Мелочи

Чистим System volume

DiskShadow
Delete shadows OLDEST c:\

ffmpeg

g729 to wav

ffmpeg -f g729 -i "C:\Video\wav\123.g729" -f wav "C:\Video\wav\123.wav"

avi to mov с использованием GPU

ffmpeg -i video.avi -c:v h264_nvenc -preset p7 -pix_fmt yuv420p -an test.mov
 50\50 CPU и GPU
ffmpeg -hwaccel cuda -c:v h264_cuvid -i input.avi -c:v h264_nvenc -preset p7 -pix_fmt yuv420p -an output.mov
100% GPU

mov to mov 

ffmpeg -hwaccel cuvid -i input.mov -c:v h264_nvenc -bsf:v h264_mp4toannexb -b:v 5M -c:a copy output.mov

100%GPU

Восстанавливаем после ошибки Check of pool pve/data failed (status:64)

lvconvert --repair pve/data

занимет около 5 минут но может и больше

Админские шары без домена

[HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Windows\CurrentVersion\Policies\System]
"LocalAccountTokenFilterPolicy"=dword:00000001

Ollama

1. Prerequisites

2. Install NVIDIA Drivers

Make sure your GPU drivers are installed and working.

sudo apt update
sudo apt install -y ubuntu-drivers-common
ubuntu-drivers devices   # check recommended drivers
sudo ubuntu-drivers autoinstall

Reboot and confirm GPU availability:

sudo reboot
nvidia-smi

You should see details of your GPU.

3. Install CUDA Toolkit

Ollama uses CUDA for GPU acceleration. Install CUDA 12.x (recommended).

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin
sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600

wget https://developer.download.nvidia.com/compute/cuda/12.2.2/local_installers/cuda-repo-ubuntu2204-12-2-local_12.2.2-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu2204-12-2-local_12.2.2-1_amd64.deb
sudo cp /var/cuda-repo-ubuntu2204-12-2-local/cuda-*-keyring.gpg /usr/share/keyrings/
sudo apt update
sudo apt install -y cuda

Check CUDA installation:

nvcc --version

3.1 

CUDA Toolkit Installer
Installation Instructions: 
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin
sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget https://developer.download.nvidia.com/compute/cuda/13.0.2/local_installers/cuda-repo-ubuntu2204-13-0-local_13.0.2-580.95.05-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu2204-13-0-local_13.0.2-580.95.05-1_amd64.deb
sudo cp /var/cuda-repo-ubuntu2204-13-0-local/cuda-*-keyring.gpg /usr/share/keyrings/sudo apt-get update
sudo apt-get -y install cuda-toolkit-13-0

3.2

sudo apt install nvidia-cuda-toolkit

 

4. Install Ollama

Download and install Ollama runtime:

curl -fsSL https://ollama.com/install.sh | sh

Verify service is running:

systemctl status ollama

Test Ollama

Run a quick model test:

ollama run tinyllama

Other models available:

ollama pull gpt-oss:20b

5. Install Docker

Open WebUI runs inside Docker. Follow these steps to install Docker and Docker Compose:

# Remove any old versions
sudo apt remove -y docker docker-engine docker.io containerd runc

# Install required packages
sudo apt update
sudo apt install -y ca-certificates curl gnupg lsb-release

# Add Docker’s official GPG key
sudo mkdir -p /etc/apt/keyrings
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg

# Add Docker repository
echo \"deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable\" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

# Install Docker and Docker Compose
sudo apt update
sudo apt install -y docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

Enable and test Docker:

sudo systemctl enable --now docker
sudo docker run hello-world

Allow your user to run Docker without sudo:

sudo usermod -aG docker $USER
newgrp docker

Check Docker Compose version:

docker compose version

6. Install Open WebUI

Clone and run Open WebUI:

git clone https://github.com/open-webui/open-webui.git
cd open-webui
docker compose up -d

Access the interface at:

http://<server-ip>:3000

7. Connect Open WebUI to Ollama

In the WebUI:

8. Enable GPU Support in Docker (Optional)

If you want Docker containers (like Open WebUI) to access GPU directly:

# Install NVIDIA Container Toolkit
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt update
sudo apt install -y nvidia-container-toolkit
sudo systemctl restart docker

Edit docker-compose.yml for Open WebUI:

services:
  open-webui:
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu]

Restart:

docker compose down
docker compose up -d

9. Verify GPU Usage

Run a model and check GPU utilization:

ollama run gpt-oss:20b

In another terminal:

nvidia-smi

You should see ollama using GPU memory.

10. Start Chatting with any Model You Like

Now you can:

  1. Pull models with Ollama:

    ollama pull gpt-oss
ollama pull deepseek-r1
ollama pull llama3
ollama pull llama4
ollama pull gemma3
ollama pull phi4
ollama pull codellama

  2. Select the model in Open WebUI.

  3. Chat through your browser!

Reverse proxy для WebSocket в Nginx

Минимальные настройки: /etc/nginx/conf.d/include/proxy.conf 

# WebSocket support
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "upgrade";

отключаем буферизацию

proxy_buffering off;