To everyone: this project is not validly licensed. Don't use it.
AGPL 3.0 prohibits the author from imposing additional restrictions on the use of the software, and the README contains this: "**Non-Commercial Use Only:** Commercial use of this software is **not permitted** without an explicit, written license from the author."
Dear author: please contact a lawyer, discard all external contributions and GPLed dependencies accumulated so far, and relicense it under a proprietary license not based on AGPL, which would then legitimise the prohibition of commercial use that still complies with AGPL terms. Alternatively, drop the restriction.
it looks like the `requirements.txt` file was "frozen" from the author's environment (non-windows)
I haven't tested this, but you could try installing just the direct dependencies without all the transient ones, from a quick look I think the list of needed packages is:
flask
flask-cors
python-dotenv
loguru
pillow
torch
diffusers
dfloat11
maybe try without the pinned versions
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I got it working. I essentially removed the requirements that caused errors ( I can give you the requirements.txt file tomorrow if you want ) and then used a Python311 environment, worked like a charm, with Cuda.
I was just installing it right now and got this critical error, do I have to use the env file to use any access token?
https://preview.redd.it/fe1rbds7jqaf1.png?width=960&format=png&auto=webp&s=cc9c39c9eaeb147bd54d91253cb97769526703e8
Yes! I have it in the readme that you need to either login with huggingface-cli tool or to grab a token and set that in the .env
You probably need to request access to the model itself, which is usually granted immediately, on their huggingface model page https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev
I have 16GB 4070TI Super. However, I can't run anything. It complains there's not enough VRAM. What I can do about it?
2025-07-03 08:03:23.847 | ERROR | \_\_main\_\_:image\_generation\_worker:315 - Job 828450ba-77b6-46e3-958b-48fafa4b6032 failed: Processing failed due to insufficient GPU memory. Try a smaller image size or reduce batch size. - CUDA out of memory. Tried to allocate 136.00 MiB. GPU 0 has a total capacity of 15.55 GiB of which 163.44 MiB is free. Process 24097 has 48.21 MiB memory in use. Including non-PyTorch memory, this process has 14.53 GiB memory in use. Of the allocated memory 14.17 GiB is allocated by PyTorch, and 104.61 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH\_CUDA\_ALLOC\_CONF=expandable\_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
Just a heads up, your NC clause makes this **not open source**. Also, AGPL itself says such terms can simply be removed:
Under sectoin 7
> All other non-permissive additional terms are considered "further restrictions" within the meaning of section 10. If the Program as you received it, or any part of it, contains a notice stating that it is governed by this License along with a term that is a further restriction, you may remove that term.
Part of open source is being permissive of commercial use. If it forbids commercial use, it's not open source.
very cool ! I love it !
i was looking for an easier way to generate images than the whole "war machine setup" I found online or shelling coins out ! I'd like to add image generation support in my project ( LiteChat )
Do you mind if I "inspire" myself of your image generation stuff to create some kind of local API server ?
it'll be a separate repo so I'll definitly license it the same as you :)
Switching to A1111 or ComfyUI is next. DreamFactoryAPI auto-generates REST endpoints around their web sockets, handles auth, and lets me map the existing flux routes nearly 1:1. I prototype flows in n8n for queueing jobs, while APIWrapper.ai helps batch the image payloads. So A1111/ComfyUI support is coming.
# Requirements
* **Python 3.11+**
* `pip` or `uv` (Python package installer; `uv` is recommended for speed)
* **NVIDIA GPU** (recommended for speed; CPU fallback supported)
* **\~21GB VRAM** is preferred for the best performance.
* Modern web browser (Chrome, Firefox, Edge, etc.)
* Some images to Ghiblify!
*Info pulled from github page.*
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