proxy interrupt request

- Fixed TypeError when accessing 'content' property of null/undefined array elements
- Removed empty options.push() that was adding undefined to the array
- Bump version to 2.3.3

.github/workflows/publish.yml

@@ -0,0 +1,25 @@
+name: Publish to Comfy registry
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+    paths:
+      - "pyproject.toml"
+
+permissions:
+  issues: write
+
+jobs:
+  publish-node:
+    name: Publish Custom Node to registry
+    runs-on: ubuntu-latest
+    if: ${{ github.repository_owner == 'BennyKok' }}
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v4
+      - name: Publish Custom Node
+        uses: Comfy-Org/publish-node-action@v1
+        with:
+          ## Add your own personal access token to your Github Repository secrets and reference it here.
+          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}

.gitignore

@@ -1,2 +1,3 @@
 __pycache__
-.DS_Store
+.DS_Store
+file-hash-cache.json

LICENSE

@@ -1,21 +1,208 @@
-MIT License
+GNU AFFERO GENERAL PUBLIC LICENSE
+Version 3, 19 November 2007
 
-Copyright (c) 2023 BennyKok
+Copyright © 2007 Free Software Foundation, Inc. <https://fsf.org/>
+Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed.
 
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
+Preamble
+The GNU Affero General Public License is a free, copyleft license for software and other kinds of works, specifically designed to ensure cooperation with the community in the case of network server software.
 
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
+The licenses for most software and other practical works are designed to take away your freedom to share and change the works. By contrast, our General Public Licenses are intended to guarantee your freedom to share and change all versions of a program--to make sure it remains free software for all its users.
 
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
+When we speak of free software, we are referring to freedom, not price. Our General Public Licenses are designed to make sure that you have the freedom to distribute copies of free software (and charge for them if you wish), that you receive source code or can get it if you want it, that you can change the software or use pieces of it in new free programs, and that you know you can do these things.
+
+Developers that use our General Public Licenses protect your rights with two steps: (1) assert copyright on the software, and (2) offer you this License which gives you legal permission to copy, distribute and/or modify the software.
+
+A secondary benefit of defending all users' freedom is that improvements made in alternate versions of the program, if they receive widespread use, become available for other developers to incorporate. Many developers of free software are heartened and encouraged by the resulting cooperation. However, in the case of software used on network servers, this result may fail to come about. The GNU General Public License permits making a modified version and letting the public access it on a server without ever releasing its source code to the public.
+
+The GNU Affero General Public License is designed specifically to ensure that, in such cases, the modified source code becomes available to the community. It requires the operator of a network server to provide the source code of the modified version running there to the users of that server. Therefore, public use of a modified version, on a publicly accessible server, gives the public access to the source code of the modified version.
+
+An older license, called the Affero General Public License and published by Affero, was designed to accomplish similar goals. This is a different license, not a version of the Affero GPL, but Affero has released a new version of the Affero GPL which permits relicensing under this license.
+
+The precise terms and conditions for copying, distribution and modification follow.
+
+TERMS AND CONDITIONS
+0. Definitions.
+"This License" refers to version 3 of the GNU Affero General Public License.
+
+"Copyright" also means copyright-like laws that apply to other kinds of works, such as semiconductor masks.
+
+"The Program" refers to any copyrightable work licensed under this License. Each licensee is addressed as "you". "Licensees" and "recipients" may be individuals or organizations.
+
+To "modify" a work means to copy from or adapt all or part of the work in a fashion requiring copyright permission, other than the making of an exact copy. The resulting work is called a "modified version" of the earlier work or a work "based on" the earlier work.
+
+A "covered work" means either the unmodified Program or a work based on the Program.
+
+To "propagate" a work means to do anything with it that, without permission, would make you directly or secondarily liable for infringement under applicable copyright law, except executing it on a computer or modifying a private copy. Propagation includes copying, distribution (with or without modification), making available to the public, and in some countries other activities as well.
+
+To "convey" a work means any kind of propagation that enables other parties to make or receive copies. Mere interaction with a user through a computer network, with no transfer of a copy, is not conveying.
+
+An interactive user interface displays "Appropriate Legal Notices" to the extent that it includes a convenient and prominently visible feature that (1) displays an appropriate copyright notice, and (2) tells the user that there is no warranty for the work (except to the extent that warranties are provided), that licensees may convey the work under this License, and how to view a copy of this License. If the interface presents a list of user commands or options, such as a menu, a prominent item in the list meets this criterion.
+
+1. Source Code.
+The "source code" for a work means the preferred form of the work for making modifications to it. "Object code" means any non-source form of a work.
+
+A "Standard Interface" means an interface that either is an official standard defined by a recognized standards body, or, in the case of interfaces specified for a particular programming language, one that is widely used among developers working in that language.
+
+The "System Libraries" of an executable work include anything, other than the work as a whole, that (a) is included in the normal form of packaging a Major Component, but which is not part of that Major Component, and (b) serves only to enable use of the work with that Major Component, or to implement a Standard Interface for which an implementation is available to the public in source code form. A "Major Component", in this context, means a major essential component (kernel, window system, and so on) of the specific operating system (if any) on which the executable work runs, or a compiler used to produce the work, or an object code interpreter used to run it.
+
+The "Corresponding Source" for a work in object code form means all the source code needed to generate, install, and (for an executable work) run the object code and to modify the work, including scripts to control those activities. However, it does not include the work's System Libraries, or general-purpose tools or generally available free programs which are used unmodified in performing those activities but which are not part of the work. For example, Corresponding Source includes interface definition files associated with source files for the work, and the source code for shared libraries and dynamically linked subprograms that the work is specifically designed to require, such as by intimate data communication or control flow between those subprograms and other parts of the work.
+
+The Corresponding Source need not include anything that users can regenerate automatically from other parts of the Corresponding Source.
+
+The Corresponding Source for a work in source code form is that same work.
+
+2. Basic Permissions.
+All rights granted under this License are granted for the term of copyright on the Program, and are irrevocable provided the stated conditions are met. This License explicitly affirms your unlimited permission to run the unmodified Program. The output from running a covered work is covered by this License only if the output, given its content, constitutes a covered work. This License acknowledges your rights of fair use or other equivalent, as provided by copyright law.
+
+You may make, run and propagate covered works that you do not convey, without conditions so long as your license otherwise remains in force. You may convey covered works to others for the sole purpose of having them make modifications exclusively for you, or provide you with facilities for running those works, provided that you comply with the terms of this License in conveying all material for which you do not control copyright. Those thus making or running the covered works for you must do so exclusively on your behalf, under your direction and control, on terms that prohibit them from making any copies of your copyrighted material outside their relationship with you.
+
+Conveying under any other circumstances is permitted solely under the conditions stated below. Sublicensing is not allowed; section 10 makes it unnecessary.
+
+3. Protecting Users' Legal Rights From Anti-Circumvention Law.
+No covered work shall be deemed part of an effective technological measure under any applicable law fulfilling obligations under article 11 of the WIPO copyright treaty adopted on 20 December 1996, or similar laws prohibiting or restricting circumvention of such measures.
+
+When you convey a covered work, you waive any legal power to forbid circumvention of technological measures to the extent such circumvention is effected by exercising rights under this License with respect to the covered work, and you disclaim any intention to limit operation or modification of the work as a means of enforcing, against the work's users, your or third parties' legal rights to forbid circumvention of technological measures.
+
+4. Conveying Verbatim Copies.
+You may convey verbatim copies of the Program's source code as you receive it, in any medium, provided that you conspicuously and appropriately publish on each copy an appropriate copyright notice; keep intact all notices stating that this License and any non-permissive terms added in accord with section 7 apply to the code; keep intact all notices of the absence of any warranty; and give all recipients a copy of this License along with the Program.
+
+You may charge any price or no price for each copy that you convey, and you may offer support or warranty protection for a fee.
+
+5. Conveying Modified Source Versions.
+You may convey a work based on the Program, or the modifications to produce it from the Program, in the form of source code under the terms of section 4, provided that you also meet all of these conditions:
+
+a) The work must carry prominent notices stating that you modified it, and giving a relevant date.
+b) The work must carry prominent notices stating that it is released under this License and any conditions added under section 7. This requirement modifies the requirement in section 4 to "keep intact all notices".
+c) You must license the entire work, as a whole, under this License to anyone who comes into possession of a copy. This License will therefore apply, along with any applicable section 7 additional terms, to the whole of the work, and all its parts, regardless of how they are packaged. This License gives no permission to license the work in any other way, but it does not invalidate such permission if you have separately received it.
+d) If the work has interactive user interfaces, each must display Appropriate Legal Notices; however, if the Program has interactive interfaces that do not display Appropriate Legal Notices, your work need not make them do so.
+A compilation of a covered work with other separate and independent works, which are not by their nature extensions of the covered work, and which are not combined with it such as to form a larger program, in or on a volume of a storage or distribution medium, is called an "aggregate" if the compilation and its resulting copyright are not used to limit the access or legal rights of the compilation's users beyond what the individual works permit. Inclusion of a covered work in an aggregate does not cause this License to apply to the other parts of the aggregate.
+
+6. Conveying Non-Source Forms.
+You may convey a covered work in object code form under the terms of sections 4 and 5, provided that you also convey the machine-readable Corresponding Source under the terms of this License, in one of these ways:
+
+a) Convey the object code in, or embodied in, a physical product (including a physical distribution medium), accompanied by the Corresponding Source fixed on a durable physical medium customarily used for software interchange.
+b) Convey the object code in, or embodied in, a physical product (including a physical distribution medium), accompanied by a written offer, valid for at least three years and valid for as long as you offer spare parts or customer support for that product model, to give anyone who possesses the object code either (1) a copy of the Corresponding Source for all the software in the product that is covered by this License, on a durable physical medium customarily used for software interchange, for a price no more than your reasonable cost of physically performing this conveying of source, or (2) access to copy the Corresponding Source from a network server at no charge.
+c) Convey individual copies of the object code with a copy of the written offer to provide the Corresponding Source. This alternative is allowed only occasionally and noncommercially, and only if you received the object code with such an offer, in accord with subsection 6b.
+d) Convey the object code by offering access from a designated place (gratis or for a charge), and offer equivalent access to the Corresponding Source in the same way through the same place at no further charge. You need not require recipients to copy the Corresponding Source along with the object code. If the place to copy the object code is a network server, the Corresponding Source may be on a different server (operated by you or a third party) that supports equivalent copying facilities, provided you maintain clear directions next to the object code saying where to find the Corresponding Source. Regardless of what server hosts the Corresponding Source, you remain obligated to ensure that it is available for as long as needed to satisfy these requirements.
+e) Convey the object code using peer-to-peer transmission, provided you inform other peers where the object code and Corresponding Source of the work are being offered to the general public at no charge under subsection 6d.
+A separable portion of the object code, whose source code is excluded from the Corresponding Source as a System Library, need not be included in conveying the object code work.
+
+A "User Product" is either (1) a "consumer product", which means any tangible personal property which is normally used for personal, family, or household purposes, or (2) anything designed or sold for incorporation into a dwelling. In determining whether a product is a consumer product, doubtful cases shall be resolved in favor of coverage. For a particular product received by a particular user, "normally used" refers to a typical or common use of that class of product, regardless of the status of the particular user or of the way in which the particular user actually uses, or expects or is expected to use, the product. A product is a consumer product regardless of whether the product has substantial commercial, industrial or non-consumer uses, unless such uses represent the only significant mode of use of the product.
+
+"Installation Information" for a User Product means any methods, procedures, authorization keys, or other information required to install and execute modified versions of a covered work in that User Product from a modified version of its Corresponding Source. The information must suffice to ensure that the continued functioning of the modified object code is in no case prevented or interfered with solely because modification has been made.
+
+If you convey an object code work under this section in, or with, or specifically for use in, a User Product, and the conveying occurs as part of a transaction in which the right of possession and use of the User Product is transferred to the recipient in perpetuity or for a fixed term (regardless of how the transaction is characterized), the Corresponding Source conveyed under this section must be accompanied by the Installation Information. But this requirement does not apply if neither you nor any third party retains the ability to install modified object code on the User Product (for example, the work has been installed in ROM).
+
+The requirement to provide Installation Information does not include a requirement to continue to provide support service, warranty, or updates for a work that has been modified or installed by the recipient, or for the User Product in which it has been modified or installed. Access to a network may be denied when the modification itself materially and adversely affects the operation of the network or violates the rules and protocols for communication across the network.
+
+Corresponding Source conveyed, and Installation Information provided, in accord with this section must be in a format that is publicly documented (and with an implementation available to the public in source code form), and must require no special password or key for unpacking, reading or copying.
+
+7. Additional Terms.
+"Additional permissions" are terms that supplement the terms of this License by making exceptions from one or more of its conditions. Additional permissions that are applicable to the entire Program shall be treated as though they were included in this License, to the extent that they are valid under applicable law. If additional permissions apply only to part of the Program, that part may be used separately under those permissions, but the entire Program remains governed by this License without regard to the additional permissions.
+
+When you convey a copy of a covered work, you may at your option remove any additional permissions from that copy, or from any part of it. (Additional permissions may be written to require their own removal in certain cases when you modify the work.) You may place additional permissions on material, added by you to a covered work, for which you have or can give appropriate copyright permission.
+
+Notwithstanding any other provision of this License, for material you add to a covered work, you may (if authorized by the copyright holders of that material) supplement the terms of this License with terms:
+
+a) Disclaiming warranty or limiting liability differently from the terms of sections 15 and 16 of this License; or
+b) Requiring preservation of specified reasonable legal notices or author attributions in that material or in the Appropriate Legal Notices displayed by works containing it; or
+c) Prohibiting misrepresentation of the origin of that material, or requiring that modified versions of such material be marked in reasonable ways as different from the original version; or
+d) Limiting the use for publicity purposes of names of licensors or authors of the material; or
+e) Declining to grant rights under trademark law for use of some trade names, trademarks, or service marks; or
+f) Requiring indemnification of licensors and authors of that material by anyone who conveys the material (or modified versions of it) with contractual assumptions of liability to the recipient, for any liability that these contractual assumptions directly impose on those licensors and authors.
+All other non-permissive additional terms are considered "further restrictions" within the meaning of section 10. If the Program as you received it, or any part of it, contains a notice stating that it is governed by this License along with a term that is a further restriction, you may remove that term. If a license document contains a further restriction but permits relicensing or conveying under this License, you may add to a covered work material governed by the terms of that license document, provided that the further restriction does not survive such relicensing or conveying.
+
+If you add terms to a covered work in accord with this section, you must place, in the relevant source files, a statement of the additional terms that apply to those files, or a notice indicating where to find the applicable terms.
+
+Additional terms, permissive or non-permissive, may be stated in the form of a separately written license, or stated as exceptions; the above requirements apply either way.
+
+8. Termination.
+You may not propagate or modify a covered work except as expressly provided under this License. Any attempt otherwise to propagate or modify it is void, and will automatically terminate your rights under this License (including any patent licenses granted under the third paragraph of section 11).
+
+However, if you cease all violation of this License, then your license from a particular copyright holder is reinstated (a) provisionally, unless and until the copyright holder explicitly and finally terminates your license, and (b) permanently, if the copyright holder fails to notify you of the violation by some reasonable means prior to 60 days after the cessation.
+
+Moreover, your license from a particular copyright holder is reinstated permanently if the copyright holder notifies you of the violation by some reasonable means, this is the first time you have received notice of violation of this License (for any work) from that copyright holder, and you cure the violation prior to 30 days after your receipt of the notice.
+
+Termination of your rights under this section does not terminate the licenses of parties who have received copies or rights from you under this License. If your rights have been terminated and not permanently reinstated, you do not qualify to receive new licenses for the same material under section 10.
+
+9. Acceptance Not Required for Having Copies.
+You are not required to accept this License in order to receive or run a copy of the Program. Ancillary propagation of a covered work occurring solely as a consequence of using peer-to-peer transmission to receive a copy likewise does not require acceptance. However, nothing other than this License grants you permission to propagate or modify any covered work. These actions infringe copyright if you do not accept this License. Therefore, by modifying or propagating a covered work, you indicate your acceptance of this License to do so.
+
+10. Automatic Licensing of Downstream Recipients.
+Each time you convey a covered work, the recipient automatically receives a license from the original licensors, to run, modify and propagate that work, subject to this License. You are not responsible for enforcing compliance by third parties with this License.
+
+An "entity transaction" is a transaction transferring control of an organization, or substantially all assets of one, or subdividing an organization, or merging organizations. If propagation of a covered work results from an entity transaction, each party to that transaction who receives a copy of the work also receives whatever licenses to the work the party's predecessor in interest had or could give under the previous paragraph, plus a right to possession of the Corresponding Source of the work from the predecessor in interest, if the predecessor has it or can get it with reasonable efforts.
+
+You may not impose any further restrictions on the exercise of the rights granted or affirmed under this License. For example, you may not impose a license fee, royalty, or other charge for exercise of rights granted under this License, and you may not initiate litigation (including a cross-claim or counterclaim in a lawsuit) alleging that any patent claim is infringed by making, using, selling, offering for sale, or importing the Program or any portion of it.
+
+11. Patents.
+A "contributor" is a copyright holder who authorizes use under this License of the Program or a work on which the Program is based. The work thus licensed is called the contributor's "contributor version".
+
+A contributor's "essential patent claims" are all patent claims owned or controlled by the contributor, whether already acquired or hereafter acquired, that would be infringed by some manner, permitted by this License, of making, using, or selling its contributor version, but do not include claims that would be infringed only as a consequence of further modification of the contributor version. For purposes of this definition, "control" includes the right to grant patent sublicenses in a manner consistent with the requirements of this License.
+
+Each contributor grants you a non-exclusive, worldwide, royalty-free patent license under the contributor's essential patent claims, to make, use, sell, offer for sale, import and otherwise run, modify and propagate the contents of its contributor version.
+
+In the following three paragraphs, a "patent license" is any express agreement or commitment, however denominated, not to enforce a patent (such as an express permission to practice a patent or covenant not to sue for patent infringement). To "grant" such a patent license to a party means to make such an agreement or commitment not to enforce a patent against the party.
+
+If you convey a covered work, knowingly relying on a patent license, and the Corresponding Source of the work is not available for anyone to copy, free of charge and under the terms of this License, through a publicly available network server or other readily accessible means, then you must either (1) cause the Corresponding Source to be so available, or (2) arrange to deprive yourself of the benefit of the patent license for this particular work, or (3) arrange, in a manner consistent with the requirements of this License, to extend the patent license to downstream recipients. "Knowingly relying" means you have actual knowledge that, but for the patent license, your conveying the covered work in a country, or your recipient's use of the covered work in a country, would infringe one or more identifiable patents in that country that you have reason to believe are valid.
+
+If, pursuant to or in connection with a single transaction or arrangement, you convey, or propagate by procuring conveyance of, a covered work, and grant a patent license to some of the parties receiving the covered work authorizing them to use, propagate, modify or convey a specific copy of the covered work, then the patent license you grant is automatically extended to all recipients of the covered work and works based on it.
+
+A patent license is "discriminatory" if it does not include within the scope of its coverage, prohibits the exercise of, or is conditioned on the non-exercise of one or more of the rights that are specifically granted under this License. You may not convey a covered work if you are a party to an arrangement with a third party that is in the business of distributing software, under which you make payment to the third party based on the extent of your activity of conveying the work, and under which the third party grants, to any of the parties who would receive the covered work from you, a discriminatory patent license (a) in connection with copies of the covered work conveyed by you (or copies made from those copies), or (b) primarily for and in connection with specific products or compilations that contain the covered work, unless you entered into that arrangement, or that patent license was granted, prior to 28 March 2007.
+
+Nothing in this License shall be construed as excluding or limiting any implied license or other defenses to infringement that may otherwise be available to you under applicable patent law.
+
+12. No Surrender of Others' Freedom.
+If conditions are imposed on you (whether by court order, agreement or otherwise) that contradict the conditions of this License, they do not excuse you from the conditions of this License. If you cannot convey a covered work so as to satisfy simultaneously your obligations under this License and any other pertinent obligations, then as a consequence you may not convey it at all. For example, if you agree to terms that obligate you to collect a royalty for further conveying from those to whom you convey the Program, the only way you could satisfy both those terms and this License would be to refrain entirely from conveying the Program.
+
+13. Remote Network Interaction; Use with the GNU General Public License.
+Notwithstanding any other provision of this License, if you modify the Program, your modified version must prominently offer all users interacting with it remotely through a computer network (if your version supports such interaction) an opportunity to receive the Corresponding Source of your version by providing access to the Corresponding Source from a network server at no charge, through some standard or customary means of facilitating copying of software. This Corresponding Source shall include the Corresponding Source for any work covered by version 3 of the GNU General Public License that is incorporated pursuant to the following paragraph.
+
+Notwithstanding any other provision of this License, you have permission to link or combine any covered work with a work licensed under version 3 of the GNU General Public License into a single combined work, and to convey the resulting work. The terms of this License will continue to apply to the part which is the covered work, but the work with which it is combined will remain governed by version 3 of the GNU General Public License.
+
+14. Revised Versions of this License.
+The Free Software Foundation may publish revised and/or new versions of the GNU Affero General Public License from time to time. Such new versions will be similar in spirit to the present version, but may differ in detail to address new problems or concerns.
+
+Each version is given a distinguishing version number. If the Program specifies that a certain numbered version of the GNU Affero General Public License "or any later version" applies to it, you have the option of following the terms and conditions either of that numbered version or of any later version published by the Free Software Foundation. If the Program does not specify a version number of the GNU Affero General Public License, you may choose any version ever published by the Free Software Foundation.
+
+If the Program specifies that a proxy can decide which future versions of the GNU Affero General Public License can be used, that proxy's public statement of acceptance of a version permanently authorizes you to choose that version for the Program.
+
+Later license versions may give you additional or different permissions. However, no additional obligations are imposed on any author or copyright holder as a result of your choosing to follow a later version.
+
+15. Disclaimer of Warranty.
+THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+16. Limitation of Liability.
+IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
+
+17. Interpretation of Sections 15 and 16.
+If the disclaimer of warranty and limitation of liability provided above cannot be given local legal effect according to their terms, reviewing courts shall apply local law that most closely approximates an absolute waiver of all civil liability in connection with the Program, unless a warranty or assumption of liability accompanies a copy of the Program in return for a fee.
+
+END OF TERMS AND CONDITIONS
+
+How to Apply These Terms to Your New Programs
+If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve this is to make it free software which everyone can redistribute and change under these terms.
+
+To do so, attach the following notices to the program. It is safest to attach them to the start of each source file to most effectively state the exclusion of warranty; and each file should have at least the "copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the program's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU Affero General Public License as
+    published by the Free Software Foundation, either version 3 of the
+    License, or (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU Affero General Public License for more details.
+
+    You should have received a copy of the GNU Affero General Public License
+    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+Also add information on how to contact you by electronic and paper mail.
+
+If your software can interact with users remotely through a computer network, you should also make sure that it provides a way for users to get its source. For example, if your program is a web application, its interface could display a "Source" link that leads users to an archive of the code. There are many ways you could offer source, and different solutions will be better for different programs; see section 13 for the specific requirements.
+
+You should also get your employer (if you work as a programmer) or school, if any, to sign a "copyright disclaimer" for the program, if necessary. For more information on this, and how to apply and follow the GNU AGPL, see <https://www.gnu.org/licenses/>.

README.md

@@ -2,6 +2,9 @@
 
 Open source comfyui deployment platform, a `vercel` for generative workflow infra. (serverless hosted gpu with vertical intergation with comfyui)
 
+> [!NOTE]  
+> Im looking for creative hacker to join ComfyDeploy's core team! DM me on [twitter](https://x.com/BennyKokMusic)
+
 Join [Discord](https://discord.gg/EEYcQmdYZw) to chat more or visit [Comfy Deploy](https://comfydeploy.com/) to get started!
 
 Check out our latest [nextjs starter kit](https://github.com/BennyKok/comfyui-deploy-next-example) with Comfy Deploy

__init__.py

@@ -2,8 +2,9 @@
 @author: BennyKok
 @title: comfyui-deploy
 @nickname: Comfy Deploy
-@description: 
+@description:
 """
+
 import os
 import sys
 
@@ -17,19 +18,23 @@ import requests
 import folder_paths
 from folder_paths import add_model_folder_path, get_filename_list, get_folder_paths
 from tqdm import tqdm
+import re
 
 from . import custom_routes
 # import routes
 
 ag_path = os.path.join(os.path.dirname(__file__))
 
+
 def get_python_files(path):
     return [f[:-3] for f in os.listdir(path) if f.endswith(".py")]
 
+
 def append_to_sys_path(path):
     if path not in sys.path:
         sys.path.append(path)
 
+
 paths = ["comfy-nodes"]
 files = []
 
@@ -41,14 +46,45 @@ for path in paths:
 NODE_CLASS_MAPPINGS = {}
 NODE_DISPLAY_NAME_MAPPINGS = {}
 
+
+def split_camel_case(name):
+    # Split on underscores first, then split each part on camelCase
+    parts = []
+    for part in name.split("_"):
+        # Find all camelCase boundaries
+        words = re.findall("[A-Z][^A-Z]*", part)
+        if not words:  # If no camelCase found, use the whole part
+            words = [part]
+        parts.extend(words)
+    return parts
+
+
 # Import all the modules and append their mappings
 for file in files:
     module = importlib.import_module(file)
 
+    # Check if the module has explicit mappings
     if hasattr(module, "NODE_CLASS_MAPPINGS"):
         NODE_CLASS_MAPPINGS.update(module.NODE_CLASS_MAPPINGS)
     if hasattr(module, "NODE_DISPLAY_NAME_MAPPINGS"):
         NODE_DISPLAY_NAME_MAPPINGS.update(module.NODE_DISPLAY_NAME_MAPPINGS)
 
+    # Auto-discover classes with ComfyUI node attributes
+    for name, obj in inspect.getmembers(module):
+        # Check if it's a class and has the required ComfyUI node attributes
+        if (
+            inspect.isclass(obj)
+            and hasattr(obj, "INPUT_TYPES")
+            and hasattr(obj, "RETURN_TYPES")
+        ):
+            # Use the class name as the key if not already in mappings
+            if name not in NODE_CLASS_MAPPINGS:
+                NODE_CLASS_MAPPINGS[name] = obj
+                # Create a display name by converting camelCase to Title Case with spaces
+                words = split_camel_case(name.replace("ComfyUIDeploy", ""))
+                display_name = " ".join(word.capitalize() for word in words)
+                # print(display_name, name)
+                NODE_DISPLAY_NAME_MAPPINGS[name] = display_name
+
 WEB_DIRECTORY = "web-plugin"
 __all__ = ["NODE_CLASS_MAPPINGS", "NODE_DISPLAY_NAME_MAPPINGS"]

comfy-nodes/external_audio.py

@@ -0,0 +1,82 @@
+import io
+from folder_paths import get_annotated_filepath
+
+
+class ComfyUIDeployExternalAudio:
+    RETURN_TYPES = ("AUDIO",)
+    RETURN_NAMES = ("audio",)
+    FUNCTION = "load_audio"
+    CATEGORY = "🔗ComfyDeploy"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_audio"},
+                ),
+                "audio_file": ("STRING", {"default": ""}),
+            },
+            "optional": {
+                "default_value": ("AUDIO",),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+            },
+        }
+
+    @classmethod
+    def VALIDATE_INPUTS(s, audio_file, **kwargs):
+        return True
+
+    def load_audio(
+        self,
+        input_id,
+        audio_file,
+        default_value=None,
+        display_name=None,
+        description=None,
+    ):
+        try:
+            import torchaudio
+
+            if audio_file and audio_file != "":
+                if audio_file.startswith(("http://", "https://")):
+                    # Handle URL input
+                    try:
+                        import requests
+
+                        response = requests.get(audio_file)
+                        audio_data = io.BytesIO(response.content)
+                        waveform, sample_rate = torchaudio.load(audio_data)
+                    except Exception as e:
+                        print(f"Error loading audio from URL: {e}")
+                        return (default_value,)
+                else:
+                    # Handle local file
+                    try:
+                        audio_path = get_annotated_filepath(audio_file)
+                        waveform, sample_rate = torchaudio.load(audio_path)
+                    except Exception as e:
+                        print(f"Error loading local audio file: {e}")
+                        return (default_value,)
+
+                audio = {"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate}
+                return (audio,)
+            else:
+                return (default_value,)
+        except ImportError as e:
+            print(f"Error: torchaudio not installed or cannot be imported: {e}")
+            return (default_value,)
+
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalAudio": ComfyUIDeployExternalAudio}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployExternalAudio": "External Audio (ComfyUI Deploy)"
+}

comfy-nodes/external_boolean.py

@@ -0,0 +1,36 @@
+class ComfyUIDeployExternalBoolean:
+    @classmethod    
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_bool"},
+                ),
+                "default_value": ("BOOLEAN", {"default": False})
+            },
+            "optional": {
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("BOOLEAN",)
+    RETURN_NAMES = ("bool_value",)
+        
+    FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
+    
+    def run(self, input_id, default_value=None, display_name=None, description=None):
+        print(f"Node '{input_id}' processing with switch set to {default_value}")
+        return [default_value]
+    
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalBoolean": ComfyUIDeployExternalBoolean}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalBoolean": "External Boolean (ComfyUI Deploy)"}

comfy-nodes/external_checkpoints.py

@@ -5,6 +5,12 @@ import torch
 import folder_paths
 from tqdm import tqdm
 
+class AnyType(str):
+    def __ne__(self, __value: object) -> bool:
+        return False
+        
+WILDCARD = AnyType("*")
+
 class ComfyUIDeployExternalCheckpoint:
     @classmethod
     def INPUT_TYPES(s):
@@ -16,23 +22,32 @@ class ComfyUIDeployExternalCheckpoint:
                 ),
             },
             "optional": {
-                "default_checkpoint_name": (folder_paths.get_filename_list("checkpoints"), ),
+                "default_value": (folder_paths.get_filename_list("checkpoints"), ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
             }
         }
 
-    RETURN_TYPES = (folder_paths.get_filename_list("checkpoints"),)
+    RETURN_TYPES = (WILDCARD,)
     RETURN_NAMES = ("path",)
+    
 
     FUNCTION = "run"
 
-    CATEGORY = "deploy"
+    CATEGORY = "🔗ComfyDeploy"
 
-    def run(self, input_id, default_checkpoint_name=None):
+    def run(self, input_id, default_value=None, display_name=None, description=None):
         import requests
         import os
         import uuid
 
-        if input_id and input_id.startswith('http'):
+        if default_value.startswith('http'):
             unique_filename = str(uuid.uuid4()) + ".safetensors"
             print(unique_filename)
             print(folder_paths.folder_names_and_paths["checkpoints"][0][0])
@@ -59,7 +74,7 @@ class ComfyUIDeployExternalCheckpoint:
                     out_file.write(chunk)
             return (unique_filename,)
         else:
-            return (default_checkpoints_name,)
+            return (default_value,)
 
 
 NODE_CLASS_MAPPINGS = {

comfy-nodes/external_enum.py

@@ -0,0 +1,46 @@
+class AnyType(str):
+    def __ne__(self, __value: object) -> bool:
+        return False
+
+
+WILDCARD = AnyType("*")
+
+class ComfyUIDeployExternalEnum:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_enum"},
+                ),
+            },
+            "optional": {
+                "default_value": (
+                    "STRING",
+                    {"multiline": False, "default": "", "dynamic_enum": True},
+                ),
+                "options": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+            }
+        }
+
+    RETURN_TYPES = (WILDCARD,)
+    RETURN_NAMES = ("text",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "🔗ComfyDeploy"
+
+    def run(self, input_id, options=None, default_value=None, display_name=None, description=None):
+        return [default_value]

comfy-nodes/external_exr.py

@@ -0,0 +1,110 @@
+import os
+import io
+import cv2 as cv
+import numpy as np
+import torch
+import requests
+from folder_paths import get_annotated_filepath
+
+class ComfyUIDeployExternalEXR:
+    RETURN_TYPES = ("IMAGE", "MASK")
+    RETURN_NAMES = ("image", "mask") 
+    FUNCTION = "load_exr"
+    CATEGORY = "🔗ComfyDeploy"
+    
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_exr"},
+                ),
+                "exr_file": ("STRING", {"default": ""}),
+                "tonemap": (["linear", "sRGB", "Reinhard"], {"default": "sRGB"}),
+            },
+            "optional": {
+                "default_image": ("IMAGE",),
+                "default_mask": ("MASK",),
+                "display_name": (
+                    "STRING", 
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+            }
+        }
+
+    @classmethod
+    def VALIDATE_INPUTS(s, exr_file, **kwargs):
+        return True
+
+    def sRGBtoLinear(self, npArray):
+        less = npArray <= 0.0404482362771082
+        npArray[less] = npArray[less] / 12.92
+        npArray[~less] = np.power((npArray[~less] + 0.055) / 1.055, 2.4)
+
+    def linearToSRGB(self, npArray):
+        less = npArray <= 0.0031308
+        npArray[less] = npArray[less] * 12.92
+        npArray[~less] = np.power(npArray[~less], 1/2.4) * 1.055 - 0.055
+
+    def load_exr(self, input_id, exr_file, tonemap="sRGB", 
+                 default_image=None, default_mask=None,
+                 display_name=None, description=None):
+        try:
+            if exr_file and exr_file != "":
+                if exr_file.startswith(('http://', 'https://')):
+                    # Handle URL input
+                    response = requests.get(exr_file)
+                    # Write to temp buffer
+                    buffer = io.BytesIO(response.content)
+                    nparr = np.frombuffer(buffer.getvalue(), np.uint8)
+                    image = cv.imdecode(nparr, cv.IMREAD_UNCHANGED).astype(np.float32)
+                else:
+                    # Handle local file
+                    exr_path = get_annotated_filepath(exr_file)
+                    image = cv.imread(exr_path, cv.IMREAD_UNCHANGED).astype(np.float32)
+
+                if len(image.shape) == 2:
+                    image = np.repeat(image[..., np.newaxis], 3, axis=2)
+                
+                # Extract RGB and flip channels
+                rgb = np.flip(image[:,:,:3], 2).copy()
+                
+                # Apply tonemapping
+                if tonemap == "sRGB":
+                    self.linearToSRGB(rgb)
+                    rgb = np.clip(rgb, 0, 1)
+                elif tonemap == "Reinhard":
+                    rgb = np.clip(rgb, 0, None)
+                    rgb = rgb / (rgb + 1)
+                    self.linearToSRGB(rgb)
+                    rgb = np.clip(rgb, 0, 1)
+                
+                rgb = torch.unsqueeze(torch.from_numpy(rgb), 0)
+                
+                # Handle alpha/mask
+                mask = torch.zeros((1, image.shape[0], image.shape[1]), dtype=torch.float32)
+                if image.shape[2] > 3:
+                    mask[0] = torch.from_numpy(np.clip(image[:,:,3], 0, 1))
+
+                return (rgb, mask)
+            else:
+                # Return defaults if no file provided
+                return (default_image, default_mask)
+
+        except Exception as e:
+            print(f"Error loading EXR: {str(e)}")
+            # Return defaults on error
+            return (default_image, default_mask)
+
+NODE_CLASS_MAPPINGS = {
+    "ComfyUIDeployExternalEXR": ComfyUIDeployExternalEXR
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployExternalEXR": "External EXR (ComfyUI Deploy)"
+}

comfy-nodes/external_face_model.py

@@ -0,0 +1,106 @@
+from PIL import Image, ImageOps
+import numpy as np
+import torch
+import folder_paths
+
+
+class AnyType(str):
+    def __ne__(self, __value: object) -> bool:
+        return False
+
+
+WILDCARD = AnyType("*")
+
+
+class ComfyUIDeployExternalFaceModel:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_reactor_face_model"},
+                ),
+            },
+            "optional": {
+                "default_face_model_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "face_model_save_name": (  # if `default_face_model_name` is a link to download a file, we will attempt to save it with this name
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+                "face_model_url": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+            },
+        }
+
+    RETURN_TYPES = (WILDCARD,)
+    RETURN_NAMES = ("path",)
+    FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
+
+    def run(
+        self,
+        input_id,
+        default_face_model_name=None,
+        face_model_save_name=None,
+        display_name=None,
+        description=None,
+        face_model_url=None,
+    ):
+        import requests
+        import os
+        import uuid
+
+        if face_model_url and face_model_url.startswith("http"):
+            if face_model_save_name:
+                existing_face_models = folder_paths.get_filename_list("reactor/faces")
+                # Check if face_model_save_name exists in the list
+                if face_model_save_name in existing_face_models:
+                    print(f"using face model: {face_model_save_name}")
+                    return (face_model_save_name,)
+            else:
+                face_model_save_name = str(uuid.uuid4()) + ".safetensors"
+            print(face_model_save_name)
+            print(folder_paths.folder_names_and_paths["reactor/faces"][0][0])
+            destination_path = os.path.join(
+                folder_paths.folder_names_and_paths["reactor/faces"][0][0],
+                face_model_save_name,
+            )
+
+            print(destination_path)
+            print(
+                "Downloading external face model - "
+                + face_model_url
+                + " to "
+                + destination_path
+            )
+            response = requests.get(
+                face_model_url,
+                headers={"User-Agent": "Mozilla/5.0"},
+                allow_redirects=True,
+            )
+            with open(destination_path, "wb") as out_file:
+                out_file.write(response.content)
+            return (face_model_save_name,)
+        else:
+            print(f"using face model: {default_face_model_name}")
+            return (default_face_model_name,)
+
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalFaceModel": ComfyUIDeployExternalFaceModel}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployExternalFaceModel": "External Face Model (ComfyUI Deploy)"
+}

comfy-nodes/external_image.py

@@ -15,42 +15,61 @@ class ComfyUIDeployExternalImage:
             },
             "optional": {
                 "default_value": ("IMAGE",),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "default_value_url": ("STRING", {"image_preview": True, "default": ""}),
             }
         }
 
     RETURN_TYPES = ("IMAGE",)
     RETURN_NAMES = ("image",)
-
     FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
 
-    CATEGORY = "image"
-
-    def run(self, input_id, default_value=None):
+    def run(self, input_id, default_value=None, display_name=None, description=None, default_value_url=None):
         image = default_value
-        try:
-            if input_id.startswith('http'):
-                import requests
-                from io import BytesIO
-                print("Fetching image from url: ", input_id)
-                response = requests.get(input_id)
-                image = Image.open(BytesIO(response.content))
-            elif input_id.startswith('data:image/png;base64,') or input_id.startswith('data:image/jpeg;base64,') or input_id.startswith('data:image/jpg;base64,'):
-                import base64
-                from io import BytesIO
-                print("Decoding base64 image")
-                base64_image = input_id[input_id.find(",")+1:]
-                decoded_image = base64.b64decode(base64_image)
-                image = Image.open(BytesIO(decoded_image))
-            else:
-                raise ValueError("Invalid image url provided.")
-
-            image = ImageOps.exif_transpose(image)
-            image = image.convert("RGB")
-            image = np.array(image).astype(np.float32) / 255.0
-            image = torch.from_numpy(image)[None,]
-            return [image]
-        except:
-            return [image]
+        
+        # Try both input_id and default_value_url
+        urls_to_try = [url for url in [input_id, default_value_url] if url]
+        
+        print(default_value_url)
+        
+        for url in urls_to_try:
+            try:
+                if url.startswith('http'):
+                    import requests
+                    from io import BytesIO
+                    print(f"Fetching image from url: {url}")
+                    response = requests.get(url)
+                    image = Image.open(BytesIO(response.content))
+                    break
+                elif url.startswith(('data:image/png;base64,', 'data:image/jpeg;base64,', 'data:image/jpg;base64,')):
+                    import base64
+                    from io import BytesIO
+                    print("Decoding base64 image")
+                    base64_image = url[url.find(",")+1:]
+                    decoded_image = base64.b64decode(base64_image)
+                    image = Image.open(BytesIO(decoded_image))
+                    break
+            except:
+                continue
+        
+        if image is not None:
+            try:
+                image = ImageOps.exif_transpose(image)
+                image = image.convert("RGB")
+                image = np.array(image).astype(np.float32) / 255.0
+                image = torch.from_numpy(image)[None,]
+            except:
+                pass
+                
+        return [image]
 
 
 NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalImage": ComfyUIDeployExternalImage}

comfy-nodes/external_image_alpha.py

@@ -15,17 +15,23 @@ class ComfyUIDeployExternalImageAlpha:
             },
             "optional": {
                 "default_value": ("IMAGE",),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
             }
         }
 
     RETURN_TYPES = ("IMAGE",)
     RETURN_NAMES = ("image",)
-
     FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
 
-    CATEGORY = "image"
-
-    def run(self, input_id, default_value=None):
+    def run(self, input_id, default_value=None, display_name=None, description=None):
         image = default_value
         try:
             if input_id.startswith('http'):

comfy-nodes/external_image_batch.py

@@ -0,0 +1,111 @@
+import folder_paths
+from PIL import Image, ImageOps
+import numpy as np
+import torch
+import json
+import comfy
+
+class ComfyUIDeployExternalImageBatch:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_images"},
+                ),
+                "images": (
+                    "STRING",
+                    {"multiline": False, "default": "[]"},
+                ),
+            },
+            "optional": {
+                "default_value": ("IMAGE",),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    RETURN_NAMES = ("image",)
+    FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
+    
+    def process_image(self, image):
+        image = ImageOps.exif_transpose(image)
+        image = image.convert("RGB")
+        image = np.array(image).astype(np.float32) / 255.0
+        image_tensor = torch.from_numpy(image)[None,]
+        return image_tensor
+    
+    def run(self, input_id, images=None, default_value=None, display_name=None, description=None):
+        import requests
+        import zipfile
+        import io
+        
+        processed_images = []
+        try:
+            images_list = json.loads(images)  # Assuming images is a JSON array string
+            print(images_list)
+            for img_input in images_list:
+                if img_input.startswith('http') and img_input.endswith('.zip'):
+                    print("Fetching zip file from url: ", img_input)
+                    response = requests.get(img_input)
+                    zip_file = zipfile.ZipFile(io.BytesIO(response.content))
+                    for file_name in zip_file.namelist():
+                        if file_name.lower().endswith(('.png', '.jpg', '.jpeg')):
+                            with zip_file.open(file_name) as file:
+                                image = Image.open(file)
+                                image = self.process_image(image)
+                                processed_images.append(image)
+                elif  img_input.startswith('http'):
+                    from io import BytesIO
+                    print("Fetching image from url: ", img_input)
+                    response = requests.get(img_input)
+                    image = Image.open(BytesIO(response.content))
+                elif img_input.startswith('data:image/png;base64,') or img_input.startswith('data:image/jpeg;base64,') or img_input.startswith('data:image/jpg;base64,'):
+                    import base64
+                    from io import BytesIO
+                    print("Decoding base64 image")
+                    base64_image = img_input[img_input.find(",")+1:]
+                    decoded_image = base64.b64decode(base64_image)
+                    image = Image.open(BytesIO(decoded_image))
+                else:
+                    raise ValueError("Invalid image url or base64 data provided.")
+
+                image = ImageOps.exif_transpose(image)
+                image = image.convert("RGB")
+                image = np.array(image).astype(np.float32) / 255.0
+                image_tensor = torch.from_numpy(image)[None,]
+                processed_images.append(image_tensor)
+        except Exception as e:
+            print(f"Error processing images: {e}")
+            pass
+            
+        if default_value is not None and len(images_list) == 0:
+            processed_images.append(default_value)  # Assuming default_value is a pre-processed image tensor
+
+        # Resize images if necessary and concatenate from MakeImageBatch in ImpactPack
+        if processed_images:
+            base_shape = processed_images[0].shape[1:]  # Get the shape of the first image for comparison
+            batch_tensor = processed_images[0]
+            for i in range(1, len(processed_images)):
+                if processed_images[i].shape[1:] != base_shape:
+                    # Resize to match the first image's dimensions
+                    processed_images[i] = comfy.utils.common_upscale(processed_images[i].movedim(-1, 1), base_shape[1], base_shape[0], "lanczos", "center").movedim(1, -1)
+
+                batch_tensor = torch.cat((batch_tensor, processed_images[i]), dim=0)
+            # Concatenate using torch.cat
+        else:
+            batch_tensor = None  # or handle the empty case as needed
+        return (batch_tensor, )
+
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalImageBatch": ComfyUIDeployExternalImageBatch}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalImageBatch": "External Image Batch (ComfyUI Deploy)"}

comfy-nodes/external_lora.py

@@ -1,8 +1,12 @@
 import folder_paths
-from PIL import Image, ImageOps
-import numpy as np
-import torch
-import folder_paths
+
+
+class AnyType(str):
+    def __ne__(self, __value: object) -> bool:
+        return False
+
+
+WILDCARD = AnyType("*")
 
 
 class ComfyUIDeployExternalLora:
@@ -16,36 +20,93 @@ class ComfyUIDeployExternalLora:
                 ),
             },
             "optional": {
-                "default_lora_name": (folder_paths.get_filename_list("loras"), ),
-            }
+                "default_lora_name": (folder_paths.get_filename_list("loras"),),
+                "lora_save_name": (  # if `default_lora_name` is a link to download a file, we will attempt to save it with this name
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+                "lora_url": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "bearer_token": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+            },
         }
 
-    RETURN_TYPES = (folder_paths.get_filename_list("loras"),)
+    RETURN_TYPES = (WILDCARD,)
     RETURN_NAMES = ("path",)
-
     FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
 
-    CATEGORY = "deploy"
-
-    def run(self, input_id, default_lora_name=None):
+    def run(
+        self,
+        input_id,
+        default_lora_name=None,
+        lora_save_name=None,
+        display_name=None,
+        description=None,
+        lora_url=None,
+        bearer_token=None,
+    ):
         import requests
         import os
         import uuid
 
-        if input_id and input_id.startswith('http'):
-            unique_filename = str(uuid.uuid4()) + ".safetensors"
-            print(unique_filename)
-            print(folder_paths.folder_names_and_paths["loras"][0][0])
-            destination_path = os.path.join(folder_paths.folder_names_and_paths["loras"][0][0], unique_filename)
-            print(destination_path)
-            print("Downloading external lora - " + input_id + " to " + destination_path)
-            response = requests.get(input_id, headers={'User-Agent': 'Mozilla/5.0'}, allow_redirects=True)
-            with open(destination_path, 'wb') as out_file:
-                out_file.write(response.content)
-            return (unique_filename,)
+        if lora_url:
+            if lora_url.startswith("http"):
+                if lora_save_name:
+                    existing_loras = folder_paths.get_filename_list("loras")
+                    # Check if lora_save_name exists in the list
+                    if lora_save_name in existing_loras:
+                        print(f"using lora: {lora_save_name}")
+                        return (lora_save_name,)
+                else:
+                    lora_save_name = str(uuid.uuid4()) + ".safetensors"
+                print(lora_save_name)
+                print(folder_paths.folder_names_and_paths["loras"][0][0])
+                destination_path = os.path.join(
+                    folder_paths.folder_names_and_paths["loras"][0][0], lora_save_name
+                )
+                print(destination_path)
+                print(
+                    "Downloading external lora - "
+                    + lora_url
+                    + " to "
+                    + destination_path
+                )
+                headers = {"User-Agent": "Mozilla/5.0"}
+                if bearer_token:
+                    headers["Authorization"] = f"Bearer {bearer_token}"
+                    print("using bearer token")
+                response = requests.get(
+                    lora_url,
+                    headers=headers,
+                    allow_redirects=True,
+                )
+                with open(destination_path, "wb") as out_file:
+                    out_file.write(response.content)
+                print(f"Ext Lora loading: {lora_url} to {lora_save_name}")
+                return (lora_save_name,)
+            else:
+                print(f"Ext Lora loading: {lora_url}")
+                return (lora_url,)
         else:
+            print(f"Ext Lora loading: {default_lora_name}")
             return (default_lora_name,)
-        
+
 
 NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalLora": ComfyUIDeployExternalLora}
-NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalLora": "External Lora (ComfyUI Deploy)"}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployExternalLora": "External Lora (ComfyUI Deploy)"
+}

comfy-nodes/external_number.py

@@ -16,22 +16,31 @@ class ComfyUIDeployExternalNumber:
             "optional": {
                 "default_value": (
                     "FLOAT",
-                    {"multiline": True, "display": "number", "default": 0},
+                    {"multiline": True, "display": "number", "default": 0, "min": -2147483647, "max": 2147483647, "step": 0.01},
+                ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
                 ),
             }
         }
 
     RETURN_TYPES = ("FLOAT",)
     RETURN_NAMES = ("value",)
-
     FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
 
-    CATEGORY = "number"
-
-    def run(self, input_id, default_value=None):
-        if not input_id or not input_id.strip().isdigit():
+    def run(self, input_id, default_value=None, display_name=None, description=None):
+        try:
+            float_value = float(input_id)
+            print("my number", float_value)
+            return [float_value]
+        except ValueError:
             return [default_value]
-        return [int(input_id)]
 
 
 NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalNumber": ComfyUIDeployExternalNumber}

comfy-nodes/external_number_int.py

@@ -16,20 +16,26 @@ class ComfyUIDeployExternalNumberInt:
             "optional": {
                 "default_value": (
                     "INT",
-                    {"multiline": True, "display": "number", "default": 0},
+                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 0},
+                ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
                 ),
             }
         }
 
     RETURN_TYPES = ("INT",)
     RETURN_NAMES = ("value",)
-
     FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
 
-    CATEGORY = "number"
-
-    def run(self, input_id, default_value=None):
-        if not input_id or not input_id.strip().isdigit():
+    def run(self, input_id, default_value=None, display_name=None, description=None):
+        if not input_id or (isinstance(input_id, str) and not input_id.strip().isdigit()):
             return [default_value]
         return [int(input_id)]
 

comfy-nodes/external_number_slider.py

@@ -0,0 +1,54 @@
+class ComfyUIDeployExternalNumberSlider:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_number_slider"},
+                ),
+            },
+            "optional": {
+                "default_value": (
+                    "FLOAT",
+                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 0.5, "step": 0.01},
+                ),
+                "min_value": (
+                    "FLOAT",
+                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 0, "step": 0.01},
+                ),
+                "max_value": (
+                    "FLOAT",
+                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 1, "step": 0.01},
+                ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("FLOAT",)
+    RETURN_NAMES = ("value",)
+    FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
+
+    def run(self, input_id, default_value=None, min_value=0, max_value=1, display_name=None, description=None):
+        try:
+            float_value = float(input_id)
+            if min_value <= float_value <= max_value:
+                print("my number", float_value)
+                return [float_value]
+            else:
+                print("Number out of range. Returning default value:", default_value)
+                return [default_value]
+        except ValueError:
+            print("Invalid input. Returning default value:", default_value)
+            return [default_value]
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalNumberSlider": ComfyUIDeployExternalNumberSlider}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalNumberSlider": "External Number Slider (ComfyUI Deploy)"}

comfy-nodes/external_number_slider_int.py

@@ -0,0 +1,54 @@
+class ComfyUIDeployExternalNumberSliderInt:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_number_slider_int"},
+                ),
+            },
+            "optional": {
+                "default_value": (
+                    "INT",
+                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 1, "step": 1},
+                ),
+                "min_value": (
+                    "INT",
+                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 0, "step": 1},
+                ),
+                "max_value": (
+                    "INT",
+                    {"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 10, "step": 1},
+                ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+            }
+        }
+
+    RETURN_TYPES = ("INT",)
+    RETURN_NAMES = ("value",)
+    FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
+
+    def run(self, input_id, default_value=None, min_value=0, max_value=10, display_name=None, description=None):
+        try:
+            int_value = int(round(float(input_id)))
+            if min_value <= int_value <= max_value:
+                print("my integer", int_value)
+                return [int_value]
+            else:
+                print("Integer out of range. Returning default value:", default_value)
+                return [default_value]
+        except (ValueError, TypeError):
+            print("Invalid input. Returning default value:", default_value)
+            return [default_value]
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalNumberSliderInt": ComfyUIDeployExternalNumberSliderInt}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalNumberSliderInt": "External Number Slider Int (ComfyUI Deploy)"}

comfy-nodes/external_seed.py

@@ -0,0 +1,116 @@
+import random
+
+
+class ComfyUIDeployExternalSeed:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_seed"},
+                ),
+                "default_value": (
+                    "INT",
+                    {"default": -1},
+                ),
+                "min_value": (
+                    "INT",
+                    {"default": 1, "min": 1, "max": 999999999999999},
+                ),
+                "max_value": (
+                    "INT",
+                    {"default": 4294967295, "min": 1, "max": 999999999999999},
+                ),
+            },
+            "optional": {
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {
+                        "multiline": True,
+                        "default": 'For default value:\n"-1" (i.e. not in range): Randomize within the min and max value range. \nin range: Fixed, always the same value\n',
+                    },
+                ),
+            },
+        }
+
+    RETURN_TYPES = ("INT",)
+    RETURN_NAMES = ("seed",)
+    FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
+
+    # Limits
+    _MAX_LIMIT = 999_999_999_999_999  # 15 digits
+
+    # Store cached seed when fixed flag is enabled
+    _cached_seed = None
+
+    @classmethod
+    def IS_CHANGED(
+        cls,
+        input_id,
+        min_value,
+        max_value,
+        default_value=None,
+        **kwargs,
+    ):
+        """Inform ComfyUI whether the node output should be considered changed.
+
+        If default_value is within range (Fixed mode), we return the inputs tuple
+        so the cached result is reused until the user changes something.
+        For Randomize mode, we force re-execution each queue.
+        """
+        # Clamp values to allowed range for check
+        min_value = max(1, min_value)
+        max_value = min(cls._MAX_LIMIT, max_value)
+
+        # Fixed mode when default_value is within range
+        if (
+            default_value is not None
+            and default_value >= min_value
+            and default_value <= max_value
+        ):
+            return (input_id, default_value)
+
+        # For Randomize (default_value is -1 or out of range) we force re-execution
+        import random as _rnd
+
+        return _rnd.random()
+
+    def run(
+        self,
+        input_id,
+        min_value: int,
+        max_value: int,
+        display_name=None,
+        description=None,
+        default_value: int = -1,
+    ):
+        # Clamp values to allowed range
+        min_value = max(1, min_value)
+        max_value = min(self._MAX_LIMIT, max_value)
+
+        # Ensure limits are in correct order after clamping
+        if min_value > max_value:
+            min_value, max_value = max_value, min_value
+
+        # Fixed mode: default_value is within range
+        if default_value >= min_value and default_value <= max_value:
+            seed = int(default_value)
+            self._cached_seed = seed
+            return [seed]
+
+        # Randomize mode: default_value is -1 or out of range
+        seed = random.randint(min_value, max_value)
+        self._cached_seed = seed
+        return [seed]
+
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalSeed": ComfyUIDeployExternalSeed}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployExternalSeed": "External Seed (ComfyUI Deploy)"
+}

comfy-nodes/external_string_combine.py

@@ -0,0 +1,53 @@
+import re
+
+
+class StringFunction:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "action": (["append", "replace"], {}),
+                "tidy_tags": (["yes", "no"], {}),
+            },
+            "optional": {
+                "text_a": ("STRING", {"multiline": True, "dynamicPrompts": False}),
+                "text_b": ("STRING", {"multiline": True, "dynamicPrompts": False}),
+                "text_c": ("STRING", {"multiline": True, "dynamicPrompts": False}),
+            },
+        }
+
+    RETURN_TYPES = ("STRING",)
+    FUNCTION = "exec"
+    CATEGORY = "🔗ComfyDeploy"
+    OUTPUT_NODE = True
+
+    def exec(self, action, tidy_tags, text_a="", text_b="", text_c=""):
+        tidy_tags = tidy_tags == "yes"
+        out = ""
+        if action == "append":
+            out = (", " if tidy_tags else "").join(
+                filter(None, [text_a, text_b, text_c])
+            )
+        else:
+            if text_c is None:
+                text_c = ""
+            if text_b.startswith("/") and text_b.endswith("/"):
+                regex = text_b[1:-1]
+                out = re.sub(regex, text_c, text_a)
+            else:
+                out = text_a.replace(text_b, text_c)
+        if tidy_tags:
+            out = re.sub(r"\s{2,}", " ", out)
+            out = out.replace(" ,", ",")
+            out = re.sub(r",{2,}", ",", out)
+            out = out.strip()
+        return {"ui": {"text": (out,)}, "result": (out,)}
+
+
+NODE_CLASS_MAPPINGS = {
+    "ComfyUIDeployStringCombine": StringFunction,
+}
+
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployStringCombine": "String Combine (ComfyUI Deploy)",
+}

comfy-nodes/external_text.py

@@ -18,6 +18,14 @@ class ComfyUIDeployExternalText:
                     "STRING",
                     {"multiline": True, "default": ""},
                 ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
             }
         }
 
@@ -26,9 +34,9 @@ class ComfyUIDeployExternalText:
 
     FUNCTION = "run"
 
-    CATEGORY = "text"
+    CATEGORY = "🔗ComfyDeploy"
 
-    def run(self, input_id, default_value=None):
+    def run(self, input_id, default_value=None, display_name=None, description=None):
         return [default_value]
 
 

comfy-nodes/external_text_any.py

@@ -0,0 +1,46 @@
+class AnyType(str):
+    def __ne__(self, __value: object) -> bool:
+        return False
+
+
+WILDCARD = AnyType("*")
+
+class ComfyUIDeployExternalTextAny:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_text"},
+                ),
+            },
+            "optional": {
+                "default_value": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+            }
+        }
+
+    RETURN_TYPES = (WILDCARD,)
+    RETURN_NAMES = ("text",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "🔗ComfyDeploy"
+
+    def run(self, input_id, default_value=None, display_name=None, description=None):
+        return [default_value]
+
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalTextAny": ComfyUIDeployExternalTextAny}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyUIDeployExternalTextAny": "External Text Any (ComfyUI Deploy)"}

comfy-nodes/external_vid.py

@@ -0,0 +1,79 @@
+import os
+import folder_paths
+import uuid
+
+from tqdm import tqdm
+
+video_extensions = ["webm", "mp4", "mkv", "gif"]
+
+
+class ComfyUIDeployExternalVideo:
+    @classmethod
+    def INPUT_TYPES(s):
+        input_dir = folder_paths.get_input_directory()
+        files = []
+        for f in os.listdir(input_dir):
+            if os.path.isfile(os.path.join(input_dir, f)):
+                file_parts = f.split(".")
+                if len(file_parts) > 1 and (file_parts[-1] in video_extensions):
+                    files.append(f)
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_video"},
+                ),
+            },
+            "optional": {
+                "meta_batch": ("VHS_BatchManager",),
+                "default_value": (sorted(files),),
+            },
+        }
+
+    CATEGORY = "Video Helper Suite 🎥🅥🅗🅢"
+
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("video")
+
+    FUNCTION = "load_video"
+    CATEGORY = "🔗ComfyDeploy"
+
+    def load_video(self, input_id, default_value):
+        input_dir = folder_paths.get_input_directory()
+        if input_id.startswith("http"):
+            import requests
+
+            print("Fetching video from URL: ", input_id)
+            response = requests.get(input_id, stream=True)
+            file_size = int(response.headers.get("Content-Length", 0))
+            file_extension = input_id.split(".")[-1].split("?")[
+                0
+            ]  # Extract extension and handle URLs with parameters
+            if file_extension not in video_extensions:
+                file_extension = ".mp4"
+
+            unique_filename = str(uuid.uuid4()) + "." + file_extension
+            video_path = os.path.join(input_dir, unique_filename)
+            chunk_size = 1024  # 1 Kibibyte
+
+            num_bars = int(file_size / chunk_size)
+
+            with open(video_path, "wb") as out_file:
+                for chunk in tqdm(
+                    response.iter_content(chunk_size=chunk_size),
+                    total=num_bars,
+                    unit="KB",
+                    desc="Downloading",
+                    leave=True,
+                ):
+                    out_file.write(chunk)
+        else:
+            video_path = os.path.abspath(os.path.join(input_dir, default_value))
+
+        return (video_path,)
+
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalVid": ComfyUIDeployExternalVideo}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployExternalVid": "External Video (ComfyUI Deploy) path"
+}

comfy-nodes/external_video.py

@@ -0,0 +1,898 @@
+# credit goes to https://github.com/Kosinkadink/ComfyUI-VideoHelperSuite
+# Intended to work with https://github.com/NicholasKao1029/ComfyUI-VideoHelperSuite/tree/main
+import os
+import itertools
+import numpy as np
+import torch
+from typing import Union
+from torch import Tensor
+import cv2
+import psutil
+
+from collections.abc import Mapping
+import folder_paths
+from comfy.utils import common_upscale
+
+### Utils
+import hashlib
+from typing import Iterable
+import shutil
+import subprocess
+import re
+import uuid
+
+import server
+from tqdm import tqdm
+
+BIGMIN = -(2**53 - 1)
+BIGMAX = 2**53 - 1
+
+DIMMAX = 8192
+
+
+def ffmpeg_suitability(path):
+    try:
+        version = subprocess.run(
+            [path, "-version"], check=True, capture_output=True
+        ).stdout.decode("utf-8")
+    except:
+        return 0
+    score = 0
+    # rough layout of the importance of various features
+    simple_criterion = [
+        ("libvpx", 20),
+        ("264", 10),
+        ("265", 3),
+        ("svtav1", 5),
+        ("libopus", 1),
+    ]
+    for criterion in simple_criterion:
+        if version.find(criterion[0]) >= 0:
+            score += criterion[1]
+    # obtain rough compile year from copyright information
+    copyright_index = version.find("2000-2")
+    if copyright_index >= 0:
+        copyright_year = version[copyright_index + 6 : copyright_index + 9]
+        if copyright_year.isnumeric():
+            score += int(copyright_year)
+    return score
+
+
+if "VHS_FORCE_FFMPEG_PATH" in os.environ:
+    ffmpeg_path = os.environ.get("VHS_FORCE_FFMPEG_PATH")
+else:
+    ffmpeg_paths = []
+    try:
+        from imageio_ffmpeg import get_ffmpeg_exe
+
+        imageio_ffmpeg_path = get_ffmpeg_exe()
+        ffmpeg_paths.append(imageio_ffmpeg_path)
+    except:
+        if "VHS_USE_IMAGEIO_FFMPEG" in os.environ:
+            raise
+    if "VHS_USE_IMAGEIO_FFMPEG" in os.environ:
+        ffmpeg_path = imageio_ffmpeg_path
+    else:
+        system_ffmpeg = shutil.which("ffmpeg")
+        if system_ffmpeg is not None:
+            ffmpeg_paths.append(system_ffmpeg)
+        if os.path.isfile("ffmpeg"):
+            ffmpeg_paths.append(os.path.abspath("ffmpeg"))
+        if os.path.isfile("ffmpeg.exe"):
+            ffmpeg_paths.append(os.path.abspath("ffmpeg.exe"))
+        if len(ffmpeg_paths) == 0:
+            ffmpeg_path = None
+        elif len(ffmpeg_paths) == 1:
+            # Evaluation of suitability isn't required, can take sole option
+            # to reduce startup time
+            ffmpeg_path = ffmpeg_paths[0]
+        else:
+            ffmpeg_path = max(ffmpeg_paths, key=ffmpeg_suitability)
+gifski_path = os.environ.get("VHS_GIFSKI", None)
+if gifski_path is None:
+    gifski_path = os.environ.get("JOV_GIFSKI", None)
+    if gifski_path is None:
+        gifski_path = shutil.which("gifski")
+
+
+def is_safe_path(path):
+    if "VHS_STRICT_PATHS" not in os.environ:
+        return True
+    basedir = os.path.abspath(".")
+    try:
+        common_path = os.path.commonpath([basedir, path])
+    except:
+        # Different drive on windows
+        return False
+    return common_path == basedir
+
+
+def get_sorted_dir_files_from_directory(
+    directory: str,
+    skip_first_images: int = 0,
+    select_every_nth: int = 1,
+    extensions: Iterable = None,
+):
+    directory = strip_path(directory)
+    dir_files = os.listdir(directory)
+    dir_files = sorted(dir_files)
+    dir_files = [os.path.join(directory, x) for x in dir_files]
+    dir_files = list(filter(lambda filepath: os.path.isfile(filepath), dir_files))
+    # filter by extension, if needed
+    if extensions is not None:
+        extensions = list(extensions)
+        new_dir_files = []
+        for filepath in dir_files:
+            ext = "." + filepath.split(".")[-1]
+            if ext.lower() in extensions:
+                new_dir_files.append(filepath)
+        dir_files = new_dir_files
+    # start at skip_first_images
+    dir_files = dir_files[skip_first_images:]
+    dir_files = dir_files[0::select_every_nth]
+    return dir_files
+
+
+# modified from https://stackoverflow.com/questions/22058048/hashing-a-file-in-python
+def calculate_file_hash(filename: str, hash_every_n: int = 1):
+    # Larger video files were taking >.5 seconds to hash even when cached,
+    # so instead the modified time from the filesystem is used as a hash
+    h = hashlib.sha256()
+    h.update(filename.encode())
+    h.update(str(os.path.getmtime(filename)).encode())
+    return h.hexdigest()
+
+
+prompt_queue = server.PromptServer.instance.prompt_queue
+
+
+def requeue_workflow_unchecked():
+    """Requeues the current workflow without checking for multiple requeues"""
+    currently_running = prompt_queue.currently_running
+    (_, _, prompt, extra_data, outputs_to_execute) = next(
+        iter(currently_running.values())
+    )
+
+    # Ensure batch_managers are marked stale
+    prompt = prompt.copy()
+    for uid in prompt:
+        if prompt[uid]["class_type"] == "VHS_BatchManager":
+            prompt[uid]["inputs"]["requeue"] = (
+                prompt[uid]["inputs"].get("requeue", 0) + 1
+            )
+
+    # execution.py has guards for concurrency, but server doesn't.
+    # TODO: Check that this won't be an issue
+    number = -server.PromptServer.instance.number
+    server.PromptServer.instance.number += 1
+    prompt_id = str(server.uuid.uuid4())
+    prompt_queue.put((number, prompt_id, prompt, extra_data, outputs_to_execute))
+
+
+requeue_guard = [None, 0, 0, {}]
+
+
+def requeue_workflow(requeue_required=(-1, True)):
+    assert len(prompt_queue.currently_running) == 1
+    global requeue_guard
+    (run_number, _, prompt, _, _) = next(iter(prompt_queue.currently_running.values()))
+    if requeue_guard[0] != run_number:
+        # Calculate a count of how many outputs are managed by a batch manager
+        managed_outputs = 0
+        for bm_uid in prompt:
+            if prompt[bm_uid]["class_type"] == "VHS_BatchManager":
+                for output_uid in prompt:
+                    if prompt[output_uid]["class_type"] in ["VHS_VideoCombine"]:
+                        for inp in prompt[output_uid]["inputs"].values():
+                            if inp == [bm_uid, 0]:
+                                managed_outputs += 1
+        requeue_guard = [run_number, 0, managed_outputs, {}]
+    requeue_guard[1] = requeue_guard[1] + 1
+    requeue_guard[3][requeue_required[0]] = requeue_required[1]
+    if requeue_guard[1] == requeue_guard[2] and max(requeue_guard[3].values()):
+        requeue_workflow_unchecked()
+
+
+def get_audio(file, start_time=0, duration=0):
+    args = [ffmpeg_path, "-i", file]
+    if start_time > 0:
+        args += ["-ss", str(start_time)]
+    if duration > 0:
+        args += ["-t", str(duration)]
+    try:
+        # TODO: scan for sample rate and maintain
+        res = subprocess.run(
+            args + ["-f", "f32le", "-"], capture_output=True, check=True
+        )
+        audio = torch.frombuffer(bytearray(res.stdout), dtype=torch.float32)
+        match = re.search(", (\\d+) Hz, (\\w+), ", res.stderr.decode("utf-8"))
+    except subprocess.CalledProcessError as e:
+        raise Exception(
+            f"VHS failed to extract audio from {file}:\n" + e.stderr.decode("utf-8")
+        )
+    if match:
+        ar = int(match.group(1))
+        # NOTE: Just throwing an error for other channel types right now
+        # Will deal with issues if they come
+        ac = {"mono": 1, "stereo": 2}[match.group(2)]
+    else:
+        ar = 44100
+        ac = 2
+    audio = audio.reshape((-1, ac)).transpose(0, 1).unsqueeze(0)
+    return {"waveform": audio, "sample_rate": ar}
+
+
+class LazyAudioMap(Mapping):
+    def __init__(self, file, start_time, duration):
+        self.file = file
+        self.start_time = start_time
+        self.duration = duration
+        self._dict = None
+
+    def __getitem__(self, key):
+        if self._dict is None:
+            self._dict = get_audio(self.file, self.start_time, self.duration)
+        return self._dict[key]
+
+    def __iter__(self):
+        if self._dict is None:
+            self._dict = get_audio(self.file, self.start_time, self.duration)
+        return iter(self._dict)
+
+    def __len__(self):
+        if self._dict is None:
+            self._dict = get_audio(self.file, self.start_time, self.duration)
+        return len(self._dict)
+
+
+def lazy_get_audio(file, start_time=0, duration=0):
+    return LazyAudioMap(file, start_time, duration)
+
+
+def lazy_eval(func):
+    class Cache:
+        def __init__(self, func):
+            self.res = None
+            self.func = func
+
+        def get(self):
+            if self.res is None:
+                self.res = self.func()
+            return self.res
+
+    cache = Cache(func)
+    return lambda: cache.get()
+
+
+def is_url(url):
+    return url.split("://")[0] in ["http", "https"]
+
+
+def validate_sequence(path):
+    # Check if path is a valid ffmpeg sequence that points to at least one file
+    (path, file) = os.path.split(path)
+    if not os.path.isdir(path):
+        return False
+    match = re.search("%0?\d+d", file)
+    if not match:
+        return False
+    seq = match.group()
+    if seq == "%d":
+        seq = "\\\\d+"
+    else:
+        seq = "\\\\d{%s}" % seq[1:-1]
+    file_matcher = re.compile(re.sub("%0?\d+d", seq, file))
+    for file in os.listdir(path):
+        if file_matcher.fullmatch(file):
+            return True
+    return False
+
+
+def strip_path(path):
+    # This leaves whitespace inside quotes and only a single "
+    # thus ' ""test"' -> '"test'
+    # consider path.strip(string.whitespace+"\"")
+    # or weightier re.fullmatch("[\\s\"]*(.+?)[\\s\"]*", path).group(1)
+    path = path.strip()
+    if path.startswith('"'):
+        path = path[1:]
+    if path.endswith('"'):
+        path = path[:-1]
+    return path
+
+
+def hash_path(path):
+    if path is None:
+        return "input"
+    if is_url(path):
+        return "url"
+    return calculate_file_hash(path.strip('"'))
+
+
+def validate_path(path, allow_none=False, allow_url=True):
+    if path is None:
+        return allow_none
+    if is_url(path):
+        # Probably not feasible to check if url resolves here
+        return True if allow_url else "URLs are unsupported for this path"
+    if not os.path.isfile(path.strip('"')):
+        return "Invalid file path: {}".format(path)
+    return True
+
+
+### Utils
+
+video_extensions = ["webm", "mp4", "mkv", "gif"]
+
+
+def is_gif(filename) -> bool:
+    file_parts = filename.split(".")
+    return len(file_parts) > 1 and file_parts[-1] == "gif"
+
+
+def target_size(
+    width, height, force_size, custom_width, custom_height
+) -> tuple[int, int]:
+    if force_size == "Custom":
+        return (custom_width, custom_height)
+    elif force_size == "Custom Height":
+        force_size = "?x" + str(custom_height)
+    elif force_size == "Custom Width":
+        force_size = str(custom_width) + "x?"
+
+    if force_size != "Disabled":
+        force_size = force_size.split("x")
+        if force_size[0] == "?":
+            width = (width * int(force_size[1])) // height
+            # Limit to a multple of 8 for latent conversion
+            width = int(width) + 4 & ~7
+            height = int(force_size[1])
+        elif force_size[1] == "?":
+            height = (height * int(force_size[0])) // width
+            height = int(height) + 4 & ~7
+            width = int(force_size[0])
+        else:
+            width = int(force_size[0])
+            height = int(force_size[1])
+    return (width, height)
+
+
+def validate_index(
+    index: int,
+    length: int = 0,
+    is_range: bool = False,
+    allow_negative=False,
+    allow_missing=False,
+) -> int:
+    # if part of range, do nothing
+    if is_range:
+        return index
+    # otherwise, validate index
+    # validate not out of range - only when latent_count is passed in
+    if length > 0 and index > length - 1 and not allow_missing:
+        raise IndexError(f"Index '{index}' out of range for {length} item(s).")
+    # if negative, validate not out of range
+    if index < 0:
+        if not allow_negative:
+            raise IndexError(f"Negative indeces not allowed, but was '{index}'.")
+        conv_index = length + index
+        if conv_index < 0 and not allow_missing:
+            raise IndexError(
+                f"Index '{index}', converted to '{conv_index}' out of range for {length} item(s)."
+            )
+        index = conv_index
+    return index
+
+
+def convert_to_index_int(
+    raw_index: str,
+    length: int = 0,
+    is_range: bool = False,
+    allow_negative=False,
+    allow_missing=False,
+) -> int:
+    try:
+        return validate_index(
+            int(raw_index),
+            length=length,
+            is_range=is_range,
+            allow_negative=allow_negative,
+            allow_missing=allow_missing,
+        )
+    except ValueError as e:
+        raise ValueError(f"Index '{raw_index}' must be an integer.", e)
+
+
+def convert_str_to_indexes(
+    indexes_str: str, length: int = 0, allow_missing=False
+) -> list[int]:
+    if not indexes_str:
+        return []
+    int_indexes = list(range(0, length))
+    allow_negative = length > 0
+    chosen_indexes = []
+    # parse string - allow positive ints, negative ints, and ranges separated by ':'
+    groups = indexes_str.split(",")
+    groups = [g.strip() for g in groups]
+    for g in groups:
+        # parse range of indeces (e.g. 2:16)
+        if ":" in g:
+            index_range = g.split(":", 2)
+            index_range = [r.strip() for r in index_range]
+
+            start_index = index_range[0]
+            if len(start_index) > 0:
+                start_index = convert_to_index_int(
+                    start_index,
+                    length=length,
+                    is_range=True,
+                    allow_negative=allow_negative,
+                    allow_missing=allow_missing,
+                )
+            else:
+                start_index = 0
+            end_index = index_range[1]
+            if len(end_index) > 0:
+                end_index = convert_to_index_int(
+                    end_index,
+                    length=length,
+                    is_range=True,
+                    allow_negative=allow_negative,
+                    allow_missing=allow_missing,
+                )
+            else:
+                end_index = length
+            # support step as well, to allow things like reversing, every-other, etc.
+            step = 1
+            if len(index_range) > 2:
+                step = index_range[2]
+                if len(step) > 0:
+                    step = convert_to_index_int(
+                        step,
+                        length=length,
+                        is_range=True,
+                        allow_negative=True,
+                        allow_missing=True,
+                    )
+                else:
+                    step = 1
+            # if latents were passed in, base indeces on known latent count
+            if len(int_indexes) > 0:
+                chosen_indexes.extend(int_indexes[start_index:end_index][::step])
+            # otherwise, assume indeces are valid
+            else:
+                chosen_indexes.extend(list(range(start_index, end_index, step)))
+        # parse individual indeces
+        else:
+            chosen_indexes.append(
+                convert_to_index_int(
+                    g,
+                    length=length,
+                    allow_negative=allow_negative,
+                    allow_missing=allow_missing,
+                )
+            )
+    return chosen_indexes
+
+
+def select_indexes(input_obj: Union[Tensor, list], idxs: list):
+    if type(input_obj) == Tensor:
+        return input_obj[idxs]
+    else:
+        return [input_obj[i] for i in idxs]
+
+
+def select_indexes_from_str(
+    input_obj: Union[Tensor, list], indexes: str, err_if_missing=True, err_if_empty=True
+):
+    real_idxs = convert_str_to_indexes(
+        indexes, len(input_obj), allow_missing=not err_if_missing
+    )
+    if err_if_empty and len(real_idxs) == 0:
+        raise Exception(f"Nothing was selected based on indexes found in '{indexes}'.")
+    return select_indexes(input_obj, real_idxs)
+
+
+###
+
+
+def cv_frame_generator(
+    video,
+    force_rate,
+    frame_load_cap,
+    skip_first_frames,
+    select_every_nth,
+    meta_batch=None,
+    unique_id=None,
+):
+    video_cap = cv2.VideoCapture(strip_path(video))
+    if not video_cap.isOpened():
+        raise ValueError(f"{video} could not be loaded with cv.")
+    pbar = None
+
+    # extract video metadata
+    fps = video_cap.get(cv2.CAP_PROP_FPS)
+    width = int(video_cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    height = int(video_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    total_frames = int(video_cap.get(cv2.CAP_PROP_FRAME_COUNT))
+    duration = total_frames / fps
+
+    # set video_cap to look at start_index frame
+    total_frame_count = 0
+    total_frames_evaluated = -1
+    frames_added = 0
+    base_frame_time = 1 / fps
+    prev_frame = None
+
+    if force_rate == 0:
+        target_frame_time = base_frame_time
+    else:
+        target_frame_time = 1 / force_rate
+
+    yield (width, height, fps, duration, total_frames, target_frame_time)
+    if meta_batch is not None:
+        yield min(frame_load_cap, total_frames)
+
+    time_offset = target_frame_time - base_frame_time
+    while video_cap.isOpened():
+        if time_offset < target_frame_time:
+            is_returned = video_cap.grab()
+            # if didn't return frame, video has ended
+            if not is_returned:
+                break
+            time_offset += base_frame_time
+        if time_offset < target_frame_time:
+            continue
+        time_offset -= target_frame_time
+        # if not at start_index, skip doing anything with frame
+        total_frame_count += 1
+        if total_frame_count <= skip_first_frames:
+            continue
+        else:
+            total_frames_evaluated += 1
+
+        # if should not be selected, skip doing anything with frame
+        if total_frames_evaluated % select_every_nth != 0:
+            continue
+
+        # opencv loads images in BGR format (yuck), so need to convert to RGB for ComfyUI use
+        # follow up: can videos ever have an alpha channel?
+        # To my testing: No. opencv has no support for alpha
+        unused, frame = video_cap.retrieve()
+        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        # convert frame to comfyui's expected format
+        # TODO: frame contains no exif information. Check if opencv2 has already applied
+        frame = np.array(frame, dtype=np.float32)
+        torch.from_numpy(frame).div_(255)
+        if prev_frame is not None:
+            inp = yield prev_frame
+            if inp is not None:
+                # ensure the finally block is called
+                return
+        prev_frame = frame
+        frames_added += 1
+        if pbar is not None:
+            pbar.update_absolute(frames_added, frame_load_cap)
+        # if cap exists and we've reached it, stop processing frames
+        if frame_load_cap > 0 and frames_added >= frame_load_cap:
+            break
+    if meta_batch is not None:
+        meta_batch.inputs.pop(unique_id)
+        meta_batch.has_closed_inputs = True
+    if prev_frame is not None:
+        yield prev_frame
+
+
+def batched(it, n):
+    while batch := tuple(itertools.islice(it, n)):
+        yield batch
+
+
+def batched_vae_encode(images, vae, frames_per_batch):
+    for batch in batched(images, frames_per_batch):
+        image_batch = torch.from_numpy(np.array(batch))
+        yield from vae.encode(image_batch).numpy()
+
+
+def load_video_cv(
+    video: str,
+    force_rate: int,
+    force_size: str,
+    custom_width: int,
+    custom_height: int,
+    frame_load_cap: int,
+    skip_first_frames: int,
+    select_every_nth: int,
+    meta_batch=None,
+    unique_id=None,
+    memory_limit_mb=None,
+    vae=None,
+):
+    if meta_batch is None or unique_id not in meta_batch.inputs:
+        gen = cv_frame_generator(
+            video,
+            force_rate,
+            frame_load_cap,
+            skip_first_frames,
+            select_every_nth,
+            meta_batch,
+            unique_id,
+        )
+        (width, height, fps, duration, total_frames, target_frame_time) = next(gen)
+
+        if meta_batch is not None:
+            meta_batch.inputs[unique_id] = (
+                gen,
+                width,
+                height,
+                fps,
+                duration,
+                total_frames,
+                target_frame_time,
+            )
+            meta_batch.total_frames = min(meta_batch.total_frames, next(gen))
+
+    else:
+        (gen, width, height, fps, duration, total_frames, target_frame_time) = (
+            meta_batch.inputs[unique_id]
+        )
+
+    memory_limit = None
+    if memory_limit_mb is not None:
+        memory_limit *= 2**20
+    else:
+        # TODO: verify if garbage collection should be performed here.
+        # leaves ~128 MB unreserved for safety
+        try:
+            memory_limit = (
+                psutil.virtual_memory().available + psutil.swap_memory().free
+            ) - 2**27
+        except:
+            print(
+                "Failed to calculate available memory. Memory load limit has been disabled"
+            )
+    if memory_limit is not None:
+        if vae is not None:
+            # space required to load as f32, exist as latent with wiggle room, decode to f32
+            max_loadable_frames = int(
+                memory_limit // (width * height * 3 * (4 + 4 + 1 / 10))
+            )
+        else:
+            # TODO: use better estimate for when vae is not None
+            # Consider completely ignoring for load_latent case?
+            max_loadable_frames = int(memory_limit // (width * height * 3 * (0.1)))
+        if meta_batch is not None:
+            if meta_batch.frames_per_batch > max_loadable_frames:
+                raise RuntimeError(
+                    f"Meta Batch set to {meta_batch.frames_per_batch} frames but only {max_loadable_frames} can fit in memory"
+                )
+            gen = itertools.islice(gen, meta_batch.frames_per_batch)
+        else:
+            original_gen = gen
+            gen = itertools.islice(gen, max_loadable_frames)
+    downscale_ratio = getattr(vae, "downscale_ratio", 8)
+    frames_per_batch = (1920 * 1080 * 16) // (width * height) or 1
+    if force_size != "Disabled" or vae is not None:
+        new_size = target_size(
+            width, height, force_size, custom_width, custom_height, downscale_ratio
+        )
+        if new_size[0] != width or new_size[1] != height:
+
+            def rescale(frame):
+                s = torch.from_numpy(
+                    np.fromiter(frame, np.dtype((np.float32, (height, width, 3))))
+                )
+                s = s.movedim(-1, 1)
+                s = common_upscale(s, new_size[0], new_size[1], "lanczos", "center")
+                return s.movedim(1, -1).numpy()
+
+            gen = itertools.chain.from_iterable(
+                map(rescale, batched(gen, frames_per_batch))
+            )
+    else:
+        new_size = width, height
+    if vae is not None:
+        gen = batched_vae_encode(gen, vae, frames_per_batch)
+        vw, vh = new_size[0] // downscale_ratio, new_size[1] // downscale_ratio
+        images = torch.from_numpy(np.fromiter(gen, np.dtype((np.float32, (4, vh, vw)))))
+    else:
+        # Some minor wizardry to eliminate a copy and reduce max memory by a factor of ~2
+        images = torch.from_numpy(
+            np.fromiter(gen, np.dtype((np.float32, (new_size[1], new_size[0], 3))))
+        )
+    if meta_batch is None and memory_limit is not None:
+        try:
+            next(original_gen)
+            raise RuntimeError(
+                f"Memory limit hit after loading {len(images)} frames. Stopping execution."
+            )
+        except StopIteration:
+            pass
+    if len(images) == 0:
+        raise RuntimeError("No frames generated")
+
+    # Setup lambda for lazy audio capture
+    audio = lazy_get_audio(
+        video,
+        skip_first_frames * target_frame_time,
+        frame_load_cap * target_frame_time * select_every_nth,
+    )
+    # Adjust target_frame_time for select_every_nth
+    target_frame_time *= select_every_nth
+    video_info = {
+        "source_fps": fps,
+        "source_frame_count": total_frames,
+        "source_duration": duration,
+        "source_width": width,
+        "source_height": height,
+        "loaded_fps": 1 / target_frame_time,
+        "loaded_frame_count": len(images),
+        "loaded_duration": len(images) * target_frame_time,
+        "loaded_width": new_size[0],
+        "loaded_height": new_size[1],
+    }
+    if vae is None:
+        return (images, len(images), audio, video_info, None)
+    else:
+        return (None, len(images), audio, video_info, {"samples": images})
+
+
+# modeled after Video upload node
+class ComfyUIDeployExternalVideo:
+    @classmethod
+    def INPUT_TYPES(s):
+        input_dir = folder_paths.get_input_directory()
+        files = []
+        for f in os.listdir(input_dir):
+            if os.path.isfile(os.path.join(input_dir, f)):
+                file_parts = f.split(".")
+                if len(file_parts) > 1 and (file_parts[-1] in video_extensions):
+                    files.append(f)
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_video"},
+                ),
+                "force_rate": ("INT", {"default": 0, "min": 0, "max": 60, "step": 1}),
+                "force_size": (
+                    [
+                        "Disabled",
+                        "Custom Height",
+                        "Custom Width",
+                        "Custom",
+                        "256x?",
+                        "?x256",
+                        "256x256",
+                        "512x?",
+                        "?x512",
+                        "512x512",
+                    ],
+                ),
+                "custom_width": (
+                    "INT",
+                    {"default": 512, "min": 0, "max": DIMMAX, "step": 8},
+                ),
+                "custom_height": (
+                    "INT",
+                    {"default": 512, "min": 0, "max": DIMMAX, "step": 8},
+                ),
+                "frame_load_cap": (
+                    "INT",
+                    {"default": 0, "min": 0, "max": BIGMAX, "step": 1},
+                ),
+                "skip_first_frames": (
+                    "INT",
+                    {"default": 0, "min": 0, "max": BIGMAX, "step": 1},
+                ),
+                "select_every_nth": (
+                    "INT",
+                    {"default": 1, "min": 1, "max": BIGMAX, "step": 1},
+                ),
+            },
+            "optional": {
+                "meta_batch": ("VHS_BatchManager",),
+                "vae": ("VAE",),
+                "default_video": (sorted(files),),
+                "display_name": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+                "description": (
+                    "STRING",
+                    {"multiline": True, "default": ""},
+                ),
+                "default_value_url": ("STRING", {"image_preview": True, "default": ""}),
+            },
+            "hidden": {"unique_id": "UNIQUE_ID"},
+        }
+
+    CATEGORY = "Video Helper Suite 🎥🅥🅗🅢"
+
+    RETURN_TYPES = ("IMAGE", "INT", "AUDIO", "VHS_VIDEOINFO", "LATENT")
+    RETURN_NAMES = (
+        "IMAGE",
+        "frame_count",
+        "audio",
+        "video_info",
+        "LATENT",
+    )
+
+    FUNCTION = "load_video"
+    CATEGORY = "🔗ComfyDeploy"
+
+    def load_video(self, **kwargs):
+        input_id = kwargs.get("input_id")
+        force_rate = kwargs.get("force_rate")
+        force_size = kwargs.get("force_size", "Disabled")
+        custom_width = kwargs.get("custom_width")
+        custom_height = kwargs.get("custom_height")
+        frame_load_cap = kwargs.get("frame_load_cap")
+        skip_first_frames = kwargs.get("skip_first_frames")
+        select_every_nth = kwargs.get("select_every_nth")
+        meta_batch = kwargs.get("meta_batch")
+        unique_id = kwargs.get("unique_id")
+        default_value_url = kwargs.get("default_value_url")
+
+        input_dir = folder_paths.get_input_directory()
+        if input_id.startswith("http") or (
+            default_value_url and default_value_url.startswith("http")
+        ):
+            import requests
+
+            # Use input_id if it's a URL, otherwise use default_value_url
+            url = input_id if input_id.startswith("http") else default_value_url
+
+            print("Fetching video from URL: ", url)
+            response = requests.get(url, stream=True)
+            file_size = int(response.headers.get("Content-Length", 0))
+            file_extension = url.split(".")[-1].split("?")[
+                0
+            ]  # Extract extension and handle URLs with parameters
+            if file_extension not in video_extensions:
+                file_extension = ".mp4"
+
+            unique_filename = str(uuid.uuid4()) + "." + file_extension
+            video_path = os.path.join(input_dir, unique_filename)
+            chunk_size = 1024  # 1 Kibibyte
+
+            num_bars = int(file_size / chunk_size)
+
+            with open(video_path, "wb") as out_file:
+                for chunk in tqdm(
+                    response.iter_content(chunk_size=chunk_size),
+                    total=num_bars,
+                    unit="KB",
+                    desc="Downloading",
+                    leave=True,
+                ):
+                    out_file.write(chunk)
+        else:
+            video = kwargs.get("default_video", None)
+            if video is None:
+                raise "No default video given and no external video provided"
+            video_path = folder_paths.get_annotated_filepath(video.strip('"'))
+
+        return load_video_cv(
+            video=video_path,
+            force_rate=force_rate,
+            force_size=force_size,
+            custom_width=custom_width,
+            custom_height=custom_height,
+            frame_load_cap=frame_load_cap,
+            skip_first_frames=skip_first_frames,
+            select_every_nth=select_every_nth,
+            meta_batch=meta_batch,
+            unique_id=unique_id,
+        )
+
+    @classmethod
+    def IS_CHANGED(s, video, **kwargs):
+        image_path = folder_paths.get_annotated_filepath(video)
+        return calculate_file_hash(image_path)
+
+
+NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalVideo": ComfyUIDeployExternalVideo}
+NODE_DISPLAY_NAME_MAPPINGS = {
+    "ComfyUIDeployExternalVideo": "External Video (ComfyUI Deploy x VHS)"
+}

comfy-nodes/input_websocket_image.py

@@ -0,0 +1,67 @@
+import folder_paths
+from PIL import Image, ImageOps
+import numpy as np
+import torch
+from server import PromptServer, BinaryEventTypes
+import asyncio
+
+from globals import streaming_prompt_metadata, max_output_id_length
+
+class ComfyDeployWebscoketImageInput:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "input_id": (
+                    "STRING",
+                    {"multiline": False, "default": "input_id"},
+                ),
+                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
+            },
+            "optional": {
+                "default_value": ("IMAGE", ),
+                "client_id": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+            }
+        }
+
+    OUTPUT_NODE = True
+
+    RETURN_TYPES = ("IMAGE", )
+    RETURN_NAMES = ("images",)
+
+    FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
+
+    @classmethod
+    def VALIDATE_INPUTS(s, input_id):
+        try:
+            if len(input_id.encode('ascii')) > max_output_id_length:
+                raise ValueError(f"input_id size is greater than {max_output_id_length} bytes")
+        except UnicodeEncodeError:
+            raise ValueError("input_id is not ASCII encodable")
+
+        return True
+
+    def run(self, input_id, seed, default_value=None ,client_id=None):
+        # print(streaming_prompt_metadata[client_id].inputs)
+        if client_id in streaming_prompt_metadata and input_id in streaming_prompt_metadata[client_id].inputs:
+            if isinstance(streaming_prompt_metadata[client_id].inputs[input_id], Image.Image):
+                print("Returning image from websocket input")
+                
+                image = streaming_prompt_metadata[client_id].inputs[input_id]
+                
+                image = ImageOps.exif_transpose(image)
+                image = image.convert("RGB")
+                image = np.array(image).astype(np.float32) / 255.0
+                image = torch.from_numpy(image)[None,]
+                
+                return [image]
+
+        print("Returning default value")
+        return [default_value]
+
+NODE_CLASS_MAPPINGS = {"ComfyDeployWebscoketImageInput": ComfyDeployWebscoketImageInput}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyDeployWebscoketImageInput": "Image Websocket Input (ComfyDeploy)"}

comfy-nodes/output_exr.py

@@ -0,0 +1,78 @@
+# In file: comfyui-deploy/comfy-nodes/output_exr.py
+
+import os
+import numpy as np
+import folder_paths
+
+# Try to set up OpenCV for EXR writing.
+try:
+    os.environ["OPENCV_IO_ENABLE_OPENEXR"] = "1"
+    import cv2
+    OPENCV_AVAILABLE = True
+except ImportError:
+    print("Warning: OpenCV not found for ComfyDeployOutputEXR. Please add opencv-python-headless to requirements.txt")
+    OPENCV_AVAILABLE = False
+
+# ALIGNED: Renamed class to match project conventions
+class ComfyDeployOutputEXR:
+    def __init__(self):
+        self.output_dir = folder_paths.get_output_directory()
+        self.type = "output"
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "images": ("IMAGE", ),
+                "filename_prefix": ("STRING", {"default": "ComfyDeploy_EXR"})
+            },
+            # ADDED: Optional output_id for consistency with other ComfyDeploy nodes
+            "optional": {
+                "output_id": ("STRING", {"multiline": False, "default": "output_exr"}),
+            },
+        }
+    
+    RETURN_TYPES = ()
+    # ALIGNED: Changed function name to 'run'
+    FUNCTION = "run"
+    OUTPUT_NODE = True
+    # ALIGNED: Matched the category name
+    CATEGORY = "🔗ComfyDeploy"
+    DESCRIPTION = "Saves the input images as EXR (HDR) files."
+
+    def run(self, images, filename_prefix="ComfyDeploy_EXR", output_id="output_exr"):
+        if not OPENCV_AVAILABLE:
+            raise ImportError("OpenCV is required to save EXR files. Please ensure opencv-python-headless is in requirements.txt.")
+
+        full_output_folder, filename, counter, subfolder, filename_prefix = (
+            folder_paths.get_save_image_path(
+                filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0]
+            )
+        )
+        results = list()
+
+        for image in images:
+            image_np = image.cpu().numpy()
+
+            if image_np.dtype != np.float32:
+                 image_np = image_np.astype(np.float32)
+
+            file = f"{filename}_{counter:05}.exr"
+            file_path = os.path.join(full_output_folder, file)
+
+            image_np_bgr = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)
+            cv2.imwrite(file_path, image_np_bgr)
+
+            results.append({
+                "filename": file,
+                "subfolder": subfolder,
+                "type": self.type,
+                "output_id": output_id, # ADDED
+            })
+            counter += 1
+
+        return {"ui": {"images": results}}
+
+# ALIGNED: Mappings are defined at the bottom of the node file in this project
+NODE_CLASS_MAPPINGS = {"ComfyDeployOutputEXR": ComfyDeployOutputEXR}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyDeployOutputEXR": "EXR Output (ComfyDeploy)"}

comfy-nodes/output_image.py

@@ -0,0 +1,101 @@
+import os
+import json
+import numpy as np
+from PIL import Image
+from PIL.PngImagePlugin import PngInfo
+import folder_paths
+
+
+class ComfyDeployOutputImage:
+    def __init__(self):
+        self.output_dir = folder_paths.get_output_directory()
+        self.type = "output"
+        self.prefix_append = ""
+        self.compress_level = 4
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "images": ("IMAGE", {"tooltip": "The images to save."}),
+                "filename_prefix": (
+                    "STRING",
+                    {
+                        "default": "ComfyUI",
+                        "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% or %Empty Latent Image.width% to include values from nodes.",
+                    },
+                ),
+                "file_type": (["png", "jpg", "webp"], {"default": "webp"}),
+                "quality": ("INT", {"default": 80, "min": 1, "max": 100, "step": 1}),
+            },
+            "optional": {
+                "output_id": (
+                    "STRING",
+                    {"multiline": False, "default": "output_images"},
+                ),
+            },
+            "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
+        }
+
+    RETURN_TYPES = ()
+    FUNCTION = "run"
+
+    OUTPUT_NODE = True
+    CATEGORY = "🔗ComfyDeploy"
+    DESCRIPTION = "Saves the input images to your ComfyUI output directory."
+
+    def run(
+        self,
+        images,
+        filename_prefix="ComfyUI",
+        file_type="png",
+        quality=80,
+        output_id="output_images",
+        prompt=None,
+        extra_pnginfo=None,
+    ):
+        filename_prefix += self.prefix_append
+        full_output_folder, filename, counter, subfolder, filename_prefix = (
+            folder_paths.get_save_image_path(
+                filename_prefix, self.output_dir, images[0].shape[1], images[0].shape[0]
+            )
+        )
+        results = list()
+        for batch_number, image in enumerate(images):
+            i = 255.0 * image.cpu().numpy()
+            img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
+            metadata = PngInfo()
+            if prompt is not None:
+                metadata.add_text("prompt", json.dumps(prompt))
+            if extra_pnginfo is not None:
+                for x in extra_pnginfo:
+                    metadata.add_text(x, json.dumps(extra_pnginfo[x]))
+
+            filename_with_batch_num = filename.replace("%batch_num%", str(batch_number))
+            file = f"{filename_with_batch_num}_{counter:05}_.{file_type}"
+            file_path = os.path.join(full_output_folder, file)
+
+            if file_type == "png":
+                img.save(
+                    file_path, pnginfo=metadata, compress_level=self.compress_level
+                )
+            elif file_type == "jpg":
+                img.save(file_path, quality=quality, optimize=True)
+            elif file_type == "webp":
+                img.save(file_path, quality=quality)
+
+            results.append(
+                {
+                    "filename": file,
+                    "subfolder": subfolder,
+                    "type": self.type,
+                    "output_id": output_id,
+                }
+            )
+            counter += 1
+
+        return {"ui": {"images": results}}
+
+
+NODE_CLASS_MAPPINGS = {"ComfyDeployOutputImage": ComfyDeployOutputImage}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyDeployOutputImage": "Image Output (ComfyDeploy)"}

comfy-nodes/output_text.py

@@ -0,0 +1,99 @@
+import os
+import json
+import folder_paths
+
+
+class ComfyDeployOutputText:
+    def __init__(self):
+        self.output_dir = folder_paths.get_output_directory()
+        self.type = "output"
+        self.prefix_append = ""
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "text": (
+                    "STRING",
+                    {
+                        "multiline": True,
+                        "forceInput": True,
+                        "tooltip": "The text to save.",
+                    },
+                ),
+                "filename_prefix": (
+                    "STRING",
+                    {
+                        "default": "ComfyUI",
+                        "tooltip": "The prefix for the file to save. This may include formatting information such as %date:yyyy-MM-dd% to include values from nodes.",
+                    },
+                ),
+                "file_type": (["txt", "json", "md"], {"default": "txt"}),
+            },
+            "optional": {
+                "output_id": (
+                    "STRING",
+                    {"multiline": False, "default": "output_text"},
+                ),
+            },
+            "hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
+        }
+
+    RETURN_TYPES = ()
+    FUNCTION = "run"
+
+    OUTPUT_NODE = True
+    CATEGORY = "🔗ComfyDeploy"
+    DESCRIPTION = "Saves the input text to your ComfyUI output directory."
+
+    def run(
+        self,
+        text,
+        filename_prefix="ComfyUI",
+        file_type="txt",
+        output_id="output_text",
+        prompt=None,
+        extra_pnginfo=None,
+    ):
+        filename_prefix += self.prefix_append
+        # For text, we don't need dimensions, so pass 0, 0
+        full_output_folder, filename, counter, subfolder, filename_prefix = (
+            folder_paths.get_save_image_path(filename_prefix, self.output_dir, 0, 0)
+        )
+
+        results = list()
+
+        # Create file path
+        file = f"{filename}_{counter:05}_.{file_type}"
+        file_path = os.path.join(full_output_folder, file)
+
+        # Save the text based on file type
+        if file_type == "json":
+            try:
+                # Try to save as JSON if the text is valid JSON
+                json_data = json.loads(text) if isinstance(text, str) else text
+                with open(file_path, "w", encoding="utf-8") as f:
+                    json.dump(json_data, f, indent=2)
+            except json.JSONDecodeError:
+                # Fall back to saving as plain text if not valid JSON
+                with open(file_path, "w", encoding="utf-8") as f:
+                    f.write(text)
+        else:
+            # Save as plain text for txt and md
+            with open(file_path, "w", encoding="utf-8") as f:
+                f.write(text)
+
+        results.append(
+            {
+                "filename": file,
+                "subfolder": subfolder,
+                "type": self.type,
+                "output_id": output_id,
+            }
+        )
+
+        return {"ui": {"text_file": results}}
+
+
+NODE_CLASS_MAPPINGS = {"ComfyDeployOutputText": ComfyDeployOutputText}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyDeployOutputText": "Text Output (ComfyDeploy)"}

comfy-nodes/output_websocket_image.py

@@ -0,0 +1,69 @@
+import folder_paths
+from PIL import Image, ImageOps
+import numpy as np
+import torch
+from server import PromptServer, BinaryEventTypes
+import asyncio
+
+from globals import send_image, max_output_id_length
+
+class ComfyDeployWebscoketImageOutput:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "output_id": (
+                    "STRING",
+                    {"multiline": False, "default": "output_id"},
+                ),
+                "images": ("IMAGE", ),
+                "file_type": (["WEBP", "PNG", "JPEG"], ),
+                "quality": ("INT", {"default": 80, "min": 1, "max": 100, "step": 1}),
+            },
+            "optional": {
+                    "client_id": (
+                    "STRING",
+                    {"multiline": False, "default": ""},
+                ),
+            }
+            # "hidden": {"client_id": "CLIENT_ID"},
+        }
+
+    OUTPUT_NODE = True
+
+    RETURN_TYPES = ()
+    RETURN_NAMES = ("text",)
+    FUNCTION = "run"
+    CATEGORY = "🔗ComfyDeploy"
+    
+    @classmethod
+    def VALIDATE_INPUTS(s, output_id):
+        try:
+            if len(output_id.encode('ascii')) > max_output_id_length:
+                raise ValueError(f"output_id size is greater than {max_output_id_length} bytes")
+        except UnicodeEncodeError:
+            raise ValueError("output_id is not ASCII encodable")
+
+        return True
+
+    def run(self, output_id, images, file_type, quality, client_id):
+        prompt_server = PromptServer.instance
+        loop = prompt_server.loop
+        
+        def schedule_coroutine_blocking(target, *args):
+            future = asyncio.run_coroutine_threadsafe(target(*args), loop)
+            return future.result()  # This makes the call blocking
+        
+        for tensor in images:
+            array = 255.0 * tensor.cpu().numpy()
+            image = Image.fromarray(np.clip(array, 0, 255).astype(np.uint8))
+
+            schedule_coroutine_blocking(send_image, [file_type, image, None, quality], client_id, output_id)
+            print("Image sent")
+
+        return {"ui": {}}
+        
+
+
+NODE_CLASS_MAPPINGS = {"ComfyDeployWebscoketImageOutput": ComfyDeployWebscoketImageOutput}
+NODE_DISPLAY_NAME_MAPPINGS = {"ComfyDeployWebscoketImageOutput": "Image Websocket Output (ComfyDeploy)"}

example_workflows/lora-model.json

@@ -0,0 +1,152 @@
+{
+  "id": "ed93ac94-4f26-4ed3-a57b-73cd8f4d3494",
+  "revision": 0,
+  "last_node_id": 5,
+  "last_link_id": 1,
+  "nodes": [
+    {
+      "id": 2,
+      "type": "LoraLoader",
+      "pos": [
+        736.646728515625,
+        628.3823852539062
+      ],
+      "size": [
+        315,
+        126
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "model",
+          "type": "MODEL",
+          "link": null
+        },
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": null
+        },
+        {
+          "name": "lora_name",
+          "type": "COMBO",
+          "widget": {
+            "name": "lora_name"
+          },
+          "link": 1
+        }
+      ],
+      "outputs": [
+        {
+          "name": "MODEL",
+          "type": "MODEL",
+          "links": null
+        },
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "LoraLoader"
+      },
+      "widgets_values": [
+        "1-292.safetensors",
+        1,
+        1
+      ]
+    },
+    {
+      "id": 1,
+      "type": "ComfyUIDeployExternalLora",
+      "pos": [
+        299.6898498535156,
+        624.7929077148438
+      ],
+      "size": [
+        400,
+        208
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "path",
+          "type": "*",
+          "links": [
+            1
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfyui-deploy",
+        "ver": "cd3a2ff5471828f9c840e746551592e882c05aa4",
+        "Node name for S&R": "ComfyUIDeployExternalLora"
+      },
+      "widgets_values": [
+        "input_lora",
+        "HyperSD\\FLUX.1\\Hyper-FLUX.1-dev-16steps-lora.safetensors",
+        "",
+        "",
+        "",
+        ""
+      ]
+    },
+    {
+      "id": 5,
+      "type": "Note",
+      "pos": [
+        302.09033203125,
+        401.2951965332031
+      ],
+      "size": [
+        479.4894104003906,
+        161.61924743652344
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "\"External Lora\" node will let you to use different loras from the Comfy Deploy UI or even via API.\n\n- lora_url:\n  url that will be used to download your LoRA model in execution time\n\n- lora_save_name:\n  when we download your model, this will be saved in your private storage, \n  give it a good name :D"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    }
+  ],
+  "links": [
+    [
+      1,
+      1,
+      0,
+      2,
+      2,
+      "COMBO"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 1.167184107045006,
+      "offset": [
+        298.431389807788,
+        -207.58877445762934
+      ]
+    },
+    "VHS_latentpreview": false,
+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true
+  },
+  "version": 0.4
+}

example_workflows/masks.json

@@ -0,0 +1,873 @@
+{
+  "id": "351f402b-62f2-4f62-8a5e-0b9d3510e8f9",
+  "revision": 0,
+  "last_node_id": 29,
+  "last_link_id": 28,
+  "nodes": [
+    {
+      "id": 11,
+      "type": "JoinImageWithAlpha",
+      "pos": [
+        814.478271484375,
+        419.3052062988281
+      ],
+      "size": [
+        264.5999755859375,
+        46
+      ],
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 10
+        },
+        {
+          "name": "alpha",
+          "type": "MASK",
+          "link": 12
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            11
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "JoinImageWithAlpha"
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 15,
+      "type": "PreviewImage",
+      "pos": [
+        1950,
+        640
+      ],
+      "size": [
+        210,
+        246
+      ],
+      "flags": {},
+      "order": 18,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 16
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "PreviewImage"
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 10,
+      "type": "LoadImage",
+      "pos": [
+        467.8168640136719,
+        422.453857421875
+      ],
+      "size": [
+        315,
+        314
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            10
+          ]
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": [
+            12
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "Bob-Minion-Background-PNG-Image.png",
+        "image",
+        ""
+      ]
+    },
+    {
+      "id": 18,
+      "type": "Note",
+      "pos": [
+        460.8001708984375,
+        263.64251708984375
+      ],
+      "size": [
+        379.4292297363281,
+        88
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Option 1: CREATE THE MASK FROM THE ALPHA CHANNEL (Useful for example to generate the background of an image)\n\nMake sure that you are using \"External Image Alpha\". \n"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 21,
+      "type": "LoadImage",
+      "pos": [
+        469.57025146484375,
+        1506.3018798828125
+      ],
+      "size": [
+        315,
+        314
+      ],
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            18
+          ]
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "ComfyUI_temp_otmos_00005_.png",
+        "image",
+        ""
+      ]
+    },
+    {
+      "id": 25,
+      "type": "MaskToImage",
+      "pos": [
+        1283.1668701171875,
+        1579.603271484375
+      ],
+      "size": [
+        176.39999389648438,
+        26
+      ],
+      "flags": {},
+      "order": 13,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "mask",
+          "type": "MASK",
+          "link": 28
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            21
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "MaskToImage"
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 13,
+      "type": "SplitImageWithAlpha",
+      "pos": [
+        1602.5518798828125,
+        417.59869384765625
+      ],
+      "size": [
+        277.20001220703125,
+        46
+      ],
+      "flags": {},
+      "order": 11,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 13
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            14,
+            25
+          ]
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": [
+            15,
+            26
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "SplitImageWithAlpha"
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 29,
+      "type": "VAEEncodeForInpaint",
+      "pos": [
+        2220.89453125,
+        401.0885009765625
+      ],
+      "size": [
+        340.20001220703125,
+        98
+      ],
+      "flags": {},
+      "order": 16,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "pixels",
+          "type": "IMAGE",
+          "link": 25
+        },
+        {
+          "name": "vae",
+          "type": "VAE",
+          "link": null
+        },
+        {
+          "name": "mask",
+          "type": "MASK",
+          "link": 26
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "VAEEncodeForInpaint"
+      },
+      "widgets_values": [
+        6
+      ]
+    },
+    {
+      "id": 14,
+      "type": "PreviewImage",
+      "pos": [
+        1950,
+        350
+      ],
+      "size": [
+        210,
+        246
+      ],
+      "flags": {},
+      "order": 14,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 14
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "PreviewImage"
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 17,
+      "type": "MaskToImage",
+      "pos": [
+        1752.33203125,
+        572.061767578125
+      ],
+      "size": [
+        176.39999389648438,
+        26
+      ],
+      "flags": {},
+      "order": 15,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "mask",
+          "type": "MASK",
+          "link": 15
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            16
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "MaskToImage"
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 27,
+      "type": "PreviewImage",
+      "pos": [
+        1329.2960205078125,
+        1132.759765625
+      ],
+      "size": [
+        210,
+        246
+      ],
+      "flags": {},
+      "order": 10,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 22
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "PreviewImage"
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 20,
+      "type": "LoadImage",
+      "pos": [
+        468.1963806152344,
+        1128.9498291015625
+      ],
+      "size": [
+        315,
+        314
+      ],
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            17
+          ]
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": []
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "LoadImage"
+      },
+      "widgets_values": [
+        "clipspace/clipspace-mask-1126817.300000012.png [input]",
+        "image",
+        ""
+      ]
+    },
+    {
+      "id": 24,
+      "type": "ImageToMask",
+      "pos": [
+        1255.560302734375,
+        1468.347900390625
+      ],
+      "size": [
+        315,
+        58
+      ],
+      "flags": {},
+      "order": 9,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 19
+        }
+      ],
+      "outputs": [
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": [
+            24,
+            28
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "ImageToMask"
+      },
+      "widgets_values": [
+        "red"
+      ]
+    },
+    {
+      "id": 26,
+      "type": "PreviewImage",
+      "pos": [
+        1488.1925048828125,
+        1579.146728515625
+      ],
+      "size": [
+        210,
+        246
+      ],
+      "flags": {},
+      "order": 17,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 21
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "PreviewImage"
+      },
+      "widgets_values": []
+    },
+    {
+      "id": 28,
+      "type": "VAEEncodeForInpaint",
+      "pos": [
+        1637.603271484375,
+        1182.81298828125
+      ],
+      "size": [
+        340.20001220703125,
+        98
+      ],
+      "flags": {},
+      "order": 12,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "pixels",
+          "type": "IMAGE",
+          "link": 23
+        },
+        {
+          "name": "vae",
+          "type": "VAE",
+          "link": null
+        },
+        {
+          "name": "mask",
+          "type": "MASK",
+          "link": 24
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": null
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.3.27",
+        "Node name for S&R": "VAEEncodeForInpaint"
+      },
+      "widgets_values": [
+        6
+      ]
+    },
+    {
+      "id": 19,
+      "type": "Note",
+      "pos": [
+        467.4615173339844,
+        985.1439819335938
+      ],
+      "size": [
+        379.4292297363281,
+        88
+      ],
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Option 2: UPLOAD THE MASK AS OTHER IMAGE (useful if you require the image that is below the mask to do inpainting, in this case to generate new glasses)"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 22,
+      "type": "ComfyUIDeployExternalImage",
+      "pos": [
+        910.8199462890625,
+        1132.306396484375
+      ],
+      "size": [
+        390.5999755859375,
+        154
+      ],
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "default_value",
+          "shape": 7,
+          "type": "IMAGE",
+          "link": 17
+        }
+      ],
+      "outputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "links": [
+            22,
+            23
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfyui-deploy",
+        "ver": "cd3a2ff5471828f9c840e746551592e882c05aa4",
+        "Node name for S&R": "ComfyUIDeployExternalImage"
+      },
+      "widgets_values": [
+        "input_image",
+        "",
+        "",
+        "",
+        ""
+      ]
+    },
+    {
+      "id": 23,
+      "type": "ComfyUIDeployExternalImage",
+      "pos": [
+        843.6348876953125,
+        1467.8876953125
+      ],
+      "size": [
+        390.5999755859375,
+        154
+      ],
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "default_value",
+          "shape": 7,
+          "type": "IMAGE",
+          "link": 18
+        }
+      ],
+      "outputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "links": [
+            19
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfyui-deploy",
+        "ver": "cd3a2ff5471828f9c840e746551592e882c05aa4",
+        "Node name for S&R": "ComfyUIDeployExternalImage"
+      },
+      "widgets_values": [
+        "input_image_mask",
+        "",
+        "",
+        "",
+        ""
+      ]
+    },
+    {
+      "id": 12,
+      "type": "ComfyUIDeployExternalImageAlpha",
+      "pos": [
+        1107.891357421875,
+        418.2679138183594
+      ],
+      "size": [
+        466.1999816894531,
+        200
+      ],
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "default_value",
+          "shape": 7,
+          "type": "IMAGE",
+          "link": 11
+        }
+      ],
+      "outputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "links": [
+            13
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfyui-deploy",
+        "ver": "cd3a2ff5471828f9c840e746551592e882c05aa4",
+        "Node name for S&R": "ComfyUIDeployExternalImageAlpha"
+      },
+      "widgets_values": [
+        "input_image_alpha",
+        "",
+        ""
+      ]
+    }
+  ],
+  "links": [
+    [
+      10,
+      10,
+      0,
+      11,
+      0,
+      "IMAGE"
+    ],
+    [
+      11,
+      11,
+      0,
+      12,
+      0,
+      "IMAGE"
+    ],
+    [
+      12,
+      10,
+      1,
+      11,
+      1,
+      "MASK"
+    ],
+    [
+      13,
+      12,
+      0,
+      13,
+      0,
+      "IMAGE"
+    ],
+    [
+      14,
+      13,
+      0,
+      14,
+      0,
+      "IMAGE"
+    ],
+    [
+      15,
+      13,
+      1,
+      17,
+      0,
+      "MASK"
+    ],
+    [
+      16,
+      17,
+      0,
+      15,
+      0,
+      "IMAGE"
+    ],
+    [
+      17,
+      20,
+      0,
+      22,
+      0,
+      "IMAGE"
+    ],
+    [
+      18,
+      21,
+      0,
+      23,
+      0,
+      "IMAGE"
+    ],
+    [
+      19,
+      23,
+      0,
+      24,
+      0,
+      "IMAGE"
+    ],
+    [
+      21,
+      25,
+      0,
+      26,
+      0,
+      "IMAGE"
+    ],
+    [
+      22,
+      22,
+      0,
+      27,
+      0,
+      "IMAGE"
+    ],
+    [
+      23,
+      22,
+      0,
+      28,
+      0,
+      "IMAGE"
+    ],
+    [
+      24,
+      24,
+      0,
+      28,
+      2,
+      "MASK"
+    ],
+    [
+      25,
+      13,
+      0,
+      29,
+      0,
+      "IMAGE"
+    ],
+    [
+      26,
+      13,
+      1,
+      29,
+      2,
+      "MASK"
+    ],
+    [
+      28,
+      24,
+      0,
+      25,
+      0,
+      "MASK"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {
+    "ds": {
+      "scale": 0.9646149645000013,
+      "offset": [
+        48.66905973637718,
+        -817.5683540167485
+      ]
+    },
+    "VHS_latentpreview": false,
+    "VHS_latentpreviewrate": 0,
+    "VHS_MetadataImage": true,
+    "VHS_KeepIntermediate": true
+  },
+  "version": 0.4
+}

examples/flux-dev.json

@@ -0,0 +1,359 @@
+{
+  "extra": {
+    "ds": {
+      "scale": 0.6010518407212623,
+      "offset": [815.5938895649746, 84.94304700477853]
+    },
+    "node_versions": {
+      "comfy-core": "0.3.19",
+      "comfyui-deploy": "b3df94d1affcf7ce05ee7eeda99989194bcd9159"
+    }
+  },
+  "links": [
+    [9, 8, 0, 9, 0, "IMAGE"],
+    [45, 30, 1, 6, 0, "CLIP"],
+    [46, 30, 2, 8, 1, "VAE"],
+    [47, 30, 0, 31, 0, "MODEL"],
+    [51, 27, 0, 31, 3, "LATENT"],
+    [52, 31, 0, 8, 0, "LATENT"],
+    [54, 30, 1, 33, 0, "CLIP"],
+    [55, 33, 0, 31, 2, "CONDITIONING"],
+    [56, 6, 0, 35, 0, "CONDITIONING"],
+    [57, 35, 0, 31, 1, "CONDITIONING"],
+    [58, 38, 0, 6, 1, "STRING"],
+    [59, 40, 0, 27, 0, "INT"],
+    [60, 39, 0, 27, 1, "INT"]
+  ],
+  "nodes": [
+    {
+      "id": 6,
+      "pos": [384, 192],
+      "mode": 0,
+      "size": [422.8500061035156, 164.30999755859375],
+      "type": "CLIPTextEncode",
+      "color": "#232",
+      "flags": {},
+      "order": 7,
+      "title": "CLIP Text Encode (Positive Prompt)",
+      "inputs": [
+        { "link": 45, "name": "clip", "type": "CLIP" },
+        {
+          "pos": [10, 36],
+          "link": 58,
+          "name": "text",
+          "type": "STRING",
+          "widget": { "name": "text" }
+        }
+      ],
+      "bgcolor": "#353",
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [56],
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPTextEncode" },
+      "widgets_values": [
+        "cute anime girl with massive fluffy fennec ears and a big fluffy tail blonde messy long hair blue eyes wearing a maid outfit with a long black gold leaf pattern dress and a white apron mouth open placing a fancy black forest cake with candles on top of a dinner table of an old dark Victorian mansion lit by candlelight with a bright window to the foggy forest and very expensive stuff everywhere there are paintings on the walls"
+      ]
+    },
+    {
+      "id": 8,
+      "pos": [1151, 195],
+      "mode": 0,
+      "size": [210, 46],
+      "type": "VAEDecode",
+      "flags": {},
+      "order": 11,
+      "inputs": [
+        { "link": 52, "name": "samples", "type": "LATENT" },
+        { "link": 46, "name": "vae", "type": "VAE" }
+      ],
+      "outputs": [
+        { "name": "IMAGE", "type": "IMAGE", "links": [9], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "VAEDecode" },
+      "widgets_values": []
+    },
+    {
+      "id": 9,
+      "pos": [1375, 194],
+      "mode": 0,
+      "size": [985.2999877929688, 1060.3800048828125],
+      "type": "SaveImage",
+      "flags": {},
+      "order": 12,
+      "inputs": [{ "link": 9, "name": "images", "type": "IMAGE" }],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": ["ComfyUI"]
+    },
+    {
+      "id": 31,
+      "pos": [816, 192],
+      "mode": 0,
+      "size": [315, 262],
+      "type": "KSampler",
+      "flags": {},
+      "order": 10,
+      "inputs": [
+        { "link": 47, "name": "model", "type": "MODEL" },
+        { "link": 57, "name": "positive", "type": "CONDITIONING" },
+        { "link": 55, "name": "negative", "type": "CONDITIONING" },
+        { "link": 51, "name": "latent_image", "type": "LATENT" }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": [52],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "KSampler" },
+      "widgets_values": [
+        1024035737089801,
+        "randomize",
+        20,
+        1,
+        "euler",
+        "simple",
+        1
+      ]
+    },
+    {
+      "id": 35,
+      "pos": [576, 96],
+      "mode": 0,
+      "size": [211.60000610351562, 58],
+      "type": "FluxGuidance",
+      "flags": {},
+      "order": 9,
+      "inputs": [
+        { "link": 56, "name": "conditioning", "type": "CONDITIONING" }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [57],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "FluxGuidance" },
+      "widgets_values": [3.5]
+    },
+    {
+      "id": 37,
+      "pos": [60, 345],
+      "mode": 0,
+      "size": [225, 88],
+      "type": "MarkdownNote",
+      "color": "#432",
+      "flags": {},
+      "order": 0,
+      "inputs": [],
+      "bgcolor": "#653",
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "🛈 [Learn more about this workflow](https://comfyanonymous.github.io/ComfyUI_examples/flux/#flux-dev-1)"
+      ]
+    },
+    {
+      "id": 34,
+      "pos": [825, 510],
+      "mode": 0,
+      "size": [282.8599853515625, 164.0800018310547],
+      "type": "Note",
+      "color": "#432",
+      "flags": {},
+      "order": 1,
+      "inputs": [],
+      "bgcolor": "#653",
+      "outputs": [],
+      "properties": { "text": "" },
+      "widgets_values": [
+        "Note that Flux dev and schnell do not have any negative prompt so CFG should be set to 1.0. Setting CFG to 1.0 means the negative prompt is ignored."
+      ]
+    },
+    {
+      "id": 30,
+      "pos": [48, 192],
+      "mode": 0,
+      "size": [315, 98],
+      "type": "CheckpointLoaderSimple",
+      "flags": {},
+      "order": 2,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "MODEL",
+          "type": "MODEL",
+          "links": [47],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": [45, 54],
+          "shape": 3,
+          "slot_index": 1
+        },
+        {
+          "name": "VAE",
+          "type": "VAE",
+          "links": [46],
+          "shape": 3,
+          "slot_index": 2
+        }
+      ],
+      "properties": { "Node name for S&R": "CheckpointLoaderSimple" },
+      "widgets_values": ["FLUX1/flux1-dev-fp8.safetensors"]
+    },
+    {
+      "id": 33,
+      "pos": [390, 400],
+      "mode": 0,
+      "size": [422.8500061035156, 164.30999755859375],
+      "type": "CLIPTextEncode",
+      "color": "#322",
+      "flags": { "collapsed": true },
+      "order": 6,
+      "title": "CLIP Text Encode (Negative Prompt)",
+      "inputs": [
+        { "link": 54, "name": "clip", "type": "CLIP", "slot_index": 0 }
+      ],
+      "bgcolor": "#533",
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [55],
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPTextEncode" },
+      "widgets_values": [""]
+    },
+    {
+      "id": 27,
+      "pos": [461.8629455566406, 460.2491149902344],
+      "mode": 0,
+      "size": [315, 126],
+      "type": "EmptySD3LatentImage",
+      "color": "#323",
+      "flags": {},
+      "order": 8,
+      "inputs": [
+        {
+          "pos": [10, 60],
+          "link": 59,
+          "name": "height",
+          "type": "INT",
+          "widget": { "name": "height" }
+        },
+        {
+          "pos": [10, 36],
+          "link": 60,
+          "name": "width",
+          "type": "INT",
+          "widget": { "name": "width" }
+        }
+      ],
+      "bgcolor": "#535",
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": [51],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "EmptySD3LatentImage" },
+      "widgets_values": [1024, 1024, 1]
+    },
+    {
+      "id": 38,
+      "pos": [-497.3238525390625, 306.5517578125],
+      "mode": 0,
+      "size": [400, 200],
+      "type": "ComfyUIDeployExternalText",
+      "flags": {},
+      "order": 3,
+      "inputs": [],
+      "outputs": [{ "name": "text", "type": "STRING", "links": [58] }],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalText" },
+      "widgets_values": [
+        "prompt",
+        "cute anime girl with massive fluffy fennec ears and a big fluffy tail blonde messy long hair blue eyes wearing a maid outfit with a long black gold leaf pattern dress and a white apron mouth open placing a fancy black forest cake with candles on top of a dinner table of an old dark Victorian mansion lit by candlelight with a bright window to the foggy forest and very expensive stuff everywhere there are paintings on the walls",
+        "Prompt",
+        "The prompt to generate an image from."
+      ]
+    },
+    {
+      "id": 39,
+      "pos": [-507.4543762207031, 612.9552001953125],
+      "mode": 0,
+      "size": [453.5999755859375, 200],
+      "type": "ComfyUIDeployExternalNumberInt",
+      "flags": {},
+      "order": 4,
+      "inputs": [],
+      "outputs": [
+        { "name": "value", "type": "INT", "links": [60], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["width", 1024, "Width", "The width of the image."]
+    },
+    {
+      "id": 40,
+      "pos": [-497.8695068359375, 864.68994140625],
+      "mode": 0,
+      "size": [453.5999755859375, 200],
+      "type": "ComfyUIDeployExternalNumberInt",
+      "flags": {},
+      "order": 5,
+      "inputs": [],
+      "outputs": [
+        { "name": "value", "type": "INT", "links": [59], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["height", 1024, "Height", "The height of the image."]
+    }
+  ],
+  "config": {},
+  "groups": [
+    {
+      "id": 1,
+      "color": "#3f789e",
+      "flags": {},
+      "title": "Input",
+      "bounding": [
+        -508.010986328125, 186.76593017578125, 453.23040771484375,
+        334.3218994140625
+      ],
+      "font_size": 24
+    },
+    {
+      "id": 2,
+      "color": "#A88",
+      "flags": {},
+      "title": "Additional",
+      "bounding": [
+        -517.1227416992188, 537.53759765625, 644.4954223632812,
+        599.2609252929688
+      ],
+      "font_size": 24
+    }
+  ],
+  "version": 0.4,
+  "last_link_id": 60,
+  "last_node_id": 40
+}

examples/flux-schnell.json

@@ -0,0 +1,423 @@
+{
+  "extra": {
+    "ds": {
+      "scale": 0.6830134553650709,
+      "offset": [750.2474149300585, 120.48924647647146]
+    },
+    "node_versions": {
+      "comfy-core": "0.3.19",
+      "comfyui-deploy": "171a227856bd5f31e97828d89f83f3741004d05e"
+    }
+  },
+  "links": [
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+    [10, 11, 0, 6, 0, "CLIP"],
+    [12, 10, 0, 8, 1, "VAE"],
+    [19, 16, 0, 13, 2, "SAMPLER"],
+    [20, 17, 0, 13, 3, "SIGMAS"],
+    [23, 5, 0, 13, 4, "LATENT"],
+    [24, 13, 0, 8, 0, "LATENT"],
+    [30, 22, 0, 13, 1, "GUIDER"],
+    [37, 25, 0, 13, 0, "NOISE"],
+    [38, 12, 0, 17, 0, "MODEL"],
+    [39, 12, 0, 22, 0, "MODEL"],
+    [40, 6, 0, 22, 1, "CONDITIONING"],
+    [41, 28, 0, 6, 1, "STRING"],
+    [44, 29, 0, 5, 0, "INT"],
+    [45, 30, 0, 5, 1, "INT"]
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+      "size": [355.20001220703125, 106],
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+      "flags": {},
+      "order": 14,
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+        { "link": 30, "name": "guider", "type": "GUIDER", "slot_index": 1 },
+        { "link": 19, "name": "sampler", "type": "SAMPLER", "slot_index": 2 },
+        { "link": 20, "name": "sigmas", "type": "SIGMAS", "slot_index": 3 },
+        {
+          "link": 23,
+          "name": "latent_image",
+          "type": "LATENT",
+          "slot_index": 4
+        }
+      ],
+      "outputs": [
+        {
+          "name": "output",
+          "type": "LATENT",
+          "links": [24],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "denoised_output",
+          "type": "LATENT",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": { "Node name for S&R": "SamplerCustomAdvanced" },
+      "widgets_values": []
+    },
+    {
+      "id": 8,
+      "pos": [1248, 192],
+      "mode": 0,
+      "size": [210, 46],
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+      "inputs": [
+        { "link": 24, "name": "samples", "type": "LATENT" },
+        { "link": 12, "name": "vae", "type": "VAE" }
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+        { "name": "IMAGE", "type": "IMAGE", "links": [9], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "VAEDecode" },
+      "widgets_values": []
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+      "pos": [559, 125],
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+      "size": [241.79998779296875, 46],
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+        {
+          "link": 40,
+          "name": "conditioning",
+          "type": "CONDITIONING",
+          "slot_index": 1
+        }
+      ],
+      "outputs": [
+        {
+          "name": "GUIDER",
+          "type": "GUIDER",
+          "links": [30],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "BasicGuider" },
+      "widgets_values": []
+    },
+    {
+      "id": 16,
+      "pos": [480, 720],
+      "mode": 0,
+      "size": [315, 58],
+      "type": "KSamplerSelect",
+      "flags": {},
+      "order": 0,
+      "inputs": [],
+      "outputs": [
+        { "name": "SAMPLER", "type": "SAMPLER", "links": [19], "shape": 3 }
+      ],
+      "properties": { "Node name for S&R": "KSamplerSelect" },
+      "widgets_values": ["euler"]
+    },
+    {
+      "id": 17,
+      "pos": [480, 816],
+      "mode": 0,
+      "size": [315, 106],
+      "type": "BasicScheduler",
+      "flags": {},
+      "order": 10,
+      "inputs": [
+        { "link": 38, "name": "model", "type": "MODEL", "slot_index": 0 }
+      ],
+      "outputs": [
+        { "name": "SIGMAS", "type": "SIGMAS", "links": [20], "shape": 3 }
+      ],
+      "properties": { "Node name for S&R": "BasicScheduler" },
+      "widgets_values": ["simple", 4, 1]
+    },
+    {
+      "id": 27,
+      "pos": [480, 960],
+      "mode": 0,
+      "size": [311.3529052734375, 131.16229248046875],
+      "type": "Note",
+      "color": "#432",
+      "flags": {},
+      "order": 1,
+      "inputs": [],
+      "bgcolor": "#653",
+      "outputs": [],
+      "properties": { "text": "" },
+      "widgets_values": [
+        "The schnell model is a distilled model that can generate a good image with only 4 steps."
+      ]
+    },
+    {
+      "id": 9,
+      "pos": [1488, 192],
+      "mode": 0,
+      "size": [985.3012084960938, 1060.3828125],
+      "type": "SaveImage",
+      "flags": {},
+      "order": 16,
+      "inputs": [{ "link": 9, "name": "images", "type": "IMAGE" }],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": ["ComfyUI"]
+    },
+    {
+      "id": 25,
+      "pos": [480, 587.7890625],
+      "mode": 0,
+      "size": [315, 82],
+      "type": "RandomNoise",
+      "color": "#2a363b",
+      "flags": {},
+      "order": 2,
+      "inputs": [],
+      "bgcolor": "#3f5159",
+      "outputs": [
+        { "name": "NOISE", "type": "NOISE", "links": [37], "shape": 3 }
+      ],
+      "properties": { "Node name for S&R": "RandomNoise" },
+      "widgets_values": [393845863554716, "randomize"]
+    },
+    {
+      "id": 5,
+      "pos": [471.7746276855469, 423.91571044921875],
+      "mode": 0,
+      "size": [315, 126],
+      "type": "EmptyLatentImage",
+      "color": "#323",
+      "flags": {},
+      "order": 12,
+      "inputs": [
+        {
+          "pos": [10, 36],
+          "link": 44,
+          "name": "width",
+          "type": "INT",
+          "widget": { "name": "width" }
+        },
+        {
+          "pos": [10, 60],
+          "link": 45,
+          "name": "height",
+          "type": "INT",
+          "widget": { "name": "height" }
+        }
+      ],
+      "bgcolor": "#535",
+      "outputs": [
+        { "name": "LATENT", "type": "LATENT", "links": [23], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "EmptyLatentImage" },
+      "widgets_values": [1024, 1024, 1]
+    },
+    {
+      "id": 26,
+      "pos": [41.60395812988281, 517.059326171875],
+      "mode": 0,
+      "size": [336, 288],
+      "type": "Note",
+      "color": "#432",
+      "flags": {},
+      "order": 3,
+      "inputs": [],
+      "bgcolor": "#653",
+      "outputs": [],
+      "properties": { "text": "" },
+      "widgets_values": [
+        "If you get an error in any of the nodes above make sure the files are in the correct directories.\n\nSee the top of the examples page for the links : https://comfyanonymous.github.io/ComfyUI_examples/flux/\n\nflux1-schnell.safetensors goes in: ComfyUI/models/unet/\n\nt5xxl_fp16.safetensors and clip_l.safetensors go in: ComfyUI/models/clip/\n\nae.safetensors goes in: ComfyUI/models/vae/\n\n\nTip: You can set the weight_dtype above to one of the fp8 types if you have memory issues."
+      ]
+    },
+    {
+      "id": 11,
+      "pos": [45.584651947021484, 229.13525390625],
+      "mode": 0,
+      "size": [315, 122],
+      "type": "DualCLIPLoader",
+      "flags": {},
+      "order": 4,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": [10],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "DualCLIPLoader" },
+      "widgets_values": [
+        "t5xxl_fp16.safetensors",
+        "clip_l.safetensors",
+        "flux",
+        "default"
+      ]
+    },
+    {
+      "id": 12,
+      "pos": [45.92215347290039, 95.6536865234375],
+      "mode": 0,
+      "size": [315, 82],
+      "type": "UNETLoader",
+      "color": "#223",
+      "flags": { "pinned": true },
+      "order": 5,
+      "inputs": [],
+      "bgcolor": "#335",
+      "outputs": [
+        {
+          "name": "MODEL",
+          "type": "MODEL",
+          "links": [38, 39],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "UNETLoader" },
+      "widgets_values": ["flux1-schnell.safetensors", "default"]
+    },
+    {
+      "id": 6,
+      "pos": [385.87054443359375, 216.75625610351562],
+      "mode": 0,
+      "size": [422.84503173828125, 164.31304931640625],
+      "type": "CLIPTextEncode",
+      "color": "#232",
+      "flags": {},
+      "order": 11,
+      "inputs": [
+        { "link": 10, "name": "clip", "type": "CLIP" },
+        {
+          "pos": [10, 36],
+          "link": 41,
+          "name": "text",
+          "type": "STRING",
+          "widget": { "name": "text" }
+        }
+      ],
+      "bgcolor": "#353",
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [40],
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPTextEncode" },
+      "widgets_values": [
+        "a bottle with a beautiful rainbow galaxy inside it on top of a wooden table in the middle of a modern kitchen beside a plate of vegetables and mushrooms and a wine glasse that contains a planet earth with a plate with a half eaten apple pie on it"
+      ]
+    },
+    {
+      "id": 10,
+      "pos": [42.45906066894531, 405.2187805175781],
+      "mode": 0,
+      "size": [315, 58],
+      "type": "VAELoader",
+      "flags": {},
+      "order": 6,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "VAE",
+          "type": "VAE",
+          "links": [12],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "VAELoader" },
+      "widgets_values": ["ae.sft"]
+    },
+    {
+      "id": 28,
+      "pos": [-620.3922119140625, 199.8013916015625],
+      "mode": 0,
+      "size": [400, 200],
+      "type": "ComfyUIDeployExternalText",
+      "flags": {},
+      "order": 7,
+      "inputs": [],
+      "outputs": [{ "name": "text", "type": "STRING", "links": [41] }],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalText" },
+      "widgets_values": [
+        "prompt",
+        "a bottle with a beautiful rainbow galaxy inside it on top of a wooden table in the middle of a modern kitchen beside a plate of vegetables and mushrooms and a wine glasse that contains a planet earth with a plate with a half eaten apple pie on it",
+        "Prompt",
+        "The prompt to generate an image from."
+      ]
+    },
+    {
+      "id": 29,
+      "pos": [-677.4290161132812, 597.3389282226562],
+      "mode": 0,
+      "size": [453.5999755859375, 200],
+      "type": "ComfyUIDeployExternalNumberInt",
+      "flags": {},
+      "order": 8,
+      "inputs": [],
+      "outputs": [
+        { "name": "value", "type": "INT", "links": [44], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["width", 1024, "Width", "The width of the image."]
+    },
+    {
+      "id": 30,
+      "pos": [-670.0703735351562, 848.3707885742188],
+      "mode": 0,
+      "size": [453.5999755859375, 200],
+      "type": "ComfyUIDeployExternalNumberInt",
+      "flags": {},
+      "order": 9,
+      "inputs": [],
+      "outputs": [
+        { "name": "value", "type": "INT", "links": [45], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["height", 1024, "Height", "The height of the image."]
+    }
+  ],
+  "config": {},
+  "groups": [
+    {
+      "id": 1,
+      "color": "#3f789e",
+      "flags": {},
+      "title": "Input",
+      "bounding": [
+        -652.184326171875, 99.11231994628906, 565.7923583984375,
+        362.8800354003906
+      ],
+      "font_size": 24
+    },
+    {
+      "id": 2,
+      "color": "#A88",
+      "flags": {},
+      "title": "Additional",
+      "bounding": [
+        -720.3274536132812, 508.1206970214844, 703.0422973632812,
+        576.5584716796875
+      ],
+      "font_size": 24
+    }
+  ],
+  "version": 0.4,
+  "last_link_id": 45,
+  "last_node_id": 30
+}

examples/hunyuan-video.json

@@ -0,0 +1,482 @@
+{
+  "extra": {
+    "ds": {
+      "scale": 0.6830134553650709,
+      "offset": [1030.9627343190857, 159.73178253107423]
+    },
+    "groupNodes": {},
+    "node_versions": {
+      "comfy-core": "0.3.12",
+      "comfyui-deploy": "b3df94d1affcf7ce05ee7eeda99989194bcd9159"
+    }
+  },
+  "links": [
+    [19, 16, 0, 13, 2, "SAMPLER"],
+    [20, 17, 0, 13, 3, "SIGMAS"],
+    [30, 22, 0, 13, 1, "GUIDER"],
+    [37, 25, 0, 13, 0, "NOISE"],
+    [129, 26, 0, 22, 1, "CONDITIONING"],
+    [175, 44, 0, 26, 0, "CONDITIONING"],
+    [180, 45, 0, 13, 4, "LATENT"],
+    [181, 13, 0, 8, 0, "LATENT"],
+    [190, 12, 0, 17, 0, "MODEL"],
+    [195, 67, 0, 22, 0, "MODEL"],
+    [205, 11, 0, 44, 0, "CLIP"],
+    [206, 10, 0, 8, 1, "VAE"],
+    [209, 12, 0, 67, 0, "MODEL"],
+    [210, 13, 0, 73, 0, "LATENT"],
+    [211, 10, 0, 73, 1, "VAE"],
+    [215, 73, 0, 75, 0, "IMAGE"],
+    [216, 78, 0, 44, 1, "STRING"],
+    [217, 79, 0, 45, 0, "INT"],
+    [218, 83, 0, 45, 1, "INT"]
+  ],
+  "nodes": [
+    {
+      "id": 16,
+      "pos": [484, 751],
+      "mode": 0,
+      "size": [315, 58],
+      "type": "KSamplerSelect",
+      "flags": {},
+      "order": 0,
+      "inputs": [],
+      "outputs": [
+        { "name": "SAMPLER", "type": "SAMPLER", "links": [19], "shape": 3 }
+      ],
+      "properties": { "Node name for S&R": "KSamplerSelect" },
+      "widgets_values": ["euler"]
+    },
+    {
+      "id": 17,
+      "pos": [478, 860],
+      "mode": 0,
+      "size": [315, 106],
+      "type": "BasicScheduler",
+      "flags": {},
+      "order": 10,
+      "inputs": [
+        { "link": 190, "name": "model", "type": "MODEL", "slot_index": 0 }
+      ],
+      "outputs": [
+        { "name": "SIGMAS", "type": "SIGMAS", "links": [20], "shape": 3 }
+      ],
+      "properties": { "Node name for S&R": "BasicScheduler" },
+      "widgets_values": ["simple", 20, 1]
+    },
+    {
+      "id": 26,
+      "pos": [520, 100],
+      "mode": 0,
+      "size": [317.4000244140625, 58],
+      "type": "FluxGuidance",
+      "color": "#233",
+      "flags": {},
+      "order": 14,
+      "inputs": [
+        { "link": 175, "name": "conditioning", "type": "CONDITIONING" }
+      ],
+      "bgcolor": "#355",
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [129],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "FluxGuidance" },
+      "widgets_values": [6]
+    },
+    {
+      "id": 45,
+      "pos": [475.540771484375, 432.673583984375],
+      "mode": 0,
+      "size": [315, 130],
+      "type": "EmptyHunyuanLatentVideo",
+      "flags": {},
+      "order": 13,
+      "inputs": [
+        {
+          "link": 217,
+          "name": "width",
+          "type": "INT",
+          "widget": { "name": "width" }
+        },
+        {
+          "link": 218,
+          "name": "height",
+          "type": "INT",
+          "widget": { "name": "height" }
+        }
+      ],
+      "outputs": [
+        { "name": "LATENT", "type": "LATENT", "links": [180], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "EmptyHunyuanLatentVideo" },
+      "widgets_values": [848, 480, 73, 1]
+    },
+    {
+      "id": 22,
+      "pos": [600, 0],
+      "mode": 0,
+      "size": [222.3482666015625, 46],
+      "type": "BasicGuider",
+      "flags": {},
+      "order": 15,
+      "inputs": [
+        { "link": 195, "name": "model", "type": "MODEL", "slot_index": 0 },
+        {
+          "link": 129,
+          "name": "conditioning",
+          "type": "CONDITIONING",
+          "slot_index": 1
+        }
+      ],
+      "outputs": [
+        {
+          "name": "GUIDER",
+          "type": "GUIDER",
+          "links": [30],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "BasicGuider" },
+      "widgets_values": []
+    },
+    {
+      "id": 67,
+      "pos": [360, 0],
+      "mode": 0,
+      "size": [210, 58],
+      "type": "ModelSamplingSD3",
+      "flags": {},
+      "order": 11,
+      "inputs": [{ "link": 209, "name": "model", "type": "MODEL" }],
+      "outputs": [
+        { "name": "MODEL", "type": "MODEL", "links": [195], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ModelSamplingSD3" },
+      "widgets_values": [7]
+    },
+    {
+      "id": 73,
+      "pos": [1150, 200],
+      "mode": 0,
+      "size": [210, 150],
+      "type": "VAEDecodeTiled",
+      "flags": {},
+      "order": 18,
+      "inputs": [
+        { "link": 210, "name": "samples", "type": "LATENT" },
+        { "link": 211, "name": "vae", "type": "VAE" }
+      ],
+      "outputs": [
+        { "name": "IMAGE", "type": "IMAGE", "links": [215], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "VAEDecodeTiled" },
+      "widgets_values": [256, 64, 64, 8]
+    },
+    {
+      "id": 8,
+      "pos": [1150, 90],
+      "mode": 2,
+      "size": [210, 46],
+      "type": "VAEDecode",
+      "flags": {},
+      "order": 17,
+      "inputs": [
+        { "link": 181, "name": "samples", "type": "LATENT" },
+        { "link": 206, "name": "vae", "type": "VAE" }
+      ],
+      "outputs": [
+        { "name": "IMAGE", "type": "IMAGE", "links": [], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "VAEDecode" },
+      "widgets_values": []
+    },
+    {
+      "id": 77,
+      "pos": [0, 0],
+      "mode": 0,
+      "size": [350, 110],
+      "type": "Note",
+      "color": "#432",
+      "flags": {},
+      "order": 1,
+      "inputs": [],
+      "bgcolor": "#653",
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Select a fp8 weight_dtype if you are running out of  memory."
+      ]
+    },
+    {
+      "id": 13,
+      "pos": [860, 200],
+      "mode": 0,
+      "size": [272.3617858886719, 124.53733825683594],
+      "type": "SamplerCustomAdvanced",
+      "flags": {},
+      "order": 16,
+      "inputs": [
+        { "link": 37, "name": "noise", "type": "NOISE", "slot_index": 0 },
+        { "link": 30, "name": "guider", "type": "GUIDER", "slot_index": 1 },
+        { "link": 19, "name": "sampler", "type": "SAMPLER", "slot_index": 2 },
+        { "link": 20, "name": "sigmas", "type": "SIGMAS", "slot_index": 3 },
+        {
+          "link": 180,
+          "name": "latent_image",
+          "type": "LATENT",
+          "slot_index": 4
+        }
+      ],
+      "outputs": [
+        {
+          "name": "output",
+          "type": "LATENT",
+          "links": [181, 210],
+          "shape": 3,
+          "slot_index": 0
+        },
+        {
+          "name": "denoised_output",
+          "type": "LATENT",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": { "Node name for S&R": "SamplerCustomAdvanced" },
+      "widgets_values": []
+    },
+    {
+      "id": 75,
+      "pos": [1410, 200],
+      "mode": 0,
+      "size": [315, 366],
+      "type": "SaveAnimatedWEBP",
+      "flags": {},
+      "order": 19,
+      "inputs": [{ "link": 215, "name": "images", "type": "IMAGE" }],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": ["ComfyUI", 24, false, 80, "default"]
+    },
+    {
+      "id": 25,
+      "pos": [479, 618],
+      "mode": 0,
+      "size": [315, 82],
+      "type": "RandomNoise",
+      "color": "#2a363b",
+      "flags": {},
+      "order": 2,
+      "inputs": [],
+      "bgcolor": "#3f5159",
+      "outputs": [
+        { "name": "NOISE", "type": "NOISE", "links": [37], "shape": 3 }
+      ],
+      "properties": { "Node name for S&R": "RandomNoise" },
+      "widgets_values": [1, "randomize"]
+    },
+    {
+      "id": 12,
+      "pos": [0, 150],
+      "mode": 0,
+      "size": [350, 82],
+      "type": "UNETLoader",
+      "color": "#223",
+      "flags": {},
+      "order": 3,
+      "inputs": [],
+      "bgcolor": "#335",
+      "outputs": [
+        {
+          "name": "MODEL",
+          "type": "MODEL",
+          "links": [190, 209],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "UNETLoader" },
+      "widgets_values": ["hunyuan_video_t2v_720p_bf16.safetensors", "default"]
+    },
+    {
+      "id": 10,
+      "pos": [0, 420],
+      "mode": 0,
+      "size": [350, 60],
+      "type": "VAELoader",
+      "flags": {},
+      "order": 4,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "VAE",
+          "type": "VAE",
+          "links": [206, 211],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "VAELoader" },
+      "widgets_values": ["hunyuan_video_vae_bf16.safetensors"]
+    },
+    {
+      "id": 11,
+      "pos": [0, 270],
+      "mode": 0,
+      "size": [350, 106],
+      "type": "DualCLIPLoader",
+      "flags": {},
+      "order": 5,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": [205],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "DualCLIPLoader" },
+      "widgets_values": [
+        "clip_l.safetensors",
+        "llava_llama3_fp8_scaled.safetensors",
+        "hunyuan_video",
+        "default"
+      ]
+    },
+    {
+      "id": 44,
+      "pos": [459.0518798828125, 226.60147094726562],
+      "mode": 0,
+      "size": [285.6000061035156, 54],
+      "type": "CLIPTextEncode",
+      "color": "#232",
+      "flags": {},
+      "order": 12,
+      "title": "CLIP Text Encode (Positive Prompt)",
+      "inputs": [
+        { "link": 205, "name": "clip", "type": "CLIP" },
+        {
+          "link": 216,
+          "name": "text",
+          "type": "STRING",
+          "widget": { "name": "text" }
+        }
+      ],
+      "bgcolor": "#353",
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [175],
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPTextEncode" },
+      "widgets_values": [
+        "anime style anime girl with massive fennec ears and one big fluffy tail, she has blonde hair long hair blue eyes wearing a pink sweater and a long blue skirt walking in a beautiful outdoor scenery with snow mountains in the background"
+      ]
+    },
+    {
+      "id": 83,
+      "pos": [-591.1870727539062, 751.6737670898438],
+      "mode": 0,
+      "size": [453.5999755859375, 200],
+      "type": "ComfyUIDeployExternalNumberInt",
+      "flags": {},
+      "order": 6,
+      "inputs": [],
+      "outputs": [
+        { "name": "value", "type": "INT", "links": [218], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["height", 480, "Height", "The height of the video."]
+    },
+    {
+      "id": 74,
+      "pos": [1151.89599609375, 402.439697265625],
+      "mode": 0,
+      "size": [210, 170],
+      "type": "Note",
+      "color": "#432",
+      "flags": {},
+      "order": 7,
+      "inputs": [],
+      "bgcolor": "#653",
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Use the tiled decode node by default because most people will need it.\n\nLower the tile_size and overlap if you run out of memory."
+      ]
+    },
+    {
+      "id": 78,
+      "pos": [-560.058837890625, 155.3986358642578],
+      "mode": 0,
+      "size": [400, 200],
+      "type": "ComfyUIDeployExternalText",
+      "flags": {},
+      "order": 8,
+      "inputs": [],
+      "outputs": [{ "name": "text", "type": "STRING", "links": [216] }],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalText" },
+      "widgets_values": [
+        "prompt",
+        "anime style anime girl with massive fennec ears and one big fluffy tail, she has blonde hair long hair blue eyes wearing a pink sweater and a long blue skirt walking in a beautiful outdoor scenery with snow mountains in the background",
+        "Prompt",
+        "The prompt to generate the video from."
+      ]
+    },
+    {
+      "id": 79,
+      "pos": [-588.2138061523438, 493.3861389160156],
+      "mode": 0,
+      "size": [453.5999755859375, 200],
+      "type": "ComfyUIDeployExternalNumberInt",
+      "flags": {},
+      "order": 9,
+      "inputs": [],
+      "outputs": [
+        { "name": "value", "type": "INT", "links": [217], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["width", 848, "Width", "The width of the video."]
+    }
+  ],
+  "config": {},
+  "groups": [
+    {
+      "id": 1,
+      "color": "#3f789e",
+      "flags": {},
+      "title": "Input",
+      "bounding": [
+        -662.9779052734375, 14.93773078918457, 575.2218627929688,
+        384.41424560546875
+      ],
+      "font_size": 24
+    },
+    {
+      "id": 2,
+      "color": "#b06634",
+      "flags": {},
+      "title": "Additional",
+      "bounding": [
+        -659.7621459960938, 414.3213195800781, 570.7182006835938,
+        594.72216796875
+      ],
+      "font_size": 24
+    }
+  ],
+  "version": 0.4,
+  "last_link_id": 218,
+  "last_node_id": 83
+}

examples/stable-diffusion-v15.json

@@ -0,0 +1,240 @@
+{
+  "extra": {
+    "ds": { "scale": 1, "offset": { "0": 0, "1": 0 } },
+    "node_versions": {
+      "comfy-core": "0.3.12",
+      "comfyui-deploy": "171a227856bd5f31e97828d89f83f3741004d05e"
+    }
+  },
+  "links": [
+    [1, 4, 0, 3, 0, "MODEL"],
+    [2, 5, 0, 3, 3, "LATENT"],
+    [3, 4, 1, 6, 0, "CLIP"],
+    [4, 6, 0, 3, 1, "CONDITIONING"],
+    [5, 4, 1, 7, 0, "CLIP"],
+    [6, 7, 0, 3, 2, "CONDITIONING"],
+    [7, 3, 0, 8, 0, "LATENT"],
+    [8, 4, 2, 8, 1, "VAE"],
+    [9, 8, 0, 9, 0, "IMAGE"],
+    [10, 12, 0, 6, 1, "STRING"],
+    [11, 13, 0, 7, 1, "STRING"]
+  ],
+  "nodes": [
+    {
+      "id": 5,
+      "pos": [473, 609],
+      "mode": 0,
+      "size": [315, 106],
+      "type": "EmptyLatentImage",
+      "flags": {},
+      "order": 0,
+      "inputs": [],
+      "outputs": [
+        { "name": "LATENT", "type": "LATENT", "links": [2], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "EmptyLatentImage" },
+      "widgets_values": [512, 512, 1]
+    },
+    {
+      "id": 3,
+      "pos": [863, 186],
+      "mode": 0,
+      "size": [315, 262],
+      "type": "KSampler",
+      "flags": {},
+      "order": 7,
+      "inputs": [
+        { "link": 1, "name": "model", "type": "MODEL" },
+        { "link": 4, "name": "positive", "type": "CONDITIONING" },
+        { "link": 6, "name": "negative", "type": "CONDITIONING" },
+        { "link": 2, "name": "latent_image", "type": "LATENT" }
+      ],
+      "outputs": [
+        { "name": "LATENT", "type": "LATENT", "links": [7], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "KSampler" },
+      "widgets_values": [
+        156680208700286,
+        "randomize",
+        20,
+        8,
+        "euler",
+        "normal",
+        1
+      ]
+    },
+    {
+      "id": 8,
+      "pos": [1209, 188],
+      "mode": 0,
+      "size": [210, 46],
+      "type": "VAEDecode",
+      "flags": {},
+      "order": 8,
+      "inputs": [
+        { "link": 7, "name": "samples", "type": "LATENT" },
+        { "link": 8, "name": "vae", "type": "VAE" }
+      ],
+      "outputs": [
+        { "name": "IMAGE", "type": "IMAGE", "links": [9], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "VAEDecode" },
+      "widgets_values": []
+    },
+    {
+      "id": 9,
+      "pos": [1451, 189],
+      "mode": 0,
+      "size": [210, 58],
+      "type": "SaveImage",
+      "flags": {},
+      "order": 9,
+      "inputs": [{ "link": 9, "name": "images", "type": "IMAGE" }],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": ["ComfyUI"]
+    },
+    {
+      "id": 4,
+      "pos": [26, 474],
+      "mode": 0,
+      "size": [315, 98],
+      "type": "CheckpointLoaderSimple",
+      "flags": {},
+      "order": 1,
+      "inputs": [],
+      "outputs": [
+        { "name": "MODEL", "type": "MODEL", "links": [1], "slot_index": 0 },
+        { "name": "CLIP", "type": "CLIP", "links": [3, 5], "slot_index": 1 },
+        { "name": "VAE", "type": "VAE", "links": [8], "slot_index": 2 }
+      ],
+      "properties": { "Node name for S&R": "CheckpointLoaderSimple" },
+      "widgets_values": ["v1-5-pruned-emaonly.ckpt"]
+    },
+    {
+      "id": 6,
+      "pos": [415, 186],
+      "mode": 0,
+      "size": [422.84503173828125, 164.31304931640625],
+      "type": "CLIPTextEncode",
+      "flags": {},
+      "order": 6,
+      "inputs": [
+        { "link": 3, "name": "clip", "type": "CLIP" },
+        {
+          "link": 10,
+          "name": "text",
+          "type": "STRING",
+          "widget": { "name": "text" }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [4],
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPTextEncode" },
+      "widgets_values": [
+        "beautiful scenery nature glass bottle landscape, , purple galaxy bottle,"
+      ]
+    },
+    {
+      "id": 7,
+      "pos": [413, 389],
+      "mode": 0,
+      "size": [425.27801513671875, 180.6060791015625],
+      "type": "CLIPTextEncode",
+      "flags": {},
+      "order": 5,
+      "inputs": [
+        { "link": 5, "name": "clip", "type": "CLIP" },
+        {
+          "link": 11,
+          "name": "text",
+          "type": "STRING",
+          "widget": { "name": "text" }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [6],
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPTextEncode" },
+      "widgets_values": ["text, watermark"]
+    },
+    {
+      "id": 13,
+      "pos": [-70, -60],
+      "mode": 0,
+      "size": [400, 200],
+      "type": "ComfyUIDeployExternalText",
+      "flags": {},
+      "order": 2,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "links": [11],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalText" },
+      "widgets_values": ["negative_prompt", "text, watermark", "", ""]
+    },
+    {
+      "id": 12,
+      "pos": [-72, 193],
+      "mode": 0,
+      "size": [400, 200],
+      "type": "ComfyUIDeployExternalText",
+      "flags": {},
+      "order": 3,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "links": [10],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalText" },
+      "widgets_values": [
+        "positive_prompt",
+        "beautiful scenery nature glass bottle landscape, , purple galaxy bottle,",
+        "",
+        ""
+      ]
+    },
+    {
+      "id": 14,
+      "pos": [419, 23],
+      "mode": 0,
+      "size": [210, 96],
+      "type": "ComfyDeploy",
+      "color": "#432",
+      "flags": {},
+      "order": 4,
+      "inputs": [],
+      "bgcolor": "#653",
+      "outputs": [],
+      "properties": { "version": "", "workflow_id": "", "workflow_name": "" },
+      "widgets_values": ["", "", "1"]
+    }
+  ],
+  "config": {},
+  "groups": [],
+  "version": 0.4,
+  "last_link_id": 11,
+  "last_node_id": 14
+}

examples/stable-diffusion-v35-large.json

@@ -0,0 +1,409 @@
+{
+  "extra": {
+    "ds": {
+      "scale": 0.620921323059155,
+      "offset": [1535.1422819333457, 285.0502099350181]
+    },
+    "node_versions": {
+      "comfy-core": "0.3.12",
+      "comfyui-deploy": "171a227856bd5f31e97828d89f83f3741004d05e"
+    }
+  },
+  "links": [
+    [7, 3, 0, 8, 0, "LATENT"],
+    [21, 16, 0, 3, 1, "CONDITIONING"],
+    [51, 8, 0, 9, 0, "IMAGE"],
+    [53, 4, 2, 8, 1, "VAE"],
+    [80, 40, 0, 3, 2, "CONDITIONING"],
+    [99, 4, 0, 3, 0, "MODEL"],
+    [100, 53, 0, 3, 3, "LATENT"],
+    [103, 43, 0, 16, 0, "CLIP"],
+    [104, 43, 0, 40, 0, "CLIP"],
+    [105, 54, 0, 16, 1, "STRING"],
+    [106, 55, 0, 40, 1, "STRING"],
+    [107, 56, 0, 53, 0, "INT"],
+    [108, 57, 0, 53, 1, "INT"]
+  ],
+  "nodes": [
+    {
+      "id": 8,
+      "pos": [1200, 96],
+      "mode": 0,
+      "size": [210, 46],
+      "type": "VAEDecode",
+      "flags": {},
+      "order": 14,
+      "inputs": [
+        { "link": 7, "name": "samples", "type": "LATENT" },
+        { "link": 53, "name": "vae", "type": "VAE", "slot_index": 1 }
+      ],
+      "outputs": [
+        { "name": "IMAGE", "type": "IMAGE", "links": [51], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "VAEDecode" },
+      "widgets_values": []
+    },
+    {
+      "id": 9,
+      "pos": [1440, 96],
+      "mode": 0,
+      "size": [952.5112915039062, 1007.9328002929688],
+      "type": "SaveImage",
+      "flags": {},
+      "order": 15,
+      "inputs": [
+        { "link": 51, "name": "images", "type": "IMAGE", "slot_index": 0 }
+      ],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": ["ComfyUI"]
+    },
+    {
+      "id": 53,
+      "pos": [480, 576],
+      "mode": 0,
+      "size": [315, 106],
+      "type": "EmptySD3LatentImage",
+      "flags": {},
+      "order": 10,
+      "inputs": [
+        {
+          "link": 107,
+          "name": "width",
+          "type": "INT",
+          "widget": { "name": "width" }
+        },
+        {
+          "link": 108,
+          "name": "height",
+          "type": "INT",
+          "widget": { "name": "height" }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": [100],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "EmptySD3LatentImage" },
+      "widgets_values": [1024, 1024, 1]
+    },
+    {
+      "id": 50,
+      "pos": [-384, 144],
+      "mode": 0,
+      "size": [223.34756469726562, 254.37765502929688],
+      "type": "Note",
+      "color": "#432",
+      "flags": {},
+      "order": 0,
+      "inputs": [],
+      "bgcolor": "#653",
+      "outputs": [],
+      "properties": { "text": "" },
+      "widgets_values": [
+        "SD3 supports different text encoder configurations, you can see how to load them here.\n\n\nMake sure to put these files:\nclip_g.safetensors\nclip_l.safetensors\nt5xxl_fp16.safetensors\n\n\nIn the ComfyUI/models/clip directory"
+      ]
+    },
+    {
+      "id": 41,
+      "pos": [-96, 0],
+      "mode": 0,
+      "size": [315, 82],
+      "type": "CLIPLoader",
+      "flags": {},
+      "order": 1,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": [],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPLoader" },
+      "widgets_values": ["t5xxl_fp16.safetensors", "sd3", "default"]
+    },
+    {
+      "id": 4,
+      "pos": [-96, 480],
+      "mode": 0,
+      "size": [384.75592041015625, 98],
+      "type": "CheckpointLoaderSimple",
+      "flags": {},
+      "order": 2,
+      "inputs": [],
+      "outputs": [
+        { "name": "MODEL", "type": "MODEL", "links": [99], "slot_index": 0 },
+        { "name": "CLIP", "type": "CLIP", "links": [], "slot_index": 1 },
+        { "name": "VAE", "type": "VAE", "links": [53], "slot_index": 2 }
+      ],
+      "properties": { "Node name for S&R": "CheckpointLoaderSimple" },
+      "widgets_values": ["sd3.5_large.safetensors"]
+    },
+    {
+      "id": 3,
+      "pos": [864, 96],
+      "mode": 0,
+      "size": [315, 474],
+      "type": "KSampler",
+      "flags": {},
+      "order": 13,
+      "inputs": [
+        { "link": 99, "name": "model", "type": "MODEL", "slot_index": 0 },
+        { "link": 21, "name": "positive", "type": "CONDITIONING" },
+        { "link": 80, "name": "negative", "type": "CONDITIONING" },
+        { "link": 100, "name": "latent_image", "type": "LATENT" }
+      ],
+      "outputs": [
+        { "name": "LATENT", "type": "LATENT", "links": [7], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "KSampler" },
+      "widgets_values": [
+        797639488625463,
+        "randomize",
+        20,
+        5.45,
+        "euler",
+        "sgm_uniform",
+        1
+      ]
+    },
+    {
+      "id": 51,
+      "pos": [-96, 624],
+      "mode": 0,
+      "size": [384, 192],
+      "type": "Note",
+      "color": "#432",
+      "flags": {},
+      "order": 3,
+      "inputs": [],
+      "bgcolor": "#653",
+      "outputs": [],
+      "properties": { "text": "" },
+      "widgets_values": [
+        "sd3.5_large.safetensors and sd3.5_medium.safetensors are files that do not contain any CLIP/text encoder weights so you need to load them separately.\n\nThey go in the ComfyUI/models/checkpoints directory."
+      ]
+    },
+    {
+      "id": 43,
+      "pos": [-96, 288],
+      "mode": 0,
+      "size": [315, 106],
+      "type": "TripleCLIPLoader",
+      "flags": {},
+      "order": 4,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": [103, 104],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "TripleCLIPLoader" },
+      "widgets_values": [
+        "clip_l.safetensors",
+        "clip_g.safetensors",
+        "t5xxl_fp16.safetensors"
+      ]
+    },
+    {
+      "id": 42,
+      "pos": [-96, 144],
+      "mode": 0,
+      "size": [315, 106],
+      "type": "DualCLIPLoader",
+      "flags": {},
+      "order": 5,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": [],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "DualCLIPLoader" },
+      "widgets_values": [
+        "clip_l.safetensors",
+        "clip_g.safetensors",
+        "sd3",
+        "default"
+      ]
+    },
+    {
+      "id": 40,
+      "pos": [399.0046081542969, 337.009765625],
+      "mode": 0,
+      "size": [397.45977783203125, 151.2898406982422],
+      "type": "CLIPTextEncode",
+      "color": "#322",
+      "flags": {},
+      "order": 11,
+      "title": "Negative Prompt",
+      "inputs": [
+        { "link": 104, "name": "clip", "type": "CLIP" },
+        {
+          "link": 106,
+          "name": "text",
+          "type": "STRING",
+          "widget": { "name": "text" }
+        }
+      ],
+      "bgcolor": "#533",
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [80],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPTextEncode" },
+      "widgets_values": [""]
+    },
+    {
+      "id": 16,
+      "pos": [398.5880432128906, 108.27188110351562],
+      "mode": 0,
+      "size": [397.21484375, 158.671875],
+      "type": "CLIPTextEncode",
+      "color": "#232",
+      "flags": {},
+      "order": 12,
+      "title": "Positive Prompt",
+      "inputs": [
+        { "link": 103, "name": "clip", "type": "CLIP" },
+        {
+          "link": 105,
+          "name": "text",
+          "type": "STRING",
+          "widget": { "name": "text" }
+        }
+      ],
+      "bgcolor": "#353",
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [21],
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPTextEncode" },
+      "widgets_values": [
+        "a bottle with a rainbow galaxy inside it on top of a wooden table on a snowy mountain top with the ocean and clouds in the background with a shot glass beside containing darkness beside a snow sculpture in the shape of a fox"
+      ]
+    },
+    {
+      "id": 57,
+      "pos": [-1015.1683349609375, 980.396240234375],
+      "mode": 0,
+      "size": [453.5999755859375, 200],
+      "type": "ComfyUIDeployExternalNumberInt",
+      "flags": {},
+      "order": 6,
+      "inputs": [],
+      "outputs": [
+        { "name": "value", "type": "INT", "links": [108], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["height", 1024, "Height", "The height of the image. "]
+    },
+    {
+      "id": 56,
+      "pos": [-1014.532470703125, 732.8568725585938],
+      "mode": 0,
+      "size": [453.5999755859375, 200],
+      "type": "ComfyUIDeployExternalNumberInt",
+      "flags": {},
+      "order": 7,
+      "inputs": [],
+      "outputs": [
+        { "name": "value", "type": "INT", "links": [107], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["width", 1024, "Width", "The width of the image. "]
+    },
+    {
+      "id": 55,
+      "pos": [-1010.8035278320312, 487.404052734375],
+      "mode": 0,
+      "size": [400, 200],
+      "type": "ComfyUIDeployExternalText",
+      "flags": {},
+      "order": 8,
+      "inputs": [],
+      "outputs": [{ "name": "text", "type": "STRING", "links": [106] }],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalText" },
+      "widgets_values": ["negative_prompt", "", "Negative Prompt", ""]
+    },
+    {
+      "id": 54,
+      "pos": [-1059.1072998046875, 127.12823486328125],
+      "mode": 0,
+      "size": [400, 200],
+      "type": "ComfyUIDeployExternalText",
+      "flags": {},
+      "order": 9,
+      "inputs": [],
+      "outputs": [{ "name": "text", "type": "STRING", "links": [105] }],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalText" },
+      "widgets_values": [
+        "prompt",
+        "a bottle with a rainbow galaxy inside it on top of a wooden table on a snowy mountain top with the ocean and clouds in the background with a shot glass beside containing darkness beside a snow sculpture in the shape of a fox",
+        "Prompt",
+        "The prompt to generate an image from."
+      ]
+    }
+  ],
+  "config": {},
+  "groups": [
+    {
+      "id": 1,
+      "color": "#3f789e",
+      "flags": {},
+      "title": "Different Text Encoder Configurations",
+      "bounding": [-144, -96, 480, 528],
+      "font_size": 24
+    },
+    {
+      "id": 2,
+      "color": "#b06634",
+      "flags": {},
+      "title": "Additional",
+      "bounding": [
+        -1194.5233154296875, 388.3871154785156, 722.5393676757812,
+        824.6746215820312
+      ],
+      "font_size": 24
+    },
+    {
+      "id": 3,
+      "color": "#3f789e",
+      "flags": {},
+      "title": "Input",
+      "bounding": [
+        -1148.487060546875, 30.449382781982422, 552.3358764648438,
+        329.3829040527344
+      ],
+      "font_size": 24
+    }
+  ],
+  "version": 0.4,
+  "last_link_id": 108,
+  "last_node_id": 57
+}

examples/wan-21-i2v-480p.json

@@ -0,0 +1,452 @@
+{
+  "extra": {
+    "ds": {
+      "scale": 0.6934334949441662,
+      "offset": [276.7941771713029, -7.923387380923855]
+    },
+    "node_versions": {
+      "comfy-core": "0.3.18",
+      "comfyui-deploy": "b3df94d1affcf7ce05ee7eeda99989194bcd9159"
+    }
+  },
+  "links": [
+    [35, 3, 0, 8, 0, "LATENT"],
+    [56, 8, 0, 28, 0, "IMAGE"],
+    [74, 38, 0, 6, 0, "CLIP"],
+    [75, 38, 0, 7, 0, "CLIP"],
+    [76, 39, 0, 8, 1, "VAE"],
+    [93, 8, 0, 47, 0, "IMAGE"],
+    [94, 49, 0, 51, 0, "CLIP_VISION"],
+    [97, 6, 0, 50, 0, "CONDITIONING"],
+    [98, 7, 0, 50, 1, "CONDITIONING"],
+    [99, 39, 0, 50, 2, "VAE"],
+    [101, 50, 0, 3, 1, "CONDITIONING"],
+    [102, 50, 1, 3, 2, "CONDITIONING"],
+    [103, 50, 2, 3, 3, "LATENT"],
+    [107, 51, 0, 50, 3, "CLIP_VISION_OUTPUT"],
+    [110, 37, 0, 54, 0, "MODEL"],
+    [111, 54, 0, 3, 0, "MODEL"],
+    [112, 55, 0, 6, 1, "STRING"],
+    [113, 56, 0, 7, 1, "STRING"],
+    [115, 57, 0, 50, 4, "IMAGE"],
+    [116, 57, 0, 51, 1, "IMAGE"],
+    [117, 58, 0, 50, 5, "INT"],
+    [118, 59, 0, 50, 6, "INT"]
+  ],
+  "nodes": [
+    {
+      "id": 8,
+      "pos": [1210, 190],
+      "mode": 0,
+      "size": [210, 46],
+      "type": "VAEDecode",
+      "flags": {},
+      "order": 15,
+      "inputs": [
+        { "link": 35, "name": "samples", "type": "LATENT" },
+        { "link": 76, "name": "vae", "type": "VAE" }
+      ],
+      "outputs": [
+        { "name": "IMAGE", "type": "IMAGE", "links": [56, 93], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "VAEDecode" },
+      "widgets_values": []
+    },
+    {
+      "id": 39,
+      "pos": [866.3932495117188, 499.18597412109375],
+      "mode": 0,
+      "size": [306.36004638671875, 58],
+      "type": "VAELoader",
+      "flags": {},
+      "order": 0,
+      "inputs": [],
+      "outputs": [
+        { "name": "VAE", "type": "VAE", "links": [76, 99], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "VAELoader" },
+      "widgets_values": ["wan_2.1_vae.safetensors"]
+    },
+    {
+      "id": 28,
+      "pos": [1460, 190],
+      "mode": 0,
+      "size": [870.8511352539062, 643.7430419921875],
+      "type": "SaveAnimatedWEBP",
+      "flags": {},
+      "order": 16,
+      "inputs": [{ "link": 56, "name": "images", "type": "IMAGE" }],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": ["ComfyUI", 16, false, 90, "default", ""]
+    },
+    {
+      "id": 47,
+      "pos": [2367.213134765625, 193.6114959716797],
+      "mode": 4,
+      "size": [315, 130],
+      "type": "SaveWEBM",
+      "flags": {},
+      "order": 17,
+      "inputs": [{ "link": 93, "name": "images", "type": "IMAGE" }],
+      "outputs": [],
+      "properties": { "Node name for S&R": "SaveWEBM" },
+      "widgets_values": ["ComfyUI", "vp9", 24, 32]
+    },
+    {
+      "id": 50,
+      "pos": [673.0507202148438, 627.272705078125],
+      "mode": 0,
+      "size": [342.5999755859375, 250],
+      "type": "WanImageToVideo",
+      "flags": {},
+      "order": 13,
+      "inputs": [
+        { "link": 97, "name": "positive", "type": "CONDITIONING" },
+        { "link": 98, "name": "negative", "type": "CONDITIONING" },
+        { "link": 99, "name": "vae", "type": "VAE" },
+        {
+          "link": 107,
+          "name": "clip_vision_output",
+          "type": "CLIP_VISION_OUTPUT",
+          "shape": 7
+        },
+        { "link": 115, "name": "start_image", "type": "IMAGE", "shape": 7 },
+        {
+          "pos": [10, 116],
+          "link": 117,
+          "name": "width",
+          "type": "INT",
+          "widget": { "name": "width" }
+        },
+        {
+          "pos": [10, 140],
+          "link": 118,
+          "name": "height",
+          "type": "INT",
+          "widget": { "name": "height" }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "positive",
+          "type": "CONDITIONING",
+          "links": [101],
+          "slot_index": 0
+        },
+        {
+          "name": "negative",
+          "type": "CONDITIONING",
+          "links": [102],
+          "slot_index": 1
+        },
+        { "name": "latent", "type": "LATENT", "links": [103], "slot_index": 2 }
+      ],
+      "properties": { "Node name for S&R": "WanImageToVideo" },
+      "widgets_values": [512, 512, 33, 1]
+    },
+    {
+      "id": 3,
+      "pos": [863, 187],
+      "mode": 0,
+      "size": [315, 262],
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+        { "link": 102, "name": "negative", "type": "CONDITIONING" },
+        { "link": 103, "name": "latent_image", "type": "LATENT" }
+      ],
+      "outputs": [
+        { "name": "LATENT", "type": "LATENT", "links": [35], "slot_index": 0 }
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+        { "link": 116, "name": "image", "type": "IMAGE" }
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+          "name": "CLIP_VISION_OUTPUT",
+          "type": "CLIP_VISION_OUTPUT",
+          "links": [107],
+          "slot_index": 0
+        }
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+      "title": "CLIP Text Encode (Positive Prompt)",
+      "inputs": [
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+        {
+          "pos": [10, 36],
+          "link": 112,
+          "name": "text",
+          "type": "STRING",
+          "widget": { "name": "text" }
+        }
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+      "bgcolor": "#353",
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [97],
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPTextEncode" },
+      "widgets_values": [
+        "a cute anime girl with massive fennec ears and a big fluffy tail wearing a maid outfit turning around"
+      ]
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+      "outputs": [{ "name": "text", "type": "STRING", "links": [112] }],
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+      "widgets_values": [
+        "positive_prompt",
+        "a cute anime girl with massive fennec ears and a big fluffy tail wearing a maid outfit turning around",
+        "Prompt",
+        "The text prompt to guide video generation."
+      ]
+    },
+    {
+      "id": 57,
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+      "flags": {},
+      "order": 2,
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+        { "link": null, "name": "default_value", "type": "IMAGE", "shape": 7 }
+      ],
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+      "properties": { "Node name for S&R": "ComfyUIDeployExternalImage" },
+      "widgets_values": [
+        "image_url",
+        "Image Url",
+        "URL of the input image.",
+        "https://comfy-deploy-output.s3.us-east-2.amazonaws.com/assets/img_GZMJYXDnLbYjWybu.png",
+        ""
+      ]
+    },
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+        "Negative Prompt",
+        "The negative prompt to use. Use it to address details that you don't want in the video. This could be colors, objects, scenery and even the small details (e.g. moustache, blurry, low resolution). "
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+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["width", 512, "Width", "The width of the video. "]
+    },
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+      "widgets_values": ["height", 512, "Height", "The Height of the video."]
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+      "properties": { "Node name for S&R": "UNETLoader" },
+      "widgets_values": ["wan2.1_i2v_480p_14B_bf16.safetensors", "default"]
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+      "inputs": [],
+      "outputs": [
+        { "name": "CLIP", "type": "CLIP", "links": [74, 75], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "CLIPLoader" },
+      "widgets_values": [
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+      "outputs": [
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+      "properties": { "Node name for S&R": "CLIPVisionLoader" },
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+          "name": "text",
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+      "bgcolor": "#533",
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+          "type": "CONDITIONING",
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+  "last_node_id": 59
+}

examples/wav-21-i2v-720p.json

@@ -0,0 +1,452 @@
+{
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+          "links": [5],
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+      ],
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+      "properties": { "Node name for S&R": "ComfyUIDeployExternalImage" },
+      "widgets_values": [
+        "image_url",
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+        "URL of the input image.",
+        "https://comfy-deploy-output.s3.us-east-2.amazonaws.com/assets/img_GZMJYXDnLbYjWybu.png",
+        ""
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+        "Negative Prompt",
+        "The negative prompt to use. Use it to address details that you don't want in the video. This could be colors, objects, scenery and even the small details (e.g. moustache, blurry, low resolution). "
+      ]
+    },
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+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["width", 512, "Width", "The width of the video. "]
+    },
+    {
+      "id": 14,
+      "pos": [-51.8943977355957, 1973.8795166015625],
+      "mode": 0,
+      "size": [453.5999755859375, 200],
+      "type": "ComfyUIDeployExternalNumberInt",
+      "flags": {},
+      "order": 4,
+      "inputs": [],
+      "outputs": [
+        { "name": "value", "type": "INT", "links": [11], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["height", 512, "Height", "The Height of the video."]
+    },
+    {
+      "id": 16,
+      "pos": [610.257080078125, 743.389404296875],
+      "mode": 0,
+      "size": [390, 98],
+      "type": "CLIPLoader",
+      "flags": {},
+      "order": 5,
+      "inputs": [],
+      "outputs": [
+        { "name": "CLIP", "type": "CLIP", "links": [19, 21], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "CLIPLoader" },
+      "widgets_values": [
+        "umt5_xxl_fp8_e4m3fn_scaled.safetensors",
+        "wan",
+        "default"
+      ]
+    },
+    {
+      "id": 17,
+      "pos": [630.5606079101562, 1152.8475341796875],
+      "mode": 0,
+      "size": [315, 58],
+      "type": "CLIPVisionLoader",
+      "flags": {},
+      "order": 6,
+      "inputs": [],
+      "outputs": [
+        {
+          "name": "CLIP_VISION",
+          "type": "CLIP_VISION",
+          "links": [16],
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPVisionLoader" },
+      "widgets_values": ["clip_vision_h.safetensors"]
+    },
+    {
+      "id": 18,
+      "pos": [1028.169921875, 906.5068969726562],
+      "mode": 0,
+      "size": [425.27801513671875, 180.6060791015625],
+      "type": "CLIPTextEncode",
+      "color": "#322",
+      "flags": {},
+      "order": 9,
+      "title": "CLIP Text Encode (Negative Prompt)",
+      "inputs": [
+        { "link": 21, "name": "clip", "type": "CLIP" },
+        {
+          "pos": [10, 36],
+          "link": 22,
+          "name": "text",
+          "type": "STRING",
+          "widget": { "name": "text" }
+        }
+      ],
+      "bgcolor": "#533",
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [6],
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPTextEncode" },
+      "widgets_values": [
+        "色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走"
+      ]
+    },
+    {
+      "id": 15,
+      "pos": [610.6187744140625, 594.3209838867188],
+      "mode": 0,
+      "size": [346.7470703125, 82],
+      "type": "UNETLoader",
+      "flags": {},
+      "order": 7,
+      "inputs": [],
+      "outputs": [
+        { "name": "MODEL", "type": "MODEL", "links": [18], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "UNETLoader" },
+      "widgets_values": ["wan2.1_i2v_720p_14B_bf16.safetensors", "default"]
+    },
+    {
+      "id": 10,
+      "pos": [-60.696964263916016, 649.5515747070312],
+      "mode": 0,
+      "size": [400, 200],
+      "type": "ComfyUIDeployExternalText",
+      "flags": {},
+      "order": 8,
+      "inputs": [],
+      "outputs": [{ "name": "text", "type": "STRING", "links": [20] }],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalText" },
+      "widgets_values": [
+        "positive_prompt",
+        "a cute anime girl with massive fennec ears and a big fluffy tail wearing a maid outfit running towards front happily",
+        "Prompt",
+        "The text prompt to guide video generation."
+      ]
+    }
+  ],
+  "config": {},
+  "groups": [
+    {
+      "id": 1,
+      "color": "#3f789e",
+      "flags": {},
+      "title": "Input",
+      "bounding": [
+        -94.30522155761719, 560.1735229492188, 617.7969360351562,
+        761.303955078125
+      ],
+      "font_size": 24
+    },
+    {
+      "id": 2,
+      "color": "#b06634",
+      "flags": {},
+      "title": "Additional",
+      "bounding": [
+        -89.63090515136719, 1373.9351806640625, 625.998779296875,
+        845.0675048828125
+      ],
+      "font_size": 24
+    }
+  ],
+  "version": 0.4,
+  "last_link_id": 22,
+  "last_node_id": 18
+}

examples/wav-21-t2v-13b.json

@@ -0,0 +1,359 @@
+{
+  "extra": {
+    "ds": {
+      "scale": 0.8390545288824369,
+      "offset": [814.3725295729478, -347.90757575249455]
+    },
+    "node_versions": {
+      "comfy-core": "0.3.18",
+      "comfyui-deploy": "b3df94d1affcf7ce05ee7eeda99989194bcd9159"
+    }
+  },
+  "links": [
+    [35, 3, 0, 8, 0, "LATENT"],
+    [46, 6, 0, 3, 1, "CONDITIONING"],
+    [52, 7, 0, 3, 2, "CONDITIONING"],
+    [56, 8, 0, 28, 0, "IMAGE"],
+    [74, 38, 0, 6, 0, "CLIP"],
+    [75, 38, 0, 7, 0, "CLIP"],
+    [76, 39, 0, 8, 1, "VAE"],
+    [91, 40, 0, 3, 3, "LATENT"],
+    [93, 8, 0, 47, 0, "IMAGE"],
+    [94, 37, 0, 48, 0, "MODEL"],
+    [95, 48, 0, 3, 0, "MODEL"],
+    [96, 49, 0, 6, 1, "STRING"],
+    [97, 50, 0, 7, 1, "STRING"],
+    [99, 52, 0, 40, 1, "INT"],
+    [100, 51, 0, 40, 0, "INT"]
+  ],
+  "nodes": [
+    {
+      "id": 8,
+      "pos": [1210, 190],
+      "mode": 0,
+      "size": [210, 46],
+      "type": "VAEDecode",
+      "flags": {},
+      "order": 12,
+      "inputs": [
+        { "link": 35, "name": "samples", "type": "LATENT" },
+        { "link": 76, "name": "vae", "type": "VAE" }
+      ],
+      "outputs": [
+        { "name": "IMAGE", "type": "IMAGE", "links": [56, 93], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "VAEDecode" },
+      "widgets_values": []
+    },
+    {
+      "id": 39,
+      "pos": [866.3932495117188, 499.18597412109375],
+      "mode": 0,
+      "size": [306.36004638671875, 58],
+      "type": "VAELoader",
+      "flags": {},
+      "order": 0,
+      "inputs": [],
+      "outputs": [
+        { "name": "VAE", "type": "VAE", "links": [76], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "VAELoader" },
+      "widgets_values": ["wan_2.1_vae.safetensors"]
+    },
+    {
+      "id": 47,
+      "pos": [2367.213134765625, 193.6114959716797],
+      "mode": 4,
+      "size": [315, 130],
+      "type": "SaveWEBM",
+      "flags": {},
+      "order": 14,
+      "inputs": [{ "link": 93, "name": "images", "type": "IMAGE" }],
+      "outputs": [],
+      "properties": { "Node name for S&R": "SaveWEBM" },
+      "widgets_values": ["ComfyUI", "vp9", 24, 32]
+    },
+    {
+      "id": 3,
+      "pos": [863, 187],
+      "mode": 0,
+      "size": [315, 262],
+      "type": "KSampler",
+      "flags": {},
+      "order": 11,
+      "inputs": [
+        { "link": 95, "name": "model", "type": "MODEL" },
+        { "link": 46, "name": "positive", "type": "CONDITIONING" },
+        { "link": 52, "name": "negative", "type": "CONDITIONING" },
+        { "link": 91, "name": "latent_image", "type": "LATENT" }
+      ],
+      "outputs": [
+        { "name": "LATENT", "type": "LATENT", "links": [35], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "KSampler" },
+      "widgets_values": [
+        577746309562741,
+        "randomize",
+        30,
+        6,
+        "uni_pc",
+        "simple",
+        1
+      ]
+    },
+    {
+      "id": 48,
+      "pos": [440, 50],
+      "mode": 0,
+      "size": [210, 58],
+      "type": "ModelSamplingSD3",
+      "flags": {},
+      "order": 7,
+      "inputs": [{ "link": 94, "name": "model", "type": "MODEL" }],
+      "outputs": [
+        { "name": "MODEL", "type": "MODEL", "links": [95], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ModelSamplingSD3" },
+      "widgets_values": [8]
+    },
+    {
+      "id": 37,
+      "pos": [20, 40],
+      "mode": 0,
+      "size": [346.7470703125, 82],
+      "type": "UNETLoader",
+      "flags": {},
+      "order": 1,
+      "inputs": [],
+      "outputs": [
+        { "name": "MODEL", "type": "MODEL", "links": [94], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "UNETLoader" },
+      "widgets_values": ["wan2.1_t2v_1.3B_fp16.safetensors", "default"]
+    },
+    {
+      "id": 6,
+      "pos": [415, 186],
+      "mode": 0,
+      "size": [422.84503173828125, 164.31304931640625],
+      "type": "CLIPTextEncode",
+      "color": "#232",
+      "flags": {},
+      "order": 8,
+      "title": "CLIP Text Encode (Positive Prompt)",
+      "inputs": [
+        { "link": 74, "name": "clip", "type": "CLIP" },
+        {
+          "pos": [10, 36],
+          "link": 96,
+          "name": "text",
+          "type": "STRING",
+          "widget": { "name": "text" }
+        }
+      ],
+      "bgcolor": "#353",
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [46],
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPTextEncode" },
+      "widgets_values": [
+        "a fox moving quickly in a beautiful winter scenery nature trees mountains daytime tracking camera"
+      ]
+    },
+    {
+      "id": 7,
+      "pos": [413, 389],
+      "mode": 0,
+      "size": [425.27801513671875, 180.6060791015625],
+      "type": "CLIPTextEncode",
+      "color": "#322",
+      "flags": {},
+      "order": 9,
+      "title": "CLIP Text Encode (Negative Prompt)",
+      "inputs": [
+        { "link": 75, "name": "clip", "type": "CLIP" },
+        {
+          "pos": [10, 36],
+          "link": 97,
+          "name": "text",
+          "type": "STRING",
+          "widget": { "name": "text" }
+        }
+      ],
+      "bgcolor": "#533",
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [52],
+          "slot_index": 0
+        }
+      ],
+      "properties": { "Node name for S&R": "CLIPTextEncode" },
+      "widgets_values": [
+        "色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走"
+      ]
+    },
+    {
+      "id": 38,
+      "pos": [-10.047812461853027, 187.37384033203125],
+      "mode": 0,
+      "size": [390, 98],
+      "type": "CLIPLoader",
+      "flags": {},
+      "order": 2,
+      "inputs": [],
+      "outputs": [
+        { "name": "CLIP", "type": "CLIP", "links": [74, 75], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "CLIPLoader" },
+      "widgets_values": [
+        "umt5_xxl_fp8_e4m3fn_scaled.safetensors",
+        "wan",
+        "default"
+      ]
+    },
+    {
+      "id": 49,
+      "pos": [-535.2967529296875, 342.3277587890625],
+      "mode": 0,
+      "size": [400, 200],
+      "type": "ComfyUIDeployExternalText",
+      "flags": {},
+      "order": 3,
+      "inputs": [],
+      "outputs": [{ "name": "text", "type": "STRING", "links": [96] }],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalText" },
+      "widgets_values": [
+        "positive_prompt",
+        "a fox moving quickly in a beautiful winter scenery nature trees mountains daytime tracking camera",
+        "Prompt",
+        "The text prompt to guide video generation. "
+      ]
+    },
+    {
+      "id": 50,
+      "pos": [-526.2716064453125, 703.8343505859375],
+      "mode": 0,
+      "size": [400, 200],
+      "type": "ComfyUIDeployExternalText",
+      "flags": {},
+      "order": 4,
+      "inputs": [],
+      "outputs": [{ "name": "text", "type": "STRING", "links": [97] }],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalText" },
+      "widgets_values": [
+        "negative_prompt",
+        "色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走",
+        "Negative Prompt",
+        "The negative prompt to use. Use it to address details that you don't want in the image. This could be colors, objects, scenery and even the small details (e.g. moustache, blurry, low resolution). "
+      ]
+    },
+    {
+      "id": 40,
+      "pos": [516.926513671875, 619.59716796875],
+      "mode": 0,
+      "size": [315, 150],
+      "type": "EmptyHunyuanLatentVideo",
+      "flags": {},
+      "order": 10,
+      "inputs": [
+        {
+          "pos": [10, 36],
+          "link": 100,
+          "name": "width",
+          "type": "INT",
+          "widget": { "name": "width" }
+        },
+        {
+          "pos": [10, 60],
+          "link": 99,
+          "name": "height",
+          "type": "INT",
+          "widget": { "name": "height" }
+        }
+      ],
+      "outputs": [
+        { "name": "LATENT", "type": "LATENT", "links": [91], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "EmptyHunyuanLatentVideo" },
+      "widgets_values": [832, 480, 33, 1]
+    },
+    {
+      "id": 28,
+      "pos": [1460, 190],
+      "mode": 0,
+      "size": [870.8511352539062, 643.7430419921875],
+      "type": "SaveAnimatedWEBP",
+      "flags": {},
+      "order": 13,
+      "inputs": [{ "link": 56, "name": "images", "type": "IMAGE" }],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": ["ComfyUI", 16, false, 90, "default"]
+    },
+    {
+      "id": 51,
+      "pos": [-522.7415161132812, 959.3386840820312],
+      "mode": 0,
+      "size": [453.5999755859375, 200],
+      "type": "ComfyUIDeployExternalNumberInt",
+      "flags": {},
+      "order": 5,
+      "inputs": [],
+      "outputs": [
+        { "name": "value", "type": "INT", "links": [100], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["width", 832, "Width", "The Width of the Video. "]
+    },
+    {
+      "id": 52,
+      "pos": [-518.9917602539062, 1207.9444580078125],
+      "mode": 0,
+      "size": [453.5999755859375, 200],
+      "type": "ComfyUIDeployExternalNumberInt",
+      "flags": {},
+      "order": 6,
+      "inputs": [],
+      "outputs": [
+        { "name": "value", "type": "INT", "links": [99], "slot_index": 0 }
+      ],
+      "properties": { "Node name for S&R": "ComfyUIDeployExternalNumberInt" },
+      "widgets_values": ["height", 480, "Height", "The Height of the Video. "]
+    }
+  ],
+  "config": {},
+  "groups": [
+    {
+      "id": 1,
+      "color": "#3f789e",
+      "flags": {},
+      "title": "Inputs",
+      "bounding": [
+        -560.9110717773438, 255.1485595703125, 500.94989013671875,
+        333.4786682128906
+      ],
+      "font_size": 24
+    },
+    {
+      "id": 2,
+      "color": "#b06634",
+      "flags": {},
+      "title": "Additional",
+      "bounding": [
+        -556.5305786132812, 619.87548828125, 761.2673950195312,
+        811.6837768554688
+      ],
+      "font_size": 24
+    }
+  ],
+  "version": 0.4,
+  "last_link_id": 100,
+  "last_node_id": 52
+}

globals.py

@@ -0,0 +1,137 @@
+import struct
+from enum import Enum
+import aiohttp
+from typing import List, Union, Any, Optional
+from PIL import Image, ImageOps
+from io import BytesIO
+from pydantic import BaseModel as PydanticBaseModel
+
+
+class BaseModel(PydanticBaseModel):
+    class Config:
+        arbitrary_types_allowed = True
+
+
+class Status(Enum):
+    NOT_STARTED = "not-started"
+    RUNNING = "running"
+    SUCCESS = "success"
+    FAILED = "failed"
+    UPLOADING = "uploading"
+    CANCELLED = "cancelled"
+
+
+class StreamingPrompt(BaseModel):
+    workflow_api: Any
+    auth_token: str
+    inputs: dict[str, Union[str, bytes, Image.Image]]
+    running_prompt_ids: set[str] = set()
+    status_endpoint: Optional[str]
+    file_upload_endpoint: Optional[str]
+    workflow: Any
+    gpu_event_id: Optional[str] = None
+
+
+class SimplePrompt(BaseModel):
+    status_endpoint: Optional[str]
+    file_upload_endpoint: Optional[str]
+
+    token: Optional[str]
+
+    workflow_api: dict
+    status: Status = Status.NOT_STARTED
+    progress: set = set()
+    last_updated_node: Optional[str] = None
+    uploading_nodes: set = set()
+    done: bool = False
+    is_realtime: bool = False
+    start_time: Optional[float] = None
+    gpu_event_id: Optional[str] = None
+
+
+sockets = dict()
+prompt_metadata: dict[str, SimplePrompt] = {}
+streaming_prompt_metadata: dict[str, StreamingPrompt] = {}
+
+
+class BinaryEventTypes:
+    PREVIEW_IMAGE = 1
+    UNENCODED_PREVIEW_IMAGE = 2
+
+
+max_output_id_length = 24
+
+
+async def send_image(image_data, sid=None, output_id: str = None):
+    max_length = max_output_id_length
+    output_id = output_id[:max_length]
+    padded_output_id = output_id.ljust(max_length, "\x00")
+    encoded_output_id = padded_output_id.encode("ascii", "replace")
+
+    image_type = image_data[0]
+    image = image_data[1]
+    max_size = image_data[2]
+    quality = image_data[3]
+    if max_size is not None:
+        if hasattr(Image, "Resampling"):
+            resampling = Image.Resampling.BILINEAR
+        else:
+            resampling = Image.ANTIALIAS
+
+        image = ImageOps.contain(image, (max_size, max_size), resampling)
+    type_num = 1
+    if image_type == "JPEG":
+        type_num = 1
+    elif image_type == "PNG":
+        type_num = 2
+    elif image_type == "WEBP":
+        type_num = 3
+
+    bytesIO = BytesIO()
+    header = struct.pack(">I", type_num)
+    # 4 bytes for the type
+    bytesIO.write(header)
+    # 10 bytes for the output_id
+    position_before = bytesIO.tell()
+    bytesIO.write(encoded_output_id)
+    position_after = bytesIO.tell()
+    bytes_written = position_after - position_before
+    print(f"Bytes written: {bytes_written}")
+
+    image.save(bytesIO, format=image_type, quality=quality, compress_level=1)
+    preview_bytes = bytesIO.getvalue()
+    await send_bytes(BinaryEventTypes.PREVIEW_IMAGE, preview_bytes, sid=sid)
+
+
+async def send_socket_catch_exception(function, message):
+    try:
+        await function(message)
+    except (
+        aiohttp.ClientError,
+        aiohttp.ClientPayloadError,
+        ConnectionResetError,
+    ) as err:
+        print("send error:", err)
+
+
+def encode_bytes(event, data):
+    if not isinstance(event, int):
+        raise RuntimeError(f"Binary event types must be integers, got {event}")
+
+    packed = struct.pack(">I", event)
+    message = bytearray(packed)
+    message.extend(data)
+    return message
+
+
+async def send_bytes(event, data, sid=None):
+    message = encode_bytes(event, data)
+
+    print("sending image to ", event, sid)
+
+    if sid is None:
+        _sockets = list(sockets.values())
+        for ws in _sockets:
+            await send_socket_catch_exception(ws.send_bytes, message)
+    elif sid in sockets:
+        await send_socket_catch_exception(sockets[sid].send_bytes, message)

prestartup_script.py

@@ -58,6 +58,9 @@ if cd_enable_log:
    print("** Comfy Deploy logging enabled")
    setup() 
 
+
+# Store the original working directory
+original_cwd = os.getcwd()
 try:
     # Get the absolute path of the script's directory
     script_dir = os.path.dirname(os.path.abspath(__file__))
@@ -66,4 +69,7 @@ try:
     current_git_commit = subprocess.check_output(['git', 'rev-parse', 'HEAD']).decode('utf-8').strip()
     print(f"** Comfy Deploy Revision: {current_git_commit}")
 except Exception as e:
-    print(f"** Comfy Deploy failed to get current git commit: {str(e)}")
+    print(f"** Comfy Deploy failed to get current git commit: {str(e)}")
+finally:
+    # Change back to the original directory
+    os.chdir(original_cwd)

pyproject.toml

@@ -0,0 +1,15 @@
+[project]
+name = "comfyui-deploy"
+description = "Open source comfyui deployment platform, a vercel for generative workflow infra."
+version = "2.3.3"
+license = { file = "LICENSE" }
+dependencies = ["aiofiles", "pydantic", "opencv-python", "imageio-ffmpeg", "tabulate", "brotli"]
+
+[project.urls]
+Repository = "https://github.com/BennyKok/comfyui-deploy"
+#  Used by Comfy Registry https://comfyregistry.org
+
+[tool.comfy]
+PublisherId = "comfydeploy"
+DisplayName = "comfyui-deploy"
+Icon = ""

requirements.txt

@@ -0,0 +1,7 @@
+aiofiles
+pydantic
+opencv-python
+imageio-ffmpeg
+brotli
+tabulate
+# logfire

web-plugin/api.js

@@ -1,4 +0,0 @@
-/** @typedef {import('../../../web/scripts/api.js').api} API*/
-import { api as _api } from '../../scripts/api.js';
-/** @type {API} */
-export const api = _api;

web-plugin/app.js

@@ -1,4 +0,0 @@
-/** @typedef {import('../../../web/scripts/app.js').ComfyApp} ComfyApp*/
-import { app as _app } from '../../scripts/app.js';
-/** @type {ComfyApp} */
-export const app = _app;

web-plugin/snapshot-utils.js

@@ -0,0 +1,82 @@
+// Snapshot Utilities
+// Centralized snapshot fetching with ComfyUI version fallback
+
+/**
+ * Fetches the current snapshot with ComfyUI version fallback
+ * If the snapshot response has null comfyui field, it will fetch the latest ComfyUI version
+ * and update the snapshot with the comfyui_hash
+ *
+ * @param {Function} getDataFn - Function that returns { apiKey, apiUrl } for ComfyUI version API calls
+ * @returns {Promise<Object>} - The snapshot data with comfyui field populated
+ */
+export async function fetchSnapshot(getDataFn = null) {
+  try {
+    // Fetch the current snapshot
+    const response = await fetch("/snapshot/get_current");
+    if (!response.ok) {
+      throw new Error(`Snapshot fetch failed: ${response.status}`);
+    }
+
+    const snapshot = await response.json();
+
+    // Check if comfyui field is null and we have getDataFn for fallback
+    if (snapshot.comfyui === null && getDataFn) {
+      console.log(
+        "ComfyUI version is null in snapshot, fetching latest version..."
+      );
+
+      try {
+        const data = getDataFn();
+        if (data && data.apiKey) {
+          const comfyuiVersionResponse = await fetch(
+            `/comfyui-deploy/comfyui-version?api_url=${encodeURIComponent(
+              data.apiUrl || "https://api.comfydeploy.com"
+            )}`,
+            {
+              headers: {
+                Authorization: `Bearer ${data.apiKey}`,
+              },
+            }
+          );
+
+          if (comfyuiVersionResponse.ok) {
+            const versionData = await comfyuiVersionResponse.json();
+            if (versionData.comfyui_hash) {
+              console.log(
+                `Using ComfyUI hash from API: ${versionData.comfyui_hash}`
+              );
+              snapshot.comfyui = versionData.comfyui_hash;
+            }
+          } else {
+            console.warn(
+              "Failed to fetch ComfyUI version from API:",
+              comfyuiVersionResponse.status
+            );
+          }
+        }
+      } catch (error) {
+        console.warn("Error fetching ComfyUI version fallback:", error);
+        // Continue with original snapshot even if fallback fails
+      }
+    }
+
+    return snapshot;
+  } catch (error) {
+    console.error("Error fetching snapshot:", error);
+    throw error;
+  }
+}
+
+/**
+ * Simple snapshot fetch without ComfyUI version fallback
+ * Use this when you don't need the ComfyUI version fallback logic
+ *
+ * @returns {Promise<Object>} - The snapshot data as-is
+ */
+export async function fetchSnapshotSimple() {
+  const response = await fetch("/snapshot/get_current");
+  if (!response.ok) {
+    throw new Error(`Snapshot fetch failed: ${response.status}`);
+  }
+  return response.json();
+}

web-plugin/widgets.js

@@ -1,18 +0,0 @@
-// /** @typedef {import('../../../web/scripts/api.js').api} API*/
-// import { api as _api } from "../../scripts/api.js";
-// /** @type {API} */
-// export const api = _api;
-
-/** @typedef {typeof import('../../../web/scripts/widgets.js').ComfyWidgets} Widgets*/
-import { ComfyWidgets as _ComfyWidgets } from "../../scripts/widgets.js";
-
-/**
- * @type {Widgets}
- */
-export const ComfyWidgets = _ComfyWidgets;
-
-// import { LGraphNode as _LGraphNode } from "../../types/litegraph.js";
-
-/** @typedef {typeof import('../../../web/types/litegraph.js').LGraphNode} LGraphNode*/
-/** @type {LGraphNode}*/
-export const LGraphNode = LiteGraph.LGraphNode;

web-plugin/workflow-list.js

@@ -0,0 +1,417 @@
+// Workflow list management
+let workflowsState = {
+  workflows: [],
+  offset: 0,
+  limit: 20,
+  loading: false,
+  hasMore: true,
+  initialized: false,
+  currentSearch: "",
+};
+
+// Make workflowsState accessible globally
+window.workflowsState = workflowsState;
+
+async function fetchWorkflows(getData, offset = 0, limit = 20, search = "") {
+  try {
+    const data = getData();
+    if (!data.apiKey) {
+      throw new Error("API key not configured");
+    }
+
+    const params = new URLSearchParams({
+      offset: offset.toString(),
+      limit: limit.toString(),
+      api_url: data.apiUrl || "https://api.comfydeploy.com",
+      ...(search && { search }),
+    });
+
+    const response = await fetch(`/comfyui-deploy/workflows?${params}`, {
+      method: "GET",
+      headers: {
+        Authorization: `Bearer ${data.apiKey}`,
+        "Content-Type": "application/json",
+      },
+    });
+
+    if (!response.ok) {
+      throw new Error(`Failed to fetch workflows: ${response.status}`);
+    }
+
+    const result = await response.json();
+    console.log("result", result);
+    return Array.isArray(result) ? result : [];
+  } catch (error) {
+    console.error("Error fetching workflows:", error);
+    return [];
+  }
+}
+
+function createWorkflowItem(workflow, getTimeAgo, getData) {
+  const li = document.createElement("li");
+  let loadingToast = null;
+  li.style.cssText = `
+      border-bottom: 1px solid #444;
+      background: transparent;
+      transition: all 0.2s ease;
+      cursor: pointer;
+    `;
+
+  li.addEventListener("mouseenter", () => {
+    li.style.background = "#333";
+  });
+
+  li.addEventListener("mouseleave", () => {
+    li.style.background = "transparent";
+  });
+
+  // Add click handler to fetch and load workflow data
+  li.addEventListener("click", async () => {
+    try {
+      const data = getData();
+      if (!data.apiKey) {
+        console.error("No API key configured");
+        return;
+      }
+
+      // Show loading toast
+      loadingToast = window.app.extensionManager.toast.add({
+        severity: "info",
+        summary: "Loading workflow...",
+        detail: `Loading "${workflow.name}"`,
+        life: 3000,
+      });
+
+      const params = new URLSearchParams({
+        workflow_id: workflow.id,
+        api_url: data.apiUrl || "https://api.comfydeploy.com",
+      });
+
+      const response = await fetch(`/comfyui-deploy/workflow?${params}`, {
+        method: "GET",
+        headers: {
+          Authorization: `Bearer ${data.apiKey}`,
+          "Content-Type": "application/json",
+        },
+      });
+
+      if (!response.ok) {
+        throw new Error(`Failed to fetch workflow: ${response.status}`);
+      }
+
+      const workflowData = await response.json();
+      console.log("Workflow data:", workflowData);
+
+      // Load the workflow into the graph
+      if (workflowData.versions && workflowData.versions.length > 0) {
+        const latestVersion = workflowData.versions[0];
+        if (latestVersion.workflow && window.app) {
+          // Load the workflow
+          window.app.loadGraphData(latestVersion.workflow);
+
+          // Wait a bit for the graph to fully load before checking for ComfyDeploy node
+          await new Promise((resolve) => setTimeout(resolve, 100));
+
+          // Check if ComfyDeploy node exists, if not add it back
+          const graph = window.app.graph;
+          let deployMeta = graph.findNodesByType("ComfyDeploy");
+
+          if (deployMeta.length === 0) {
+            // Add ComfyDeploy node with workflow metadata
+            graph.beforeChange();
+            const node = LiteGraph.createNode("ComfyDeploy");
+            node.configure({
+              widgets_values: [
+                workflow.name, // workflow_name
+                workflow.id, // workflow_id
+                latestVersion.version, // version
+              ],
+            });
+            node.pos = [0, 0];
+            graph.add(node);
+            graph.afterChange();
+
+            console.log(
+              `Added ComfyDeploy node with: name="${workflow.name}", id="${workflow.id}", version="${latestVersion.version}"`
+            );
+          }
+
+          // Show success toast
+          window.app.extensionManager.toast.add({
+            severity: "success",
+            summary: "Workflow loaded successfully",
+            detail: `Loaded "${workflow.name}" v${latestVersion.version}`,
+            life: 3000,
+          });
+        }
+      }
+    } catch (error) {
+      console.error("Error loading workflow:", error);
+      // Show error toast
+      window.app.extensionManager.toast.add({
+        severity: "error",
+        summary: "Failed to load workflow",
+        detail: error.message,
+        life: 5000,
+      });
+    } finally {
+      if (loadingToast) {
+        loadingToast.close();
+      }
+    }
+  });
+
+  const updatedDate = new Date(workflow.updated_at);
+  const timeAgo = getTimeAgo(updatedDate);
+
+  li.innerHTML = `
+      <div style="padding: 12px 16px;">
+        <div style="display: flex; align-items: flex-start; gap: 12px;">
+          ${
+            workflow.cover_image
+              ? `<img src="${workflow.cover_image}" 
+                     style="width: 40px; height: 40px; border-radius: 4px; object-fit: cover; flex-shrink: 0;"
+                     onerror="this.style.display='none'">`
+              : `<div style="width: 40px; height: 40px; border-radius: 4px; background: #444; flex-shrink: 0; display: flex; align-items: center; justify-content: center; font-size: 14px; color: #888;">
+                   ${workflow.name.charAt(0).toUpperCase()}
+                 </div>`
+          }
+          
+          <div style="flex: 1; min-width: 0;">
+            <div style="display: flex; align-items: center; gap: 8px; margin-bottom: 4px;">
+              <h4 style="margin: 0; font-size: 14px; font-weight: 400; color: #fff; white-space: nowrap; overflow: hidden; text-overflow: ellipsis;">
+                ${workflow.name}
+              </h4>
+              ${
+                workflow.pinned
+                  ? `<span style="color: #ffd700; font-size: 12px;">📌</span>`
+                  : ""
+              }
+            </div>
+            
+            ${
+              workflow.description
+                ? `<p style="margin: 0 0 8px 0; font-size: 12px; color: #bbb; line-height: 1.3; overflow: hidden; display: -webkit-box; -webkit-line-clamp: 2; -webkit-box-orient: vertical;">
+                     ${workflow.description}
+                   </p>`
+                : ""
+            }
+            
+            <div style="display: flex; align-items: center; gap: 8px; margin-top: 8px;">
+              <img src="${workflow.user_icon}" 
+                   style="width: 16px; height: 16px; border-radius: 50%;"
+                   onerror="this.style.display='none'">
+              <span style="font-size: 11px; color: #888;">
+                ${workflow.user_name} • Updated ${timeAgo}
+              </span>
+            </div>
+          </div>
+        </div>
+      </div>
+    `;
+
+  return li;
+}
+
+async function loadMoreWorkflows(element, getData, getTimeAgo) {
+  if (workflowsState.loading || !workflowsState.hasMore) return;
+
+  workflowsState.loading = true;
+
+  const workflowsList = element.querySelector("#workflows-list");
+  const workflowsLoading = element.querySelector("#workflows-loading");
+
+  // Show loading indicator
+  workflowsLoading.style.display = "flex";
+
+  try {
+    const newWorkflows = await fetchWorkflows(
+      getData,
+      workflowsState.offset,
+      workflowsState.limit,
+      workflowsState.currentSearch
+    );
+
+    if (newWorkflows.length === 0) {
+      workflowsState.hasMore = false;
+    } else {
+      workflowsState.workflows.push(...newWorkflows);
+      workflowsState.offset += newWorkflows.length;
+
+      // Render new workflow items
+      newWorkflows.forEach((workflow) => {
+        const workflowItem = createWorkflowItem(workflow, getTimeAgo, getData);
+        workflowsList.appendChild(workflowItem);
+      });
+    }
+  } catch (error) {
+    console.error("Error loading more workflows:", error);
+  } finally {
+    workflowsState.loading = false;
+    workflowsLoading.style.display = "none";
+  }
+}
+
+function setupInfiniteScroll(container, element, getData, getTimeAgo) {
+  let isScrolling = false;
+
+  container.addEventListener("scroll", () => {
+    if (isScrolling) return;
+
+    const { scrollTop, scrollHeight, clientHeight } = container;
+
+    // Load more when scrolled to bottom (with 100px threshold)
+    if (scrollTop + clientHeight >= scrollHeight - 100) {
+      isScrolling = true;
+      loadMoreWorkflows(element, getData, getTimeAgo).finally(() => {
+        isScrolling = false;
+      });
+    }
+  });
+}
+
+async function initializeWorkflowsList(element, getData, getTimeAgo) {
+  const workflowsContainer = element.querySelector("#workflows-container");
+  const workflowsList = element.querySelector("#workflows-list");
+  const workflowsLoading = element.querySelector("#workflows-loading");
+
+  // Check if already initialized AND the DOM elements still exist
+  if (
+    workflowsState.initialized &&
+    workflowsList &&
+    workflowsList.children.length > 0
+  )
+    return;
+
+  try {
+    // Reset state (always reset when reinitializing)
+    workflowsState = {
+      workflows: [],
+      offset: 0,
+      limit: 20,
+      loading: false,
+      hasMore: true,
+      initialized: true,
+      currentSearch: "",
+    };
+
+    // Clear existing content in case of reinitialization
+    if (workflowsList) {
+      workflowsList.innerHTML = "";
+    }
+
+    // Show container and loading
+    workflowsContainer.style.display = "block";
+    workflowsLoading.style.display = "flex";
+
+    // Style the workflows list for full height scrolling
+    workflowsList.style.cssText = `
+        list-style-type: none;
+        padding: 0;
+        margin: 0;
+        height: calc(100vh - 550px);
+        overflow-y: auto;
+        scrollbar-width: thin;
+        scrollbar-color: #666 transparent;
+        border-top: 1px solid #444;
+      `;
+
+    // Add webkit scrollbar styles
+    const style = document.createElement("style");
+    style.textContent = `
+        #workflows-list::-webkit-scrollbar {
+          width: 6px;
+        }
+        #workflows-list::-webkit-scrollbar-track {
+          background: transparent;
+        }
+        #workflows-list::-webkit-scrollbar-thumb {
+          background: #666;
+          border-radius: 3px;
+        }
+        #workflows-list::-webkit-scrollbar-thumb:hover {
+          background: #777;
+        }
+      `;
+    document.head.appendChild(style);
+
+    // Setup infinite scroll
+    setupInfiniteScroll(workflowsList, element, getData, getTimeAgo);
+
+    // Load initial workflows
+    await loadMoreWorkflows(element, getData, getTimeAgo);
+
+    // Show the list
+    workflowsList.style.display = "block";
+  } catch (error) {
+    console.error("Error initializing workflows list:", error);
+    workflowsLoading.innerHTML = `
+        <div style="text-align: center; color: #e74c3c; font-size: 12px; padding: 20px;">
+          <div>Failed to load workflows</div>
+          <button onclick="initializeWorkflowsList(this.closest('.comfy-menu'), getData, getTimeAgo)" 
+                  style="margin-top: 8px; padding: 4px 8px; font-size: 11px; background: #f0f0f0; border: 1px solid #ccc; border-radius: 4px; cursor: pointer;">
+            Retry
+          </button>
+        </div>
+      `;
+  }
+}
+
+// Search functionality
+function addWorkflowSearch(element, getData, getTimeAgo) {
+  const workflowsContainer = element.querySelector("#workflows-container");
+  const h4 = workflowsContainer.querySelector("h4");
+
+  const searchContainer = document.createElement("div");
+  searchContainer.style.cssText = "margin-bottom: 12px;";
+
+  const searchInput = document.createElement("input");
+  searchInput.type = "text";
+  searchInput.placeholder = "Search workflows...";
+  searchInput.style.cssText = `
+      width: 100%;
+      padding: 8px 12px;
+      border: 1px solid #555;
+      border-radius: 6px;
+      font-size: 12px;
+      box-sizing: border-box;
+      background: #333;
+      color: #fff;
+    `;
+
+  let searchTimeout;
+  searchInput.addEventListener("input", (e) => {
+    clearTimeout(searchTimeout);
+    searchTimeout = setTimeout(async () => {
+      const searchTerm = e.target.value.trim();
+
+      // Update the tracked search term
+      workflowsState.currentSearch = searchTerm;
+
+      // Reset state for new search
+      workflowsState.workflows = [];
+      workflowsState.offset = 0;
+      workflowsState.hasMore = true;
+
+      // Clear current list
+      const workflowsList = element.querySelector("#workflows-list");
+      workflowsList.innerHTML = "";
+
+      // Load with search term
+      workflowsState.loading = false;
+      await loadMoreWorkflows(element, getData, getTimeAgo);
+    }, 300);
+  });
+
+  searchContainer.appendChild(searchInput);
+  h4.after(searchContainer);
+}
+
+// Export the functions
+export {
+  initializeWorkflowsList,
+  addWorkflowSearch,
+  workflowsState,
+  fetchWorkflows,
+  loadMoreWorkflows,
+};

web/package.json

@@ -74,7 +74,7 @@
     "mitata": "^0.1.6",
     "ms": "^2.1.3",
     "nanoid": "^5.0.4",
-    "next": "14.1",
+    "next": "14.2",
     "next-plausible": "^3.12.0",
     "next-themes": "^0.2.1",
     "next-usequerystate": "^1.13.2",

web/src/app/(app)/globals.css

@@ -80,7 +80,9 @@
   /* @apply rounded-lg p-2 overflow-x-scroll */
   @apply  p-2 max-w-full overflow-auto w-full
 }
- 
+.vsc-controller{
+  position: absolute;
+}
 @layer base {
   * {
     @apply border-border;

web/src/components/NavbarMenu.tsx

@@ -5,7 +5,6 @@ import { Tabs, TabsList, TabsTrigger } from "@/components/ui/tabs";
 import { cn } from "@/lib/utils";
 import Link from "next/link";
 import { usePathname } from "next/navigation";
-import { useRouter } from "next/navigation";
 import { useEffect, useState } from "react";
 import { useMediaQuery } from "usehooks-ts";
 
@@ -25,8 +24,6 @@ export function NavbarMenu({
   const pathnames = usePathname();
   const pathname = `/${pathnames.split("/")[1]}`;
 
-  const router = useRouter();
-
   const pages = [
     {
       name: "Workflows",
@@ -59,11 +56,8 @@ export function NavbarMenu({
               <TabsTrigger
                 key={page.name}
                 value={page.path}
-                onClick={() => {
-                  router.push(page.path);
-                }}
               >
-                {page.name}
+                <Link href={page.path}>{page.name}</Link>
               </TabsTrigger>
             ))}
           </TabsList>

web/src/components/VersionSelect.tsx

@@ -60,6 +60,7 @@ import { callServerPromise } from "./callServerPromise";
 import fetcher from "./fetcher";
 import { ButtonAction } from "@/components/ButtonActionLoader";
 import { editWorkflowOnMachine } from "@/server/editWorkflowOnMachine";
+import { VisualizeImagesGrid } from "@/components/VisualizeImagesGrid";
 
 export function VersionSelect({
   workflow,
@@ -169,19 +170,21 @@ export function useSelectedMachine(
 }
 
 type PublicRunStore = {
-  image: string;
+  image: {
+    url: string;
+  }[] | null;
   loading: boolean;
   runId: string;
   status: string;
 
-  setImage: (image: string) => void;
+  setImage: (image: { url: string; }[]) => void;
   setLoading: (loading: boolean) => void;
   setRunId: (runId: string) => void;
   setStatus: (status: string) => void;
 };
 
 export const publicRunStore = create<PublicRunStore>((set) => ({
-  image: "",
+  image: null,
   loading: false,
   runId: "",
   status: "",
@@ -205,7 +208,10 @@ export function PublicRunOutputs(props: {
         console.log(res?.status);
         if (res) setStatus(res.status);
         if (res && res.status === "success") {
-          setImage(res.outputs[0]?.data.images[0].url);
+          const imageURLs = res.outputs[0]?.data.images.map((item: { url: string; }) => {
+            return { url: item.url };
+          });
+          setImage(imageURLs);
           setLoading(false);
           clearInterval(interval);
         }
@@ -214,30 +220,25 @@ export function PublicRunOutputs(props: {
     return () => clearInterval(interval);
   }, [runId]);
 
-  return (
-    <div className="border border-gray-200 w-full square h-[400px] rounded-lg relative">
-      {!loading && !image && props.preview && props.preview.length > 0 && (
-        <>
-          <img
-            className="w-full h-full object-contain"
-            src={props.preview[0]?.url}
-            alt="Generated image"
-          />
-        </>
-      )}
-      {!loading && image && (
-        <img
-          className="w-full h-full object-contain"
-          src={image}
-          alt="Generated image"
-        />
-      )}
-      {loading && (
+  if (loading) {
+    return (
+      <div className="border border-gray-200 w-full h-[400px] square rounded-lg relative p-4 ">
         <div className="absolute top-0 left-0 w-full h-full flex items-center justify-center gap-2">
           {status} <LoadingIcon />
         </div>
+        <Skeleton className="w-full h-full" />
+      </div>
+    );
+  }
+
+  return (
+    <div className="border border-gray-200 w-full min-h-[400px] square rounded-lg relative p-4 ">
+      {!image && props.preview && props.preview.length > 0 &&
+        <VisualizeImagesGrid images={props.preview} />
+      }
+      {image && (
+        <VisualizeImagesGrid images={image} />
       )}
-      {loading && <Skeleton className="w-full h-full" />}
     </div>
   );
 }
@@ -328,7 +329,7 @@ export function RunWorkflowButton({
             className="px-1"
           >
             <div className="flex justify-end">
-              <AutoFormSubmit>
+              <AutoFormSubmit disabled={isLoading}>
                 Run
                 {isLoading ? <LoadingIcon /> : <Play size={14} />}
               </AutoFormSubmit>

web/src/components/VisualizeImagesGrid.tsx

@@ -0,0 +1,42 @@
+type imagesType = {
+  url: string;
+  width?: number;
+  height?: number;
+};
+type VisualizeImagesGridProps = {
+  images: imagesType[];
+  layout?: 'justify-between' | 'justify-center' | 'justify-start' | 'justify-end';
+};
+export function VisualizeImagesGrid({ images, layout }: VisualizeImagesGridProps) {
+
+  return (
+    <div className={`flex gap-4 flex-wrap ${layout || 'justify-center'}`}>
+      <>
+        {images && images.length > 0 &&
+          images.map(item => {
+            if (!item) {
+              return;
+            }
+            if (item?.url.endsWith(".mp4") || item?.url.endsWith(".webm")) {
+              return (
+                <video key={item?.url} controls autoPlay className="rounded-xl" style={{ maxHeight: item.height || 370, maxWidth: item.width || "auto" }}>
+                  <source src={item?.url} type="video/mp4" />
+                  <source src={item?.url} type="video/webm" />
+                  Your browser does not support the video tag.
+                </video>
+              );
+            }
+            return <img
+              key={item?.url}
+              className="object-contain overflow-hidden rounded-xl"
+              src={item?.url}
+              alt="Generated image"
+              style={{ maxHeight: item.height || 370, maxWidth: item.width || "auto" }}
+            />;
+          })
+        }
+      </>
+    </div>
+  );
+
+}

web/src/components/customInputNodes.tsx

@@ -6,4 +6,5 @@ export const customInputNodes: Record<string, string> = {
   ComfyUIDeployExternalNumberInt: "integer",
   ComfyUIDeployExternalLora: "string - (public lora download url)",
   ComfyUIDeployExternalCheckpoint: "string - (public checkpoints download url)",
+  ComfyUIDeployExternalFaceModel: "string - (public face model download url)",
 };

web/src/routes/registerCreateRunRoute.ts

@@ -51,7 +51,9 @@ const createRunRoute = createRoute({
 export const registerCreateRunRoute = (app: App) => {
   app.openapi(createRunRoute, async (c) => {
     const data = c.req.valid("json");
-    const origin = new URL(c.req.url).origin;
+    const proto = c.req.headers.get('x-forwarded-proto')  || "http";
+    const host = c.req.headers.get('x-forwarded-host') || c.req.headers.get('host');
+    const origin = `${proto}://${host}` || new URL(c.req.url).origin;
     const apiKeyTokenData = c.get("apiKeyTokenData")!;
 
     const { deployment_id, inputs } = data;

web/src/server/createRun.ts

@@ -102,7 +102,7 @@ export const createRun = withServerPromise(
 
     let prompt_id: string | undefined = undefined;
     const shareData = {
-      workflow_api: workflow_api,
+      workflow_api_raw: workflow_api,
       status_endpoint: `${origin}/api/update-run`,
       file_upload_endpoint: `${origin}/api/file-upload`,
     };