AI大模型部署Ubuntu服务器攻略

申未曲 2024-07-19 17:01:02 阅读 57

一、下载Ollama

在线安装:

在linux中输入命令curl -fsSL https://ollama.com/install.sh | sh

由于在linux下载ollama需要经过外网,网络会不稳定,很容易造成连接超时的问题。

离线安装:

步骤一: 下载Ollama离线版本

在linux服务器中输入命令:lscpu查看服务器型号

然后再该地址中下载Ollama离线版本:

https://github.com/ollama/ollama/releases

步骤二: 下载install.sh文件修改内容

地址为:https://ollama.com/install.sh

修改位置1:

注释掉在线下载ollama的命令

修改位置2:

修改ollama安装地址,将ollama离线版本与install放到一起

install.sh最终修改的版本:

<code>#!/bin/sh

# This script installs Ollama on Linux.

# It detects the current operating system architecture and installs the appropriate version of Ollama.

set -eu

status() { echo ">>> $*" >&2; }

error() { echo "ERROR $*"; exit 1; }

warning() { echo "WARNING: $*"; }

TEMP_DIR=$(mktemp -d)

cleanup() { rm -rf $TEMP_DIR; }

trap cleanup EXIT

available() { command -v $1 >/dev/null; }

require() {

local MISSING=''code>

for TOOL in $*; do

if ! available $TOOL; then

MISSING="$MISSING $TOOL"code>

fi

done

echo $MISSING

}

[ "$(uname -s)" = "Linux" ] || error 'This script is intended to run on Linux only.'

ARCH=$(uname -m)

case "$ARCH" in

x86_64) ARCH="amd64" ;;code>

aarch64|arm64) ARCH="arm64" ;;code>

*) error "Unsupported architecture: $ARCH" ;;

esac

IS_WSL2=false

KERN=$(uname -r)

case "$KERN" in

*icrosoft*WSL2 | *icrosoft*wsl2) IS_WSL2=true;;

*icrosoft) error "Microsoft WSL1 is not currently supported. Please upgrade to WSL2 with 'wsl --set-version <distro> 2'" ;;

*) ;;

esac

VER_PARAM="${OLLAMA_VERSION:+?version=$OLLAMA_VERSION}"code>

SUDO=

if [ "$(id -u)" -ne 0 ]; then

# Running as root, no need for sudo

if ! available sudo; then

error "This script requires superuser permissions. Please re-run as root."

fi

SUDO="sudo"code>

fi

NEEDS=$(require curl awk grep sed tee xargs)

if [ -n "$NEEDS" ]; then

status "ERROR: The following tools are required but missing:"

for NEED in $NEEDS; do

echo " - $NEED"

done

exit 1

fi

status "Downloading ollama..."

# curl --fail --show-error --location --progress-bar -o $TEMP_DIR/ollama "https://ollama.com/download/ollama-linux-${ARCH}${VER_PARAM}"

for BINDIR in /usr/local/bin /usr/bin /bin; do

echo $PATH | grep -q $BINDIR && break || continue

done

status "Installing ollama to $BINDIR..."

$SUDO install -o0 -g0 -m755 -d $BINDIR

# $SUDO install -o0 -g0 -m755 $TEMP_DIR/ollama $BINDIR/ollama

$SUDO install -o0 -g0 -m755 ./ollama-linux-amd64 $BINDIR/ollama

install_success() {

status 'The Ollama API is now available at 127.0.0.1:11434.'

status 'Install complete. Run "ollama" from the command line.'

}

trap install_success EXIT

# Everything from this point onwards is optional.

configure_systemd() {

if ! id ollama >/dev/null 2>&1; then

status "Creating ollama user..."

$SUDO useradd -r -s /bin/false -U -m -d /usr/share/ollama ollama

fi

if getent group render >/dev/null 2>&1; then

status "Adding ollama user to render group..."

$SUDO usermod -a -G render ollama

fi

if getent group video >/dev/null 2>&1; then

status "Adding ollama user to video group..."

$SUDO usermod -a -G video ollama

fi

status "Adding current user to ollama group..."

$SUDO usermod -a -G ollama $(whoami)

status "Creating ollama systemd service..."

cat <<EOF | $SUDO tee /etc/systemd/system/ollama.service >/dev/null

[Unit]

Description=Ollama Service

After=network-online.target

[Service]

ExecStart=$BINDIR/ollama serve

User=ollama

Group=ollama

Restart=always

RestartSec=3

Environment="PATH=$PATH"code>

[Install]

WantedBy=default.target

EOF

SYSTEMCTL_RUNNING="$(systemctl is-system-running || true)"code>

case $SYSTEMCTL_RUNNING in

running|degraded)

status "Enabling and starting ollama service..."

$SUDO systemctl daemon-reload

$SUDO systemctl enable ollama

start_service() { $SUDO systemctl restart ollama; }

trap start_service EXIT

;;

esac

}

if available systemctl; then

configure_systemd

fi

# WSL2 only supports GPUs via nvidia passthrough

# so check for nvidia-smi to determine if GPU is available

if [ "$IS_WSL2" = true ]; then

if available nvidia-smi && [ -n "$(nvidia-smi | grep -o "CUDA Version: [0-9]*\.[0-9]*")" ]; then

status "Nvidia GPU detected."

fi

install_success

exit 0

fi

# Install GPU dependencies on Linux

if ! available lspci && ! available lshw; then

warning "Unable to detect NVIDIA/AMD GPU. Install lspci or lshw to automatically detect and install GPU dependencies."

exit 0

fi

check_gpu() {

# Look for devices based on vendor ID for NVIDIA and AMD

case $1 in

lspci)

case $2 in

nvidia) available lspci && lspci -d '10de:' | grep -q 'NVIDIA' || return 1 ;;

amdgpu) available lspci && lspci -d '1002:' | grep -q 'AMD' || return 1 ;;

esac ;;

lshw)

case $2 in

nvidia) available lshw && $SUDO lshw -c display -numeric | grep -q 'vendor: .* \[10DE\]' || return 1 ;;

amdgpu) available lshw && $SUDO lshw -c display -numeric | grep -q 'vendor: .* \[1002\]' || return 1 ;;

esac ;;

nvidia-smi) available nvidia-smi || return 1 ;;

esac

}

if check_gpu nvidia-smi; then

status "NVIDIA GPU installed."

exit 0

fi

if ! check_gpu lspci nvidia && ! check_gpu lshw nvidia && ! check_gpu lspci amdgpu && ! check_gpu lshw amdgpu; then

install_success

warning "No NVIDIA/AMD GPU detected. Ollama will run in CPU-only mode."

exit 0

fi

if check_gpu lspci amdgpu || check_gpu lshw amdgpu; then

# Look for pre-existing ROCm v6 before downloading the dependencies

for search in "${HIP_PATH:-''}" "${ROCM_PATH:-''}" "/opt/rocm" "/usr/lib64"; do

if [ -n "${search}" ] && [ -e "${search}/libhipblas.so.2" -o -e "${search}/lib/libhipblas.so.2" ]; then

status "Compatible AMD GPU ROCm library detected at ${search}"

install_success

exit 0

fi

done

status "Downloading AMD GPU dependencies..."

$SUDO rm -rf /usr/share/ollama/lib

$SUDO chmod o+x /usr/share/ollama

$SUDO install -o ollama -g ollama -m 755 -d /usr/share/ollama/lib/rocm

curl --fail --show-error --location --progress-bar "https://ollama.com/download/ollama-linux-amd64-rocm.tgz${VER_PARAM}" \

| $SUDO tar zx --owner ollama --group ollama -C /usr/share/ollama/lib/rocm .

install_success

status "AMD GPU ready."

exit 0

fi

# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#rhel-7-centos-7

# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#rhel-8-rocky-8

# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#rhel-9-rocky-9

# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#fedora

install_cuda_driver_yum() {

status 'Installing NVIDIA repository...'

case $PACKAGE_MANAGER in

yum)

$SUDO $PACKAGE_MANAGER -y install yum-utils

$SUDO $PACKAGE_MANAGER-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/$1$2/$(uname -m)/cuda-$1$2.repo

;;

dnf)

$SUDO $PACKAGE_MANAGER config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/$1$2/$(uname -m)/cuda-$1$2.repo

;;

esac

case $1 in

rhel)

status 'Installing EPEL repository...'

# EPEL is required for third-party dependencies such as dkms and libvdpau

$SUDO $PACKAGE_MANAGER -y install https://dl.fedoraproject.org/pub/epel/epel-release-latest-$2.noarch.rpm || true

;;

esac

status 'Installing CUDA driver...'

if [ "$1" = 'centos' ] || [ "$1$2" = 'rhel7' ]; then

$SUDO $PACKAGE_MANAGER -y install nvidia-driver-latest-dkms

fi

$SUDO $PACKAGE_MANAGER -y install cuda-drivers

}

# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#ubuntu

# ref: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#debian

install_cuda_driver_apt() {

status 'Installing NVIDIA repository...'

curl -fsSL -o $TEMP_DIR/cuda-keyring.deb https://developer.download.nvidia.com/compute/cuda/repos/$1$2/$(uname -m)/cuda-keyring_1.1-1_all.deb

case $1 in

debian)

status 'Enabling contrib sources...'

$SUDO sed 's/main/contrib/' < /etc/apt/sources.list | $SUDO tee /etc/apt/sources.list.d/contrib.list > /dev/null

if [ -f "/etc/apt/sources.list.d/debian.sources" ]; then

$SUDO sed 's/main/contrib/' < /etc/apt/sources.list.d/debian.sources | $SUDO tee /etc/apt/sources.list.d/contrib.sources > /dev/null

fi

;;

esac

status 'Installing CUDA driver...'

$SUDO dpkg -i $TEMP_DIR/cuda-keyring.deb

$SUDO apt-get update

[ -n "$SUDO" ] && SUDO_E="$SUDO -E" || SUDO_E=code>

DEBIAN_FRONTEND=noninteractive $SUDO_E apt-get -y install cuda-drivers -q

}

if [ ! -f "/etc/os-release" ]; then

error "Unknown distribution. Skipping CUDA installation."

fi

. /etc/os-release

OS_NAME=$ID

OS_VERSION=$VERSION_ID

PACKAGE_MANAGER=

for PACKAGE_MANAGER in dnf yum apt-get; do

if available $PACKAGE_MANAGER; then

break

fi

done

if [ -z "$PACKAGE_MANAGER" ]; then

error "Unknown package manager. Skipping CUDA installation."

fi

if ! check_gpu nvidia-smi || [ -z "$(nvidia-smi | grep -o "CUDA Version: [0-9]*\.[0-9]*")" ]; then

case $OS_NAME in

centos|rhel) install_cuda_driver_yum 'rhel' $(echo $OS_VERSION | cut -d '.' -f 1) ;;

rocky) install_cuda_driver_yum 'rhel' $(echo $OS_VERSION | cut -c1) ;;

fedora) [ $OS_VERSION -lt '37' ] && install_cuda_driver_yum $OS_NAME $OS_VERSION || install_cuda_driver_yum $OS_NAME '37';;

amzn) install_cuda_driver_yum 'fedora' '37' ;;

debian) install_cuda_driver_apt $OS_NAME $OS_VERSION ;;

ubuntu) install_cuda_driver_apt $OS_NAME $(echo $OS_VERSION | sed 's/\.//') ;;

*) exit ;;

esac

fi

if ! lsmod | grep -q nvidia || ! lsmod | grep -q nvidia_uvm; then

KERNEL_RELEASE="$(uname -r)"code>

case $OS_NAME in

rocky) $SUDO $PACKAGE_MANAGER -y install kernel-devel kernel-headers ;;

centos|rhel|amzn) $SUDO $PACKAGE_MANAGER -y install kernel-devel-$KERNEL_RELEASE kernel-headers-$KERNEL_RELEASE ;;

fedora) $SUDO $PACKAGE_MANAGER -y install kernel-devel-$KERNEL_RELEASE ;;

debian|ubuntu) $SUDO apt-get -y install linux-headers-$KERNEL_RELEASE ;;

*) exit ;;

esac

NVIDIA_CUDA_VERSION=$($SUDO dkms status | awk -F: '/added/ { print $1 }')

if [ -n "$NVIDIA_CUDA_VERSION" ]; then

$SUDO dkms install $NVIDIA_CUDA_VERSION

fi

if lsmod | grep -q nouveau; then

status 'Reboot to complete NVIDIA CUDA driver install.'

exit 0

fi

$SUDO modprobe nvidia

$SUDO modprobe nvidia_uvm

fi

# make sure the NVIDIA modules are loaded on boot with nvidia-persistenced

if command -v nvidia-persistenced > /dev/null 2>&1; then

$SUDO touch /etc/modules-load.d/nvidia.conf

MODULES="nvidia nvidia-uvm"code>

for MODULE in $MODULES; do

if ! grep -qxF "$MODULE" /etc/modules-load.d/nvidia.conf; then

echo "$MODULE" | sudo tee -a /etc/modules-load.d/nvidia.conf > /dev/null

fi

done

fi

status "NVIDIA GPU ready."

install_success

出现该内容说明Ollama已经安装完成

二、启动Nginx并部署Vue

启动nginx命令:systemctl start nginx.service

查看nginx状态:systemctl status nginx.service

关闭nginx命令:systemctl stop nginx.service

修改子配置文件,因为子配置文件内是写http的内容。

nginx服务所在地址为:/etc/nginx/sites-available

进入该目录编辑default文件:vim default

index index.html index.htm index.nginx-debian.html;

# First attempt to serve request as file, then

# as directory, then fall back to displaying a 404.

try_files $uri $uri/ @router;

}

location @router {

rewrite ^.*$ /index.html last;

}

如果你前端使用的是vue并且用了vue-router,那么就需要配置该代码,否则你进行router跳转的时候,就会出现404的问题。

三、启动Python脚本

进入存放python脚本的目录,运行命令:python xxx.py。运行脚本后,系统可能会提示有一些模块没有安装,按照提示安装即可。

命令:pip install module_name

其中可能有些脚本提示不对,比如:

ModuleNotFoundError: No module named 'docx'

如果出现这个问题,不能直接安装docx模块,而是应该安装python-docx。

将该安装的库全部安装后,进入放置python脚本的目录启动入口文件,短暂启动命令:python ai_analysis.py

持久后台运行命令:

nohup python ai_analysis.py /opt/app/llm_python/ai_analysis_project/log 2>&1

四、目前项目需要的库

使用MimiCPM需要的库,官方测试所用的环境:

Pillow10.1.0

torch2.1.2 / 1.13.0(原本的库版本)

torchvision0.16.2 / 0.17.1(原本的库版本)

transformers4.40.0

sentencepiece0.1.99

accelerate0.30.1

bitsandbytes==0.43.1

AI分析所需要的库

langchain

langchain_community

分析文档所需要的库

pandasai

python-docx

fitz

faiss-gpu (conda install faiss-gpu -c pytorch)



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