flex-wrap: wrap; }
.status-stage { font-weight: 600; }
.status-meta { font-size: 12px; opacity: 0.75; }
.status-bar { height: 6px; background: rgba(255,255,255,0.08); border-radius: 99px; overflow: hidden; }
.status-fill { height: 100%; background: linear-gradient(90deg,#6ea8fe,#8de9fe); transition: width .3s; }
.status-mem { font-size: 11px; opacity: 0.6; margin-top: 6px; font-family: ui-monospace, monospace; }
.status-error { background: rgba(255,90,90,0.08); border-color: rgba(255,90,90,0.25); }
/* Model status badge */
.aio-model-badge { padding: 8px 10px; border-radius: 8px; background: rgba(255,255,255,0.04); font-size: 11.5px; font-family: ui-monospace, monospace; opacity: 0.85; }
/* Responsive: tablet */
@media (max-width: 1024px) {
.aio-sidebar { min-width: 160px !important; }
.aio-mode-btn { font-size: 13px !important; padding: 6px 10px !important; }
}
/* Responsive: mobile — sidebar collapses to top, single column body */
@media (max-width: 700px) {
.aio-shell { flex-direction: column !important; }
.aio-sidebar { width: 100% !important; min-width: unset !important; padding: 0 !important; }
.aio-body { width: 100% !important; }
.aio-mode-btn-row { display: grid !important; grid-template-columns: repeat(2, 1fr) !important; gap: 6px !important; padding: 8px !important; }
.aio-mode-btn { width: 100% !important; font-size: 12.5px !important; padding: 8px !important; text-align: center !important; margin: 0 !important; }
.aio-sidebar-heading { font-size: 10px !important; margin: 12px 0 4px !important; padding: 0 8px !important; }
.aio-model-badge { margin: 0 8px !important; word-break: break-word; white-space: normal !important; }
/* sliders + side-by-side rows: stack vertically on mobile so each value
gets its own width budget */
.aio-body .form > div, .aio-body [class*="row"] > div { flex: 1 1 100% !important; min-width: 0 !important; }
.aio-body [class*="row"] { flex-wrap: wrap !important; }
}
"""
# ---------------------------------------------------------------------------
# UI
# ---------------------------------------------------------------------------
def build_app() -> gr.Blocks:
with gr.Blocks(theme=gr.themes.Soft(), title="LTX 2.3 All-in-One", css=_CUSTOM_CSS) as app:
gr.Markdown("# ⚡ LTX 2.3 All-in-One")
with gr.Row(elem_classes=["aio-shell"]):
# Sidebar
with gr.Column(scale=1, min_width=200, elem_classes=["aio-sidebar"]):
gr.Markdown("**Modes**", elem_classes=["aio-sidebar-heading"])
with gr.Column(elem_classes=["aio-mode-btn-row"]):
mode_buttons = {
name: gr.Button(
f"{m.icon} {m.label}",
elem_classes=["aio-mode-btn"],
variant="secondary",
)
for name, m in modes.MODE_REGISTRY.items()
}
gr.Markdown("**Models**", elem_classes=["aio-sidebar-heading"])
model_status = gr.HTML(_render_model_status_idle(), elem_id="aio-model-status")
refresh_btn = gr.Button("Refresh", size="sm", variant="secondary")
unload_btn = gr.Button("Unload all models", size="sm", variant="secondary")
gr.Markdown("**Settings**", elem_classes=["aio-sidebar-heading"])
gr.Markdown(
"Output: `comfyui/output/LTX2.3/`<br>"
"Set `LTX23_AIO_VRAM=lowvram|normalvram|highvram` to override the auto-detected VRAM tier.",
elem_classes=["aio-model-badge"],
)
# Body
with gr.Column(scale=4, elem_classes=["aio-body"]):
handles, tabs_component = _render_mode_panels()
# Wire generate buttons
for name, h in handles.items():
inputs = _collect_inputs_for_mode(name, h)
h["generate_btn"].click(
fn=_make_handler(name, h),
inputs=inputs,
outputs=[h["status"], h["video_out"]],
)
# Sidebar mode buttons drive Tabs.selected via Gradio's update.
for name, btn in mode_buttons.items():
btn.click(
fn=lambda mode_id=name: gr.Tabs(selected=mode_id),
inputs=None,
outputs=[tabs_component],
)
# Sidebar model info wiring
refresh_btn.click(fn=_render_model_status, inputs=None, outputs=[model_status])
unload_btn.click(fn=_unload_models, inputs=None, outputs=[model_status])
return app
def _render_model_status_idle() -> str:
return (
'<div class="aio-model-badge">device: detecting…<br>'
"loaded: —<br>free: —</div>"
)
def _render_model_status() -> str:
"""Best-effort device + memory readout for the sidebar."""
try:
be = _get_backend() # ensure ComfyUI is loaded
except Exception as exc:
return f'<div class="aio-model-badge">backend not ready<br>{exc}</div>'
try:
import comfy.model_management as mm
import torch
device = mm.get_torch_device()
free_gb = mm.get_free_memory(device) / (1024**3)
if torch.backends.mps.is_available():
# MPS unified memory: total physical = total system RAM. The
# "recommended max" from torch.mps is a soft cap (~75% of total)
# used by the allocator, but actual free can exceed it because
# macOS shares RAM between CPU and GPU.
try:
import psutil
total_gb = psutil.virtual_memory().total / (1024**3)
except Exception:
total_gb = torch.mps.recommended_max_memory() / (1024**3)
cap_gb = torch.mps.recommended_max_memory() / (1024**3)
label = "MPS (unified)"
extra = f"<br>mps cap: {cap_gb:.1f} GB"
elif torch.cuda.is_available():
total_gb = torch.cuda.get_device_properties(0).total_memory / (1024**3)
label = "CUDA"
extra = ""
else:
total_gb = 0.0
label = "CPU"
extra = ""
loaded = len(getattr(mm, "current_loaded_models", []))
return (
'<div class="aio-model-badge">'
f"device: {label}<br>"
f"loaded: {loaded} model(s)<br>"
f"free: {free_gb:.1f} GB / {total_gb:.1f} GB total"
f"{extra}"
"</div>"
)
except Exception as exc:
return f'<div class="aio-model-badge">memory probe failed: {exc}</div>'
def _unload_models() -> str:
try:
import comfy.model_management as mm
import torch
mm.unload_all_models()
if torch.backends.mps.is_available():
torch.mps.empty_cache()
if torch.cuda.is_available():
torch.cuda.empty_cache()
except Exception as exc:
return f'<div class="aio-model-badge">unload failed: {exc}</div>'
return _render_model_status()
def _render_mode_panels() -> tuple[dict[str, dict], gr.Tabs]:
"""Render one (hidden-tab) panel per mode. Returns the component handles + the Tabs component."""
handles: dict[str, dict] = {}
with gr.Tabs(elem_classes=["aio-tabs"]) as tabs:
for name, mode in modes.MODE_REGISTRY.items():
with gr.Tab(label=f"{mode.icon} {mode.label}", id=name):
handles[name] = _render_one_mode(name)
return handles, tabs
def _render_one_mode(name: str) -> dict:
"""Render a per-mode form. Returns component handles for the generate handler."""
handles: dict = {"mode": name}
with gr.Row():
with gr.Column(scale=2, min_width=280):
handles["prompt"] = gr.Textbox(
label="Prompt", lines=4, placeholder="Describe the shot..."
)
# Mode-specific media inputs
if name == "i2v":
handles["image"] = gr.Image(label="Source image", type="filepath")
elif name == "a2v":
handles["audio"] = gr.Audio(label="Source audio", type="filepath")
elif name == "lipsync":
handles["image"] = gr.Image(label="Portrait", type="filepath")
handles["audio"] = gr.Audio(label="Speech audio", type="filepath")
elif name == "keyframe":
handles["first_frame"] = gr.Image(label="First frame", type="filepath")
handles["last_frame"] = gr.Image(label="Last frame", type="filepath")
elif name == "style":
handles["input_video"] = gr.Video(label="Source video")
handles["preset"] = ui.preset_bar()
# Resolution — up to 4K, /32 step
with gr.Row():
handles["width"] = gr.Slider(
256, 4096, value=512, step=32, label="Width"
)
handles["height"] = gr.Slider(
256, 4096, value=768, step=32, label="Height"
)
# Length controlled in seconds (matches the master workflow's mxSlider).
# Frames are derived: frames = round(seconds * fps / 8) * 8 + 1.
with gr.Row():
handles["seconds"] = gr.Slider(
minimum=1, maximum=30, value=3, step=1,
label="Length (seconds)",
info="Frames are computed as 8·round(seconds·fps/8)+1 (LTX requires 8k+1)",
)
handles["fps"] = gr.Slider(8, 30, value=24, step=1, label="FPS")
handles["frames_display"] = gr.Markdown("Frames: 73", elem_classes=["aio-frames-display"])
with gr.Row():
handles["seed"] = gr.Number(label="Seed", value=42, precision=0, minimum=0)
handles["randomize_seed"] = gr.Checkbox(label="Randomize seed each run", value=True)
with gr.Accordion("Advanced ▾", open=False):
handles["lora"] = ui.lora_chrome(name)
handles["negative_prompt"] = gr.Textbox(label="Negative prompt", lines=2)
handles["generate_btn"] = gr.Button("▶ Generate", variant="primary", size="lg")
# Live frames-display update when seconds/fps change
def _update_frames(seconds, fps):
f = max(9, int(round(float(seconds) * float(fps) / 8) * 8) + 1)
return f"**Frames:** {f} (`{seconds}s` × `{fps} fps`)"
handles["seconds"].change(
fn=_update_frames,
inputs=[handles["seconds"], handles["fps"]],
outputs=[handles["frames_display"]],
)
handles["fps"].change(
fn=_update_frames,
inputs=[handles["seconds"], handles["fps"]],
outputs=[handles["frames_display"]],
)
with gr.Column(scale=2, min_width=280):
handles["status"] = ui.status_banner()
handles["video_out"] = gr.Video(label="Output", autoplay=True)
handles["history"] = gr.Markdown("")
return handles
# ---------------------------------------------------------------------------
# Backend wiring
# ---------------------------------------------------------------------------
_BACKEND: backend_module.ComfyUILibraryBackend | None = None
def _get_backend() -> backend_module.ComfyUILibraryBackend:
global _BACKEND
if _BACKEND is None:
_BACKEND = backend_module.ComfyUILibraryBackend()
return _BACKEND
_COMFY_INPUT_DIR = pathlib.Path(__file__).parent / "comfyui" / "input"
def _stage_to_comfy_input(file_path) -> str | None:
"""Copy/stage a path into comfyui/input/ so ComfyUI's LoadImage etc. can find it."""
if not file_path:
return None
if not isinstance(file_path, (str, pathlib.Path)):
file_path = (
file_path.get("name") or file_path.get("path") or file_path.get("orig_name")
if isinstance(file_path, dict)
else None
)
if not file_path:
return None
src = pathlib.Path(file_path)
if not src.exists() or not src.is_file():
print(f"[_stage] skip {file_path!r}", flush=True)
return None
_COMFY_INPUT_DIR.mkdir(parents=True, exist_ok=True)
try:
if src.resolve().is_relative_to(_COMFY_INPUT_DIR.resolve()):
return src.name
except (ValueError, OSError):
pass
dst = _COMFY_INPUT_DIR / src.name
if not dst.exists() or dst.stat().st_size != src.stat().st_size:
import shutil
shutil.copy2(src, dst)
return src.name
PRESET_DURATION = {"Fast": 60, "Balanced": 120, "Quality": 300}
def _seconds_to_frames(seconds: float, fps: int) -> int:
return max(9, int(round(float(seconds) * float(fps) / 8) * 8) + 1)
async def _on_generate(mode_name: str, **inputs: Any):
"""Generate handler — async generator yielding (status_html, video_path)."""
mode = modes.MODE_REGISTRY[mode_name]
fps = int(inputs.get("fps", 24))
seconds = float(inputs.get("seconds", 3))
frames = _seconds_to_frames(seconds, fps)
# Seed: respect the explicit value unless the "randomize" checkbox is on.
seed = int(inputs.get("seed", 42))
if inputs.get("randomize_seed"):
seed = random.randint(0, 2**31 - 1)
params: dict[str, Any] = {
"prompt": inputs.get("prompt", ""),
"negative_prompt": inputs.get("negative_prompt", ""),
"preset": str(inputs.get("preset", "Balanced")).lower(),
"width": int(inputs.get("width", 512)),
"height": int(inputs.get("height", 768)),
"frames": frames,
"fps": fps,
"seed": seed,
}
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]
for key in ("image", "audio", "first_frame", "last_frame", "input_video"):
if key in params and params[key]:
staged = _stage_to_comfy_input(params[key])
if staged is None:
params.pop(key, None)
else:
params[key] = staged
patches = mode.parameterize_fn(params)
workflow = wf_module.load_template(mode_name)
for patch in patches:
wf_module.set_input(workflow, *patch)
backend = _get_backend()
duration = PRESET_DURATION.get(str(inputs.get("preset", "Balanced")), 120)
started = time.time()
async for event in backend.submit(mode_name, workflow, gpu_duration=duration):
elapsed = time.time() - started
if isinstance(event, backend_module.DownloadEvent):
status = ui.render_status(
stage_index=0,
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,
)
yield status, gr.update()
elif isinstance(event, backend_module.ProgressEvent):
# Each sampler in the workflow gets its own stage label "Diffusion (n)".
# The static `mode.stage_map` describes the full pipeline (encode →
# diffusion → upscale → diffusion → decode) but our progress hook
# only fires inside samplers, so we label by sampler index instead.
label = f"Diffusion (Stage {event.stage})"
eta = (elapsed / max(event.step, 1)) * (event.total_steps - event.step)
status = ui.render_status(
stage_index=event.stage,
stage_label=label,
step=event.step,
total_steps=event.total_steps,
elapsed_s=elapsed,
eta_s=eta,
)
yield status, gr.update()
elif isinstance(event, backend_module.OutputEvent):
video_update = event.video_path if event.video_path else gr.update()
yield ui._render_idle(), video_update
elif isinstance(event, backend_module.ErrorEvent):
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>"
)
yield error_html, gr.update()
def _input_keys_for_mode(mode_name: str, h: dict) -> list[str]:
base = ["prompt", "preset", "width", "height", "seconds", "fps", "seed", "randomize_seed"]
if mode_name == "i2v":
base.append("image")
elif mode_name == "a2v":
base.append("audio")
elif mode_name == "lipsync":
base.extend(["image", "audio"])
elif mode_name == "keyframe":
base.extend(["first_frame", "last_frame"])
elif mode_name == "style":
base.append("input_video")
base.append("negative_prompt")
base.extend(["camera_lora", "camera_strength", "detailer_on", "detailer_strength"])
if h["lora"].ic_lora is not None:
base.extend(["ic_lora", "ic_strength"])
if h["lora"].pose_on is not None:
base.append("pose_on")
return base
def _collect_inputs_for_mode(mode_name: str, h: dict) -> list:
base = [
h["prompt"], h["preset"], h["width"], h["height"],
h["seconds"], h["fps"], h["seed"], h["randomize_seed"],
]
if mode_name == "i2v":
base.append(h["image"])
elif mode_name == "a2v":
base.append(h["audio"])
elif mode_name == "lipsync":
base.extend([h["image"], h["audio"]])
elif mode_name == "keyframe":
base.extend([h["first_frame"], h["last_frame"]])
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,
])
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:
base.append(h["lora"].pose_on)
return base
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, strict=False))
async for output in _on_generate(mode_name, **kwargs):
yield output
return handler
if __name__ == "__main__":
app = build_app()
app.launch(server_name="0.0.0.0", server_port=7860)
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