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Author SHA1 Message Date
bennykok 5443dcd20b feat: add loading text for machine operation 2024-01-27 22:37:29 +08:00
bennykok e5097a5ed5 chore: add machine delete logic check for only new version 2024-01-27 22:33:25 +08:00
bennykok 9a1ab21e91 chore: update prod fly io settings and name 2024-01-27 22:15:43 +08:00
bennykok d2dbe3410f feat(builder): update builder for updating time log and migrate to class objects 2024-01-27 18:07:37 +08:00
bennykok 0ce07c88f8 fix: adding more time log for the run status 2024-01-27 18:06:48 +08:00
bennykok c7727fc1be feat: revamp cold start time counter 2024-01-27 14:21:59 +08:00
bennykok 72325a4217 feat: add loading dialog for when rebuilding machine request was loading 2024-01-27 14:19:50 +08:00
bennykok 5eba792579 fix: attempt fixing timeout 2024-01-27 13:15:28 +08:00
bennykok fe8f5a49ff test timeout 2024-01-27 12:32:01 +08:00
bennykok f4d93a82e2 attempt to fix timeout issues 2024-01-27 12:25:53 +08:00
bennykok 18c410ba4e fix: machine list 2024-01-27 11:44:56 +08:00
bennykok 6aa9a44f4b fix: when there is auth token, replace it locally 2024-01-27 11:41:29 +08:00
bennykok d3e1ca1b0b Merge branch 'main' of https://github.com/comfy-deploy/comfyui-deploy 2024-01-27 11:38:28 +08:00
bennykok 8f7f06470c feat: ensure open in comfy ui will carry over the auth token 2024-01-27 11:38:10 +08:00
Nicholas Koben Kao 2a55b20887 add a note and change so that by default it uses preview toml file 2024-01-26 19:37:21 -08:00
Nicholas Koben Kao dd0af2a3e9 note about the 2 toml files 2024-01-26 19:35:00 -08:00
Nicholas Koben Kao 9a715e9766 preview toml file use with fly deploy -c 2024-01-26 19:34:07 -08:00
Nick Kao ac5aba2aa9 model volume rename, env for flyio, public and private volumes tested tgt, everything is a public model (#3) 2024-01-27 10:21:15 +08:00
bennykok 95e454e687 fix: maxDuration for workflow page 2024-01-26 21:38:25 +08:00
bennykok 8b790fe7c5 chore: update dev container 2024-01-26 20:57:21 +08:00
bennykok 9e07ccadb4 fix: build finish dialog 2024-01-26 20:57:08 +08:00
bennykok 954de12d08 feat(builder): add ipadapter support - exposing pip install 2024-01-26 20:16:10 +08:00
bennykok 731bdf3982 feat: update with error machine built dialog 2024-01-26 20:13:44 +08:00
bennykok 97aa88eac8 feat: add built finished dialog 2024-01-26 19:39:29 +08:00
bennykok d7ee49aa49 fix: remove duplicated machine badge 2024-01-26 17:15:11 +08:00
bennykok 2bace09f5e feat: add pip modules when selecting custom_nodes 2024-01-26 17:02:55 +08:00
bennykok 78721b3129 chore: update git ignore 2024-01-26 16:10:39 +08:00
bennykok 112c6bb0f6 Squashed commit of the following:
commit 2afcade4f2
Author: bennykok <itechbenny@gmail.com>
Date:   Fri Jan 26 16:07:54 2024 +0800

    fix: add fly io to dev container

commit d70333baa6
Author: BennyKok <itechbenny@gmail.com>
Date:   Fri Jan 26 07:47:41 2024 +0000

    fix: comment typo

commit 43cfebd97a
Author: BennyKok <itechbenny@gmail.com>
Date:   Fri Jan 26 07:33:30 2024 +0000

    fix: only create share slug when public-share deployment
2024-01-26 16:09:50 +08:00
bennykok 0311638ab1 Squashed commit of the following:
commit d70333baa6
Author: BennyKok <itechbenny@gmail.com>
Date:   Fri Jan 26 07:47:41 2024 +0000

    fix: comment typo

commit 43cfebd97a
Author: BennyKok <itechbenny@gmail.com>
Date:   Fri Jan 26 07:33:30 2024 +0000

    fix: only create share slug when public-share deployment
2024-01-26 16:06:27 +08:00
bennykok 15e1b1ccb4 Squashed commit of the following:
commit 43cfebd97a
Author: BennyKok <itechbenny@gmail.com>
Date:   Fri Jan 26 07:33:30 2024 +0000

    fix: only create share slug when public-share deployment
2024-01-26 15:40:42 +08:00
bennykok 4bca9a7376 fix: navbar issues 2024-01-26 12:53:21 +08:00
bennykok e95811474e fix: migration again 2024-01-26 11:58:16 +08:00
bennykok cc03c780e8 fix: migration 2024-01-26 11:52:54 +08:00
bennykok 93b1fa9c79 fix(schema): set default value for mode_type to checkpoint to preview existing db migration issues 2024-01-26 10:13:03 +08:00
bennykok 85477aba9d Squashed commit of the following:
commit c36b0ec0b374dd8ccbee3a6044ee7e3f1fefe368
Author: Nicholas Koben Kao <kobenkao@gmail.com>
Date:   Thu Jan 25 17:54:54 2024 -0800

    nits on wording and removing link to broken storage/:id page

commit 0777fdcf7b0002244bc713199d3d64eea6b6061e
Author: Nicholas Koben Kao <kobenkao@gmail.com>
Date:   Thu Jan 25 17:23:55 2024 -0800

    builder update config and such

commit 958b795bb2b6ac27ce33c5729ef265b068420e1a
Author: Nicholas Koben Kao <kobenkao@gmail.com>
Date:   Thu Jan 25 17:23:43 2024 -0800

    rename all from checkponit to model

commit 7a9c5636e73bd005499b141a4dd382db5672c962
Author: Nicholas Koben Kao <kobenkao@gmail.com>
Date:   Thu Jan 25 16:51:59 2024 -0800

    rename for consistency

commit 48bebbafab9a95388817df97c15f8ea97e0fea75
Author: Nicholas Koben Kao <kobenkao@gmail.com>
Date:   Thu Jan 25 16:18:36 2024 -0800

    bulider

commit 81dacd9af457886f2f027994d225a7748c738abb
Author: Nicholas Koben Kao <kobenkao@gmail.com>
Date:   Thu Jan 25 16:17:56 2024 -0800

    different types of models
2024-01-26 10:08:37 +08:00
bennykok 62a69dba06 chore: update example 2024-01-26 00:28:33 +08:00
bennykok 8305134a8e fix: make sure we were able to detect the pricing plan correct when not in a org 2024-01-26 00:28:05 +08:00
bennykok 6f0499c657 Merge branch 'nickkao/checkpoint-volume'
# Conflicts:
#	web/bun.lockb
2024-01-25 21:07:27 +08:00
bennykok b968fded32 fix: update clerk 2024-01-25 20:35:54 +08:00
bennykok aa419c80f1 fix: add after signout url 2024-01-25 20:25:11 +08:00
bennykok 3c1e49b451 fix: login issues 2024-01-25 19:34:40 +08:00
Nicholas Koben Kao 72312c7a40 generate 2024-01-24 22:37:02 -08:00
Nicholas Koben Kao f22f5eef4e Merge branch 'main' into nickkao/checkpoint-volume 2024-01-24 22:33:00 -08:00
Nicholas Koben Kao 982ef0780d lock 2024-01-24 22:32:48 -08:00
Nicholas Koben Kao a295df973f clean up 2024-01-24 22:28:50 -08:00
Nicholas Koben Kao d8df580339 remove divergent sql 2024-01-24 22:26:42 -08:00
Nicholas Koben Kao 0d88907cfd clean up web 2024-01-24 22:22:59 -08:00
Nicholas Koben Kao 4c047aea62 clean up checkpoint build 2024-01-24 22:20:00 -08:00
Nicholas Koben Kao db04d02d34 working 2024-01-24 22:15:12 -08:00
BennyKok 3d2eacccc9 fix: build 2024-01-25 12:08:09 +08:00
BennyKok 85e4219ea7 fix: remove unused import, fix build 2024-01-25 11:16:41 +08:00
BennyKok df4dfba31d chore: migrate sign in to domain relative path with clerk, add .env.example as well 2024-01-25 10:57:13 +08:00
Nicholas Koben Kao 911cc8d16b merge0 2024-01-24 16:26:16 -08:00
Nicholas Koben Kao 224b006ec2 somethingg 2024-01-24 15:15:05 -08:00
Nicholas Koben Kao dfd139294f print 2024-01-24 14:44:05 -08:00
Nicholas Koben Kao eb04f246a4 status 2024-01-24 12:53:43 -08:00
BennyKok d644edd3c4 Merge branch 'main' into main-private 2024-01-25 00:40:31 +08:00
BennyKok 1143b469ad Merge branch 'main' of https://github.com/comfy-deploy/comfyui-deploy into main-private 2024-01-25 00:37:52 +08:00
BennyKok 0f9e0c9c76 feat: pricing plan + usage page 2024-01-25 00:34:41 +08:00
Nicholas Koben Kao b1e9bcc4e6 blah 2024-01-24 01:58:00 -08:00
BennyKok 14c3ca6bf5 Merge branch 'pricing-plan'
# Conflicts:
#	web/bun.lockb
#	web/drizzle/meta/_journal.json
#	web/src/db/schema.ts
2024-01-23 11:43:53 +08:00
BennyKok 7a7ced3e08 drop migration for merge 2024-01-23 11:41:28 +08:00
Karrix a9f46b0846 chore: old testing code in pricing page 2024-01-23 02:00:19 +08:00
Karrix f948fca78c add: add unit (per second) to lemonsqueezy after run, and sync to db table 2024-01-23 01:58:05 +08:00
Karrix 0ba1a6d1f0 add: feature flag 2024-01-21 19:49:26 +08:00
Karrix ac8f6e2808 update: pricing plan with usage base 2024-01-21 15:48:56 +08:00
Karrix 8a134ed39e fix: gpu table width too large 2024-01-21 15:47:47 +08:00
Karrix 9cbf0760a0 feat: implement lemonsqueezy to pricing table 2024-01-21 15:47:47 +08:00
Karrix 931b4e144a feat: pricing plan & gpu ui 2024-01-21 15:47:47 +08:00
159 changed files with 16015 additions and 18980 deletions
+5
View File
@@ -12,6 +12,11 @@ RUN curl -L https://fly.io/install.sh | sh
ENV FLYCTL_INSTALL="/root/.fly"
ENV PATH="$FLYCTL_INSTALL/bin:$PATH"
RUN sudo apt-get update
RUN sudo apt-get install python3-pip python3 -y
RUN pip3 install modal
# RUN echo 'export FLYCTL_INSTALL="/home/node/.fly"' >> ~/.bashrc
# RUN echo 'export PATH="$FLYCTL_INSTALL/bin:$PATH"' >> ~/.bashrc
+2 -1
View File
@@ -14,7 +14,8 @@
"stivo.tailwind-fold",
"streetsidesoftware.code-spell-checker",
"GitHub.copilot",
"ms-azuretools.vscode-docker"
"ms-azuretools.vscode-docker",
"ms-python.python"
]
}
}
-25
View File
@@ -1,25 +0,0 @@
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 }}
+1 -1
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@@ -1,3 +1,3 @@
__pycache__
.DS_Store
file-hash-cache.json
.vercel
+21 -208
View File
@@ -1,208 +1,21 @@
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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.
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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.
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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/>.
MIT License
Copyright (c) 2023 BennyKok
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:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
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.
+2 -10
View File
@@ -2,13 +2,6 @@
Open source comfyui deployment platform, a `vercel` for generative workflow infra. (serverless hosted gpu with vertical intergation with comfyui)
Check out our latest lcoal demo -> https://github.com/comfy-deploy/comfyui-api-comfydeploy
Full backend and frontend is here -> https://github.com/comfy-deploy/comfydeploy
> [!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
@@ -82,11 +75,10 @@ Major areas
3. `bun i`
4. Start docker
5. `cp .env.example .env.local`
6. Replace `JWT_SECRET` with `openssl rand -hex 32`
6. Repace `JWT_SECRET` with `openssl rand -hex 32`
7. Get a local clerk dev key for `NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY` and `CLERK_SECRET_KEY`
8. Keep a terminal live for `bun run db-dev`
9. Execute the local migration to create the initial data `bun run migrate-local`
10. Finally start the next server with `bun dev`
9. Finally start the next server with `bun dev`
**Schema Changes**
+1 -37
View File
@@ -2,9 +2,8 @@
@author: BennyKok
@title: comfyui-deploy
@nickname: Comfy Deploy
@description:
@description:
"""
import os
import sys
@@ -18,23 +17,19 @@ 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 = []
@@ -46,45 +41,14 @@ 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"]
+4 -1
View File
@@ -1,5 +1,8 @@
MODAL_TOKEN_ID=
MODAL_TOKEN_SECRET=
CIVITAI_API_KEY=
# On production set to False
DEPLOY_TEST_FLAG=True
DEPLOY_TEST_FLAG=True
CIVITAI_API_KEY=
PUBLIC_MODEL_VOLUME_NAME=
+4 -1
View File
@@ -42,6 +42,9 @@ fly secrets set MODAL_TOKEN_SECRET=
## To deploy
We have 2 `toml` files one for `production` and the other for `staging`
it will default to `staging` if you don't include the `-c` flag to choose your config file
```
// model-builder/fly.toml
app = <APP_NAME>
@@ -54,4 +57,4 @@ fly launch
if not, run this instead
```
fly deploy
```
```
+22
View File
@@ -0,0 +1,22 @@
# fly.toml app configuration file generated for modal-builder on 2024-01-03T22:29:34+08:00
#
# See https://fly.io/docs/reference/configuration/ for information about how to use this file.
#
app = "modal-builder-production"
primary_region = "sea"
[build]
[http_service]
internal_port = 8080
force_https = true
auto_stop_machines = true
auto_start_machines = true
min_machines_running = 0
processes = ["app"]
[[vm]]
cpu_kind = 'shared'
cpus = 1
memory_mb = 1024
+9 -4
View File
@@ -1,10 +1,10 @@
# fly.toml app configuration file generated for modal-builder on 2024-01-03T22:29:34+08:00
# fly.toml app configuration file generated for modal-builder-preview on 2024-01-25T09:26:31Z
#
# See https://fly.io/docs/reference/configuration/ for information about how to use this file.
#
app = "modal-builder"
primary_region = "sea"
app = 'modal-builder-preview'
primary_region = 'sea'
[build]
@@ -14,4 +14,9 @@ primary_region = "sea"
auto_stop_machines = true
auto_start_machines = true
min_machines_running = 0
processes = ["app"]
processes = ['app']
[[vm]]
cpu_kind = 'shared'
cpus = 1
memory_mb = 1024
+79 -1
View File
@@ -8,6 +8,7 @@ from enum import Enum
import json
import subprocess
import time
from uuid import uuid4
from contextlib import asynccontextmanager
import asyncio
import threading
@@ -19,6 +20,7 @@ from urllib.parse import parse_qs
from starlette.middleware.base import BaseHTTPMiddleware
from starlette.types import ASGIApp, Scope, Receive, Send
from concurrent.futures import ThreadPoolExecutor
# executor = ThreadPoolExecutor(max_workers=5)
@@ -45,6 +47,8 @@ machine_id_websocket_dict = {}
machine_id_status = {}
fly_instance_id = os.environ.get('FLY_ALLOC_ID', 'local').split('-')[0]
civitai_api_key = os.environ.get('FLY_ALLOC_ID', 'local')
public_model_volume_name = os.environ.get('PUBLIC_MODEL_VOLUME_NAME', 'local')
class FlyReplayMiddleware(BaseHTTPMiddleware):
@@ -139,6 +143,7 @@ def read_root():
class GitCustomNodes(BaseModel):
hash: str
disabled: bool
pip: Optional[List[str]] = None
class FileCustomNodes(BaseModel):
filename: str
@@ -174,6 +179,7 @@ class Item(BaseModel):
snapshot: Snapshot
models: List[Model]
callback_url: str
model_volume_name: str
gpu: GPUType = Field(default=GPUType.T4)
@field_validator('gpu')
@@ -223,6 +229,71 @@ async def websocket_endpoint(websocket: WebSocket, machine_id: str):
# return {"Hello": "World"}
# definition based on web schema
class UploadType(str, Enum):
checkpoint = "checkpoint"
lora = "lora"
embedding = "embedding"
class UploadBody(BaseModel):
download_url: str
volume_name: str
volume_id: str
model_id: str
upload_type: UploadType
callback_url: str
# based on ComfyUI's model dir, and our mappings in ./src/template/data/extra_model_paths.yaml
UPLOAD_TYPE_DIR_MAP = {
UploadType.checkpoint: "checkpoints",
UploadType.lora: "loras",
UploadType.embedding: "embeddings",
}
@app.post("/upload-volume")
async def upload_model(body: UploadBody):
global last_activity_time
last_activity_time = time.time()
logger.info(f"Extended inactivity time to {global_timeout}")
asyncio.create_task(upload_logic(body))
# check that this
return JSONResponse(status_code=200, content={"message": "Volume uploading", "build_machine_instance_id": fly_instance_id})
async def upload_logic(body: UploadBody):
folder_path = f"/app/builds/{body.volume_id}"
cp_process = await asyncio.subprocess.create_subprocess_exec("cp", "-r", "/app/src/volume-builder", folder_path)
await cp_process.wait()
upload_path = UPLOAD_TYPE_DIR_MAP[body.upload_type]
config = {
"volume_names": {
body.volume_name: {"download_url": body.download_url, "folder_path": upload_path}
},
"volume_paths": {
body.volume_name: f'/volumes/{uuid4()}'
},
"callback_url": body.callback_url,
"callback_body": {
"model_id": body.model_id,
"volume_id": body.volume_id,
"folder_path": upload_path,
},
"civitai_api_key": os.environ.get('CIVITAI_API_KEY')
}
with open(f"{folder_path}/config.py", "w") as f:
f.write("config = " + json.dumps(config))
await asyncio.subprocess.create_subprocess_shell(
f"modal run app.py",
cwd=folder_path,
env={**os.environ, "COLUMNS": "10000"}
)
@app.post("/create")
async def create_machine(item: Item):
@@ -308,12 +379,19 @@ async def build_logic(item: Item):
cp_process = await asyncio.subprocess.create_subprocess_exec("cp", "-r", "/app/src/template", folder_path)
await cp_process.wait()
pip_modules = set()
for git_custom_node in item.snapshot.git_custom_nodes.values():
if git_custom_node.pip:
pip_modules.update(git_custom_node.pip)
# Write the config file
config = {
"name": item.name,
"deploy_test": os.environ.get("DEPLOY_TEST_FLAG", "False"),
"gpu": item.gpu,
"civitai_token": os.environ.get("CIVITAI_TOKEN", "")
"public_model_volume": public_model_volume_name,
"private_model_volume": item.model_volume_name,
"pip": list(pip_modules)
}
with open(f"{folder_path}/config.py", "w") as f:
f.write("config = " + json.dumps(config))
+98 -75
View File
@@ -1,13 +1,14 @@
from config import config
import modal
from modal import Image, Mount, web_endpoint, Stub, asgi_app
from modal import Image, Mount, web_endpoint, Stub, asgi_app, method, enter, exit
import json
import urllib.request
import urllib.parse
from pydantic import BaseModel
from fastapi import FastAPI, Request
from fastapi import FastAPI, Request, HTTPException
from fastapi.responses import HTMLResponse
from volume_setup import volumes
from datetime import datetime
# deploy_test = False
import os
@@ -27,8 +28,8 @@ deploy_test = config["deploy_test"] == "True"
web_app = FastAPI()
print(config)
print("deploy_test ", deploy_test)
print('volumes', volumes)
stub = Stub(name=config["name"])
# print(stub.app_id)
if not deploy_test:
# dockerfile_image = Image.from_dockerfile(f"{current_directory}/Dockerfile", context_mount=Mount.from_local_dir(f"{current_directory}/data", remote_path="/data"))
@@ -36,9 +37,6 @@ if not deploy_test:
dockerfile_image = (
modal.Image.debian_slim()
.env({
"CIVITAI_TOKEN": config["civitai_token"],
})
.apt_install("git", "wget")
.pip_install(
"git+https://github.com/modal-labs/asgiproxy.git", "httpx", "tqdm"
@@ -55,16 +53,20 @@ if not deploy_test:
"cd /comfyui/custom_nodes/ComfyUI-Manager && pip install -r requirements.txt",
"cd /comfyui/custom_nodes/ComfyUI-Manager && mkdir startup-scripts",
)
.run_commands(f"cat /comfyui/server.py")
.run_commands(f"ls /comfyui/app")
# .run_commands(
# # Install comfy deploy
# "cd /comfyui/custom_nodes && git clone https://github.com/BennyKok/comfyui-deploy.git",
# )
# .copy_local_file(f"{current_directory}/data/extra_model_paths.yaml", "/comfyui")
.copy_local_file(f"{current_directory}/data/extra_model_paths.yaml", "/comfyui")
.copy_local_file(f"{current_directory}/data/start.sh", "/start.sh")
.run_commands("chmod +x /start.sh")
# Restore the custom nodes first
.pip_install(config["pip"])
.copy_local_file(f"{current_directory}/data/restore_snapshot.py", "/")
.copy_local_file(f"{current_directory}/data/snapshot.json", "/comfyui/custom_nodes/ComfyUI-Manager/startup-scripts/restore-snapshot.json")
.run_commands("python restore_snapshot.py")
@@ -156,90 +158,110 @@ image = Image.debian_slim()
target_image = image if deploy_test else dockerfile_image
@stub.cls(image=target_image, gpu=config["gpu"] ,volumes=volumes, timeout=60 * 10, container_idle_timeout=60 * 5)
class ComfyDeployRunner:
@stub.function(image=target_image, gpu=config["gpu"])
def run(input: Input):
import subprocess
import time
# Make sure that the ComfyUI API is available
print(f"comfy-modal - check server")
@enter()
def setup(self):
import subprocess
import time
# Make sure that the ComfyUI API is available
print(f"comfy-modal - check server")
command = ["python", "main.py",
"--disable-auto-launch", "--disable-metadata"]
server_process = subprocess.Popen(command, cwd="/comfyui")
command = ["python", "main.py",
"--disable-auto-launch", "--disable-metadata"]
check_server(
f"http://{COMFY_HOST}",
COMFY_API_AVAILABLE_MAX_RETRIES,
COMFY_API_AVAILABLE_INTERVAL_MS,
)
self.server_process = subprocess.Popen(command, cwd="/comfyui")
job_input = input
check_server(
f"http://{COMFY_HOST}",
COMFY_API_AVAILABLE_MAX_RETRIES,
COMFY_API_AVAILABLE_INTERVAL_MS,
)
# print(f"comfy-modal - got input {job_input}")
@exit()
def cleanup(self, exc_type, exc_value, traceback):
self.server_process.terminate()
# Queue the workflow
try:
# job_input is the json input
queued_workflow = queue_workflow_comfy_deploy(
job_input) # queue_workflow(workflow)
prompt_id = queued_workflow["prompt_id"]
print(f"comfy-modal - queued workflow with ID {prompt_id}")
except Exception as e:
import traceback
print(traceback.format_exc())
return {"error": f"Error queuing workflow: {str(e)}"}
@method()
def run(self, input: Input):
data = json.dumps({
"run_id": input.prompt_id,
"status": "started",
"time": datetime.now().isoformat()
}).encode('utf-8')
req = urllib.request.Request(input.status_endpoint, data=data, method='POST')
urllib.request.urlopen(req)
# Poll for completion
print(f"comfy-modal - wait until image generation is complete")
retries = 0
status = ""
try:
print("getting request")
while retries < COMFY_POLLING_MAX_RETRIES:
status_result = check_status(prompt_id=prompt_id)
# history = get_history(prompt_id)
job_input = input
# Exit the loop if we have found the history
# if prompt_id in history and history[prompt_id].get("outputs"):
# break
try:
queued_workflow = queue_workflow_comfy_deploy(job_input) # queue_workflow(workflow)
prompt_id = queued_workflow["prompt_id"]
print(f"comfy-modal - queued workflow with ID {prompt_id}")
except Exception as e:
import traceback
print(traceback.format_exc())
return {"error": f"Error queuing workflow: {str(e)}"}
# Exit the loop if we have found the status both success or failed
if 'status' in status_result and (status_result['status'] == 'success' or status_result['status'] == 'failed'):
status = status_result['status']
print(status)
break
# Poll for completion
print(f"comfy-modal - wait until image generation is complete")
retries = 0
status = ""
try:
print("getting request")
while retries < COMFY_POLLING_MAX_RETRIES:
status_result = check_status(prompt_id=prompt_id)
# history = get_history(prompt_id)
# Exit the loop if we have found the history
# if prompt_id in history and history[prompt_id].get("outputs"):
# break
# Exit the loop if we have found the status both success or failed
if 'status' in status_result and (status_result['status'] == 'success' or status_result['status'] == 'failed'):
status = status_result['status']
print(status)
break
else:
# Wait before trying again
time.sleep(COMFY_POLLING_INTERVAL_MS / 1000)
retries += 1
else:
# Wait before trying again
time.sleep(COMFY_POLLING_INTERVAL_MS / 1000)
retries += 1
else:
return {"error": "Max retries reached while waiting for image generation"}
except Exception as e:
return {"error": f"Error waiting for image generation: {str(e)}"}
return {"error": "Max retries reached while waiting for image generation"}
except Exception as e:
return {"error": f"Error waiting for image generation: {str(e)}"}
print(f"comfy-modal - Finished, turning off")
server_process.terminate()
print(f"comfy-modal - Finished, turning off")
# Get the generated image and return it as URL in an AWS bucket or as base64
# images_result = process_output_images(history[prompt_id].get("outputs"), job["id"])
# result = {**images_result, "refresh_worker": REFRESH_WORKER}
result = {"status": status}
return result
print("Running remotely on Modal!")
result = {"status": status}
return result
@web_app.post("/run")
async def bar(request_input: RequestInput):
# print(request_input)
async def post_run(request_input: RequestInput):
if not deploy_test:
run.spawn(request_input.input)
return {"status": "success"}
# pass
# print(request_input.input.prompt_id, request_input.input.status_endpoint)
data = json.dumps({
"run_id": request_input.input.prompt_id,
"status": "queued",
"time": datetime.now().isoformat()
}).encode('utf-8')
req = urllib.request.Request(request_input.input.status_endpoint, data=data, method='POST')
urllib.request.urlopen(req)
model = ComfyDeployRunner()
call = model.run.spawn(request_input.input)
@stub.function(image=image)
# call = run.spawn()
return {"call_id": call.object_id}
return {"call_id": None}
@stub.function(image=image
,volumes=volumes
)
@asgi_app()
def comfyui_api():
return web_app
@@ -289,6 +311,7 @@ def spawn_comfyui_in_background():
# to be on a single container.
concurrency_limit=1,
timeout=10 * 60,
volumes=volumes,
)
@asgi_app()
def comfyui_app():
@@ -307,4 +330,4 @@ def comfyui_app():
},
)()
return make_simple_proxy_app(ProxyContext(config))
return make_simple_proxy_app(ProxyContext(config))
+8 -1
View File
@@ -1 +1,8 @@
config = {"name": "my-app", "deploy_test": "True", "gpu": "T4"}
config = {
"name": "my-app",
"deploy_test": "False",
"gpu": "T4",
"public_model_volume": "model-store",
"private_model_volume": "private-model-store",
"pip": []
}
@@ -1,11 +1,23 @@
comfyui:
base_path: /runpod-volume/ComfyUI/
checkpoints: models/checkpoints/
clip: models/clip/
clip_vision: models/clip_vision/
configs: models/configs/
controlnet: models/controlnet/
embeddings: models/embeddings/
loras: models/loras/
upscale_models: models/upscale_models/
vae: models/vae/
public:
base_path: /public_models/
checkpoints: checkpoints
clip: clip
clip_vision: clip_vision
configs: configs
controlnet: controlnet
embeddings: embeddings
loras: loras
upscale_models: upscale_models
vae: vae
private:
base_path: /private_models/
checkpoints: checkpoints
clip: clip
clip_vision: clip_vision
configs: configs
controlnet: controlnet
embeddings: embeddings
loras: loras
upscale_models: upscale_models
vae: vae
@@ -49,15 +49,9 @@ with open('models.json') as f:
models = json.load(f)
for model in models:
import os
if "civitai.com/api" in model['url'] and not "token=" in model['url']:
if "?" in model['url']:
model['url'] += "&token=" + os.environ.get('CIVITAI_TOKEN', '')
else:
model['url'] += "?token=" + os.environ.get('CIVITAI_TOKEN', '')
response = requests.request("POST", f"{root_url}/model/install", json=model, headers=headers)
print(response.text)
# Close the server
server_process.terminate()
print("Finished installing dependencies.")
print("Finished installing dependencies.")
@@ -1,5 +1,10 @@
{
"comfyui": "d0165d819afe76bd4e6bdd710eb5f3e571b6a804",
"git_custom_nodes": {},
"file_custom_nodes": []
}
"comfyui": "d0165d819afe76bd4e6bdd710eb5f3e571b6a804",
"git_custom_nodes": {
"https://github.com/BennyKok/comfyui-deploy.git": {
"hash": "a838cb7ad425e5652c3931fbafdc886b53c48a22",
"disabled": false
}
},
"file_custom_nodes": []
}
@@ -0,0 +1,9 @@
import modal
from config import config
public_model_volume = modal.Volume.persisted(config["public_model_volume"])
private_volume = modal.Volume.persisted(config["private_model_volume"])
PUBLIC_BASEMODEL_DIR = "/public_models"
PRIVATE_BASEMODEL_DIR = "/private_models"
volumes = {PUBLIC_BASEMODEL_DIR: public_model_volume, PRIVATE_BASEMODEL_DIR: private_volume}
@@ -0,0 +1,74 @@
import modal
from config import config
import os
import subprocess
from pprint import pprint
stub = modal.Stub()
# Volume names may only contain alphanumeric characters, dashes, periods, and underscores, and must be less than 64 characters in length.
def is_valid_name(name: str) -> bool:
allowed_characters = set("abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789-._")
return 0 < len(name) <= 64 and all(char in allowed_characters for char in name)
def create_volumes(volume_names, paths):
path_to_vol = {}
for volume_name in volume_names.keys():
if not is_valid_name(volume_name):
pass
modal_volume = modal.Volume.persisted(volume_name)
path_to_vol[paths[volume_name]] = modal_volume
return path_to_vol
vol_name_to_links = config["volume_names"]
vol_name_to_path = config["volume_paths"]
callback_url = config["callback_url"]
callback_body = config["callback_body"]
civitai_key = config["civitai_api_key"]
volumes = create_volumes(vol_name_to_links, vol_name_to_path)
image = (
modal.Image.debian_slim().apt_install("wget").pip_install("requests")
)
# download config { "download_url": "", "folder_path": ""}
timeout=5000
@stub.function(volumes=volumes, image=image, timeout=timeout, gpu=None)
def download_model(volume_name, download_config):
import requests
download_url = download_config["download_url"]
folder_path = download_config["folder_path"]
volume_base_path = vol_name_to_path[volume_name]
model_store_path = os.path.join(volume_base_path, folder_path)
modified_download_url = download_url + ("&" if "?" in download_url else "?") + "token=" + civitai_key
print('downloading', modified_download_url)
subprocess.run(["wget", modified_download_url , "--content-disposition", "-P", model_store_path])
subprocess.run(["ls", "-la", volume_base_path])
subprocess.run(["ls", "-la", model_store_path])
volumes[volume_base_path].commit()
status = {"status": "success"}
requests.post(callback_url, json={**status, **callback_body})
print(f"finished! sending to {callback_url}")
pprint({**status, **callback_body})
@stub.local_entrypoint()
def simple_download():
import requests
try:
list(download_model.starmap([(vol_name, link) for vol_name,link in vol_name_to_links.items()]))
except modal.exception.FunctionTimeoutError as e:
status = {"status": "failed", "error_logs": f"{str(e)}", "timeout": timeout}
requests.post(callback_url, json={**status, **callback_body})
print(f"finished! sending to {callback_url}")
pprint({**status, **callback_body})
except Exception as e:
status = {"status": "failed", "error_logs": str(e)}
requests.post(callback_url, json={**status, **callback_body})
print(f"finished! sending to {callback_url}")
pprint({**status, **callback_body})
@@ -0,0 +1,18 @@
config = {
"volume_names": {
"user4": {
"download_url": "https://civitai.com/api/download/models/11745",
"folder_path": "checkpoints"
}
},
"volume_paths": {
"user4": "/volumes/something",
},
"callback_url": "",
"callback_body": {
"model_id": "",
"volume_id": "",
"folder_path": "checkpoints",
},
"civitai_api_key": "",
}
-82
View File
@@ -1,82 +0,0 @@
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)"
}
-36
View File
@@ -1,36 +0,0 @@
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)"}
+6 -21
View File
@@ -5,12 +5,6 @@ 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):
@@ -22,32 +16,23 @@ class ComfyUIDeployExternalCheckpoint:
),
},
"optional": {
"default_value": (folder_paths.get_filename_list("checkpoints"), ),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
),
"default_checkpoint_name": (folder_paths.get_filename_list("checkpoints"), ),
}
}
RETURN_TYPES = (WILDCARD,)
RETURN_TYPES = (folder_paths.get_filename_list("checkpoints"),)
RETURN_NAMES = ("path",)
FUNCTION = "run"
CATEGORY = "🔗ComfyDeploy"
CATEGORY = "deploy"
def run(self, input_id, default_value=None, display_name=None, description=None):
def run(self, input_id, default_checkpoint_name=None):
import requests
import os
import uuid
if default_value.startswith('http'):
if input_id and input_id.startswith('http'):
unique_filename = str(uuid.uuid4()) + ".safetensors"
print(unique_filename)
print(folder_paths.folder_names_and_paths["checkpoints"][0][0])
@@ -74,7 +59,7 @@ class ComfyUIDeployExternalCheckpoint:
out_file.write(chunk)
return (unique_filename,)
else:
return (default_value,)
return (default_checkpoints_name,)
NODE_CLASS_MAPPINGS = {
-46
View File
@@ -1,46 +0,0 @@
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]
-110
View File
@@ -1,110 +0,0 @@
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)"
}
-106
View File
@@ -1,106 +0,0 @@
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)"
}
-137
View File
@@ -1,137 +0,0 @@
import folder_paths
class AnyType(str):
def __ne__(self, __value: object) -> bool:
return False
WILDCARD = AnyType("*")
class ComfyUIDeployExternalFile:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"input_id": (
"STRING",
{"multiline": False, "default": "input_file"},
),
},
"optional": {
"display_name": (
"STRING",
{"multiline": False, "default": ""},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
),
"file_url": (
"STRING",
{"multiline": False, "default": ""},
),
},
}
RETURN_TYPES = (WILDCARD,)
RETURN_NAMES = ("path",)
FUNCTION = "run"
CATEGORY = "🔗ComfyDeploy"
def run(
self,
input_id,
display_name=None,
description=None,
file_url=None,
):
import requests
import os
import uuid
from urllib.parse import urlparse
if file_url:
if file_url.startswith("http"):
# Use cache directory for saving files
cache_dir = folder_paths.get_temp_directory()
if not os.path.exists(cache_dir):
os.makedirs(cache_dir)
# Always generate random filename to avoid conflicts
parsed_url = urlparse(file_url)
original_filename = os.path.basename(parsed_url.path)
# Extract file extension from original filename if available
file_extension = ""
if original_filename and "." in original_filename:
file_extension = os.path.splitext(original_filename)[1]
else:
# Try to determine extension from content-type if no extension found
file_extension = ".bin"
# Generate random filename with preserved extension
filename = str(uuid.uuid4()) + file_extension
destination_path = os.path.join(cache_dir, filename)
print(f"Cache directory: {cache_dir}")
print(f"Destination path: {destination_path}")
print(
"Downloading external file - "
+ file_url
+ " to "
+ destination_path
)
headers = {"User-Agent": "Mozilla/5.0"}
try:
response = requests.get(
file_url,
headers=headers,
allow_redirects=True,
timeout=30, # Add timeout to prevent hanging
)
response.raise_for_status()
with open(destination_path, "wb") as out_file:
out_file.write(response.content)
print(f"External file downloaded: {file_url} to {destination_path}")
return (destination_path,)
except requests.exceptions.HTTPError as e:
error_msg = f"HTTP Error {e.response.status_code}: {e.response.reason} for URL: {file_url}"
print(f"⚠️ Download failed - {error_msg}")
if e.response.status_code == 404:
print(
"💡 This URL might have expired or the file may have been deleted"
)
# Return empty string instead of crashing
return ("",)
except requests.exceptions.RequestException as e:
error_msg = (
f"Network error downloading file from {file_url}: {str(e)}"
)
print(f"⚠️ Download failed - {error_msg}")
return ("",)
except Exception as e:
error_msg = (
f"Unexpected error downloading file from {file_url}: {str(e)}"
)
print(f"⚠️ Download failed - {error_msg}")
return ("",)
else:
print(f"External file loading: {file_url}")
return (file_url,)
else:
print(f"No file URL provided")
return ("",)
NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalFile": ComfyUIDeployExternalFile}
NODE_DISPLAY_NAME_MAPPINGS = {
"ComfyUIDeployExternalFile": "External File (ComfyUI Deploy)"
}
+29 -48
View File
@@ -15,61 +15,42 @@ 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"
def run(self, input_id, default_value=None, display_name=None, description=None, default_value_url=None):
FUNCTION = "run"
CATEGORY = "image"
def run(self, input_id, default_value=None):
image = default_value
# 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]
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]
NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalImage": ComfyUIDeployExternalImage}
+5 -11
View File
@@ -15,23 +15,17 @@ 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"
def run(self, input_id, default_value=None, display_name=None, description=None):
FUNCTION = "run"
CATEGORY = "image"
def run(self, input_id, default_value=None):
image = default_value
try:
if input_id.startswith('http'):
-111
View File
@@ -1,111 +0,0 @@
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)"}
+25 -86
View File
@@ -1,12 +1,8 @@
import folder_paths
class AnyType(str):
def __ne__(self, __value: object) -> bool:
return False
WILDCARD = AnyType("*")
from PIL import Image, ImageOps
import numpy as np
import torch
import folder_paths
class ComfyUIDeployExternalLora:
@@ -20,93 +16,36 @@ class ComfyUIDeployExternalLora:
),
},
"optional": {
"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": ""},
),
},
"default_lora_name": (folder_paths.get_filename_list("loras"), ),
}
}
RETURN_TYPES = (WILDCARD,)
RETURN_TYPES = (folder_paths.get_filename_list("loras"),)
RETURN_NAMES = ("path",)
FUNCTION = "run"
CATEGORY = "🔗ComfyDeploy"
def run(
self,
input_id,
default_lora_name=None,
lora_save_name=None,
display_name=None,
description=None,
lora_url=None,
bearer_token=None,
):
FUNCTION = "run"
CATEGORY = "deploy"
def run(self, input_id, default_lora_name=None):
import requests
import os
import uuid
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,)
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,)
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)"}
+8 -17
View File
@@ -16,31 +16,22 @@ class ComfyUIDeployExternalNumber:
"optional": {
"default_value": (
"FLOAT",
{"multiline": True, "display": "number", "default": 0, "min": -2147483647, "max": 2147483647, "step": 0.01},
),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
{"multiline": True, "display": "number", "default": 0},
),
}
}
RETURN_TYPES = ("FLOAT",)
RETURN_NAMES = ("value",)
FUNCTION = "run"
CATEGORY = "🔗ComfyDeploy"
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:
FUNCTION = "run"
CATEGORY = "number"
def run(self, input_id, default_value=None):
if not input_id or not input_id.strip().isdigit():
return [default_value]
return [int(input_id)]
NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalNumber": ComfyUIDeployExternalNumber}
+7 -13
View File
@@ -16,26 +16,20 @@ class ComfyUIDeployExternalNumberInt:
"optional": {
"default_value": (
"INT",
{"multiline": True, "display": "number", "min": -2147483647, "max": 2147483647, "default": 0},
),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
{"multiline": True, "display": "number", "default": 0},
),
}
}
RETURN_TYPES = ("INT",)
RETURN_NAMES = ("value",)
FUNCTION = "run"
CATEGORY = "🔗ComfyDeploy"
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()):
FUNCTION = "run"
CATEGORY = "number"
def run(self, input_id, default_value=None):
if not input_id or not input_id.strip().isdigit():
return [default_value]
return [int(input_id)]
-54
View File
@@ -1,54 +0,0 @@
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)"}
-54
View File
@@ -1,54 +0,0 @@
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)"}
-116
View File
@@ -1,116 +0,0 @@
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)"
}
-53
View File
@@ -1,53 +0,0 @@
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)",
}
+5 -11
View File
@@ -18,14 +18,6 @@ class ComfyUIDeployExternalText:
"STRING",
{"multiline": True, "default": ""},
),
"display_name": (
"STRING",
{"multiline": False, "default": ""},
),
"description": (
"STRING",
{"multiline": True, "default": ""},
),
}
}
@@ -34,10 +26,12 @@ class ComfyUIDeployExternalText:
FUNCTION = "run"
CATEGORY = "🔗ComfyDeploy"
CATEGORY = "text"
def run(self, input_id, default_value=None, display_name=None, description=None):
return [default_value]
def run(self, input_id, default_value=None):
if not input_id or len(input_id.strip()) == 0:
return [default_value]
return [input_id]
NODE_CLASS_MAPPINGS = {"ComfyUIDeployExternalText": ComfyUIDeployExternalText}
-46
View File
@@ -1,46 +0,0 @@
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)"}
-79
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@@ -1,79 +0,0 @@
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"
}
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# 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)"
}
-67
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@@ -1,67 +0,0 @@
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)"}
-78
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@@ -1,78 +0,0 @@
# 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)"}
-168
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@@ -1,168 +0,0 @@
import folder_paths
import os
import shutil
import uuid
class AnyType(str):
def __ne__(self, __value: object) -> bool:
return False
WILDCARD = AnyType("*")
class ComfyDeployOutputFile:
def __init__(self):
self.output_dir = folder_paths.get_output_directory()
self.type = "output"
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"file_path": (
"STRING",
{
"forceInput": True,
"tooltip": "Path to the file to output and upload.",
},
),
},
"optional": {
"output_id": (
"STRING",
{"multiline": False, "default": "output_file"},
),
},
}
RETURN_TYPES = ()
FUNCTION = "run"
OUTPUT_NODE = True
CATEGORY = "🔗ComfyDeploy"
DESCRIPTION = "Outputs any file by path for upload to ComfyDeploy."
def run(self, file_path, output_id="output_file"):
if not file_path or not os.path.exists(file_path):
print(f"⚠️ File not found: {file_path}")
return {"ui": {"files": []}}
# Security checks - ensure file is within safe ComfyUI paths
try:
# Get absolute paths for comparison
file_abs_path = os.path.abspath(file_path)
base_path = folder_paths.base_path
temp_dir = folder_paths.get_temp_directory()
# Check if file is within ComfyUI base path or temp directory
if not (
file_abs_path.startswith(os.path.abspath(base_path))
or file_abs_path.startswith(os.path.abspath(temp_dir))
):
print(f"⚠️ Security: File outside allowed ComfyUI paths: {file_path}")
return {"ui": {"files": []}}
# Check for path traversal attempts (but allow absolute paths within ComfyUI)
if ".." in file_path:
print(f"⚠️ Security: Path traversal attempt detected: {file_path}")
return {"ui": {"files": []}}
except Exception as e:
print(f"⚠️ Security check failed: {str(e)}")
return {"ui": {"files": []}}
# Get the original filename and extension
original_filename = os.path.basename(file_path)
file_extension = os.path.splitext(original_filename)[1]
# Additional filename security check
if ".." in original_filename:
print(f"⚠️ Security: Insecure filename: {original_filename}")
return {"ui": {"files": []}}
results = []
# Check if file is in output folder, if not, symlink it there
try:
if file_path.startswith(self.output_dir):
# File is already in output directory - use as is
relative_path = os.path.relpath(file_path, self.output_dir)
path_parts = relative_path.split(os.sep)
if len(path_parts) > 1:
subfolder = os.sep.join(path_parts[:-1])
else:
subfolder = ""
filename = path_parts[-1]
file_type = self.type
else:
# File is not in output folder - symlink it to output/temp
print(
f"File is not in output folder, symlinking to output/temp: {file_path}"
)
output_temp_dir = os.path.join(self.output_dir, "temp")
if not os.path.exists(output_temp_dir):
os.makedirs(output_temp_dir)
# Use the existing filename but with UUID prefix to avoid conflicts
file_ext = os.path.splitext(original_filename)[1]
temp_filename = f"{uuid.uuid4()}{file_ext}"
temp_path = os.path.join(output_temp_dir, temp_filename)
# Create symlink to file in output/temp directory where upload system expects it
try:
# Remove existing symlink if it exists
if os.path.exists(temp_path):
os.remove(temp_path)
os.symlink(file_path, temp_path)
print(f"File symlinked to output/temp: {temp_path} -> {file_path}")
except OSError as e:
# Fall back to copying if symlink fails
print(f"Symlink failed ({e}), falling back to copy")
shutil.copy2(file_path, temp_path)
print(f"File copied to output/temp: {temp_path}")
# Use output/temp directory structure for upload
subfolder = "temp"
filename = temp_filename
file_type = self.type
results.append(
{
"filename": filename,
"subfolder": subfolder,
"type": file_type,
"output_id": output_id,
}
)
except Exception as e:
print(f"⚠️ Error processing file path: {str(e)}")
return {"ui": {"files": []}}
# Determine the appropriate UI key based on file type
file_ext = file_extension.lower()
if file_ext in [".png", ".jpg", ".jpeg", ".webp", ".gif", ".bmp", ".tiff"]:
ui_key = "images"
elif file_ext in [".mp3", ".wav", ".flac", ".aac", ".ogg"]:
ui_key = "audio"
elif file_ext in [".txt", ".json", ".md", ".csv"]:
ui_key = "text_file"
elif file_ext in [".exr", ".hdr"]:
ui_key = "images" # EXR files are still images
elif file_ext in [".zip", ".psb", ".psd"]:
ui_key = "files" # Archives and Photoshop project files
else:
ui_key = "files" # Generic files
return {"ui": {ui_key: results}}
NODE_CLASS_MAPPINGS = {
"ComfyDeployOutputFile": ComfyDeployOutputFile,
}
NODE_DISPLAY_NAME_MAPPINGS = {
"ComfyDeployOutputFile": "File Output (ComfyDeploy)",
}
-104
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@@ -1,104 +0,0 @@
import os
import json
import numpy as np
from PIL import Image
from PIL.PngImagePlugin import PngInfo
import folder_paths
from comfy.cli_args import args
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 = None
if not args.disable_metadata:
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)"}
-99
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@@ -1,99 +0,0 @@
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)"}
-69
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@@ -1,69 +0,0 @@
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)"}
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{
"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": [
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"",
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{
"id": 5,
"type": "Note",
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"size": [
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"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"
}
],
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[
1,
1,
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{
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{
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],
"outputs": [
{
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"type": "IMAGE",
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}
],
"properties": {
"cnr_id": "comfy-core",
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{
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"size": [
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"flags": {},
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"inputs": [
{
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],
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"properties": {
"cnr_id": "comfy-core",
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},
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},
{
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"order": 0,
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"inputs": [],
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{
"name": "IMAGE",
"type": "IMAGE",
"links": [
10
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},
{
"name": "MASK",
"type": "MASK",
"links": [
12
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}
],
"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.27",
"Node name for S&R": "LoadImage"
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"widgets_values": [
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{
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"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"
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{
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}
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21
]
}
],
"properties": {
"cnr_id": "comfy-core",
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{
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"size": [
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"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",
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"size": [
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"flags": {},
"order": 16,
"mode": 0,
"inputs": [
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"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
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},
{
"id": 14,
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"flags": {},
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"mode": 0,
"inputs": [
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"link": 14
}
],
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"properties": {
"cnr_id": "comfy-core",
"ver": "0.3.27",
"Node name for S&R": "PreviewImage"
},
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},
{
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"flags": {},
"order": 15,
"mode": 0,
"inputs": [
{
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"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,
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"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,
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"mode": 0,
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{
"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": [
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],
"size": [
315,
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],
"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": [
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"size": [
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"flags": {},
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"mode": 0,
"inputs": [
{
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"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": [
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1182.81298828125
],
"size": [
340.20001220703125,
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],
"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": [
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],
"size": [
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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": [
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],
"size": [
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],
"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": [
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"",
"",
"",
""
]
},
{
"id": 12,
"type": "ComfyUIDeployExternalImageAlpha",
"pos": [
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418.2679138183594
],
"size": [
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"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"
],
[
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20,
0,
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0,
"IMAGE"
],
[
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0,
"IMAGE"
],
[
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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
}
-359
View File
@@ -1,359 +0,0 @@
{
"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],
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"size": [282.8599853515625, 164.0800018310547],
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"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",
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-423
View File
@@ -1,423 +0,0 @@
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View File
@@ -1,482 +0,0 @@
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View File
@@ -1,240 +0,0 @@
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-409
View File
@@ -1,409 +0,0 @@
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"size": [390.5999755859375, 366],
"type": "ComfyUIDeployExternalImage",
"flags": {},
"order": 1,
"inputs": [
{ "link": null, "name": "default_value", "type": "IMAGE", "shape": 7 }
],
"outputs": [{ "name": "image", "type": "IMAGE", "links": [9, 17] }],
"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",
""
]
},
{
"id": 12,
"pos": [-60.4345588684082, 1465.6741943359375],
"mode": 0,
"size": [400, 200],
"type": "ComfyUIDeployExternalText",
"flags": {},
"order": 2,
"inputs": [],
"outputs": [{ "name": "text", "type": "STRING", "links": [22] }],
"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 video. This could be colors, objects, scenery and even the small details (e.g. moustache, blurry, low resolution). "
]
},
{
"id": 13,
"pos": [-54.3256721496582, 1720.8292236328125],
"mode": 0,
"size": [453.5999755859375, 200],
"type": "ComfyUIDeployExternalNumberInt",
"flags": {},
"order": 3,
"inputs": [],
"outputs": [
{ "name": "value", "type": "INT", "links": [10], "slot_index": 0 }
],
"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
}
-359
View File
@@ -1,359 +0,0 @@
{
"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
}
-137
View File
@@ -1,137 +0,0 @@
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)
+33 -50
View File
@@ -7,60 +7,46 @@ import threading
import logging
from logging.handlers import RotatingFileHandler
# Running with export CD_ENABLE_LOG=true; python main.py
handler = RotatingFileHandler('comfy-deploy.log', maxBytes=500000, backupCount=5)
# Check for 'cd-enable-log' flag in input arguments
# cd_enable_log = '--cd-enable-log' in sys.argv
cd_enable_log = os.environ.get('CD_ENABLE_LOG', 'false').lower() == 'true'
original_stdout = sys.stdout
original_stderr = sys.stderr
def setup():
handler = RotatingFileHandler('comfy-deploy.log', maxBytes=500000, backupCount=5)
class StreamToLogger():
def __init__(self, log_level):
self.log_level = log_level
original_stdout = sys.stdout
original_stderr = sys.stderr
def write(self, buf):
if (self.log_level == logging.INFO):
original_stdout.write(buf)
original_stdout.flush()
elif (self.log_level == logging.ERROR):
original_stderr.write(buf)
original_stderr.flush()
class StreamToLogger():
def __init__(self, log_level):
self.log_level = log_level
def write(self, buf):
if (self.log_level == logging.INFO):
original_stdout.write(buf)
original_stdout.flush()
elif (self.log_level == logging.ERROR):
original_stderr.write(buf)
original_stderr.flush()
for line in buf.rstrip().splitlines():
handler.handle(
logging.LogRecord(
name="comfy-deploy",
level=self.log_level,
pathname="prestartup_script.py",
lineno=1,
msg=line.rstrip(),
args=None,
exc_info=None
)
for line in buf.rstrip().splitlines():
handler.handle(
logging.LogRecord(
name="comfy-deploy",
level=self.log_level,
pathname="prestartup_script.py",
lineno=1,
msg=line.rstrip(),
args=None,
exc_info=None
)
)
def flush(self):
if (self.log_level == logging.INFO):
original_stdout.flush()
elif (self.log_level == logging.ERROR):
original_stderr.flush()
def flush(self):
if (self.log_level == logging.INFO):
original_stdout.flush()
elif (self.log_level == logging.ERROR):
original_stderr.flush()
# Redirect stdout and stderr to the logger
sys.stdout = StreamToLogger(logging.INFO)
sys.stderr = StreamToLogger(logging.ERROR)
# Redirect stdout and stderr to the logger
sys.stdout = StreamToLogger(logging.INFO)
sys.stderr = StreamToLogger(logging.ERROR)
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__))
@@ -69,7 +55,4 @@ 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)}")
finally:
# Change back to the original directory
os.chdir(original_cwd)
print(f"** Comfy Deploy failed to get current git commit: {str(e)}")
-15
View File
@@ -1,15 +0,0 @@
[project]
name = "comfyui-deploy"
description = "Open source comfyui deployment platform, a vercel for generative workflow infra."
version = "2.3.9"
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 = ""
-7
View File
@@ -1,7 +0,0 @@
aiofiles
pydantic
opencv-python
imageio-ffmpeg
brotli
tabulate
# logfire
+4
View File
@@ -0,0 +1,4 @@
/** @typedef {import('../../../web/scripts/api.js').api} API*/
import { api as _api } from '../../scripts/api.js';
/** @type {API} */
export const api = _api;
+4
View File
@@ -0,0 +1,4 @@
/** @typedef {import('../../../web/scripts/app.js').ComfyApp} ComfyApp*/
import { app as _app } from '../../scripts/app.js';
/** @type {ComfyApp} */
export const app = _app;
+240 -2693
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-68
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@@ -1,68 +0,0 @@
// 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;
}
}
+18
View File
@@ -0,0 +1,18 @@
// /** @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;
File diff suppressed because it is too large Load Diff
+11
View File
@@ -20,3 +20,14 @@ PLAUSIBLE_DOMAIN=
NEXT_PUBLIC_POSTHOG_KEY="your-api-key"
NEXT_PUBLIC_POSTHOG_HOST="your-ph-address"
NEXT_PUBLIC_CLERK_SIGN_IN_URL=/auth/sign-in
NEXT_PUBLIC_CLERK_SIGN_UP_URL=/auth/sign-up
NEXT_PUBLIC_CLERK_AFTER_SIGN_IN_URL=/
NEXT_PUBLIC_CLERK_AFTER_SIGN_UP_URL=/
STRIPE_API_KEY="sk_test_"
STRIPE_PR_PRO="price_"
STRIPE_PR_ENTERPRISE="price_"
STRIPE_PR_API="price_"
STRIPE_WEBHOOK_SECRET="whsec_"
BIN
View File
Binary file not shown.
@@ -0,0 +1,14 @@
CREATE TABLE IF NOT EXISTS "comfyui_deploy"."user_usage" (
"id" uuid PRIMARY KEY DEFAULT gen_random_uuid() NOT NULL,
"org_id" text,
"user_id" text NOT NULL,
"usage_time" real DEFAULT 0 NOT NULL,
"created_at" timestamp DEFAULT now() NOT NULL,
"ended_at" timestamp DEFAULT now() NOT NULL
);
--> statement-breakpoint
DO $$ BEGIN
ALTER TABLE "comfyui_deploy"."user_usage" ADD CONSTRAINT "user_usage_user_id_users_id_fk" FOREIGN KEY ("user_id") REFERENCES "comfyui_deploy"."users"("id") ON DELETE cascade ON UPDATE no action;
EXCEPTION
WHEN duplicate_object THEN null;
END $$;
+22
View File
@@ -0,0 +1,22 @@
DO $$ BEGIN
CREATE TYPE "subscription_plan" AS ENUM('basic', 'pro', 'enterprise');
EXCEPTION
WHEN duplicate_object THEN null;
END $$;
--> statement-breakpoint
DO $$ BEGIN
CREATE TYPE "subscription_plan_status" AS ENUM('active', 'deleted', 'paused');
EXCEPTION
WHEN duplicate_object THEN null;
END $$;
--> statement-breakpoint
CREATE TABLE IF NOT EXISTS "comfyui_deploy"."subscription_status" (
"stripe_customer_id" text PRIMARY KEY NOT NULL,
"user_id" text,
"org_id" text,
"plan" "subscription_plan" NOT NULL,
"status" "subscription_plan_status" NOT NULL,
"subscription_plan_id" text,
"created_at" timestamp DEFAULT now() NOT NULL,
"updated_at" timestamp DEFAULT now() NOT NULL
);
+3
View File
@@ -0,0 +1,3 @@
ALTER TABLE "comfyui_deploy"."subscription_status" RENAME COLUMN "subscription_plan_id" TO "subscription_id";--> statement-breakpoint
ALTER TABLE "comfyui_deploy"."subscription_status" ADD COLUMN "subscription_item_plan_id" text;--> statement-breakpoint
ALTER TABLE "comfyui_deploy"."subscription_status" ADD COLUMN "subscription_item_api_id" text;
+1
View File
@@ -0,0 +1 @@
ALTER TABLE "comfyui_deploy"."subscription_status" ADD COLUMN "cancel_at_period_end" boolean DEFAULT false;
+2
View File
@@ -0,0 +1,2 @@
ALTER TABLE "comfyui_deploy"."workflow_runs" ADD COLUMN "user_id" text;--> statement-breakpoint
ALTER TABLE "comfyui_deploy"."workflow_runs" ADD COLUMN "org_id" text;
+1
View File
@@ -0,0 +1 @@
ALTER TABLE "comfyui_deploy"."workflow_runs" ADD COLUMN "gpu" "machine_gpu";
+1
View File
@@ -0,0 +1 @@
ALTER TABLE "comfyui_deploy"."workflow_runs" ADD COLUMN "machine_type" "machine_type";
+64
View File
@@ -0,0 +1,64 @@
DO $$ BEGIN
CREATE TYPE "model_upload_type" AS ENUM('civitai', 'huggingface', 'other');
EXCEPTION
WHEN duplicate_object THEN null;
END $$;
--> statement-breakpoint
DO $$ BEGIN
CREATE TYPE "resource_upload" AS ENUM('started', 'success', 'failed');
EXCEPTION
WHEN duplicate_object THEN null;
END $$;
--> statement-breakpoint
CREATE TABLE IF NOT EXISTS "comfyui_deploy"."checkpoints" (
"id" uuid PRIMARY KEY DEFAULT gen_random_uuid() NOT NULL,
"user_id" text,
"org_id" text,
"description" text,
"checkpoint_volume_id" uuid NOT NULL,
"model_name" text,
"folder_path" text,
"civitai_id" text,
"civitai_version_id" text,
"civitai_url" text,
"civitai_download_url" text,
"civitai_model_response" jsonb,
"hf_url" text,
"s3_url" text,
"client_url" text,
"is_public" boolean DEFAULT false NOT NULL,
"status" "resource_upload" DEFAULT 'started' NOT NULL,
"upload_machine_id" text,
"upload_type" "model_upload_type" NOT NULL,
"error_log" text,
"created_at" timestamp DEFAULT now() NOT NULL,
"updated_at" timestamp DEFAULT now() NOT NULL
);
--> statement-breakpoint
CREATE TABLE IF NOT EXISTS "comfyui_deploy"."checkpoint_volume" (
"id" uuid PRIMARY KEY DEFAULT gen_random_uuid() NOT NULL,
"user_id" text,
"org_id" text,
"volume_name" text NOT NULL,
"created_at" timestamp DEFAULT now() NOT NULL,
"updated_at" timestamp DEFAULT now() NOT NULL,
"disabled" boolean DEFAULT false NOT NULL
);
--> statement-breakpoint
DO $$ BEGIN
ALTER TABLE "comfyui_deploy"."checkpoints" ADD CONSTRAINT "checkpoints_user_id_users_id_fk" FOREIGN KEY ("user_id") REFERENCES "comfyui_deploy"."users"("id") ON DELETE no action ON UPDATE no action;
EXCEPTION
WHEN duplicate_object THEN null;
END $$;
--> statement-breakpoint
DO $$ BEGIN
ALTER TABLE "comfyui_deploy"."checkpoints" ADD CONSTRAINT "checkpoints_checkpoint_volume_id_checkpoint_volume_id_fk" FOREIGN KEY ("checkpoint_volume_id") REFERENCES "comfyui_deploy"."checkpoint_volume"("id") ON DELETE cascade ON UPDATE no action;
EXCEPTION
WHEN duplicate_object THEN null;
END $$;
--> statement-breakpoint
DO $$ BEGIN
ALTER TABLE "comfyui_deploy"."checkpoint_volume" ADD CONSTRAINT "checkpoint_volume_user_id_users_id_fk" FOREIGN KEY ("user_id") REFERENCES "comfyui_deploy"."users"("id") ON DELETE no action ON UPDATE no action;
EXCEPTION
WHEN duplicate_object THEN null;
END $$;
+33
View File
@@ -0,0 +1,33 @@
DO $$ BEGIN
CREATE TYPE "model_type" AS ENUM('checkpoint', 'lora', 'embedding', 'vae');
EXCEPTION
WHEN duplicate_object THEN null;
END $$;
--> statement-breakpoint
ALTER TABLE "comfyui_deploy"."checkpoints" RENAME TO "models";--> statement-breakpoint
ALTER TABLE "comfyui_deploy"."checkpoint_volume" RENAME TO "user_volume";--> statement-breakpoint
ALTER TABLE "comfyui_deploy"."models" RENAME COLUMN "checkpoint_volume_id" TO "user_volume_id";--> statement-breakpoint
ALTER TABLE "comfyui_deploy"."models" DROP CONSTRAINT "checkpoints_user_id_users_id_fk";
--> statement-breakpoint
ALTER TABLE "comfyui_deploy"."models" DROP CONSTRAINT "checkpoints_checkpoint_volume_id_checkpoint_volume_id_fk";
--> statement-breakpoint
ALTER TABLE "comfyui_deploy"."user_volume" DROP CONSTRAINT "checkpoint_volume_user_id_users_id_fk";
--> statement-breakpoint
ALTER TABLE "comfyui_deploy"."models" ADD COLUMN "model_type" "model_type" DEFAULT 'checkpoint' NOT NULL;--> statement-breakpoint
DO $$ BEGIN
ALTER TABLE "comfyui_deploy"."models" ADD CONSTRAINT "models_user_id_users_id_fk" FOREIGN KEY ("user_id") REFERENCES "comfyui_deploy"."users"("id") ON DELETE no action ON UPDATE no action;
EXCEPTION
WHEN duplicate_object THEN null;
END $$;
--> statement-breakpoint
DO $$ BEGIN
ALTER TABLE "comfyui_deploy"."models" ADD CONSTRAINT "models_user_volume_id_user_volume_id_fk" FOREIGN KEY ("user_volume_id") REFERENCES "comfyui_deploy"."user_volume"("id") ON DELETE cascade ON UPDATE no action;
EXCEPTION
WHEN duplicate_object THEN null;
END $$;
--> statement-breakpoint
DO $$ BEGIN
ALTER TABLE "comfyui_deploy"."user_volume" ADD CONSTRAINT "user_volume_user_id_users_id_fk" FOREIGN KEY ("user_id") REFERENCES "comfyui_deploy"."users"("id") ON DELETE no action ON UPDATE no action;
EXCEPTION
WHEN duplicate_object THEN null;
END $$;
@@ -0,0 +1 @@
ALTER TABLE "comfyui_deploy"."models" ALTER COLUMN "is_public" SET DEFAULT true;
+3
View File
@@ -0,0 +1,3 @@
ALTER TYPE "workflow_run_status" ADD VALUE 'started';--> statement-breakpoint
ALTER TYPE "workflow_run_status" ADD VALUE 'queued';--> statement-breakpoint
ALTER TABLE "comfyui_deploy"."workflow_runs" ADD COLUMN "queued_at" timestamp;
+894
View File
@@ -0,0 +1,894 @@
{
"id": "2b2a5d0a-2494-45ea-9d4a-58a70df97829",
"prevId": "8d654f92-7f7e-420f-bbd3-73b6b27adf35",
"version": "5",
"dialect": "pg",
"tables": {
"api_keys": {
"name": "api_keys",
"schema": "comfyui_deploy",
"columns": {
"id": {
"name": "id",
"type": "uuid",
"primaryKey": true,
"notNull": true,
"default": "gen_random_uuid()"
},
"key": {
"name": "key",
"type": "text",
"primaryKey": false,
"notNull": true
},
"name": {
"name": "name",
"type": "text",
"primaryKey": false,
"notNull": true
},
"user_id": {
"name": "user_id",
"type": "text",
"primaryKey": false,
"notNull": true
},
"org_id": {
"name": "org_id",
"type": "text",
"primaryKey": false,
"notNull": false
},
"revoked": {
"name": "revoked",
"type": "boolean",
"primaryKey": false,
"notNull": true,
"default": false
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
},
"updated_at": {
"name": "updated_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
}
},
"indexes": {},
"foreignKeys": {
"api_keys_user_id_users_id_fk": {
"name": "api_keys_user_id_users_id_fk",
"tableFrom": "api_keys",
"tableTo": "users",
"columnsFrom": [
"user_id"
],
"columnsTo": [
"id"
],
"onDelete": "cascade",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
"uniqueConstraints": {
"api_keys_key_unique": {
"name": "api_keys_key_unique",
"nullsNotDistinct": false,
"columns": [
"key"
]
}
}
},
"auth_requests": {
"name": "auth_requests",
"schema": "comfyui_deploy",
"columns": {
"request_id": {
"name": "request_id",
"type": "text",
"primaryKey": true,
"notNull": true
},
"user_id": {
"name": "user_id",
"type": "text",
"primaryKey": false,
"notNull": false
},
"org_id": {
"name": "org_id",
"type": "text",
"primaryKey": false,
"notNull": false
},
"api_hash": {
"name": "api_hash",
"type": "text",
"primaryKey": false,
"notNull": false
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
},
"expired_date": {
"name": "expired_date",
"type": "timestamp",
"primaryKey": false,
"notNull": false
},
"updated_at": {
"name": "updated_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
}
},
"indexes": {},
"foreignKeys": {},
"compositePrimaryKeys": {},
"uniqueConstraints": {}
},
"deployments": {
"name": "deployments",
"schema": "comfyui_deploy",
"columns": {
"id": {
"name": "id",
"type": "uuid",
"primaryKey": true,
"notNull": true,
"default": "gen_random_uuid()"
},
"user_id": {
"name": "user_id",
"type": "text",
"primaryKey": false,
"notNull": true
},
"org_id": {
"name": "org_id",
"type": "text",
"primaryKey": false,
"notNull": false
},
"workflow_version_id": {
"name": "workflow_version_id",
"type": "uuid",
"primaryKey": false,
"notNull": true
},
"workflow_id": {
"name": "workflow_id",
"type": "uuid",
"primaryKey": false,
"notNull": true
},
"machine_id": {
"name": "machine_id",
"type": "uuid",
"primaryKey": false,
"notNull": true
},
"share_slug": {
"name": "share_slug",
"type": "text",
"primaryKey": false,
"notNull": false
},
"description": {
"name": "description",
"type": "text",
"primaryKey": false,
"notNull": false
},
"showcase_media": {
"name": "showcase_media",
"type": "jsonb",
"primaryKey": false,
"notNull": false
},
"environment": {
"name": "environment",
"type": "deployment_environment",
"primaryKey": false,
"notNull": true
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
},
"updated_at": {
"name": "updated_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
}
},
"indexes": {},
"foreignKeys": {
"deployments_user_id_users_id_fk": {
"name": "deployments_user_id_users_id_fk",
"tableFrom": "deployments",
"tableTo": "users",
"columnsFrom": [
"user_id"
],
"columnsTo": [
"id"
],
"onDelete": "cascade",
"onUpdate": "no action"
},
"deployments_workflow_version_id_workflow_versions_id_fk": {
"name": "deployments_workflow_version_id_workflow_versions_id_fk",
"tableFrom": "deployments",
"tableTo": "workflow_versions",
"columnsFrom": [
"workflow_version_id"
],
"columnsTo": [
"id"
],
"onDelete": "no action",
"onUpdate": "no action"
},
"deployments_workflow_id_workflows_id_fk": {
"name": "deployments_workflow_id_workflows_id_fk",
"tableFrom": "deployments",
"tableTo": "workflows",
"columnsFrom": [
"workflow_id"
],
"columnsTo": [
"id"
],
"onDelete": "cascade",
"onUpdate": "no action"
},
"deployments_machine_id_machines_id_fk": {
"name": "deployments_machine_id_machines_id_fk",
"tableFrom": "deployments",
"tableTo": "machines",
"columnsFrom": [
"machine_id"
],
"columnsTo": [
"id"
],
"onDelete": "no action",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
"uniqueConstraints": {
"deployments_share_slug_unique": {
"name": "deployments_share_slug_unique",
"nullsNotDistinct": false,
"columns": [
"share_slug"
]
}
}
},
"machines": {
"name": "machines",
"schema": "comfyui_deploy",
"columns": {
"id": {
"name": "id",
"type": "uuid",
"primaryKey": true,
"notNull": true,
"default": "gen_random_uuid()"
},
"user_id": {
"name": "user_id",
"type": "text",
"primaryKey": false,
"notNull": true
},
"name": {
"name": "name",
"type": "text",
"primaryKey": false,
"notNull": true
},
"org_id": {
"name": "org_id",
"type": "text",
"primaryKey": false,
"notNull": false
},
"endpoint": {
"name": "endpoint",
"type": "text",
"primaryKey": false,
"notNull": true
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
},
"updated_at": {
"name": "updated_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
},
"disabled": {
"name": "disabled",
"type": "boolean",
"primaryKey": false,
"notNull": true,
"default": false
},
"auth_token": {
"name": "auth_token",
"type": "text",
"primaryKey": false,
"notNull": false
},
"type": {
"name": "type",
"type": "machine_type",
"primaryKey": false,
"notNull": true,
"default": "'classic'"
},
"status": {
"name": "status",
"type": "machine_status",
"primaryKey": false,
"notNull": true,
"default": "'ready'"
},
"snapshot": {
"name": "snapshot",
"type": "jsonb",
"primaryKey": false,
"notNull": false
},
"models": {
"name": "models",
"type": "jsonb",
"primaryKey": false,
"notNull": false
},
"gpu": {
"name": "gpu",
"type": "machine_gpu",
"primaryKey": false,
"notNull": false
},
"build_machine_instance_id": {
"name": "build_machine_instance_id",
"type": "text",
"primaryKey": false,
"notNull": false
},
"build_log": {
"name": "build_log",
"type": "text",
"primaryKey": false,
"notNull": false
}
},
"indexes": {},
"foreignKeys": {
"machines_user_id_users_id_fk": {
"name": "machines_user_id_users_id_fk",
"tableFrom": "machines",
"tableTo": "users",
"columnsFrom": [
"user_id"
],
"columnsTo": [
"id"
],
"onDelete": "cascade",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
"uniqueConstraints": {}
},
"user_usage": {
"name": "user_usage",
"schema": "comfyui_deploy",
"columns": {
"id": {
"name": "id",
"type": "uuid",
"primaryKey": true,
"notNull": true,
"default": "gen_random_uuid()"
},
"org_id": {
"name": "org_id",
"type": "text",
"primaryKey": false,
"notNull": false
},
"user_id": {
"name": "user_id",
"type": "text",
"primaryKey": false,
"notNull": true
},
"usage_time": {
"name": "usage_time",
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},
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},
"_meta": {
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"columns": {}
}
}
+970
View File
@@ -0,0 +1,970 @@
{
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},
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},
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}
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}
},
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}
},
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}
},
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}
},
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}
},
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}
}
},
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},
"_meta": {
"schemas": {},
"tables": {},
"columns": {}
}
}
+984
View File
@@ -0,0 +1,984 @@
{
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},
"workflow_id": {
"name": "workflow_id",
"type": "uuid",
"primaryKey": false,
"notNull": true
},
"machine_id": {
"name": "machine_id",
"type": "uuid",
"primaryKey": false,
"notNull": false
},
"origin": {
"name": "origin",
"type": "workflow_run_origin",
"primaryKey": false,
"notNull": true,
"default": "'api'"
},
"status": {
"name": "status",
"type": "workflow_run_status",
"primaryKey": false,
"notNull": true,
"default": "'not-started'"
},
"ended_at": {
"name": "ended_at",
"type": "timestamp",
"primaryKey": false,
"notNull": false
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
},
"started_at": {
"name": "started_at",
"type": "timestamp",
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"notNull": false
}
},
"indexes": {},
"foreignKeys": {
"workflow_runs_workflow_version_id_workflow_versions_id_fk": {
"name": "workflow_runs_workflow_version_id_workflow_versions_id_fk",
"tableFrom": "workflow_runs",
"tableTo": "workflow_versions",
"columnsFrom": [
"workflow_version_id"
],
"columnsTo": [
"id"
],
"onDelete": "set null",
"onUpdate": "no action"
},
"workflow_runs_workflow_id_workflows_id_fk": {
"name": "workflow_runs_workflow_id_workflows_id_fk",
"tableFrom": "workflow_runs",
"tableTo": "workflows",
"columnsFrom": [
"workflow_id"
],
"columnsTo": [
"id"
],
"onDelete": "cascade",
"onUpdate": "no action"
},
"workflow_runs_machine_id_machines_id_fk": {
"name": "workflow_runs_machine_id_machines_id_fk",
"tableFrom": "workflow_runs",
"tableTo": "machines",
"columnsFrom": [
"machine_id"
],
"columnsTo": [
"id"
],
"onDelete": "set null",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
"uniqueConstraints": {}
},
"workflows": {
"name": "workflows",
"schema": "comfyui_deploy",
"columns": {
"id": {
"name": "id",
"type": "uuid",
"primaryKey": true,
"notNull": true,
"default": "gen_random_uuid()"
},
"user_id": {
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},
"org_id": {
"name": "org_id",
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},
"name": {
"name": "name",
"type": "text",
"primaryKey": false,
"notNull": true
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
},
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"name": "updated_at",
"type": "timestamp",
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"notNull": true,
"default": "now()"
}
},
"indexes": {},
"foreignKeys": {
"workflows_user_id_users_id_fk": {
"name": "workflows_user_id_users_id_fk",
"tableFrom": "workflows",
"tableTo": "users",
"columnsFrom": [
"user_id"
],
"columnsTo": [
"id"
],
"onDelete": "cascade",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
"uniqueConstraints": {}
},
"workflow_versions": {
"name": "workflow_versions",
"schema": "comfyui_deploy",
"columns": {
"workflow_id": {
"name": "workflow_id",
"type": "uuid",
"primaryKey": false,
"notNull": true
},
"id": {
"name": "id",
"type": "uuid",
"primaryKey": true,
"notNull": true,
"default": "gen_random_uuid()"
},
"workflow": {
"name": "workflow",
"type": "jsonb",
"primaryKey": false,
"notNull": false
},
"workflow_api": {
"name": "workflow_api",
"type": "jsonb",
"primaryKey": false,
"notNull": false
},
"version": {
"name": "version",
"type": "integer",
"primaryKey": false,
"notNull": true
},
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"name": "snapshot",
"type": "jsonb",
"primaryKey": false,
"notNull": false
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
},
"updated_at": {
"name": "updated_at",
"type": "timestamp",
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"notNull": true,
"default": "now()"
}
},
"indexes": {},
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"name": "workflow_versions_workflow_id_workflows_id_fk",
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"tableTo": "workflows",
"columnsFrom": [
"workflow_id"
],
"columnsTo": [
"id"
],
"onDelete": "cascade",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
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}
},
"enums": {
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"name": "deployment_environment",
"values": {
"staging": "staging",
"production": "production",
"public-share": "public-share"
}
},
"machine_gpu": {
"name": "machine_gpu",
"values": {
"T4": "T4",
"A10G": "A10G",
"A100": "A100"
}
},
"machine_status": {
"name": "machine_status",
"values": {
"ready": "ready",
"building": "building",
"error": "error"
}
},
"machine_type": {
"name": "machine_type",
"values": {
"classic": "classic",
"runpod-serverless": "runpod-serverless",
"modal-serverless": "modal-serverless",
"comfy-deploy-serverless": "comfy-deploy-serverless"
}
},
"subscription_plan": {
"name": "subscription_plan",
"values": {
"basic": "basic",
"pro": "pro",
"enterprise": "enterprise"
}
},
"subscription_plan_status": {
"name": "subscription_plan_status",
"values": {
"active": "active",
"deleted": "deleted",
"paused": "paused"
}
},
"workflow_run_origin": {
"name": "workflow_run_origin",
"values": {
"manual": "manual",
"api": "api",
"public-share": "public-share"
}
},
"workflow_run_status": {
"name": "workflow_run_status",
"values": {
"not-started": "not-started",
"running": "running",
"uploading": "uploading",
"success": "success",
"failed": "failed"
}
}
},
"schemas": {
"comfyui_deploy": "comfyui_deploy"
},
"_meta": {
"schemas": {},
"tables": {},
"columns": {
"\"comfyui_deploy\".\"subscription_status\".\"subscription_plan_id\"": "\"comfyui_deploy\".\"subscription_status\".\"subscription_id\""
}
}
}
+989
View File
@@ -0,0 +1,989 @@
{
"id": "bd893271-b9ea-4832-a3e8-a6970b9f20d9",
"prevId": "cde8f758-0055-4326-981d-293ac84db54a",
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},
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},
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},
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],
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},
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},
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},
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},
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},
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},
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"default": "gen_random_uuid()"
},
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},
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},
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},
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"default": "now()"
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],
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],
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}
},
"compositePrimaryKeys": {},
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},
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"schema": "comfyui_deploy",
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"default": "gen_random_uuid()"
},
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},
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},
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},
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},
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"type": "workflow_run_origin",
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"notNull": true,
"default": "'api'"
},
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"name": "status",
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"default": "'not-started'"
},
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},
"created_at": {
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"notNull": true,
"default": "now()"
},
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}
},
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"foreignKeys": {
"workflow_runs_workflow_version_id_workflow_versions_id_fk": {
"name": "workflow_runs_workflow_version_id_workflow_versions_id_fk",
"tableFrom": "workflow_runs",
"tableTo": "workflow_versions",
"columnsFrom": [
"workflow_version_id"
],
"columnsTo": [
"id"
],
"onDelete": "set null",
"onUpdate": "no action"
},
"workflow_runs_workflow_id_workflows_id_fk": {
"name": "workflow_runs_workflow_id_workflows_id_fk",
"tableFrom": "workflow_runs",
"tableTo": "workflows",
"columnsFrom": [
"workflow_id"
],
"columnsTo": [
"id"
],
"onDelete": "cascade",
"onUpdate": "no action"
},
"workflow_runs_machine_id_machines_id_fk": {
"name": "workflow_runs_machine_id_machines_id_fk",
"tableFrom": "workflow_runs",
"tableTo": "machines",
"columnsFrom": [
"machine_id"
],
"columnsTo": [
"id"
],
"onDelete": "set null",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
"uniqueConstraints": {}
},
"workflows": {
"name": "workflows",
"schema": "comfyui_deploy",
"columns": {
"id": {
"name": "id",
"type": "uuid",
"primaryKey": true,
"notNull": true,
"default": "gen_random_uuid()"
},
"user_id": {
"name": "user_id",
"type": "text",
"primaryKey": false,
"notNull": true
},
"org_id": {
"name": "org_id",
"type": "text",
"primaryKey": false,
"notNull": false
},
"name": {
"name": "name",
"type": "text",
"primaryKey": false,
"notNull": true
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
},
"updated_at": {
"name": "updated_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
}
},
"indexes": {},
"foreignKeys": {
"workflows_user_id_users_id_fk": {
"name": "workflows_user_id_users_id_fk",
"tableFrom": "workflows",
"tableTo": "users",
"columnsFrom": [
"user_id"
],
"columnsTo": [
"id"
],
"onDelete": "cascade",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
"uniqueConstraints": {}
},
"workflow_versions": {
"name": "workflow_versions",
"schema": "comfyui_deploy",
"columns": {
"workflow_id": {
"name": "workflow_id",
"type": "uuid",
"primaryKey": false,
"notNull": true
},
"id": {
"name": "id",
"type": "uuid",
"primaryKey": true,
"notNull": true,
"default": "gen_random_uuid()"
},
"workflow": {
"name": "workflow",
"type": "jsonb",
"primaryKey": false,
"notNull": false
},
"workflow_api": {
"name": "workflow_api",
"type": "jsonb",
"primaryKey": false,
"notNull": false
},
"version": {
"name": "version",
"type": "integer",
"primaryKey": false,
"notNull": true
},
"snapshot": {
"name": "snapshot",
"type": "jsonb",
"primaryKey": false,
"notNull": false
},
"created_at": {
"name": "created_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
},
"updated_at": {
"name": "updated_at",
"type": "timestamp",
"primaryKey": false,
"notNull": true,
"default": "now()"
}
},
"indexes": {},
"foreignKeys": {
"workflow_versions_workflow_id_workflows_id_fk": {
"name": "workflow_versions_workflow_id_workflows_id_fk",
"tableFrom": "workflow_versions",
"tableTo": "workflows",
"columnsFrom": [
"workflow_id"
],
"columnsTo": [
"id"
],
"onDelete": "cascade",
"onUpdate": "no action"
}
},
"compositePrimaryKeys": {},
"uniqueConstraints": {}
}
},
"enums": {
"deployment_environment": {
"name": "deployment_environment",
"values": {
"staging": "staging",
"production": "production",
"public-share": "public-share"
}
},
"machine_gpu": {
"name": "machine_gpu",
"values": {
"T4": "T4",
"A10G": "A10G",
"A100": "A100"
}
},
"machine_status": {
"name": "machine_status",
"values": {
"ready": "ready",
"building": "building",
"error": "error"
}
},
"machine_type": {
"name": "machine_type",
"values": {
"classic": "classic",
"runpod-serverless": "runpod-serverless",
"modal-serverless": "modal-serverless",
"comfy-deploy-serverless": "comfy-deploy-serverless"
}
},
"subscription_plan": {
"name": "subscription_plan",
"values": {
"basic": "basic",
"pro": "pro",
"enterprise": "enterprise"
}
},
"subscription_plan_status": {
"name": "subscription_plan_status",
"values": {
"active": "active",
"deleted": "deleted",
"paused": "paused"
}
},
"workflow_run_origin": {
"name": "workflow_run_origin",
"values": {
"manual": "manual",
"api": "api",
"public-share": "public-share"
}
},
"workflow_run_status": {
"name": "workflow_run_status",
"values": {
"not-started": "not-started",
"running": "running",
"uploading": "uploading",
"success": "success",
"failed": "failed"
}
}
},
"schemas": {
"comfyui_deploy": "comfyui_deploy"
},
"_meta": {
"schemas": {},
"tables": {},
"columns": {}
}
}
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+77
View File
@@ -246,6 +246,83 @@
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{
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"tag": "0038_yummy_darkhawk",
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"tag": "0039_nostalgic_lyja",
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{
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"tag": "0040_salty_archangel",
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"tag": "0041_thick_norrin_radd",
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{
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"tag": "0042_windy_madelyne_pryor",
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"tag": "0043_wealthy_nicolaos",
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View File
@@ -19,23 +19,26 @@
"@algolia/autocomplete-core": "^1.13.0",
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"@aws-sdk/s3-request-presigner": "^3.472.0",
"@clerk/nextjs": "^4.29.3",
"@clerk/nextjs": "4.29.5",
"@headlessui/react": "^1.7.17",
"@headlessui/tailwindcss": "^0.2.0",
"@hono/swagger-ui": "^0.2.1",
"@hono/zod-openapi": "^0.9.5",
"@hono/zod-validator": "^0.1.11",
"@hookform/resolvers": "^3.3.2",
"@lemonsqueezy/lemonsqueezy.js": "^1.2.5",
"@mdx-js/loader": "^3.0.0",
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@@ -46,6 +49,7 @@
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@@ -74,7 +78,7 @@
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@@ -94,6 +98,7 @@
"shikiji": "^0.9.3",
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"sonner": "^1.2.4",
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