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Support standalone LTXV audio VAEs#13499

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comfyanonymous merged 1 commit intoComfy-Org:masterfrom
kijai:audiovae
Apr 21, 2026
Merged

Support standalone LTXV audio VAEs#13499
comfyanonymous merged 1 commit intoComfy-Org:masterfrom
kijai:audiovae

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@kijai kijai commented Apr 21, 2026

Since the recent PR ad94d47
Supporting standalone extracted LTXV audio VAEs would be one additional line.

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coderabbitai Bot commented Apr 21, 2026

📝 Walkthrough

Walkthrough

The change modifies VAE initialization in the LTX Audio branch within comfy/sd.py. When loading the state dictionary for AudioVAE, the code now rewrites dictionary keys by replacing the audio_vae. prefix with autoencoder. before instantiating the AudioVAE object. This key mapping adjustment maintains compatibility with the AudioVAE implementation. Control flow and allocation logic remain unchanged.

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name Status Explanation Resolution
Docstring Coverage ⚠️ Warning Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%. Write docstrings for the functions missing them to satisfy the coverage threshold.
✅ Passed checks (4 passed)
Check name Status Explanation
Title check ✅ Passed The title clearly and specifically describes the main change: adding support for standalone LTXV audio VAEs.
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Out of Scope Changes check ✅ Passed Check skipped because no linked issues were found for this pull request.
Description check ✅ Passed The pull request description accurately describes the change: adding support for standalone extracted LTXV audio VAEs with a minimal one-line modification to the VAE initialization logic.

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@comfyanonymous comfyanonymous merged commit eb22225 into Comfy-Org:master Apr 21, 2026
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@zwukong
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zwukong commented Apr 22, 2026

video vae is loaded by VAELoader KJ, maybe need a conversion too

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kijai commented Apr 22, 2026

video vae is loaded by VAELoader KJ, maybe need a conversion too

Video VAE has always worked with the native VAE loader node, it was just the audio that didn't.

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zwukong commented Apr 22, 2026

really? thanks. I still use your old kjnode

Kosinkadink added a commit that referenced this pull request Apr 24, 2026
* fix: pin SQLAlchemy>=2.0 in requirements.txt (fixes #13036) (#13316)

* Refactor io to IO in nodes_ace.py (#13485)

* Bump comfyui-frontend-package to 1.42.12 (#13489)

* Make the ltx audio vae more native. (#13486)

* feat(api-nodes): add automatic downscaling of videos for ByteDance 2 nodes (#13465)

* Support standalone LTXV audio VAEs (#13499)

* [Partner Nodes]  added 4K resolution for Veo models; added Veo 3 Lite model (#13330)

* feat(api nodes): added 4K resolution for Veo models; added Veo 3 Lite model

Signed-off-by: bigcat88 <bigcat88@icloud.com>

* increase poll_interval from 5 to 9

---------

Signed-off-by: bigcat88 <bigcat88@icloud.com>
Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>

* Bump comfyui-frontend-package to 1.42.14 (#13493)

* Add gpt-image-2 as version option (#13501)

* Allow logging in comfy app files. (#13505)

* chore: update workflow templates to v0.9.59 (#13507)

* fix(veo): reject 4K resolution for veo-3.0 models in Veo3VideoGenerationNode (#13504)

The tooltip on the resolution input states that 4K is not available for
veo-3.1-lite or veo-3.0 models, but the execute guard only rejected the
lite combination. Selecting 4K with veo-3.0-generate-001 or
veo-3.0-fast-generate-001 would fall through and hit the upstream API
with an invalid request.

Broaden the guard to match the documented behavior and update the error
message accordingly.

Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>

* feat: RIFE and FILM frame interpolation model support (CORE-29) (#13258)

* initial RIFE support

* Also support FILM

* Better RAM usage, reduce FILM VRAM peak

* Add model folder placeholder

* Fix oom fallback frame loss

* Remove torch.compile for now

* Rename model input

* Shorter input type name

---------

* fix: use Parameter assignment for Stable_Zero123 cc_projection weights (fixes #13492) (#13518)

On Windows with aimdo enabled, disable_weight_init.Linear uses lazy
initialization that sets weight and bias to None to avoid unnecessary
memory allocation. This caused a crash when copy_() was called on the
None weight attribute in Stable_Zero123.__init__.

Replace copy_() with direct torch.nn.Parameter assignment, which works
correctly on both Windows (aimdo enabled) and other platforms.

* Derive InterruptProcessingException from BaseException (#13523)

* bump manager version to 4.2.1 (#13516)

* ModelPatcherDynamic: force cast stray weights on comfy layers (#13487)

the mixed_precision ops can have input_scale parameters that are used
in tensor math but arent a weight or bias so dont get proper VRAM
management. Treat these as force-castable parameters like the non comfy
weight, random params are buffers already are.

* Update logging level for invalid version format (#13526)

* [Partner Nodes] add SD2 real human support (#13509)

* feat(api-nodes): add SD2 real human support

Signed-off-by: bigcat88 <bigcat88@icloud.com>

* fix: add validation before uploading Assets

Signed-off-by: bigcat88 <bigcat88@icloud.com>

* Add asset_id and group_id displaying on the node

Signed-off-by: bigcat88 <bigcat88@icloud.com>

* extend poll_op to use instead of custom async cycle

Signed-off-by: bigcat88 <bigcat88@icloud.com>

* added the polling for the "Active" status after asset creation

Signed-off-by: bigcat88 <bigcat88@icloud.com>

* updated tooltip for group_id

* allow usage of real human in the ByteDance2FirstLastFrame node

* add reference count limits

* corrected price in status when input assets contain video

Signed-off-by: bigcat88 <bigcat88@icloud.com>

---------

Signed-off-by: bigcat88 <bigcat88@icloud.com>

* feat: SAM (segment anything) 3.1 support (CORE-34) (#13408)

* [Partner Nodes] GPTImage: fix price badges, add new resolutions (#13519)

* fix(api-nodes): fixed price badges, add new resolutions

Signed-off-by: bigcat88 <bigcat88@icloud.com>

* proper calculate the total run cost when "n > 1"

Signed-off-by: bigcat88 <bigcat88@icloud.com>

---------

Signed-off-by: bigcat88 <bigcat88@icloud.com>

* chore: update workflow templates to v0.9.61 (#13533)

* chore: update embedded docs to v0.4.4 (#13535)

* add 4K resolution to Kling nodes (#13536)

Signed-off-by: bigcat88 <bigcat88@icloud.com>

* Fix LTXV Reference Audio node (#13531)

* comfy-aimdo 0.2.14: Hotfix async allocator estimations (#13534)

This was doing an over-estimate of VRAM used by the async allocator when lots
of little small tensors were in play.

Also change the versioning scheme to == so we can roll forward aimdo without
worrying about stable regressions downstream in comfyUI core.

* Disable sageattention for SAM3 (#13529)

Causes Nans

* execution: Add anti-cycle validation (#13169)

Currently if the graph contains a cycle, the just inifitiate recursions,
hits a catch all then throws a generic error against the output node
that seeded the validation. Instead, fail the offending cycling mode
chain and handlng it as an error in its own right.

Co-authored-by: guill <jacob.e.segal@gmail.com>

* chore: update workflow templates to v0.9.62 (#13539)

---------

Signed-off-by: bigcat88 <bigcat88@icloud.com>
Co-authored-by: Octopus <liyuan851277048@icloud.com>
Co-authored-by: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
Co-authored-by: Comfy Org PR Bot <snomiao+comfy-pr@gmail.com>
Co-authored-by: Alexander Piskun <13381981+bigcat88@users.noreply.github.com>
Co-authored-by: Jukka Seppänen <40791699+kijai@users.noreply.github.com>
Co-authored-by: AustinMroz <austin@comfy.org>
Co-authored-by: Daxiong (Lin) <contact@comfyui-wiki.com>
Co-authored-by: Matt Miller <matt@miller-media.com>
Co-authored-by: blepping <157360029+blepping@users.noreply.github.com>
Co-authored-by: Dr.Lt.Data <128333288+ltdrdata@users.noreply.github.com>
Co-authored-by: rattus <46076784+rattus128@users.noreply.github.com>
Co-authored-by: guill <jacob.e.segal@gmail.com>
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3 participants