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"""LTX 2.3 All-in-One — Gradio entry point."""
from __future__ import annotations
import asyncio
import os
import pathlib
import random
import sys
import time
import uuid
from typing import Any
import gradio as gr
import backend as backend_module
import modes
import r2_uploader
import ui
import video_format as video_format_module
import watermark as watermark_module
import workflow as wf_module
# Per-Space namespace embedded in every uploaded object key. Deliberately opaque
# (not the readable Space name) but stable so the owner can tell assets apart.
# Legend: s01=ImageStudio, s02=LTX2.3-Studio, s03=wan2-2-fp8da-aoti-preview-2.
R2_NAMESPACE = "s02"
def _render_r2_status(result: dict) -> str:
"""Build the terminal status card showing the R2 upload outcome."""
if result.get("ok"):
return (
'<div class="status-card">'
' <div class="status-row"><span class="status-stage">Done</span></div>'
f' <div>Uploaded to R2: <code>{result["filekey"]}</code></div>'
"</div>"
)
return (
'<div class="status-card status-error">'
' <div class="status-row"><span class="status-stage">R2 upload failed</span></div>'
f' <div>{result.get("error", "unknown error")}</div>'
"</div>"
)
# ---------------------------------------------------------------------------
# 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", "2acf7af8991f33b5cc06ec26753cb6e88e057d04"),
("https://github.com/kijai/ComfyUI-KJNodes.git", "01d9fa9c983273532cacdf9532c74a93c7dc86d2"),
("https://github.com/rgthree/rgthree-comfy.git", "683836c46e898668936c433502504cc0627482c5"),
("https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite.git", "2984ec4c4b93292421888f38db74a5e8802a8ff8"),
("https://github.com/pythongosssss/ComfyUI-Custom-Scripts.git", "609f3afaa74b2f88ef9ce8d939626065e3247469"),
("https://github.com/city96/ComfyUI-GGUF.git", "6ea2651e7df66d7585f6ffee804b20e92fb38b8a"),
("https://github.com/Fannovel16/comfyui_controlnet_aux.git", "e8b689a513c3e6b63edc44066560ca5919c0576e"),
("https://github.com/evanspearman/ComfyMath.git", "c01177221c31b8e5fbc062778fc8254aeb541638"),
("https://github.com/Smirnov75/ComfyUI-mxToolkit.git", "7f7a0e584f12078a1c589645d866ae96bad0cc35"),
("https://github.com/DoctorDiffusion/ComfyUI-MediaMixer.git", "2bae7b5ea8fc52d8a4d668d62fed76265f4eec2c"),
]
def _git_clone(url: str, dst: pathlib.Path, ref: str) -> None:
"""Clone *url* at *ref* into *dst*. *ref* may be a branch, tag, or SHA.
`git clone --branch` only accepts branch/tag names, so we use init+fetch
which works for any object GitHub allows fetching (default: reachable
commits in public repos).
"""
import subprocess
dst = pathlib.Path(dst)
dst.mkdir(parents=True, exist_ok=True)
subprocess.check_call(["git", "-C", str(dst), "init", "-q"])
subprocess.check_call(["git", "-C", str(dst), "remote", "add", "origin", url])
subprocess.check_call(["git", "-C", str(dst), "fetch", "--depth", "1", "origin", ref])
subprocess.check_call(["git", "-C", str(dst), "checkout", "-q", "FETCH_HEAD"])
def _mirror_preload_hf_cache() -> None:
"""Mirror the build-populated HF cache into a writable runtime tree.
HF Spaces' build pipeline runs `preload_from_hub` as a different user
than the runtime container, so the populated `~/.cache/huggingface/`
is read-only for us (uid 1000). Any subsequent `hf_hub_download` call
that needs to write a NEW file (lazy-loaded LoRAs, GGUF, etc.) fails
with "Permission denied" because the parent dir isn't writable.
Fix: build a parallel tree at `~/hf-cache-rw/` that we own, with:
- dirs: created fresh via mkdir
- blob files (`blobs/<sha>`): hardlinked (shared inode, instant)
- relative snapshot symlinks: preserved as symlinks
- `refs/<branch>` files: byte-copied (HF lib overwrites these)
- everything else: byte-copied (safest default)
Then set HF_HOME / HF_HUB_CACHE so HF lib reads/writes through the
mirror. Reads are zero-copy via hardlink/symlink; new downloads land
in dirs we created.
"""
import shutil
src_root = pathlib.Path.home() / ".cache" / "huggingface"
dst_root = pathlib.Path.home() / "hf-cache-rw"
dst_root.mkdir(parents=True, exist_ok=True)
os.environ["HF_HOME"] = str(dst_root)
os.environ["HF_HUB_CACHE"] = str(dst_root / "hub")
if not src_root.exists():
return
counts = {"dirs": 0, "hardlinks": 0, "symlinks": 0, "copies": 0, "errors": 0}
def _treat_as_copy(rel_path: pathlib.PurePath) -> bool:
# Anything under a refs/ dir, anywhere in the tree.
return any(part == "refs" for part in rel_path.parts)
def _walk(s: pathlib.Path, d: pathlib.Path) -> None:
try:
d.mkdir(parents=True, exist_ok=True)
counts["dirs"] += 1
except OSError as exc:
print(f"[bootstrap] mirror mkdir fail {d}: {exc}", flush=True)
counts["errors"] += 1
return
for entry in s.iterdir():
de = d / entry.name
try:
if entry.is_symlink():
if de.exists() or de.is_symlink():
continue
target = os.readlink(str(entry))
de.symlink_to(target)
counts["symlinks"] += 1
elif entry.is_dir():
_walk(entry, de)
elif entry.is_file():
if de.exists():
continue
rel = de.relative_to(dst_root)
if _treat_as_copy(rel):
shutil.copy2(entry, de)
counts["copies"] += 1
else:
try:
os.link(str(entry), str(de))
counts["hardlinks"] += 1
except OSError:
# Cross-device or other — fall back to symlink.
de.symlink_to(entry)
counts["symlinks"] += 1
except OSError as exc:
print(f"[bootstrap] mirror skip {entry}: {exc}", flush=True)
counts["errors"] += 1
_walk(src_root, dst_root)
print(
f"[bootstrap] hf cache mirrored to {dst_root}: "
f"{counts['dirs']} dirs, {counts['hardlinks']} hardlinks, "
f"{counts['symlinks']} symlinks, {counts['copies']} copies, "
f"{counts['errors']} errors",
flush=True,
)
def _bootstrap() -> None:
on_spaces = _on_spaces()
# /data requires the paid persistent-storage add-on (separate from Pro).
# Without it, /data is unwritable. $HOME is writable and — because ZeroGPU
# containers freeze on sleep rather than tear down — the clone persists
# across calls within a single deploy.
comfy_dir = (pathlib.Path.home() / "comfyui") if on_spaces else pathlib.Path("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(comfy_dir / "models"))
# Mirror the build-time HF cache (populated by preload_from_hub, owned by
# build user → read-only for runtime user 1000) into a writable parallel
# tree under $HOME, then point HF_HUB_CACHE / HF_HOME at it. After this:
# - preloaded blobs are accessible via hardlink (no data copy, instant reads)
# - relative snapshot symlinks resolve within the mirror
# - refs/* are byte-copies so HF lib can overwrite when commits advance
# - new lazy-downloaded files write to dirs we own → no permission errors
if on_spaces:
_mirror_preload_hf_cache()
# 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 (drawer nav drives selection),
# add status-card styling, plus single responsive breakpoint at 1023 px
# (drawer slides over body) / 1024 px+ (drawer pinned).
# ---------------------------------------------------------------------------
_CUSTOM_CSS = """
/* Hide Gradio's top tab strip — sidebar drives selection. */
.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;
}
/* === Header === */
.aio-header {
display: flex;
align-items: center;
gap: 12px;
padding: 11px 18px;
border-bottom: 1px solid #262C35;
background: #12161B;
position: relative;
/* HF injects #huggingface-space-header at fixed z-index 20 (top-right
like/share widget). Stay below it by default so we don't cover it. */
z-index: 15;
}
/* When drawer is open, lift header above scrim (z-45) and drawer (z-50) so
the hamburger flips to × and remains clickable as a close affordance.
Toggled in lockstep with .aio-shell.drawer-open via the inline JS below. */
.aio-header.drawer-elevated {
z-index: 60;
}
.aio-ham-label {
display: none;
width: 32px; height: 32px;
border: 1px solid #262C35;
border-radius: 5px;
color: #7C8693;
cursor: pointer;
align-items: center; justify-content: center;
font-size: 18px; font-weight: 300;
user-select: none;
}
.aio-ham-label:hover { color: #E0A458; border-color: #E0A458; }
.aio-title {
font-size: 15px; font-weight: 600; letter-spacing: -0.01em;
color: #E6E8EB;
}
.aio-title .accent { color: #E0A458; }
.aio-mode-tag {
margin-left: auto;
padding: 4px 9px;
font-family: 'IBM Plex Mono', ui-monospace, monospace;
font-size: 11px; font-weight: 500; letter-spacing: 0.04em;
color: #E0A458;
border: 1px solid #E0A458;
border-radius: 4px;
}
.aio-tipbar {
margin: 0 0 6px 0;
padding: 6px 14px;
font-family: 'IBM Plex Sans', system-ui, sans-serif;
font-size: 12px;
color: #B5BCC6;
background: #1A1F26;
border-bottom: 1px solid #262C35;
text-align: center;
}
.aio-tipbar strong { color: #E6E8EB; font-weight: 500; }
.aio-tipbar .aio-heart { color: #E55B6E; }
.aio-mode-warning {
margin: 4px 0 10px 0 !important;
padding: 10px 14px !important;
font-family: 'IBM Plex Sans', system-ui, sans-serif !important;
font-size: 12px !important;
line-height: 1.55 !important;
color: #D4C18B !important;
background: rgba(224, 164, 88, 0.08) !important;
border-left: 3px solid #E0A458 !important;
border-radius: 4px !important;
}
.aio-mode-warning strong { color: #E0A458 !important; font-weight: 500 !important; }
.aio-hf-tip {
margin: 12px 0 8px 0 !important;
padding: 9px 14px !important;
font-family: 'IBM Plex Sans', system-ui, sans-serif !important;
font-size: 11.5px !important;
line-height: 1.5 !important;
color: #9CA8B5 !important;
background: rgba(124, 134, 147, 0.06) !important;
border-left: 3px solid #5C6671 !important;
border-radius: 4px !important;
}
.aio-hf-tip strong { color: #C8D0DA !important; font-weight: 500 !important; }
/* === Drawer === */
.aio-shell { position: relative; }
.aio-drawer {
width: 220px;
border-right: 1px solid #262C35;
background: #12161B;
padding: 14px 10px !important;
flex-shrink: 0;
transition: left 0.2s ease;
}
.aio-drawer-heading {
font-family: 'IBM Plex Mono', ui-monospace, monospace;
font-size: 10px; text-transform: uppercase; letter-spacing: 0.07em;
color: #7C8693;
padding: 6px 8px 4px !important;
margin: 0 !important;
}
/* Mode buttons */
.aio-mode-btn { width: 100%; text-align: left; margin: 2px 0 !important; }
.aio-mode-btn-active {
background: #1A1F26 !important;
color: #E0A458 !important;
border-left: 3px solid #E0A458 !important;
}
/* Model status / settings panels */
.aio-model-badge {
padding: 9px 11px;
border-radius: 6px;
background: #1A1F26;
border: 1px solid #262C35;
font-size: 11.5px;
font-family: 'IBM Plex Mono', ui-monospace, monospace;
color: #7C8693;
}
/* Discord callout — drawer-bottom community button. Warm amber-on-slate
to match the Topaz palette; the arrow nudges right on hover so it
reads as actionable without screaming. */
.aio-discord-btn {
display: flex;
align-items: center;
gap: 10px;
padding: 10px 12px;
margin: 4px 0;
border-radius: 8px;
background: linear-gradient(135deg, #1F2630 0%, #1A1F26 100%);
border: 1px solid #2C3340;
color: #E0A458 !important;
font-size: 12.5px;
font-weight: 500;
text-decoration: none !important;
transition: border-color 0.15s ease, background 0.15s ease, transform 0.15s ease;
}
.aio-discord-btn:hover {
border-color: #E0A458;
background: linear-gradient(135deg, #242C37 0%, #1F2630 100%);
}
.aio-discord-btn:hover .aio-discord-arrow { transform: translateX(3px); }
.aio-discord-glyph { font-size: 14px; line-height: 1; }
.aio-discord-arrow {
margin-left: auto;
color: #7C8693;
transition: transform 0.15s ease, color 0.15s ease;
}
.aio-discord-btn:hover .aio-discord-arrow { color: #E0A458; }
/* === Status banner === */
.status-card {
padding: 12px 16px;
border-radius: 6px;
background: #1A1F26;
border: 1px solid #262C35;
}
.status-row { display: flex; gap: 14px; align-items: center; margin-bottom: 8px; flex-wrap: wrap; }
.status-stage { font-weight: 600; color: #E0A458; }
.status-meta { font-size: 12px; color: #7C8693; font-family: 'IBM Plex Mono', ui-monospace, monospace; }
.status-bar { height: 4px; background: #262C35; border-radius: 99px; overflow: hidden; }
.status-fill { height: 100%; background: #E0A458; transition: width .3s; }
.status-mem { font-size: 11px; color: #7C8693; margin-top: 6px; font-family: 'IBM Plex Mono', ui-monospace, monospace; }
.status-error {
background: #3A1E20 !important;
border-color: #F4A6A8 !important;
color: #F4A6A8 !important;
}
.status-error .status-stage { color: #F4A6A8; }
/* === Drawer toggle behavior at the desktop boundary === */
@media (max-width: 1023px) {
.aio-ham-label { display: flex; }
.aio-drawer {
position: fixed;
top: 0; bottom: 0;
left: -100%;
z-index: 50;
box-shadow: 4px 0 24px rgba(0,0,0,0.6);
max-width: 80vw;
overflow-y: auto;
overflow-x: hidden;
padding-top: 80px !important;
}
/* `.aio-shell.drawer-open` is toggled by the hamburger's inline JS.
`body:has(:checked)` would be cleaner but Gradio prefixes user CSS
with `.gradio-container .contain `, breaking ancestor selectors. */
.aio-shell.drawer-open .aio-drawer { left: 0; }
.aio-shell.drawer-open::before {
content: ""; position: fixed; inset: 0;
background: rgba(0,0,0,0.92); z-index: 45;
backdrop-filter: blur(10px);
-webkit-backdrop-filter: blur(10px);
}
/* Mobile sub-tweaks */
.aio-mode-btn { font-size: 13px !important; padding: 7px 10px !important; }
.aio-body [class*="row"] { flex-wrap: wrap !important; }
.aio-body [class*="row"] > div { flex: 1 1 100% !important; min-width: 0 !important; }
}
@media (min-width: 1024px) {
.aio-ham-label { display: none; }
}
"""
# ---------------------------------------------------------------------------
# UI
# ---------------------------------------------------------------------------
_TOPAZ_THEME = gr.themes.Base(
primary_hue=gr.themes.Color(
c50="#FBE5C7", c100="#F5D29C", c200="#EFC174", c300="#E9B05A",
c400="#E5A75B", c500="#E0A458", c600="#C68D3F", c700="#A6722E",
c800="#7E5722", c900="#583C18", c950="#3A2810",
),
neutral_hue=gr.themes.Color(
c50="#E6E8EB", c100="#C9CDD3", c200="#ACB1B9", c300="#9097A0",
c400="#7C8693", c500="#626972", c600="#4A4F58", c700="#363B43",
c800="#262C35", c900="#1A1F26", c950="#12161B",
),
font=(gr.themes.GoogleFont("IBM Plex Sans"), "ui-sans-serif", "system-ui", "sans-serif"),
font_mono=(gr.themes.GoogleFont("IBM Plex Mono"), "ui-monospace", "monospace"),
).set(
body_background_fill="#12161B",
background_fill_primary="#12161B",
background_fill_secondary="#1A1F26",
block_background_fill="#1A1F26",
block_label_background_fill="transparent",
body_text_color="#E6E8EB",
body_text_color_subdued="#7C8693",
border_color_primary="#262C35",
border_color_accent="#E0A458",
button_primary_background_fill="#E0A458",
button_primary_background_fill_hover="#F0B870",
button_primary_text_color="#12161B",
button_secondary_background_fill="#1A1F26",
button_secondary_background_fill_hover="#232930",
button_secondary_text_color="#E6E8EB",
button_secondary_border_color="#262C35",
input_background_fill="#12161B",
input_border_color="#262C35",
input_border_color_focus="#E0A458",
error_background_fill="#3A1E20",
error_text_color="#F4A6A8",
slider_color="#E0A458",
)
_HEAD_HTML = """
<script>
(function(){
if (window._aioDismissInstalled) return;
window._aioDismissInstalled = true;
document.addEventListener("click", function(e) {
var s = document.querySelector(".aio-shell");
if (!s || !s.classList.contains("drawer-open")) return;
if (e.target.closest(".aio-drawer") || e.target.closest(".aio-ham-label")) return;
s.classList.remove("drawer-open");
var h = document.querySelector(".aio-header");
if (h) h.classList.remove("drawer-elevated");
var b = document.querySelector(".aio-ham-label");
if (b) {
b.textContent = "\\u2261";
b.setAttribute("aria-expanded", "false");
}
});
})();
</script>
"""
def build_app() -> gr.Blocks:
with gr.Blocks(theme=_TOPAZ_THEME, title="LTX 2.3 Studio", css=_CUSTOM_CSS, head=_HEAD_HTML) as app:
# Header: hamburger button toggles `.drawer-open` on `.aio-shell`.
# The click-outside dismisser is registered via gr.Blocks(head=...)
# below — Gradio strips <script> tags inside gr.HTML so it has to
# live in <head> to actually run.
gr.HTML(
'<div class="aio-header">'
' <button type="button" class="aio-ham-label" '
' onclick="(function(b){var s=document.querySelector(\'.aio-shell\');'
'var o=s.classList.toggle(\'drawer-open\');'
'var h=document.querySelector(\'.aio-header\');'
'if(h)h.classList.toggle(\'drawer-elevated\',o);'
'b.textContent=o?\'\\u00d7\':\'\\u2261\';'
'b.setAttribute(\'aria-expanded\',o?\'true\':\'false\');})(this)" '
' aria-expanded="false" aria-label="Toggle navigation">≡</button>'
' <span class="aio-title">LTX 2.3 <span class="accent">Studio</span></span>'
' <span class="aio-mode-tag" id="aio-mode-tag">T2V</span>'
'</div>'
)
gr.HTML(
'<div class="aio-tipbar">'
'Built with care. '
'<strong>Drop a <span class="aio-heart">♥</span> at the top</strong> to support it '
'· '
'Follow <a href="https://huggingface.co/techfreakworm" target="_blank" rel="noopener noreferrer">@techfreakworm</a> '
'for what\'s next '
'· '
'<a href="https://discord.gg/qbn3exeEXa" target="_blank" rel="noopener noreferrer">Chat with the maker on Discord</a>'
'</div>'
)
with gr.Row(elem_classes=["aio-shell"]):
# Drawer (drawer behaves as fixed sidebar ≥1024 px;
# absolute-positioned overlay <1024 px — see _CUSTOM_CSS).
with gr.Column(scale=1, min_width=200, elem_classes=["aio-drawer"]):
gr.Markdown("Modes", elem_classes=["aio-drawer-heading"])
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-drawer-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-drawer-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"],
)
gr.Markdown("Community", elem_classes=["aio-drawer-heading"])
gr.HTML(
'<a class="aio-discord-btn" href="https://discord.gg/qbn3exeEXa" '
'target="_blank" rel="noopener noreferrer">'
'<span class="aio-discord-glyph">✨</span>'
'<span>Chat with the maker on Discord</span>'
'<span class="aio-discord-arrow">→</span>'
'</a>'
)
gr.Markdown(
"Prefer it hosted? Generate uncensored AI images and videos online at "
"[MakeNSFW — free NSFW AI generator](https://makensfw.com/) — "
"no install, no queue.",
elem_classes=["aio-model-badge"],
)
# Body — unchanged, still hosts the 6 mode tabs.
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"], h["progress_json"]],
)
# JS to update the header mode tag without a server round-trip.
# Each mode button injects a tiny on-click that rewrites #aio-mode-tag
# and (on mobile) auto-collapses the drawer.
_MODE_TAG_BY_NAME = {
"t2v": "T2V", "a2v": "A2V", "i2v": "I2V",
"lipsync": "LIPSYNC", "keyframe": "KEY", "style": "STYLE",
}
for name, btn in mode_buttons.items():
tag = _MODE_TAG_BY_NAME.get(name, name.upper())
btn.click(
fn=lambda mode_id=name: gr.Tabs(selected=mode_id),
inputs=None,
outputs=[tabs_component],
js=f"() => {{ "
f"const el = document.getElementById('aio-mode-tag'); "
f"if (el) el.textContent = {tag!r}; "
f"if (window.matchMedia('(max-width: 1023px)').matches) {{ "
f" document.querySelector('.aio-shell')?.classList.remove('drawer-open'); "
f" document.querySelector('.aio-header')?.classList.remove('drawer-elevated'); "
f" const hb = document.querySelector('.aio-ham-label'); "
f" if (hb) {{ hb.textContent = '\\u2261'; hb.setAttribute('aria-expanded', 'false'); }} "
f"}} return []; }}",
)
# 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":
gr.Markdown(
"**Heads up — Style Transfer is the heaviest mode.** "
"It runs the source video through pose detection AND adds "
"every frame as conditioning, so even the Fast preset can "
"blow the per-call GPU budget on free/anonymous tier. "
"**A failed run still consumes daily quota.** "
"For reliable runs: HF Pro account, resolution ≤ 1024×576, "
"source video ≤ 8 s.",
elem_classes=["aio-mode-warning"],
)
handles["image"] = gr.Image(label="Style reference", type="filepath")
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)
handles["output_format"] = gr.Dropdown(
choices=video_format_module.supported_formats(),
value="mp4",
label="Output format",
info="Delivery container. MP4 plays everywhere; GIF loops without audio; WebM is smaller.",
)
with gr.Accordion("Advanced ▾", open=False):
handles["lora"] = ui.lora_chrome(name)
handles["negative_prompt"] = gr.Textbox(label="Negative prompt", lines=2)
gr.Markdown(
"**Tip for HF Spaces users:** Heavier configurations "
"(Cinematic preset, high resolution, long videos) target local "
"hardware and may abort mid-run on Spaces — burning quota with "
"no output. Stay at Fast/Balanced + ≤ 1024×576 + ≤ 6 s output "
"for safe Spaces runs.",
elem_classes=["aio-hf-tip"],
)
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("")
# Hidden structured-progress channel (index 2 of the handler outputs).
# Each yield becomes an `event: generating` frame on the
# /gradio_api/call SSE stream, so a downstream consumer reading this
# index gets live progress (mirrors ImageStudio / wan2.2 Spaces).
handles["progress_json"] = gr.JSON(label="progress", visible=False)
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
# Must match the comfy_dir used in _bootstrap() — on Spaces this is
# ~/comfyui (mirroring backend.py's _comfy_dir), otherwise repo-local.
_COMFY_INPUT_DIR = (
(pathlib.Path.home() / "comfyui" / "input")
if _on_spaces()
else 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}
_FRIENDLY_ERRORS: dict[str, tuple[str, str]] = {
"gpu_timeout": (
"Hit the GPU time limit",
"This run took longer than the GPU budget. Try the Fast preset, a "
"shorter video, or a smaller resolution — then click Generate again.",
),
"expired_token": (
"Session timed out",
"Your sign-in session expired. Refresh the page and try again — "
"you'll keep your spot in the GPU queue.",
),
"illegal_duration": (
"GPU budget too high",
"The estimator asked for more GPU time than the server allows. "
"Try Fast preset or a shorter video.",
),
"unlogged": (
"Sign-in not detected",
"Make sure you're signed into huggingface.co (top-right avatar), "
"then refresh this page. Pro accounts get 25 min of GPU per day.",
),
"quota_exceeded": (
"Daily GPU quota used up",
"You've used today's GPU minutes. Wait for the rolling 24-hour "
"reset, or upgrade Pro at huggingface.co/subscribe/pro for more.",
),
"oom": (
"Ran out of GPU memory",
"Try a smaller resolution, fewer frames, or the Fast preset.",
),
"interrupt": (
"Cancelled",
"Generation was cancelled. Click Generate to start a fresh run.",
),
"download": (
"Model download failed",
"Couldn't fetch a required model file. Check your internet and try again.",
),
}
def _friendly_error(category: str, raw_message: str) -> tuple[str, str]:
"""Translate a backend error category into (title, body) the user can act on."""
if category in _FRIENDLY_ERRORS:
return _FRIENDLY_ERRORS[category]
return (
"Generation failed",
"Something went wrong. Click Generate to retry, or check the Space "
"logs if it keeps happening.",
)
def _seconds_to_frames(seconds: float, fps: int) -> int:
return max(9, int(round(float(seconds) * float(fps) / 8) * 8) + 1)
def _prune_old_outputs(output_dir: pathlib.Path, max_age_seconds: int = 4 * 3600) -> int:
"""Delete files under *output_dir* older than *max_age_seconds*; return count.
HF Spaces ephemeral disk is 150 GB and preload already eats ~111 GB. Without
this sweep, generations accumulate in `~/comfyui/output/` until the disk
fills and the replica goes unhealthy (observed: stuck `RUNNING` with
`replicas.current=0`). Per-file OSError is swallowed so one bad file
doesn't abort a sweep that would otherwise free space.
"""
if not output_dir.exists():
return 0
cutoff = time.time() - max_age_seconds
deleted = 0
for f in output_dir.rglob("*"):
try:
if not f.is_file():
continue
if f.stat().st_mtime < cutoff:
f.unlink()
deleted += 1
except OSError:
continue
return deleted
# Modes whose output frame geometry is defined by a still input image. The
# value is the input key that carries that image. For these, output width/height
# are derived from the image's aspect ratio (long side capped at _MAX_IMAGE_DIM)
# instead of the Width/Height sliders.
_IMAGE_SIZE_SOURCE = {"i2v": "image", "lipsync": "image", "keyframe": "first_frame"}
_MAX_IMAGE_DIM = 640
def _dims_from_image(path: str, max_dim: int = _MAX_IMAGE_DIM, multiple: int = 32, min_dim: int = 256):
"""Derive (width, height) for the output video from an input image.
The long side is set to ``max_dim`` (preserving aspect ratio); both
dimensions are snapped to a multiple of ``multiple`` (LTX's VAE spatial
compression requires this) and floored at ``min_dim``. Returns ``None`` if
the image can't be read, so the caller falls back to the slider values.
"""
try:
from PIL import Image
with Image.open(path) as im:
w, h = im.size
except Exception:
return None
if not w or not h:
return None
if w >= h:
out_w = max_dim
out_h = round(max_dim * h / w / multiple) * multiple
else:
out_h = max_dim
out_w = round(max_dim * w / h / multiple) * multiple
out_w = max(min_dim, min(max_dim, out_w))
out_h = max(min_dim, min(max_dim, out_h))
return out_w, out_h
async def _on_generate(mode_name: str, *, progress: Any = None, uid: str = "",
is_api: bool = False, watermark: str = "", **inputs: Any):
"""Generate handler — async generator yielding (status_html, video_path).
`progress` is a `gr.Progress` instance injected by Gradio. It's the only
progress channel that survives the @spaces.GPU subprocess boundary on HF
Spaces; we forward it to the backend so ComfyUI's per-step counter renders
a real progress bar instead of a generic Gradio spinner.
"""
_comfy_dir_now = (
(pathlib.Path.home() / "comfyui")
if _on_spaces()
else pathlib.Path(__file__).parent / "comfyui"
)
_prune_old_outputs(_comfy_dir_now / "output")
mode = modes.MODE_REGISTRY[mode_name]
fps = int(inputs.get("fps", 24))
seconds = float(inputs.get("seconds", 3))
frames = _seconds_to_frames(seconds, fps)
# Delivery container for the rendered clip: mp4 (default), gif, or webm. The
# backend always produces an MP4; we transcode after generation/watermark.
output_format = video_format_module.normalize_format(inputs.get("output_format"))
# 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 image-driven modes, the output video size follows the input image's
# aspect ratio (long side capped at _MAX_IMAGE_DIM) rather than the
# Width/Height sliders. Done before staging so we read the original upload.
size_key = _IMAGE_SIZE_SOURCE.get(mode_name)
if size_key and params.get(size_key):
dims = _dims_from_image(params[size_key])
if dims:
params["width"], params["height"] = dims
print(
f"[app] {mode_name}: output size {dims[0]}x{dims[1]} "
f"derived from input image (slider values overridden)",
file=sys.stderr,
flush=True,
)
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()
preset = params["preset"] # already lowercased above
def _progress_payload(stage, p, step=0, total=0, label=""):
# Structured progress contract shared with the ImageStudio / wan2.2 Spaces
# and the generator orchestrator.
#
# API callers get a lean payload: the web front-end renders only `p`
# (useGeneration.ts), and the generator's readProgress() defaults every
# other field when absent (`v.stage || ''`, `Number(v.step) || 0`), while
# workflow.js falls back to its own node label. Since this dict ships on
# every sampler step over a metered proxy, dropping the four unrendered
# fields roughly halves the per-frame cost. `p` is rounded to 3 decimals —
# far finer than a progress bar can show.
p = max(0.0, min(1.0, float(p)))
if is_api:
return {"p": round(p, 3)}
return {
"stage": stage,
"p": p,
"step": int(step),
"total": int(total),
"label": label,
}
def _status(html):
"""Status-banner value for a non-terminal (in-progress) frame.
Gradio's /call protocol re-sends the *entire* output tuple on every
`generating` frame, so this HTML card — which changes each step because
it embeds the step counter and ETA — is retransmitted per sampler step.
For a Quality-preset run that is tens of KB of markup no API caller ever
renders: the generator reads progress from the structured JSON output
and drops the HTML (see registry.readProgress).
Suppressing it for API callers cuts the per-request payload by ~85% on a
metered proxy. `gr.update()` is a no-op, so the web UI is unaffected and
API callers keep an unchanged output arity.
Terminal frames MUST NOT use this: the generator scrapes the R2 filekey
out of the final card (config keyIndex 0 -> /<code>([^<]+)<\\/code>/), so
blanking it would break asset recording, permalinks and the purge trail.
"""
return gr.update() if is_api else html
async def _translate(event, started_at):
"""Translate one backend event into Gradio (status_html, video, progress).
Returns the 3-tuple to yield (or None for events with no UI effect).
"""
elapsed = time.time() - started_at
if isinstance(event, backend_module.DownloadEvent):
return (
_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,
)),
gr.update(),
_progress_payload(
"download", 0.05 * (event.mb_done / max(event.mb_total, 1)),
int(event.mb_done), int(max(event.mb_total, 1)),
f"Downloading {event.filename}",
),
)
if isinstance(event, backend_module.ProgressEvent):
label = f"Diffusion (Stage {event.stage})"
eta = (elapsed / max(event.step, 1)) * (event.total_steps - event.step)
# Diffusion occupies 0.10..0.95 of this node's progress; the leading
# 0.10 covers model load/download, the trailing 0.05 covers encode.
frac = 0.10 + 0.85 * (event.step / max(event.total_steps, 1))
return (
_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,
)),
gr.update(),
_progress_payload(
"diffusion", frac, event.step, event.total_steps, label,
),
)
if isinstance(event, backend_module.OutputEvent):
video_path = event.video_path
# Stamp the brand watermark (logo + domain) onto the clip when the
# caller supplied a valid ``wm`` cookie spec. Write it into the
# ComfyUI output dir so Gradio (allowed_paths) can still serve it.
if video_path and watermark_module.is_valid(watermark):
wm_out = str(_comfy_dir_now / "output" / f"wm_{uuid.uuid4().hex[:8]}.mp4")
video_path = await asyncio.get_event_loop().run_in_executor(
None, lambda: watermark_module.apply_to_video(event.video_path, watermark, wm_out),
)
# Transcode the MP4 into the requested delivery container (gif/webm).
# Write it into the ComfyUI output dir so Gradio (allowed_paths) can
# still serve it. No-op for mp4; falls back to the MP4 on failure.
if video_path and output_format != "mp4":
fmt_out = str(
_comfy_dir_now / "output"
/ f"fmt_{uuid.uuid4().hex[:8]}{video_format_module.ext_for(output_format)}"
)
video_path = await asyncio.get_event_loop().run_in_executor(
None, lambda: video_format_module.convert(video_path, output_format, fmt_out),
)
# gr.Video can't play an animated GIF, so for the interactive web UI we
# suppress the inline player for that format (the file is still
# uploaded). API callers (the generator) read the file path straight
# from this output, so they must always get the real path back —
# otherwise gif/webm jobs return "no result".
video_update = (
video_path
if (video_path and (is_api or output_format != "gif"))
else gr.update()
)
# Direct Gradio web-UI generations are not uploaded to R2 — only API
# calls (the generator, which forwards a uid cookie) are stored.
if video_path and is_api:
# Upload off the event loop so boto3's blocking I/O doesn't stall
# the async generator (and it already runs outside the GPU window).
result = await asyncio.get_event_loop().run_in_executor(
None,
lambda: r2_uploader.upload_asset(
namespace=R2_NAMESPACE,
prompt=params.get("prompt", ""),
params={**params, "output_format": output_format, "uid": uid},
path=video_path,
ext=video_format_module.ext_for(output_format),
content_type=video_format_module.content_type_for(output_format),
uid=uid,
),
)
return (
_render_r2_status(result), video_update,
_progress_payload("done", 1.0, label="Done"),
)
return (
ui._render_idle(), video_update,
_progress_payload("done", 1.0, label="Done"),
)
if isinstance(event, backend_module.ErrorEvent):
title, body = _friendly_error(event.category, event.message)
return (
f'<div class="status-card status-error">'
f' <div class="status-row"><span class="status-stage">{title}</span></div>'
f" <div>{body}</div>"
f"</div>",
gr.update(),
_progress_payload("error", 0.0, label=title),
)
return None
# Single attempt. ZeroGPU-side abort (duration cap) and 401 expired-token
# surface as friendly messages via _friendly_error; user clicks Generate
# again to retry with a fresh request and fresh X-IP-Token.
started = time.time()
# Rate-limit in-progress frames for API callers. The backend emits one event
# per sampler step, and each becomes a full SSE frame over a metered proxy;
# a Quality preset run is 100+ steps. A progress bar cannot usefully show
# more than a few updates a second, and the generator keeps its bar monotonic
# (engine.js maxP), so coalescing is invisible downstream.
#
# Only Download/Progress events are throttled — they are the repeating ones.
# Output/Error frames carry the result and the R2 filekey, so they always
# pass through regardless of timing.
throttle_s = 0.5 if is_api else 0.0
last_emit = 0.0
async for event in backend.submit(
mode_name, workflow,
preset=preset, duration_multiplier=1.0,
progress=progress,
):
is_interim = isinstance(
event, (backend_module.DownloadEvent, backend_module.ProgressEvent)
)
if is_interim and throttle_s:
now = time.time()
if now - last_emit < throttle_s:
continue
last_emit = now
translated = await _translate(event, started)
if translated is not None:
yield translated
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.extend(["image", "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")
base.append("output_format")
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.extend([h["image"], 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)
base.append(h["output_format"])
return base
def _make_handler(mode_name: str, h: dict):
keys = _input_keys_for_mode(mode_name, h)
# `request` must precede *values: Gradio only injects gr.Request into a
# parameter declared before the variadic, otherwise it stays None.
async def handler(request: gr.Request = None, *values, progress=gr.Progress()):
kwargs = dict(zip(keys, values, strict=False))
uid = r2_uploader.uid_from_request(request)
is_api = r2_uploader.request_is_api(request)
watermark = r2_uploader.watermark_from_request(request)
async for output in _on_generate(
mode_name, progress=progress, uid=uid, is_api=is_api,
watermark=watermark, **kwargs,
):
yield output
return handler
if __name__ == "__main__":
# Gradio 5's file-access policy refuses to serve files outside cwd /
# tempdir / allowed_paths. ComfyUI writes generated videos to
# `<comfy_dir>/output/...` which is outside our cwd on Spaces, so
# whitelist that directory tree explicitly.
_on_spaces_at_launch = bool(os.environ.get("SPACES_ZERO_GPU"))
_comfy_dir_at_launch = (
(pathlib.Path.home() / "comfyui") if _on_spaces_at_launch
else pathlib.Path(__file__).parent / "comfyui"
)
_output_dir = _comfy_dir_at_launch / "output"
_output_dir.mkdir(parents=True, exist_ok=True)
app = build_app()
app.launch(
server_name="0.0.0.0",
server_port=7860,
allowed_paths=[str(_output_dir)],
)
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