Load the projector.safetensors file with the ModelPatchLoader node and use
the siglip_vision_patch14_384.safetensors "clip vision" model and the
USOStyleReferenceNode.
* Attempting a universal implementation of EasyCache, starting with flux as test; I screwed up the math a bit, but when I set it just right it works.
* Fixed math to make threshold work as expected, refactored code to use EasyCacheHolder instead of a dict wrapped by object
* Use sigmas from transformer_options instead of timesteps to be compatible with a greater amount of models, make end_percent work
* Make log statement when not skipping useful, preparing for per-cond caching
* Added DIFFUSION_MODEL wrapper around forward function for wan model
* Add subsampling for heuristic inputs
* Add subsampling to output_prev (output_prev_subsampled now)
* Properly consider conds in EasyCache logic
* Created SuperEasyCache to test what happens if caching and reuse is moved outside the scope of conds, added PREDICT_NOISE wrapper to facilitate this test
* Change max reuse_threshold to 3.0
* Mark EasyCache/SuperEasyCache as experimental (beta)
* Make Lumina2 compatible with EasyCache
* Add EasyCache support for Qwen Image
* Fix missing comma, curse you Cursor
* Add EasyCache support to AceStep
* Add EasyCache support to Chroma
* Added EasyCache support to Cosmos Predict t2i
* Make EasyCache not crash with Cosmos Predict ImagToVideo latents, but does not work well at all
* Add EasyCache support to hidream
* Added EasyCache support to hunyuan video
* Added EasyCache support to hunyuan3d
* Added EasyCache support to LTXV (not very good, but does not crash)
* Implemented EasyCache for aura_flow
* Renamed SuperEasyCache to LazyCache, hardcoded subsample_factor to 8 on nodes
* Eatra logging when verbose is true for EasyCache
These are not real controlnets but actually a patch on the model so they
will be treated as such.
Put them in the models/model_patches/ folder.
Use the new ModelPatchLoader and QwenImageDiffsynthControlnet nodes.
* P2 of qwen edit model.
* Typo.
* Fix normal qwen.
* Fix.
* Make the TextEncodeQwenImageEdit also set the ref latent.
If you don't want it to set the ref latent and want to use the
ReferenceLatent node with your custom latent instead just disconnect the
VAE.
This node is only useful if someone trains the kontext model to properly
use multiple reference images via the index method.
The default is the offset method which feeds the multiple images like if
they were stitched together as one. This method works with the current
flux kontext model.
Turns out torch.compile has some gaps in context manager decorator
syntax support. I've sent patches to fix that in PyTorch, but it won't
be available for all the folks running older versions of PyTorch, hence
this trivial patch.
* Added initial support for basic context windows - in progress
* Add prepare_sampling wrapper for context window to more accurately estimate latent memory requirements, fixed merging wrappers/callbacks dicts in prepare_model_patcher
* Made context windows compatible with different dimensions; works for WAN, but results are bad
* Fix comfy.patcher_extension.merge_nested_dicts calls in prepare_model_patcher in sampler_helpers.py
* Considering adding some callbacks to context window code to allow extensions of behavior without the need to rewrite code
* Made dim slicing cleaner
* Add Wan Context WIndows node for testing
* Made context schedule and fuse method functions be stored on the handler instead of needing to be registered in core code to be found
* Moved some code around between node_context_windows.py and context_windows.py
* Change manual context window nodes names/ids
* Added callbacks to IndexListContexHandler
* Adjusted default values for context_length and context_overlap, made schema.inputs definition for WAN Context Windows less annoying
* Make get_resized_cond more robust for various dim sizes
* Fix typo
* Another small fix
* Change bf16 check and switch non-blocking to off default with option to force to regain speed on certain classes of iGPUs and refactor xpu check.
* Turn non_blocking off by default for xpu.
* Update README.md for Intel GPUs.
* 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
* Support for async execution functions
This commit adds support for node execution functions defined as async. When
a node's execution function is defined as async, we can continue
executing other nodes while it is processing.
Standard uses of `await` should "just work", but people will still have
to be careful if they spawn actual threads. Because torch doesn't really
have async/await versions of functions, this won't particularly help
with most locally-executing nodes, but it does work for e.g. web
requests to other machines.
In addition to the execute function, the `VALIDATE_INPUTS` and
`check_lazy_status` functions can also be defined as async, though we'll
only resolve one node at a time right now for those.
* Add the execution model tests to CI
* Add a missing file
It looks like this got caught by .gitignore? There's probably a better
place to put it, but I'm not sure what that is.
* Add the websocket library for automated tests
* Add additional tests for async error cases
Also fixes one bug that was found when an async function throws an error
after being scheduled on a task.
* Add a feature flags message to reduce bandwidth
We now only send 1 preview message of the latest type the client can
support.
We'll add a console warning when the client fails to send a feature
flags message at some point in the future.
* Add async tests to CI
* Don't actually add new tests in this PR
Will do it in a separate PR
* Resolve unit test in GPU-less runner
* Just remove the tests that GHA can't handle
* Change line endings to UNIX-style
* Avoid loading model_management.py so early
Because model_management.py has a top-level `logging.info`, we have to
be careful not to import that file before we call `setup_logging`. If we
do, we end up having the default logging handler registered in addition
to our custom one.
* feat: “--whitelist-custom-nodes” args for comfy core to go with “--disable-all-custom-nodes” for development purposes
* feat: Simplify custom nodes whitelist logic to use consistent code paths
* support wan camera models
* fix by ruff check
* change camera_condition type; make camera_condition optional
* support camera trajectory nodes
* fix camera direction
---------
Co-authored-by: Qirui Sun <sunqr0667@126.com>
* [Luma] Print download URL of successful task result directly on nodes (#177)
[Veo] Print download URL of successful task result directly on nodes (#184)
[Recraft] Print download URL of successful task result directly on nodes (#183)
[Pixverse] Print download URL of successful task result directly on nodes (#182)
[Kling] Print download URL of successful task result directly on nodes (#181)
[MiniMax] Print progress text and download URL of successful task result directly on nodes (#179)
[Docs] Link to docs in `API_NODE` class property type annotation comment (#178)
[Ideogram] Print download URL of successful task result directly on nodes (#176)
[Kling] Print download URL of successful task result directly on nodes (#181)
[Veo] Print download URL of successful task result directly on nodes (#184)
[Recraft] Print download URL of successful task result directly on nodes (#183)
[Pixverse] Print download URL of successful task result directly on nodes (#182)
[MiniMax] Print progress text and download URL of successful task result directly on nodes (#179)
[Docs] Link to docs in `API_NODE` class property type annotation comment (#178)
[Luma] Print download URL of successful task result directly on nodes (#177)
[Ideogram] Print download URL of successful task result directly on nodes (#176)
Show output URL and progress text on Pika nodes (#168)
[BFL] Print download URL of successful task result directly on nodes (#175)
[OpenAI ] Print download URL of successful task result directly on nodes (#174)
* fix ruff errors
* fix 3.10 syntax error
* Add Ideogram generate node.
* Add staging api.
* Add API_NODE and common error for missing auth token (#5)
* Add Minimax Video Generation + Async Task queue polling example (#6)
* [Minimax] Show video preview and embed workflow in ouput (#7)
* Remove uv.lock
* Remove polling operations.
* Revert "Remove polling operations."
* Update stubs.
* Added Ideogram and Minimax back in.
* Added initial BFL Flux 1.1 [pro] Ultra node (#11)
* Add --comfy-api-base launch arg (#13)
* Add instructions for staging development. (#14)
* remove validation to make it easier to run against LAN copies of the API
* Manually add BFL polling status response schema (#15)
* Add function for uploading files. (#18)
* Add Luma nodes (#16)
* Refactor util functions (#20)
* Add VIDEO type (#21)
* Add rest of Luma node functionality (#19)
* Fix image_luma_ref not working (#28)
* [Bug] Remove duplicated option T2V-01 in MinimaxTextToVideoNode (#31)
* Add utils to map from pydantic model fields to comfy node inputs (#30)
* add veo2, bump av req (#32)
* Add Recraft nodes (#29)
* Add Kling Nodes (#12)
* Add Camera Concepts (luma_concepts) to Luma Video nodes (#33)
* Add Runway nodes (#17)
* Convert Minimax node to use VIDEO output type (#34)
* Standard `CATEGORY` system for api nodes (#35)
* Set `Content-Type` header when uploading files (#36)
* add better error propagation to veo2 (#37)
* Add Realistic Image and Logo Raster styles for Recraft v3 (#38)
* Fix runway image upload and progress polling (#39)
* Fix image upload for Luma: only include `Content-Type` header field if it's set explicitly (#40)
* Moved Luma nodes to nodes_luma.py (#47)
* Moved Recraft nodes to nodes_recraft.py (#48)
* Add Pixverse nodes (#46)
* Move and fix BFL nodes to node_bfl.py (#49)
* Move and edit Minimax node to nodes_minimax.py (#50)
* Add Minimax Image to Video node + Cleanup (#51)
* Add Recraft Text to Vector node, add Save SVG node to handle its output (#53)
* Added pixverse_template support to Pixverse Text to Video node (#54)
* Added Recraft Controls + Recraft Color RGB nodes (#57)
* split remaining nodes out of nodes_api, make utility lib, refactor ideogram (#61)
* Add types and doctstrings to utils file (#64)
* Fix: `PollingOperation` progress bar update progress by absolute value (#65)
* Use common download function in kling nodes module (#67)
* Fix: Luma video nodes in `api nodes/image` category (#68)
* Set request type explicitly (#66)
* Add `control_after_generate` to all seed inputs (#69)
* Fix bug: deleting `Content-Type` when property does not exist (#73)
* Add preview to Save SVG node (#74)
* change default poll interval (#76), rework veo2
* Add Pixverse and updated Kling types (#75)
* Added Pixverse Image to VIdeo node (#77)
* Add Pixverse Transition Video node (#79)
* Proper ray-1-6 support as fix has been applied in backend (#80)
* Added Recraft Style - Infinite Style Library node (#82)
* add ideogram v3 (#83)
* [Kling] Split Camera Control config to its own node (#81)
* Add Pika i2v and t2v nodes (#52)
* Temporary Fix for Runway (#87)
* Added Stability Stable Image Ultra node (#86)
* Remove Runway nodes (#88)
* Fix: Prompt text can't be validated in Kling nodes when using primitive nodes (#90)
* Fix: typo in node name "Stabiliy" => "Stability" (#91)
* Add String (Multiline) node (#93)
* Update Pika Duration and Resolution options (#94)
* Change base branch to master. Not main. (#95)
* Fix UploadRequest file_name param (#98)
* Removed Infinite Style Library until later (#99)
* fix ideogram style types (#100)
* fix multi image return (#101)
* add metadata saving to SVG (#102)
* Bump templates version to include API node template workflows (#104)
* Fix: `download_url_to_video_output` return type (#103)
* fix 4o generation bug (#106)
* Serve SVG files directly (#107)
* Add a bunch of nodes, 3 ready to use, the rest waiting for endpoint support (#108)
* Revert "Serve SVG files directly" (#111)
* Expose 4 remaining Recraft nodes (#112)
* [Kling] Add `Duration` and `Video ID` outputs (#105)
* Fix: datamodel-codegen sets string#binary type to non-existent `bytes_aliased` variable (#114)
* Fix: Dall-e 2 not setting request content-type dynamically (#113)
* Default request timeout: one hour. (#116)
* Add Kling nodes: camera control, start-end frame, lip-sync, video extend (#115)
* Add 8 nodes - 4 BFL, 4 Stability (#117)
* Fix error for Recraft ImageToImage error for nonexistent random_seed param (#118)
* Add remaining Pika nodes (#119)
* Make controls input work for Recraft Image to Image node (#120)
* Use upstream PR: Support saving Comfy VIDEO type to buffer (#123)
* Use Upstream PR: "Fix: Error creating video when sliced audio tensor chunks are non-c-contiguous" (#127)
* Improve audio upload utils (#128)
* Fix: Nested `AnyUrl` in request model cannot be serialized (Kling, Runway) (#129)
* Show errors and API output URLs to the user (change log levels) (#131)
* Fix: Luma I2I fails when weight is <=0.01 (#132)
* Change category of `LumaConcepts` node from image to video (#133)
* Fix: `image.shape` accessed before `image` is null-checked (#134)
* Apply small fixes and most prompt validation (if needed to avoid API error) (#135)
* Node name/category modifications (#140)
* Add back Recraft Style - Infinite Style Library node (#141)
* Fixed Kling: Check attributes of pydantic types. (#144)
* Bump `comfyui-workflow-templates` version (#142)
* [Kling] Print response data when error validating response (#146)
* Fix: error validating Kling image response, trying to use `"key" in` on Pydantic class instance (#147)
* [Kling] Fix: Correct/verify supported subset of input combos in Kling nodes (#149)
* [Kling] Fix typo in node description (#150)
* [Kling] Fix: CFG min/max not being enforced (#151)
* Rebase launch-rebase (private) on prep-branch (public copy of master) (#153)
* Bump templates version (#154)
* Fix: Kling image gen nodes don't return entire batch when `n` > 1 (#152)
* Remove pixverse_template from PixVerse Transition Video node (#155)
* Invert image_weight value on Luma Image to Image node (#156)
* Invert and resize mask for Ideogram V3 node to match masking conventions (#158)
* [Kling] Fix: image generation nodes not returning Tuple (#159)
* [Bug] [Kling] Fix Kling camera control (#161)
* Kling Image Gen v2 + improve node descriptions for Flux/OpenAI (#160)
* [Kling] Don't return video_id from dual effect video (#162)
* Bump frontend to 1.18.8 (#163)
* Use 3.9 compat syntax (#164)
* Use Python 3.10
* add example env var
* Update templates to 0.1.11
* Bump frontend to 1.18.9
---------
Co-authored-by: Robin Huang <robin.j.huang@gmail.com>
Co-authored-by: Christian Byrne <cbyrne@comfy.org>
Co-authored-by: thot experiment <94414189+thot-experiment@users.noreply.github.com>
* Upload files for Chroma Implementation
* Remove trailing whitespace
* trim more trailing whitespace..oops
* remove unused imports
* Add supported_inference_dtypes
* Set min_length to 0 and remove attention_mask=True
* Set min_length to 1
* get_mdulations added from blepping and minor changes
* Add lora conversion if statement in lora.py
* Update supported_models.py
* update model_base.py
* add uptream commits
* set modelType.FLOW, will cause beta scheduler to work properly
* Adjust memory usage factor and remove unnecessary code
* fix mistake
* reduce code duplication
* remove unused imports
* refactor for upstream sync
* sync chroma-support with upstream via syncbranch patch
* Update sd.py
* Add Chroma as option for the OptimalStepsScheduler node
* Add basic support for videos as types
This PR adds support for VIDEO as first-class types. In order to avoid
unnecessary costs, VIDEO outputs must implement the `VideoInput` ABC,
but their implementation details can vary. Included are two
implementations of this type which can be returned by other nodes:
* `VideoFromFile` - Created with either a path on disk (as a string) or
a `io.BytesIO` containing the contents of a file in a supported format
(like .mp4). This implementation won't actually load the video unless
necessary. It will also avoid re-encoding when saving if possible.
* `VideoFromComponents` - Created from an image tensor and an optional
audio tensor.
Currently, only h264 encoded videos in .mp4 containers are supported for
saving, but the plan is to add additional encodings/containers in the
near future (particularly .webm).
* Add optimization to avoid parsing entire video
* Improve type declarations to reduce warnings
* Make sure bytesIO objects can be read many times
* Fix a potential issue when saving long videos
* Fix incorrect type annotation
* Add a `LoadVideo` node to make testing easier
* Refactor new types out of the base comfy folder
I've created a new `comfy_api` top-level module. The intention is that
anything within this folder would be covered by semver-style versioning
that would allow custom nodes to rely on them not introducing breaking
changes.
* Fix linting issue
This should speed up the lowvram mode a bit. It currently is only enabled when --async-offload is used but it will be enabled by default in the future if there are no problems.
* Add Ideogram generate node.
* Add staging api.
* COMFY_API_NODE_NAME node property
* switch to boolean flag and use original node name for id
* add optional to type
* Add API_NODE and common error for missing auth token (#5)
* Add Minimax Video Generation + Async Task queue polling example (#6)
* [Minimax] Show video preview and embed workflow in ouput (#7)
* [API Nodes] Send empty request body instead of empty dictionary. (#8)
* Fixed: removed function from rebase.
* Add pydantic.
* Remove uv.lock
* Remove polling operations.
* Update stubs workflow.
* Remove polling comments.
* Update stubs.
* Use pydantic v2.
* Use pydantic v2.
* Add basic OpenAITextToImage node
* Add.
* convert image to tensor.
* Improve types.
* Ruff.
* Push tests.
* Handle multi-form data.
- Don't set content-type for multi-part/form
- Use data field instead of JSON
* Change to api.comfy.org
* Handle error code 409.
* Remove nodes.
---------
Co-authored-by: bymyself <cbyrne@comfy.org>
Co-authored-by: Yoland Y <4950057+yoland68@users.noreply.github.com>
* add dependency aware cache that removed a cached node as soon as all of its decendents have executed. This allows users with lower RAM to run workflows they would otherwise not be able to run. The downside is that every workflow will fully run each time even if no nodes have changed.
* remove test code
* tidy code
* draft pass at a native comfy implementation of Lotus-D depth and normal est
* fix model_sampling kludges
* fix ruff
---------
Co-authored-by: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
