7 Commits

Author	SHA1	Message	Date
Jedrzej Kosinski	1b96430c60	Merge master into worksplit-multigpu (#13546) ... * 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>	2026-04-23 19:20:14 -07:00
Jedrzej Kosinski	aa464b36b3	Multi-GPU device selection for loader nodes + CUDA context fixes (#13483) ... * Fix Hunyuan 3D 2.1 multi-GPU worksplit: use cond_or_uncond instead of hardcoded chunk(2) Amp-Thread-ID: https://ampcode.com/threads/T-019da964-2cc8-77f9-9aae-23f65da233db Co-authored-by: Amp <amp@ampcode.com> * Add GPU device selection to all loader nodes - Add get_gpu_device_options() and resolve_gpu_device_option() helpers in model_management.py for vendor-agnostic GPU device selection - Add device widget to CheckpointLoaderSimple, UNETLoader, VAELoader - Expand device options in CLIPLoader, DualCLIPLoader, LTXAVTextEncoderLoader from [default, cpu] to include gpu:0, gpu:1, etc. on multi-GPU systems - Wire load_diffusion_model_state_dict and load_state_dict_guess_config to respect model_options['load_device'] - Graceful fallback: unrecognized devices (e.g. gpu:1 on single-GPU) silently fall back to default Amp-Thread-ID: https://ampcode.com/threads/T-019daa41-f394-731a-8955-4cff4f16283a Co-authored-by: Amp <amp@ampcode.com> * Add VALIDATE_INPUTS to skip device combo validation for workflow portability When a workflow saved on a 2-GPU machine (with device=gpu:1) is loaded on a 1-GPU machine, the combo validation would reject the unknown value. VALIDATE_INPUTS with the device parameter bypasses combo validation for that input only, allowing resolve_gpu_device_option to handle the graceful fallback at runtime. Amp-Thread-ID: https://ampcode.com/threads/T-019daa41-f394-731a-8955-4cff4f16283a Co-authored-by: Amp <amp@ampcode.com> * Set CUDA device context in outer_sample to match model load_device Custom CUDA kernels (comfy_kitchen fp8 quantization) use torch.cuda.current_device() for DLPack tensor export. When a model is loaded on a non-default GPU (e.g. cuda:1), the CUDA context must match or the kernel fails with 'Can't export tensors on a different CUDA device index'. Save and restore the previous device around sampling. Amp-Thread-ID: https://ampcode.com/threads/T-019daa41-f394-731a-8955-4cff4f16283a Co-authored-by: Amp <amp@ampcode.com> * Fix code review bugs: negative index guard, CPU offload_device, checkpoint te_model_options - resolve_gpu_device_option: reject negative indices (gpu:-1) - UNETLoader: set offload_device when cpu is selected - CheckpointLoaderSimple: pass te_model_options for CLIP device, set offload_device for cpu, pass load_device to VAE - load_diffusion_model_state_dict: respect offload_device from model_options - load_state_dict_guess_config: respect offload_device, pass load_device to VAE Amp-Thread-ID: https://ampcode.com/threads/T-019daa41-f394-731a-8955-4cff4f16283a Co-authored-by: Amp <amp@ampcode.com> * Fix CUDA device context for CLIP encoding and VAE encode/decode Add torch.cuda.set_device() calls to match model's load device in: - CLIP.encode_from_tokens: fixes 'Can't export tensors on a different CUDA device index' when CLIP is loaded on a non-default GPU - CLIP.encode_from_tokens_scheduled: same fix for the hooks code path - CLIP.generate: same fix for text generation - VAE.decode: fixes VAE decoding on non-default GPU - VAE.encode: fixes VAE encoding on non-default GPU Same pattern as the existing outer_sample fix in samplers.py - saves and restores previous CUDA device in a try/finally block. Amp-Thread-ID: https://ampcode.com/threads/T-019dabdc-8feb-766f-b4dc-f46ef4d8ff57 Co-authored-by: Amp <amp@ampcode.com> * Extract cuda_device_context manager, fix tiled VAE methods Add model_management.cuda_device_context() — a context manager that saves/restores torch.cuda.current_device when operating on a non-default GPU. Replaces 6 copies of the manual save/set/restore boilerplate. Refactored call sites: - CLIP.encode_from_tokens - CLIP.encode_from_tokens_scheduled (hooks path) - CLIP.generate - VAE.decode - VAE.encode - samplers.outer_sample Bug fixes (newly wrapped): - VAE.decode_tiled: was missing device context entirely, would fail on non-default GPU when called from 'VAE Decode (Tiled)' node - VAE.encode_tiled: same issue for 'VAE Encode (Tiled)' node Amp-Thread-ID: https://ampcode.com/threads/T-019dabdc-8feb-766f-b4dc-f46ef4d8ff57 Co-authored-by: Amp <amp@ampcode.com> * Restore CheckpointLoaderSimple, add CheckpointLoaderDevice Revert CheckpointLoaderSimple to its original form (no device input) so it remains the simple default loader. Add new CheckpointLoaderDevice node (advanced/loaders) with separate model_device, clip_device, and vae_device inputs for per-component GPU placement in multi-GPU setups. Amp-Thread-ID: https://ampcode.com/threads/T-019dabdc-8feb-766f-b4dc-f46ef4d8ff57 Co-authored-by: Amp <amp@ampcode.com> --------- Co-authored-by: Amp <amp@ampcode.com>	2026-04-23 19:10:33 -07:00
Christian Byrne	4d172e9ad7	feat: mark 429 widgets as advanced for collapsible UI (#12197) ... * feat: mark 429 widgets as advanced for collapsible UI Mark widgets as advanced across core, comfy_extras, and comfy_api_nodes to support the new collapsible advanced inputs section in the frontend. Changes: - 267 advanced markers in comfy_extras/ - 162 advanced markers in comfy_api_nodes/ - All files pass python3 -m py_compile verification Widgets marked advanced (hidden by default): - Scheduler internals: sigma_max, sigma_min, rho, mu, beta, alpha - Sampler internals: eta, s_noise, order, rtol, atol, h_init, pcoeff, etc. - Memory optimization: tile_size, overlap, temporal_size, temporal_overlap - Pipeline controls: add_noise, start_at_step, end_at_step - Timing controls: start_percent, end_percent - Layer selection: stop_at_clip_layer, layers, block_number - Video encoding: codec, crf, format - Device/dtype: device, noise_device, dtype, weight_dtype Widgets kept basic (always visible): - Core params: strength, steps, cfg, denoise, seed, width, height - Model selectors: ckpt_name, lora_name, vae_name, sampler_name - Common controls: upscale_method, crop, batch_size, fps, opacity Related: frontend PR #11939 Amp-Thread-ID: https://ampcode.com/threads/T-019c1734-6b61-702e-b333-f02c399963fc * fix: remove advanced=True from DynamicCombo.Input (unsupported) Amp-Thread-ID: https://ampcode.com/threads/T-019c1734-6b61-702e-b333-f02c399963fc * fix: address review - un-mark model merge, video, image, and training node widgets as advanced Per comfyanonymous review: - Model merge arguments should not be advanced (all 14 model-specific merge classes) - SaveAnimatedWEBP lossless/quality/method should not be advanced - SaveWEBM/SaveVideo codec/crf/format should not be advanced - TrainLoraNode options should not be advanced (7 inputs) Amp-Thread-ID: https://ampcode.com/threads/T-019c322b-a3a8-71b7-9962-d44573ca6352 * fix: un-mark batch_size and webcam width/height as advanced (should stay basic) Amp-Thread-ID: https://ampcode.com/threads/T-019c3236-1417-74aa-82a3-bcb365fbe9d1 --------- Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>	2026-02-19 19:20:02 -08:00
Jukka Seppänen	1c705f7bfb	Add device selection for LTXAVTextEncoderLoader (#11700)	2026-01-07 18:39:59 -05:00
comfyanonymous	4f3f9e72a9	Fix name. (#11638)	2026-01-05 02:41:23 -08:00
comfyanonymous	d1b9822f74	Add LTXAVTextEncoderLoader node. (#11634)	2026-01-05 02:27:31 -05:00
comfyanonymous	f2b002372b	Support the LTXV 2 model. (#11632)	2026-01-05 01:58:59 -05:00