* Initial HiDream01-image support
* Cleanup nodes
* Cleaner handling of empty placeholder models
* Remove snap_to_predefined, prefer tooltip for the trained resolutions
* Add model and block wrappers
* Fix shift tooltip
* Add node to work around the patch tile issue
Experimental, runs multiple passes with the patch grid offset and blends with various different methods.
* Qwen35 vision rotary_pos_emb cast fix
* Fix embedding layout type
* Some small optimizations
* Cleanup, don't need this fallback
* Prefix KV cache, cleanup
Bit of speed, reduce redundant code
* Get rid of redundant custom sampler, refactor noise scaling
Our existing lcm sampler is mathematically same, just added the missing options to it instead and a node to control them. Refactored the noise scaling and fix it for the stochastic samplers, add a generic node to control the initial noise scale.
* Update nodes_hidream_o1.py
* Fix some cache validation cases
* Keep existing sampling params
* Remove redundant video vision path
* Replace some numpy ops with torch
* Fx RoPE index for batch size > 1
* Prefer torch preprocessing
* Rename block_type to be compatible with existing patch nodes
* Fixes and tweaks
* Add Boolean support to math expressions
* Change boolean result test to assert values
---------
Co-authored-by: Alexis Rolland <alexisrolland@hotmail.com>
* initial WanDancer support
* nodes_wandancer: Add list form of chunker.
Create an alternate list form of the node so the chunk gens can be
trivially looped by the comfy executor.
* Closer match to original soxr resampling
* Remove librosa node
* Cleanup
---------
Co-authored-by: Rattus <rattus128@gmail.com>
* Update language options in nodes_ace.py
Modified it to include all 51 language options ace-step1.5 supports instead of the original 23 comfyui had.
* re-arrange list by popularity
changed order of the languages to be ordered by popularity
en is default
unknown is last
* Update comfy_extras/nodes_ace.py
* initial gemma4 support
* parity with reference implementation
outputs can 100% match transformers with same sdpa flags, checkpoint this and then optimize
* Cleanup, video fixes
* cleanup, enable fused rms norm by default
* update comment
* Cleanup
* Update sd.py
* Various fixes
* Add fp8 scaled embedding support
* small fixes
* Translate think tokens
* Fix image encoder attention mask type
So it works with basic attention
* Handle thinking tokens different only for Gemma4
* Code cleanup
* Update nodes_textgen.py
* Use embed scale class instead of buffer
Slight difference to HF, but technically more accurate and simpler code
* Default to fused rms_norm
* Update gemma4.py
SolidMask had a hardcoded device="cpu" while other nodes (e.g.
EmptyImage) follow intermediate_device(). This causes a RuntimeError
when MaskComposite combines masks from different device sources
under --gpu-only.
- SolidMask: use intermediate_device() instead of hardcoded "cpu"
- MaskComposite: align source device to destination before operating
Co-authored-by: Alexis Rolland <alexisrolland@hotmail.com>
Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>
* Change save 3d model's filename prefix to 3d/ComfyUI
As this node has already changed from `Save GLB` to `Save 3D Model`, using the filename prefix `3d` will be better than `mesh`
* use lowercase
---------
* 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
---------
Rename all 11 nodes in the utils/string category to include a "Text"
prefix for better discoverability and natural sorting. Regex nodes get
user-friendly names without "Regex" in the display name.
Renames:
- Concatenate → Text Concatenate
- Substring → Text Substring
- Length → Text Length
- Case Converter → Text Case Converter
- Trim → Text Trim
- Replace → Text Replace
- Contains → Text Contains
- Compare → Text Compare
- Regex Match → Text Match
- Regex Extract → Text Extract Substring
- Regex Replace → Text Replace (Regex)
All renamed nodes include their old display name as a search alias so
users can still find them by searching the original name. Regex nodes
also include "regex" as a search alias.
When training_dtype is set to "none" and the model's native dtype is
float16, GradScaler was unconditionally enabled. However, GradScaler
does not support bfloat16 gradients (only float16/float32), causing a
NotImplementedError when lora_dtype is "bf16" (the default).
Fix by only enabling GradScaler when LoRA parameters are not in
bfloat16, since bfloat16 has the same exponent range as float32 and
does not need gradient scaling to avoid underflow.
Fixes#13124
* Add Number Convert node for unified numeric type conversion
Consolidates fragmented IntToFloat/FloatToInt nodes (previously only
available via third-party packs like ComfyMath, FillNodes, etc.) into
a single core node.
- Single input accepting INT, FLOAT, STRING, and BOOL types
- Two outputs: FLOAT and INT
- Conversion: bool→0/1, string→parsed number, float↔int standard cast
- Follows Math Expression node patterns (comfy_api, io.Schema, etc.)
Refs: COM-16925
* Register nodes_number_convert.py in extras_files list
Without this entry in nodes.py, the Number Convert node file
would not be discovered and loaded at startup.
* Add isfinite guard, exception chaining, and unit tests for Number Convert node
- Add math.isfinite() check to prevent int() crash on inf/nan string inputs
- Use 'from None' for cleaner exception chaining on string parse failure
- Add 21 unit tests covering all input types and error paths
* CURVE node
* remove curve to sigmas node
* feat: add CurveInput ABC with MonotoneCubicCurve implementation (#12986)
CurveInput is an abstract base class so future curve representations
(bezier, LUT-based, analytical functions) can be added without breaking
downstream nodes that type-check against CurveInput.
MonotoneCubicCurve is the concrete implementation that:
- Mirrors frontend createMonotoneInterpolator (curveUtils.ts) exactly
- Pre-computes slopes as numpy arrays at construction time
- Provides vectorised interp_array() using numpy for batch evaluation
- interp() for single-value evaluation
- to_lut() for generating lookup tables
CurveEditor node wraps raw widget points in MonotoneCubicCurve.
* linear curve
* refactor: move CurveEditor to comfy_extras/nodes_curve.py with V3 schema
* feat: add HISTOGRAM type and histogram support to CurveEditor
* code improve
---------
Co-authored-by: Christian Byrne <cbyrne@comfy.org>
* Add slice_cond and per-model context window cond resizing
* Fix cond_value.size() call in context window cond resizing
* Expose additional advanced inputs for ContextWindowsManualNode
Necessary for WanAnimate context windows workflow, which needs cond_retain_index_list = 0 to work properly with its reference input.
---------
* feat: add essentials_category to nodes and blueprints for Essentials tab
Add ESSENTIALS_CATEGORY or essentials_category to 12 node classes and all
36 blueprint JSONs. Update SubgraphEntry TypedDict and subgraph_manager to
extract and pass through the field.
Fixes COM-15221
Amp-Thread-ID: https://ampcode.com/threads/T-019c83de-f7ab-7779-a451-0ba5940b56a9
* fix: import NotRequired from typing_extensions for Python 3.10 compat
* refactor: keep only node class ESSENTIALS_CATEGORY, remove blueprint/subgraph changes
Frontend will own blueprint categorization separately.
* fix: remove essentials_category from CreateVideo (not in spec)
---------
Co-authored-by: guill <jacob.e.segal@gmail.com>
Pytorch only filters for OOMs in its own allocators however there are
paths that can OOM on allocators made outside the pytorch allocators.
These manifest as an AllocatorError as pytorch does not have universal
error translation to its OOM type on exception. Handle it. A log I have
for this also shows a double report of the error async, so call the
async discarder to cleanup and make these OOMs look like OOMs.
* feat: add EagerEval dataclass for frontend-side node evaluation
Add EagerEval to the V3 API schema, enabling nodes to declare
frontend-evaluated JSONata expressions. The frontend uses this to
display computation results as badges without a backend round-trip.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add Math Expression node with JSONata evaluation
Add ComfyMathExpression node that evaluates JSONata expressions against
dynamically-grown numeric inputs using Autogrow + MatchType. Sends
input context via ui output so the frontend can re-evaluate when
the expression changes without a backend round-trip.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: register nodes_math.py in extras_files loader list
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address CodeRabbit review feedback
- Harden EagerEval.validate with type checks and strip() for empty strings
- Add _positional_alias for spreadsheet-style names beyond z (aa, ab...)
- Validate JSONata result is numeric before returning
- Add jsonata to requirements.txt
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* refactor: remove EagerEval, scope PR to math node only
Remove EagerEval dataclass from _io.py and eager_eval usage from
nodes_math.py. Eager execution will be designed as a general-purpose
system in a separate effort.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: use TemplateNames, cap inputs at 26, improve error message
Address Kosinkadink review feedback:
- Switch from Autogrow.TemplatePrefix to Autogrow.TemplateNames so input
slots are named a-z, matching expression variables directly
- Cap max inputs at 26 (a-z) instead of 100
- Simplify execute() by removing dual-mapping hack
- Include expression and result value in error message
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* test: add unit tests for Math Expression node
Add tests for _positional_alias (a-z mapping) and execute() covering
arithmetic operations, float inputs, $sum(values), and error cases.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* refactor: replace jsonata with simpleeval for math evaluation
jsonata PyPI package has critical issues: no Python 3.12/3.13 wheels,
no ARM/Apple Silicon wheels, abandoned (last commit 2023), C extension.
Replace with simpleeval (pure Python, 3.4M downloads/month, MIT,
AST-based security). Add math module functions (sqrt, ceil, floor,
log, sin, cos, tan) and variadic sum() supporting both sum(values)
and sum(a, b, c). Pin version to >=1.0,<2.0.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* test: update tests for simpleeval migration
Update JSONata syntax to Python syntax ($sum -> sum, $string -> str),
add tests for math functions (sqrt, ceil, floor, sin, log10) and
variadic sum(a, b, c).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* refactor: replace MatchType with MultiType inputs and dual FLOAT/INT outputs
Allow mixing INT and FLOAT connections on the same node by switching
from MatchType (which forces all inputs to the same type) to MultiType.
Output both FLOAT and INT so users can pick the type they need.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* test: update tests for mixed INT/FLOAT inputs and dual outputs
Add assertions for both FLOAT (result[0]) and INT (result[1]) outputs.
Add test_mixed_int_float_inputs and test_mixed_resolution_scale to
verify the primary use case of multiplying resolutions by a float factor.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: make expression input multiline and validate empty expression
- Add multiline=True to expression input for better UX with longer expressions
- Add empty expression validation with clear "Expression cannot be empty." message
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* test: add tests for empty expression validation
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address review feedback — safe pow, isfinite guard, test coverage
- Wrap pow() with _safe_pow to prevent DoS via huge exponents
(pow() bypasses simpleeval's safe_power guard on **)
- Add math.isfinite() check to catch inf/nan before int() conversion
- Add int/float converters to MATH_FUNCTIONS for explicit casting
- Add "calculator" search alias
- Replace _positional_alias helper with string.ascii_lowercase
- Narrow test assertions and add error path + function coverage tests
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* Update requirements.txt
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: Jedrzej Kosinski <kosinkadink1@gmail.com>
Co-authored-by: Christian Byrne <abolkonsky.rem@gmail.com>
Allows explicit control over the causal_fix flag passed to
latent_to_pixel_coords. Defaults to frame_idx == 0 when not
specified, fixing the previous heuristic.
* sd: add support for clip model reconstruction
* nodes: SetClipHooks: Demote the dynamic model patcher
* mp: Make dynamic_disable more robust
The backup need to not be cloned. In addition add a delegate object
to ModelPatcherDynamic so that non-cloning code can do
ModelPatcherDynamic demotion
* sampler_helpers: Demote to non-dynamic model patcher when hooking
* code rabbit review comments
Move essentials_category from deprecated/incorrect nodes to their replacements:
- ImageBatch → BatchImagesNode (ImageBatch is deprecated)
- Blur → removed (should use subgraph blueprint)
- GetVideoComponents → Video Slice
Amp-Thread-ID: https://ampcode.com/threads/T-019c8340-4da2-723b-a09f-83895c5bbda5
Implements per-guide attention attenuation via log-space additive bias
in self-attention. Each guide reference tracks its own strength and
optional spatial mask in conditioning metadata (guide_attention_entries).
* mp: attach re-construction arguments to model patcher
When making a model-patcher from a unet or ckpt, attach a callable
function that can be called to replay the model construction. This
can be used to deep clone model patcher WRT the actual model.
Originally written by Kosinkadink
f4b99bc623
* mp: Add disable_dynamic clone argument
Add a clone argument that lets a caller clone a ModelPatcher but disable
dynamic to demote the clone to regular MP. This is useful for legacy
features where dynamic_vram support is missing or TBD.
* torch_compile: disable dynamic_vram
This is a bigger feature. Disable for the interim to preserve
functionality.
Add 24 non-cloud essential blueprints from comfyui-wiki/Subgraph-Blueprints.
These cover common workflows: text/image/video generation, editing,
inpainting, outpainting, upscaling, depth maps, pose, captioning, and more.
Cloud-only blueprints (5) are excluded and will be added once
client-side distribution filtering lands.
Amp-Thread-ID: https://ampcode.com/threads/T-019c6f43-6212-7308-bea6-bfc35a486cbf
* lora_extract: Add a trange
If you bite off more than your GPU can chew, this kinda just hangs.
Give a rough indication of progress counting the weights in a trange.
* lora_extract: Support on-the-fly patching
Use the on-the-fly approach from the regular model saving logic for
lora extraction too. Switch off force_cast_weights accordingly.
This gets extraction working in dynamic vram while also supporting
extraction on GPU offloaded.
* Fix bypass dtype/device moving
* Force offloading mode for training
* training context var
* offloading implementation in training node
* fix wrong input type
* Support bypass load lora model, correct adapter/offloading handling
* feat(comfy_api): add basic 3D Model file types
* update Tripo nodes to use File3DGLB
* update Rodin3D nodes to use File3DGLB
* address PR review feedback:
- Rename File3D parameter 'path' to 'source'
- Convert File3D.data property to get_data()
- Make .glb extension check case-insensitive in nodes_rodin.py
- Restrict SaveGLB node to only accept File3DGLB
* Fixed a bug in the Meshy Rig and Animation nodes
* Fix backward compatability
- Add search_aliases for discoverability: resize, scale, dimensions, etc.
- Add node description for hover tooltip
- Add tooltips to all inputs explaining their behavior
- Reorder options: most common (scale dimensions) first, most technical (scale to multiple) last
Addresses user feedback that 'resize' search returned nothing useful and
options like 'match size' and 'scale to multiple' were not self-explanatory.
- Add search_aliases for discoverability: resize, scale, dimensions, etc.
- Add node description for hover tooltip
- Add tooltips to all inputs explaining their behavior
- Reorder options: most common (scale dimensions) first, most technical (scale to multiple) last
Addresses user feedback that 'resize' search returned nothing useful and
options like 'match size' and 'scale to multiple' were not self-explanatory.
* re-init
* Update model_multitalk.py
* whitespace...
* Update model_multitalk.py
* remove print
* this is redundant
* remove import
* Restore preview functionality
* Move block_idx to transformer_options
* Remove LoopingSamplerCustomAdvanced
* Remove looping functionality, keep extension functionality
* Update model_multitalk.py
* Handle ref_attn_mask with separate patch to avoid having to always return q and k from self_attn
* Chunk attention map calculation for multiple speakers to reduce peak VRAM usage
* Update model_multitalk.py
* Add ModelPatch type back
* Fix for latest upstream
* Use DynamicCombo for cleaner node
Basically just so that single_speaker mode hides mask inputs and 2nd audio input
* Update nodes_wan.py
* Support Combo outputs in a more sane way
* Remove test validate_inputs function on test node
* Make curr_prefix be a list of strings instead of string for easier parsing as keys get added to dynamic types
* Start to account for id prefixes from frontend, need to fix bug with nested dynamics
* Ensure inputs/outputs/hidden are lists in schema finalize function, remove no longer needed 'is not None' checks
* Add raw_link and extra_dict to all relevant Inputs
* Make nested DynamicCombos work properly with prefixed keys on latest frontend; breaks old Autogrow, but is pretty much ready for upcoming Autogrow keys
* Replace ... usage with a MISSING sentinel for clarity in nodes_logic.py
* Added CustomCombo node in backend to reflect frontend node
* Prepare Autogrow's expand_schema_for_dynamic to work with upcoming frontend changes
* Prepare for look up table for dynamic input stuff
* More progress towards dynamic input lookup function stuff
* Finished converting _expand_schema_for_dynamic to be done via lookup instead of OOP to guarantee working with process isolation, did refactoring to remove old implementation + cleaning INPUT_TYPES definition including v3 hidden definition
* Change order of functions
* Removed some unneeded functions after dynamic refactor
* Make MatchType's output default displayname "MATCHTYPE"
* Fix DynamicSlot get_all
* Removed redundant code - dynamic stuff no longer happens in OOP way
* Natively support AnyType (*) without __ne__ hacks
* Remove stray code that made it in
* Remove expand_schema_for_dynamic left over on DynamicInput class
* get_dynamic() on DynamicInput/Output was not doing anything anymore, so removed it
* Make validate_inputs validate combo input correctly
* Temporarily comment out conversion to 'new' (9 month old) COMBO format in get_input_info
* Remove refrences to resources feature scrapped from V3
* Expose DynamicCombo in public API
* satisfy ruff after some code got commented out
* Make missing input error prettier for dynamic types
* Created a Switch2 node as a side-by-side test, will likely go with Switch2 as the initial switch node
* Figured out Switch situation
* Pass in v3_data in IsChangedCache.get function's fingerprint_inputs, add a from_v3_data helper method to HiddenHolder
* Switch order of Switch and Soft Switch nodes in file
* Temp test node for MatchType
* Fix missing v3_data for v1 nodes in validation
* For now, remove chacking duplicate id's for dynamic types
* Add Resize Image/Mask node that thanks to MatchType+DynamicCombo is 16-nodes-in-1
* Made DynamicCombo references in DCTestNode use public interface
* Add an AnyTypeTestNode
* Make lazy status for specific inputs on DynamicInputs work by having the values of the dictionary for check_lazy_status be a tuple, where the second element is the key of the input that can be returned
* Comment out test logic nodes
* Make primitive float's step make more sense
* Add (and leave commented out) some potential logic nodes
* Change default crop option to "center" on Resize Image/Mask node
* Changed copy.copy(d) to d.copy()
* Autogrow is available in stable frontend, so exposing it in public API
* Use outputs id as display_name if no display_name present, remove v3 outputs id restriction that made them have to have unique IDs from the inputs
* Enable Custom Combo node as stable frontend now supports it
* Make id properly act like display_name on outputs
* Add Batch Images/Masks/Latents node
* Comment out Batch Images/Masks/Latents node for now, as Autogrow has a bug with MatchType where top connection is disconnected upon refresh
* Removed code for a couple test nodes in nodes_logic.py
* Add Batch Images, Batch Masks, and Batch Latents nodes with Autogrow, deprecate old Batch Images + LatentBatch nodes
Can be used to manually set the sigmas for a model.
This node accepts a list of integer and floating point numbers separated
with any non numeric character.
This operation trades in latents which in --gpu-only may be out of the GPU
The two VAE results will follow the --gpu-only defined behaviour so follow
the inpaint image device when calculating the mask in this path.
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