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llm-server-docs/README.md
Varun Vasudeva 40b28b6461 first commit
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Local LLaMA Server Setup Documentation

TL;DR: A guide to setting up a server for running local language models using ollama.

About

This repository outlines the steps to run a server for running local language models. It uses Debian specifically, but most Linux distros should follow a very similar process. It aims to be a guide for Linux beginners like me who are setting up a server for the first time.

The process involves installing the NVIDIA drivers, setting the GPU power limit, and configuring the server to run ollama at boot. It also includes setting up auto-login and scheduling the init.bash script to run at boot. All these settings are based on my ideal setup for a language model server that runs most of the day but a lot can be customized to suit your needs. For example, you can use any OpenAI-compatible server like llama.cpp or LM Studio instead of ollama.

System Requirements

This guide assumes that we're working with a system with one or more Nvidia GPUs and an Intel CPU. It should be identical for an AMD CPU (but I haven't verified this).

The same cannot be said for AMD GPUs. Specifically for ollama, there's work being done to support ROCm but it still isn't stable in the way most people would hope it is for a reliable server. However, used Nvidia cards are a good deal nowadays (as of Mar 2024).

This guide was built around the following system:

  • CPU: Intel Core i5-12600KF
  • Memory: 32GB 6000 MHz DDR5 RAM
  • Storage: 1TB M.2 NVMe SSD
  • GPU: Nvidia RTX 3090 24GB

Steps

  1. Install Debian on the server

    • Download the Debian ISO from the official website.
    • Create a bootable USB using a tool like Rufus for Windows or Balena Etcher for MacOS.
    • Boot into the USB and install Debian.

  2. Update the system

    • Run the following command: 
      sudo apt update

  3. Install the NVIDIA drivers

    • Run the following commands: 
      apt install linux-headers-amd64
apt install nvidia-driver firmware-misc-nonfree
    • Reboot the server.
    • Run the following command to verify the installation: 
      nvidia-smi

  4. Install ollama

    • Download ollama from the official repository: 
      curl -fsSL https://ollama.com/install.sh | sh
    • (Recommended) We want our LLM API endpoint to be reachable by the rest of the LAN. For ollama, this means setting OLLAMA_HOST=0.0.0.0 in the ollama.service.
      • Run the following command to edit the service: 
        systemctl edit ollama.service
      • Find the [Service] section and add Environment="OLLAMA_HOST=0.0.0.0" under it. It should look like this: 
        [Service]
Environment="OLLAMA_HOST=0.0.0.0"
      • Save and exit.
      • Reload the environment. 
        systemctl daemon-reload
systemctl restart ollama

  5. Create the init.bash script

    This script will be run at boot to set the GPU power limit and start the server using ollama/llama.cpp. We set the GPU power limit lower because it has been seen in testing and inference that there is only a 5-15% performance decrease for a 50% reduction in power consumption. This is especially important for servers that are running 24/7.

    • Run the following commands:

      touch init.bash
nano init.bash

    • Add the following lines to the script:

      #!/bin/bash
sudo nvidia-smi -pm 1
sudo nvidia-smi -pl (power limit)
ollama run (model)
ollama serve

      Replace (power limit) with the desired power limit in watts. For example, sudo nvidia-smi -pl 250.

      Replace (model) with the name of the model you want to run. For example, ollama run mistral:latest.

    • Save and exit the script.

    • Make the script executable:

      chmod +x init.bash

  6. Give nvidia-persistenced and nvidia-smi passwordless sudo permissions

    We want init.bash to run the nvidia-smi commands without having to enter a password. This is done by editing the sudoers file.

    • Run the following command:

      sudo visudo

    • Add the following lines to the file:

      (username) ALL=(ALL) NOPASSWD: /usr/bin/nvidia-persistenced
(username) ALL=(ALL) NOPASSWD: /usr/bin/nvidia-smi

      Replace (username) with your username.

      Important

      : Ensure that you add these lines AFTER %sudo ALL=(ALL:ALL) ALL. The order of the lines in the file matters - the last matching line will be used so if you add these lines before %sudo ALL=(ALL:ALL) ALL, they will be ignored.

    • Save and exit the file.

  7. Configure auto-login

    When the server boots up, we want it to automatically log in to a user account and run the init.bash script. This is done by configuring the lightdm display manager.

    • Run the following command: 
      sudo nano /etc/lightdm/lightdm.conf
    • Find the following commented line. It should be in the [Seat:*] section. 
      # autologin-user=
    • Uncomment the line and add your username: 
      autologin-user=(username)

      Replace (username) with your username.

    • Save and exit the file.

  8. Add init.bash to the crontab

    Adding the init.bash script to the crontab will schedule it to run at boot.

    • Run the following command:

      crontab -e

    • Add the following line to the file:

      @reboot /path/to/init.bash

      Replace /path/to/init.bash with the path to the init.bash script.

    • (Optional) Add the following line to shutdown the server at 12am:

      0 0 * * * /sbin/shutdown -h now

    • Save and exit the file.

  9. (Optional) Enable SSH

    Enabling SSH allows you to connect to the server remotely.

    On the server:

    • Run the following command: 
      sudo apt install openssh-server
    • Start the SSH service: 
      sudo systemctl start ssh
    • Enable the SSH service to start at boot: 
      sudo systemctl enable ssh
    • Find the server's IP address: 
      ip a

    On the client:

    • Connect to the server using SSH: 
      ssh (username)@(ip address)

      Replace (username) with your username and (ip address) with the server's IP address.

    If you expect to tunnel into your server often, I recommend following this guide to enable passwordless SSH using ssh-keygen and ssh-copy-id. It worked perfectly on my Debian system despite having been written for Raspberry Pi OS.

Accessing Ollama

Accessing ollama on the server itself is trivial. Simply run:

curl http://localhost:11434/api/generate -d '{
  "model": "llama2",
  "prompt":"Why is the sky blue?"
}'

Replace llama2 with your preferred model.

Assuming the OLLAMA_HOST environment variable has been set to 0.0.0.0, accessing ollama from anywhere on the network is still trivial! Simply replace localhost with your server's IP.

Refer to Ollama's REST API docs for more information on the entire API.

Troubleshooting

  • Disable Secure Boot in the BIOS if you're having trouble with the Nvidia drivers not working. For me, all packages were at the latest versions and nvidia-detect was able to find my GPU correctly, but nvidia-smi kept returning the NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver error. Disabling Secure Boot fixed this for me. Better practice than disabling Secure Boot is to sign the Nvidia drivers yourself but I didn't want to go through that process for a non-critical server that can afford to have Secure Boot disabled.
  • If you receive the Failed to open "/etc/systemd/system/ollama.service.d/.#override.confb927ee3c846beff8": Permission denied error from Ollama after running systemctl edit ollama.service, simply creating the file works to eliminate it. Use the following steps to edit the file.
    • Run: 
      sudo mkdir -p /etc/systemd/system/ollama.service.d
sudo nano /etc/systemd/system/ollama.service.d/override.conf
    • Retry the remaining steps.
  • If you still can't connect to your API endpoint, check your firewall settings. This guide to UFW (Uncomplicated Firewall) on Debian is a good resource.

Notes

  • This is my first foray into setting up a server and ever working with Linux so there may be better ways to do some of the steps. I will update this repository as I learn more.
  • I chose Debian because it is, apparently, one of the most stable Linux distros. I also went with an XFCE desktop environment because it is lightweight and I wasn't yet comfortable going full command line.
  • The power draw of my EVGA FTW3 Ultra RTX 3090 was 350W at stock settings. I set the power limit to 250W and the performance decrease was negligible for my use case, which is primarily code completion in VS Code and the Q&A via chat.
  • Use a user for auto-login, don't log in as root.

References

Downloading Nvidia drivers:

Secure Boot:

Monitoring GPU usage, power draw:

Passwordless sudo:

Auto-login:

Expose Ollama to LAN:

Firewall:

Passwordless ssh:

Docs:

https://github.com/ollama/ollama/blob/main/docs/api.md

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