Add get_timestamp() and format_output_filename() utilities to folder_paths.py
that generate unique filenames with UTC timestamps. This eliminates the need
for client-side cache-busting query parameters.
New filename format: prefix_00001_20260131-220945-123456_.ext
Updated all save nodes to use the new format:
- nodes.py (SaveImage, SaveLatent, SaveImageWebsocket)
- comfy_api/latest/_ui.py (UILatent)
- comfy_extras/nodes_video.py (SaveWEBM, SaveAnimatedPNG, SaveAnimatedWEBP)
- comfy_extras/nodes_images.py (SaveSVG)
- comfy_extras/nodes_hunyuan3d.py (Save3D)
- comfy_extras/nodes_model_merging.py (SaveCheckpointSimple)
- comfy_extras/nodes_lora_extract.py (LoraSave)
- comfy_extras/nodes_train.py (SaveEmbedding)
Amp-Thread-ID: https://ampcode.com/threads/T-019c17e5-1c0a-736f-970d-e411aae222fc
* Create nodes_dataset.py
* Add encoded dataset caching mechanism
* make training node to work with our dataset system
* allow trainer node to get different resolution dataset
* move all dataset related implementation to nodes_dataset
* Rewrite dataset system with new io schema
* Rewrite training system with new io schema
* add ui pbar
* Add outputs' id/name
* Fix bad id/naming
* use single process instead of input list when no need
* fix wrong output_list flag
* use torch.load/save and fix bad behaviors
* Add factorization utils for lokr
* Add lokr train impl
* Add loha train impl
* Add adapter map for algo selection
* Add optional grad ckpt and algo selection
* Update __init__.py
* correct key name for loha
* Use custom fwd/bwd func and better init for loha
* Support gradient accumulation
* Fix bugs of loha
* use more stable init
* Add OFT training
* linting