unraidrocks

I made significant progress. TLDR: Used Claude to help to create authentication between Matrix Synapse and Jitsi. I'm attaching a document of all the changes that were made for documentation purposes. The one consequence is the Jitsi Widget inside Element will not popout because that HTML code (Widget HTML comes from docker image and needs to get overwritten) the reason Tokens/Authentication wasn't properly passed. The good news is meet domain is useless and calls don't work for anonymous users. Sadly Meet Domain will only work with token authentication. Accounts in Jitsi do not work, but thats ok, because this was meant to work with only Element. The next steps, like you suggested, is to close as many ports as possible. That is the next step. End goal is to have all communication by nginx reverse proxy. matrix-uvs I had to add this to the stack, it required for tokens to get created for Matrix Synapse and Jitsi to authenticate. Again so thankful for this project. matrix-jitsi-auth-docs-SHARE.odt

Thank you so much for your hard work and effort. I was experimenting with Alpine linux, and decided to try the docker compose stack on this Virtual machine I spun up. I had to install this in the same path as Unraid, just because this is what this setup is designed for. Install worked. It installed everything. I had to add a few things, just because I manually put SSL certs for both domains. I did this install without the SSL/TSL certificates (certbot failed) because I already have the certs saved/created by another web app. I just copied over private and fullchain keys. Also, because I did this manually, and in case anyone runs this this issue, NGINX needs the path of the meet.matrix.domain.com certs or else, Jitsi addon won't display inside Element or in web browser. Also I needed to add these lines to nginx for meet.matrix.domain.com Only after adding this, UDP 10000 hits worked (Confirmed) Meetings to jitsi meet.matrix.domain.com are public. (Anyone can make a meeting) # --- ADD THESE --- proxy_http_version 1.1; proxy_set_header Upgrade $http_upgrade; proxy_set_header Connection "upgrade"; proxy_read_timeout 3600s; proxy_send_timeout 3600s; # ------------------ And I finally understand how Jitsi works. The owner of the room creates a Jitsi widget. This is where users can join call, share screen, collab, video chat, ect. The error I kept having was when joining the Jitsi meeting, it immediately closed. Web Socket error. Adding the entries to the NGINX section of meet.matrix.domain.com fixed it. Group chats are a widget, users join, and its good. This is what I modified. I added in BOLD the SSL certs meet.matrix.domain.com, or else the domain ssl_certificate /etc/nginx/certs/live/meet.matrix.domain.com/fullchain.pem; ssl_certificate_key /etc/nginx/certs/live/meet.matrix.domain.com/privkey.pem; The meet domain works as well, meet.matrix.domain.com is the direct link Jitsi server. Its public. Anyone can make a meeting and it will work. I don't know if this is meant to be open to outside world. Is it suppose to be like this? The Jitsi web conference being public? Yes, this is a starting point. But the stacks work and installed it on Alpine Linux. It was a learning process and needed to understand how this stack works. Too many moving parts. I had to ask AI alot of questions. The only question I have is the Jitsi server meet.domain.com is public and anyone that goes to the site can start meeting. Again, still learning, and as you stated, this is a good starting point. It really is. Have to tweak or lockdown the moving parts. Obliviously, this has to go with a cloud flare or other means of locking down, that is beyond the scope of this post. But I can confirm it does work.

Its really well done and written, lots of documentation. I have an error when setting up server. Certbot fails, even with ports setup 60443 and 60080 mapped to 443 and 80. Its not a big deal, I'm able to generate my own SSL certs can copy them over when the script is complete. This is an example of the domain I'm using matrix.domain.com meet.matrix.domain.com sudo bash setup.sh --domain matrix.domain.com --reset Everything works fine. Only issue I continue to have is the Video Rooms and joining call. I still get the error: Call is not supported The server is not configured to work with Element Call. Please contact your server admin (Domain: matrix.domain.com, Error Code: MISSING_MATRIX_RTC_FOCUS). I looked at my compose and opened all these ports on my server: # WAN 443 \u2192 Unraid:60443 (nginx HTTPS) # WAN 80 \u2192 Unraid:60080 (nginx HTTP / ACME) # WAN 3478 \u2192 Unraid:3478 (coturn TURN/STUN) # WAN 5349 \u2192 Unraid:5349 (coturn TURNS/TLS) # WAN 10000 UDP \u2192 Unraid:10000 (jitsi-jvb WebRTC media) I looked at the docker compose, even the status script, I don't see 10000 UDP port on any of the jitsi-jvb dockers. I don't know if I'm missing something that on the synapse server yaml that prevents it from recognizing jitsi and the 10000 UDP port. If you have a config files i can compare to, I am not sure if the Certbot failing causes script to not set all configurations. I checked my ".env" file Jitsi sees my ip and server URL. JVB_ADVERTISE_IPS JITSI_PUBLIC_URL JITSI_DOMAIN Actually, now that I'm writing this, JITSI_AUTH_DOMAIN="auth.meet.matrix.domain.com" JITSI_INTERNAL_MUC_DOMAIN="internal-muc.meet.matrix.domain.com" JITSI_MUC_DOMAIN="muc.meet.matrix.domain.com" Do I need to create these additional A records that appear in .ENV file? The other question, and ran into an issue, how do I run server local? This is also to compare and for troubleshooting purposes, to have a matrix server internally, no outside clients. LAN testing. # LAN-only / no internet / no TLS sudo bash setup.sh --domain myserver.local --no-tlsWhen I setup this server to test, the only interface to connect to synapse was nginx and it points to 60443/60080. I'm just confused on how to make the local server work. If it takes over port 80 of host, then I believe Unraid will go down, because HTTP web UI to unraid already uses port 80. Does local server still need an A Record that works internally to point to UNRAID:80 and UNRAID:443? I'm only able to make domains work. Any pointers or comparing configs would help with this setup. Thanks again. Also here's status script results: /mnt/user/appdata/matrix-textvoicevideo# ./scripts/status.sh === Container Status === NAME IMAGE COMMAND SERVICE CREATED STATUS PORTS jitsi-jicofo jitsi/jicofo:stable "/init" jitsi-jicofo 44 minutes ago Up 44 minutes jitsi-jvb jitsi/jvb:stable "/init" jitsi-jvb 44 minutes ago Up 44 minutes jitsi-prosody jitsi/prosody:stable "/init" jitsi-prosody 44 minutes ago Up 44 minutes 5222/tcp, 5280/tcp jitsi-web jitsi/web:stable "/init" jitsi-web 44 minutes ago Up 43 minutes 80/tcp, 443/tcp matrix-coturn coturn/coturn:latest "docker-entrypoint.s…" coturn 44 minutes ago Up 44 minutes matrix-element-web vectorim/element-web:latest "/docker-entrypoint.…" element-web 44 minutes ago Up 44 minutes (healthy) 8080/tcp matrix-nginx nginx:alpine "/docker-entrypoint.…" nginx 44 minutes ago Up 38 minutes 0.0.0.0:60080->80/tcp, :::60080->80/tcp, 0.0.0.0:60443->443/tcp, :::60443->443/tcp matrix-postgres postgres:16-alpine "docker-entrypoint.s…" postgres 44 minutes ago Up 44 minutes (healthy) 5432/tcp matrix-synapse matrixdotorg/synapse:latest "/start.py" synapse 44 minutes ago Up 43 minutes (healthy) 8008/tcp, 8448/tcp, 19090/tcp matrix-valkey valkey/valkey:latest "docker-entrypoint.s…" valkey 44 minutes ago Up 44 minutes (healthy) 6379/tcp === Internal Services === ✓ PostgreSQL (matrix-postgres) ✓ Valkey (matrix-valkey) ✓ Synapse API ✓ Element Web ✓ Nginx (HTTP) ✓ Jitsi Web === External Endpoints === ✓ Matrix HTTPS ✓ Well-Known Client ✓ Well-Known Server ✓ Jitsi Video === Coturn TURN Server === ⚠ Install netcat (nc) to test Coturn UDP reachability ✓ Coturn container running === Resource Usage === NAME CPU % MEM USAGE / LIMIT matrix-nginx 0.00% 46.15MiB / 125.7GiB jitsi-web 0.00% 27.3MiB / 125.7GiB jitsi-jvb 0.15% 249.4MiB / 125.7GiB matrix-synapse 0.13% 186.2MiB / 125.7GiB jitsi-jicofo 0.11% 210.2MiB / 125.7GiB jitsi-prosody 0.08% 58.47MiB / 125.7GiB matrix-postgres 0.00% 77.95MiB / 125.7GiB matrix-element-web 0.00% 25.38MiB / 125.7GiB matrix-valkey 0.14% 18.84MiB / 125.7GiB matrix-coturn 0.10% 22.9MiB / 125.7GiB matrix-awt 0.00% 12.01MiB / 125.7GiB === Configuration Summary === Domain: matrix.domain.com Public URL: https://matrix.domain.com Jitsi URL: https://meet.domain.com External IP: 67.x.x.x Internal IP: 172.x.x.x Data Dir: /mnt/user/appdata/matrix-textvoicevideo/data TLS: false

I've stumbled into this post as I'm making my Maxtrix Synapse server, manually and adding pieces, step by step with the help of Claude. HestiaCP (its a web hosting tool) is my reverse proxy and auto renews certs Matrix Synapse is configured (with Postgres) Postgres container for Matrix only is configured Coturn is configured, works with Matrix (Calls only) When I tried to make a video room, got this error. Error Code: MISSING_MATRIX_RTC_FOCUS. I'm just trying to understand because this last part I'm stuck. I added Livekit container (added a Reddis Server internally as well) Don't know if Reddis even matters Matrix-Element-call Matrix-Element-web Any chance you can give a brief explanation for adding last two dockers above. I couldn't find them on the store, Just need to know where I can get the docker details so I can add it manually as a container if it's not on AppStore. And once this is set, the Server is done yes? Calls work, but Video Rooms do not for now. The biggest headache in my opinion was making Federation work, and learning where to properly add the nginx reverse proxy settings. The script is really well done, but I'm using it as reference as I build the pieces manually, also so I can understand how this whole stack works, in case I ever have to troubleshoot something. Also, I created each one of these dockers with br0 and assigned an ip address internally. Not sure if that matters.

Right on, that worked. only issue is that ComfyUI workflow of music generator doesn't create, direct, orchestrate a prompt into detailed description or generate lyrics instantly. Have to manually add all those details into the workflow. Also have to have some music knowledge, (musician) to know what the hell I'm doing. http://localhost:7860 (Gradio) I was hoping for this to work, but it seems will require either it's dedicated docker or mess or break the ComfyUI I use for generating images. Thanks again though. Didn't know they already have templates.

I have a question about the docker, particularly if I can run other apps inside. Works great for training Flux loras. I stumbled across this project, Ace Step 1.5 This tool generates music, with click of a button. Very well produced music. GitHubGitHub - ace-step/ACE-Step-1.5: The most powerful local m...The most powerful local music generation model that outperforms most commercial alternatives - ace-step/ACE-Step-1.5My 3090 is inside my unraid server. I've been trying to create another docker container for me to install this app. Best way to run AceStep is with UV. It handles all the requirements and Python versions. This particular project uses Python 3.11 and it appears to conflict with ComfyUI docker. I really trying running it inside to see if it works. I've tried to build a docker with help from AI. No success and it has been trail and error. Is there any way you can point me to the right direction on what docker repo to use? A repo that sees and utilizes Nvidia hardware inside the docker, much like the ComfyUI docker? AceStep to me, runs best on Linux, I have to use the smaller models because my main pc has a 3080 10 gig card. Ideally I'd prefer to run this on my Unraid server. Any assistance would be of great help. Thanks again, and also, love the ComfyUI docker. Its been awesome.

Just an update about this docker container because I encountered errors that drove me mad, trying to figure it all out. Docker only supported in BRIDGE mode, assigning it to br0, with static IP, connections to port 6875 just fail. Don't know why, and I simply gave up. Needs a MariaDB Docker in BRIDGE mode, can't ping or reach MariaDB docker with static IP in br0. Again, don't know why, I just had to create a Bridged MariaDB exclusively for Bookstack When Entering APP Key, you must include 'base64:jjfsakhjklksdhkjkhkfsff......' you have to include base64 in the App Key, the docker will error out. Reddit post explained this issue, surprised no one mentioned it here. I didn't create a docker network, or some other ways for Bookstack talk to communicate with MariaDB docker, but this was a BIG issue. I wanted to Bookstack and use a static IP with br0. I couldn't get it to work, any port I assigned (6875) just refused to accept traffic to the port. I gave up. I had to settle with installing this thing in BRIDGE. Its working, testing. I really hope this post helps anyone struggling to get this docker installed and work properly.

Just completed training my first model. It really is impressive. I had purchased an image generator from a website. Model is just as good. Just wish I had discovered this earlier. But regardless. The only tricky part was setting up the VENV for the trainer. I kept getting a weird error, the command just didn't detect the video card in the docker. I had to play around with removing/downgrading certain pip requirements. I don't know what package I downgraded or upgraded, but eventually it worked. Only other thing that is important is getting the hugging face READ token. It was all downhill from there. Package Version ------------------------- ----------- absl-py 2.1.0 accelerate 0.34.2 aiofiles 23.2.1 albucore 0.0.15 albumentations 1.4.15 annotated-types 0.7.0 antlr4-python3-runtime 4.9.3 anyio 4.4.0 attrs 24.2.0 bitsandbytes 0.43.3 certifi 2024.8.30 cffi 1.17.1 charset-normalizer 3.3.2 clean-fid 0.1.35 click 8.1.7 clip-anytorch 2.6.0 contourpy 1.3.0 controlnet_aux 0.0.7 cycler 0.12.1 dctorch 0.1.2 diffusers 0.31.0.dev0 docker-pycreds 0.4.0 einops 0.8.0 eval_type_backport 0.2.0 exceptiongroup 1.2.2 fastapi 0.114.1 ffmpy 0.4.0 filelock 3.16.0 flatbuffers 24.3.25 flatten-json 0.1.14 fonttools 4.53.1 fsspec 2024.9.0 ftfy 6.2.3 gitdb 4.0.11 GitPython 3.1.43 gradio 4.44.0 gradio_client 1.3.0 grpcio 1.66.1 h11 0.14.0 hf_transfer 0.1.8 httpcore 1.0.5 httpx 0.27.2 huggingface-hub 0.24.7 idna 3.8 imageio 2.35.1 importlib_metadata 8.5.0 importlib_resources 6.4.5 inquirerpy 0.3.4 invisible-watermark 0.2.0 jax 0.4.32 jaxlib 0.4.32 Jinja2 3.1.4 jsonmerge 1.9.2 jsonschema 4.23.0 jsonschema-specifications 2023.12.1 k-diffusion 0.1.1.post1 kiwisolver 1.4.7 kornia 0.7.3 kornia_rs 0.1.5 lazy_loader 0.4 lpips 0.1.4 lycoris_lora 1.8.3 Markdown 3.7 markdown-it-py 3.0.0 MarkupSafe 2.1.5 matplotlib 3.9.2 mdurl 0.1.2 mediapipe 0.10.15 ml-dtypes 0.4.0 mpmath 1.3.0 networkx 3.3 ninja 1.11.1.1 numpy 1.26.4 nvidia-cublas-cu12 12.1.3.1 nvidia-cuda-cupti-cu12 12.1.105 nvidia-cuda-nvrtc-cu12 12.1.105 nvidia-cuda-runtime-cu12 12.1.105 nvidia-cudnn-cu12 9.1.0.70 nvidia-cufft-cu12 11.0.2.54 nvidia-curand-cu12 10.3.2.106 nvidia-cusolver-cu12 11.4.5.107 nvidia-cusparse-cu12 12.1.0.106 nvidia-nccl-cu12 2.20.5 nvidia-nvjitlink-cu12 12.6.68 nvidia-nvtx-cu12 12.1.105 omegaconf 2.3.0 open_clip_torch 2.26.1 opencv-contrib-python 4.10.0.84 opencv-python 4.10.0.84 opencv-python-headless 4.9.0.80 opt-einsum 3.3.0 optimum-quanto 0.2.4 orjson 3.10.7 oyaml 1.0 packaging 24.1 pandas 2.2.2 peft 0.12.0 pfzy 0.3.4 pillow 10.4.0 pip 22.0.2 platformdirs 4.3.2 prodigyopt 1.0 prompt_toolkit 3.0.47 protobuf 4.25.4 psutil 6.0.0 py-cpuinfo 9.0.0 pycparser 2.22 pydantic 2.9.1 pydantic_core 2.23.3 pydub 0.25.1 Pygments 2.18.0 pyparsing 3.1.4 python-dateutil 2.9.0.post0 python-dotenv 1.0.1 python-multipart 0.0.9 python-slugify 8.0.4 pytorch-fid 0.3.0 pytz 2024.2 PyWavelets 1.7.0 PyYAML 6.0.2 referencing 0.35.1 regex 2024.9.11 requests 2.32.3 rich 13.8.1 rpds-py 0.20.0 ruff 0.6.4 safetensors 0.4.5 scikit-image 0.24.0 scipy 1.14.1 seaborn 0.13.2 semantic-version 2.10.0 sentencepiece 0.2.0 sentry-sdk 2.14.0 setproctitle 1.3.3 setuptools 59.6.0 shellingham 1.5.4 six 1.16.0 smmap 5.0.1 sniffio 1.3.1 sounddevice 0.5.0 starlette 0.38.5 sympy 1.13.2 tensorboard 2.17.1 tensorboard-data-server 0.7.2 text-unidecode 1.3 tifffile 2024.8.30 timm 1.0.9 tokenizers 0.19.1 toml 0.10.2 tomlkit 0.12.0 torch 2.4.1 torchdiffeq 0.2.4 torchsde 0.2.6 torchvision 0.19.1 tqdm 4.66.5 trampoline 0.1.2 transformers 4.44.2 triton 3.0.0 typer 0.12.5 typing_extensions 4.12.2 tzdata 2024.1 ultralytics 8.2.92 ultralytics-thop 2.0.6 urllib3 2.2.3 uvicorn 0.30.6 wandb 0.18.0 wcwidth 0.2.13 websockets 12.0 Werkzeug 3.0.4 zipp 3.20.1 Backing up the training VENV. Made so much progress in 1 month and don't regret buying the 3090. The second the 5090 is out I'm getting it. This docker rocks man. This is the error I got at first before the fix: libGL.so.1: cannot open shared object file: No such file or directory This was the post that helped me solve the error: https://github.com/ultralytics/ultralytics/issues/1270 Trial and error, I played around with uninstalling/upgrading. But posted pip list of working results with the 3090 docker.

Got another question, not related to docker, but has to do more with Workflows/Image Imports I've noticed some workflows show a warning Icon that it will conflict with other installed plugins with ComfyUI. Is it safe to import workflows and installing missing custom nodes even if there is a conflict? Will the conflict cause ComfyUI to break? Is the conflict just trying to use incompatible nodes in Workflow or with incompatible nodes existing with ComfyUI? I've tried searching and don't really have a clear answer. I've been cautious about adding workflows and installing nodes that show warning. Thanks

Is the 3090 good enough to do training or is it better to get a 4090? I finally hit a wall with that workflow with Lora, the card I'm using, 3060ti can't handle more than 1 or else I get out of memory errors. I need this 5090 to come out now. Also downloading the GGUF models and try them out. My card finally hitting a wall. I have to lower the output to 512x512. I'll reach out if I have any questions. Thanks

Yes, your instructions worked and I was able to produce a Flux-NF4 from workflow provided. The most important lesson I got was how to install/update the custom python inside the VENV folder. I guess this applies to dockers and linux boxes? This is big. I followed the instructions and installed bytesandbits to the docker, and not the VENV folder. Thats why my Comfyui always reported error when loading NF4. This has been a huge help. Also very comfortable updating the ComfyUI through the Manager. My previous experience with another docker/windows versions, when I ran update, everything just breaks. So I've been scarred by that. If I can ask another question, Lora, I've applied them to Checkpoints and work, I'm unable to use Lora on full version of Flux Dev. I've attached an image with workflow I've tried using. Do you happen to have a Workflow that can use Lora? Thanks again for your help

https://civitai.com/models/638187/flux1-dev-v1v2-flux1-schnell-bnb-nf4?modelVersionId=721627 Above are the files for Flux NF4 and model from CivitAI. I was curious to make this new model work and thats where I ran into issues. It's not so straight forward. I stumbled on this reddit post that explains what needs to be done to install the NF4 models and how to fix errors https://github.com/comfyanonymous/ComfyUI_bitsandbytes_NF4 The above is the Custom Module that needs to install for ComfyUI, but need to install a requirements.txt using PIP, also need to run install "bitsandbytes" inside Python. python -s -m pip install -U bitsandbytes --user I believe the Docker environment everything installed correctly, but will not work because it wasn't installed to "/comfy/mnt/venv". I need to update the VENV just as you mentioned in your docker documentation. Still trying to figure all this out, but regardless. Thanks again for response.

I have a question about updating docker to support this and future models from Flux and Beyond. The docker, PIP command works and updated the requirements. However, when I type "python" it doesn't seem that the docker recognizes as python installed. If I ever need to run python commands to install inside the docker, please can you provide detail on how to run that? I'm trying to juggle between This Docker and ComfyUI in Windows. Most videos and documentation online all have steps for installing on Windows. I have to figure out how to take the Windows instructions and apply them to this docker. Still trying to get this to work, but at least updating ComfyUI from manager didn't break anything. python3 -s -m pip install -U bitsandbytes --user Turns out that bitsandbytes needs to be installed not only through PIP but in Python as well. Tried that command and seems to have installed. However the Custom Node NF4 just can't be loaded and doesn't recognize the bitsandbytes. Can't find the module. Not sure if you've had a chance to try the Flux NF4 models, but they require some manual steps to update ComfyUI. Thanks again.

You are my hero. For realz man. ComfyUI-Magic: This docker, somehow, I was able to make the Flux models work until I updated ComfyUI with manager. It broke and was going crazy trying to get it to work. Not even clean installs work. Your docker saved me so much headache and pain. To install the docker, just follow the instructions from this post InvokeAI, same thing, have to copy the XML file to your USB config and just run it. This InvokeAI has worked well too, another alternative to run models. Regardless, your Docker, It works. Checkpoint models and the ones that require the VAE/CLIP. No more Errors when loading Workflows from Flux examples I'm so beyond grateful mate. Now I can stop using ComfyUI on Windows and run this docker. Again, thanks so much for your post.

Wanted to post my experiences with VMs and adjusting the CPU pinning. My issue had more to do with sound audio delay when streaming any kind of videos, if it is on Youtube, twitch, plex, ect. When assigning CPU cores to my VM there was a notable improved performance but the lag and delay with video streaming cause the audio and video to sync so bad that I literally made my bluetooth soundbar my PC speakers. And even that had an occasional hick up, but was tolerable. I discovered that this lag was really caused by the VM using the Cache Drive. Performance plummets when using the cache drive for other things like VMs, file transfers, or ther VMs running. I decided to continue using my physical machine's drive and just passthrough that drive and built a VM around it. All the audio issues were gone. Combine this with CPU pinning, I can't tell the difference between my VM and my original physical machine (before it had Unraid) Just thought I'd add my experience with CPU pinning and passing through the entire dedicated OS drive instead of using the cache drive.