1. 查看服务器CPU的型号
## 查看Linux系统CPU型号命令，我的服务器cpu型号是x86_64
lscpu
2. 根据CPU型号下载Ollama安装包，并保存到/home/Ollama目录
我下载的是Ollama的v0.1.31版本，后面均以此版本为例说明
下载地址 https://github.com/ollama/ollama/releases/
# x86_64 CPU选择下载ollama-linux-amd64
# aarch64|arm64 CPU选择下载ollama-linux-arm64
3. 离线下载Linux环境的Ollama安装脚本，并保存到/home/Ollama目录
修改后的脚本
#!/bin/sh
# This script installs Ollama on Linux.
# It detects the current operating system architecture and installs the appropriate version of Ollama.set -eustatus() { echo ">>> $*" >&2; }
error() { echo "ERROR $*"; exit 1; }
warning() { echo "WARNING: $*"; }TEMP_DIR=$(mktemp -d)
cleanup() { rm -rf $TEMP_DIR; }
trap cleanup EXITavailable() { command -v $1 >/dev/null; }
require() {local MISSING=''for TOOL in $*; doif ! available $TOOL; thenMISSING="$MISSING $TOOL"fidoneecho $MISSING
}[ "$(uname -s)" = "Linux" ] || error 'This script is intended to run on Linux only.'ARCH=$(uname -m)
case "$ARCH" inx86_64) ARCH="amd64" ;;aarch64|arm64) ARCH="arm64" ;;*) error "Unsupported architecture: $ARCH" ;;
esacKERN=$(uname -r)
case "$KERN" in*icrosoft*WSL2 | *icrosoft*wsl2) ;;*icrosoft) error "Microsoft WSL1 is not currently supported. Please upgrade to WSL2 with 'wsl --set-version <distro> 2'" ;;*) ;;
esacVER_PARAM="${OLLAMA_VERSION:+?version=$OLLAMA_VERSION}"SUDO=
if [ "$(id -u)" -ne 0 ]; then# Running as root, no need for sudoif ! available sudo; thenerror "This script requires superuser permissions. Please re-run as root."fiSUDO="sudo"
fiNEEDS=$(require curl awk grep sed tee xargs)
if [ -n "$NEEDS" ]; thenstatus "ERROR: The following tools are required but missing:"for NEED in $NEEDS; doecho " - $NEED"doneexit 1
fistatus "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; doecho $PATH | grep -q $BINDIR && break || continue
donestatus "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 $BINDIR/ollamainstall_success() { status 'The Ollama API is now available at 127.0.0.1:11434.'status 'Install complete. Run "ollama" from the command line.'
}
trap install_success EXIT# Everything from this point onwards is optional.configure_systemd() {if ! id ollama >/dev/null 2>&1; thenstatus "Creating ollama user..."$SUDO useradd -r -s /bin/false -U -m -d /usr/share/ollama ollamafiif getent group render >/dev/null 2>&1; thenstatus "Adding ollama user to render group..."$SUDO usermod -a -G render ollamafiif getent group video >/dev/null 2>&1; thenstatus "Adding ollama user to video group..."$SUDO usermod -a -G video ollamafistatus "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=$PATH"[Install]
WantedBy=default.target
EOFSYSTEMCTL_RUNNING="$(systemctl is-system-running || true)"case $SYSTEMCTL_RUNNING inrunning|degraded)status "Enabling and starting ollama service..."$SUDO systemctl daemon-reload$SUDO systemctl enable ollamastart_service() { $SUDO systemctl restart ollama; }trap start_service EXIT;;esac
}if available systemctl; thenconfigure_systemd
fiif ! available lspci && ! available lshw; thenwarning "Unable to detect NVIDIA/AMD GPU. Install lspci or lshw to automatically detect and install GPU dependencies."exit 0
ficheck_gpu() {# Look for devices based on vendor ID for NVIDIA and AMDcase $1 inlspci) case $2 innvidia) 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 innvidia) 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; thenstatus "NVIDIA GPU installed."exit 0
fiif ! check_gpu lspci nvidia && ! check_gpu lshw nvidia && ! check_gpu lspci amdgpu && ! check_gpu lshw amdgpu; theninstall_successwarning "No NVIDIA/AMD GPU detected. Ollama will run in CPU-only mode."exit 0
fiif check_gpu lspci amdgpu || check_gpu lshw amdgpu; then# Look for pre-existing ROCm v6 before downloading the dependenciesfor search in "${HIP_PATH:-''}" "${ROCM_PATH:-''}" "/opt/rocm"; doif [ -n "${search}" ] && [ -e "${search}/lib/libhipblas.so.2" ]; thenstatus "Compatible AMD GPU ROCm library detected at ${search}"install_successexit 0fidonestatus "Downloading AMD GPU dependencies..."$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/rocmcurl --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_successstatus "AMD GPU dependencies installed."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 $PACKAGE_MANAGER inyum)$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;;esaccase $1 inrhel)status 'Installing EPEL repository...'# EPEL is required for third-party dependencies such as dkms and libvdpau$SUDO $PACKAGE_MANAGER -y install https://dl.fedoraproject.org/pub/epel/epel-release-latest-$2.noarch.rpm || true;;esacstatus 'Installing CUDA driver...'if [ "$1" = 'centos' ] || [ "$1$2" = 'rhel7' ]; then$SUDO $PACKAGE_MANAGER -y install nvidia-driver-latest-dkmsfi$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.debcase $1 indebian)status 'Enabling contrib sources...'$SUDO sed 's/main/contrib/' < /etc/apt/sources.list | $SUDO tee /etc/apt/sources.list.d/contrib.list > /dev/nullif [ -f "/etc/apt/sources.list.d/debian.sources" ]; then$SUDO sed 's/main/contrib/' < /etc/apt/sources.list.d/debian.sources | $SUDO tee /etc/apt/sources.list.d/contrib.sources > /dev/nullfi;;esacstatus 'Installing CUDA driver...'$SUDO dpkg -i $TEMP_DIR/cuda-keyring.deb$SUDO apt-get update[ -n "$SUDO" ] && SUDO_E="$SUDO -E" || SUDO_E=DEBIAN_FRONTEND=noninteractive $SUDO_E apt-get -y install cuda-drivers -q
}if [ ! -f "/etc/os-release" ]; thenerror "Unknown distribution. Skipping CUDA installation."
fi. /etc/os-releaseOS_NAME=$ID
OS_VERSION=$VERSION_IDPACKAGE_MANAGER=
for PACKAGE_MANAGER in dnf yum apt-get; doif available $PACKAGE_MANAGER; thenbreakfi
doneif [ -z "$PACKAGE_MANAGER" ]; thenerror "Unknown package manager. Skipping CUDA installation."
fiif ! check_gpu nvidia-smi || [ -z "$(nvidia-smi | grep -o "CUDA Version: [0-9]*\.[0-9]*")" ]; thencase $OS_NAME incentos|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 $OS_VERSION | sed 's/\.//') ;;*) exit ;;esac
fiif ! lsmod | grep -q nvidia; thenKERNEL_RELEASE="$(uname -r)"case $OS_NAME inrocky) $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 ;;esacNVIDIA_CUDA_VERSION=$($SUDO dkms status | awk -F: '/added/ { print $1 }')if [ -n "$NVIDIA_CUDA_VERSION" ]; then$SUDO dkms install $NVIDIA_CUDA_VERSIONfiif lsmod | grep -q nouveau; thenstatus 'Reboot to complete NVIDIA CUDA driver install.'exit 0fi$SUDO modprobe nvidia
fistatus "NVIDIA CUDA drivers installed."
5. 运行 install.sh脚本 ,安装
6. 配置大模型下载目录
# 执行命令
vim ~/.bashrc
# 配置 OLLAMA_MODELS 环境变量自定义路径
### ollama model dir 改为自定义的路径，默认路径/usr/share/ollama/.ollama/models
export OLLAMA_MODELS=/home/Ollama/ollama_cache
# 复制/usr/share/ollama/.ollama/models目录中（blobs manifests）的文件夹到OLLAMA_MODELS环境变量目录
cp -r /usr/share/ollama/.ollama/models /home/Ollama/ollama_cache
7. 运行大模型，如通义千问
# 需要先将大模型下载到OLLAMA_MODELS文件中
# ollama run <模型名称>
ollama run qwen
8. 关闭 Ollama 服务
# 关闭ollama服务
service ollama stop
9. 修改网络
#1.找到服务的单元文件：
#/etc/systemd/system/目录下
sudo vi /etc/systemd/system/ollama.service#2.修改配置文件，分为如下2钟情况
#情况1：添加环境变量：
[Service]
Environment="OLLAMA_HOST=0.0.0.0:11434"
#情况2：如果已经有
Environment="PATH=xxx:/root/bin" "OLLAMA_HOST=0.0.0.0:11434"#3.为了使更改生效，您需要重新加载systemd的配置。使用以下命令：
sudo systemctl daemon-reload#4.重启服务以应用更改：
sudo systemctl restart ollama10. Ollama 客户端：HTTP 访问服务
Ollama 默认提供了generate和chat这 2 个原始的 API 接口，使用方式如下：
1 generate接口的使用样例：
curl http://localhost:11434/api/generate -d "{'model': 'qwen:0.5b','prompt': '为什么天空是蓝色的？'
}"
2 chat接口的使用样例：
curl http://localhost:11434/api/chat -d '{"model": "qwen:7b","messages": [{ "role": "user", "content": "为什么天空是蓝色的？" }]
}'
Ollama 客户端：Python API 应用
第一步，安装 Python 依赖包：
pip install ollama第二步，使用 Ollama 接口，stream=True代表按照流式输出：
import ollama# 流式输出
def api_generate(text:str):print(f'提问：{text}')stream = ollama.generate(stream=True,model='qwen:7b',prompt=text,)print('-----------------------------------------')for chunk in stream:if not chunk['done']:print(chunk['response'], end='', flush=True)else:print('\n')print('-----------------------------------------')print(f'总耗时：{chunk['total_duration']}')print('-----------------------------------------')if __name__ == '__main__':# 流式输出api_generate(text='天空为什么是蓝色的？')# 非流式输出content = ollama.generate(model='qwen:0.5b', prompt='天空为什么是蓝色的？')print(content)Ollama 客户端：Java API 应用（SpringBoot 应用）
第一步，在总pom.xml中新增 SpringBoot Starter 依赖：
<dependency><groupId>io.springboot.ai</groupId><artifactId>spring-ai-ollama-spring-boot-starter</artifactId><version>1.0.0</version>
</dependency>
第二步，在 SpringBoot 配置文件application.properties中增加 Ollama 配置信息：
server.port=8088
spring.application.name=NTopicBootX
spring.ai.ollama.base-url=http://localhost:11434
spring.ai.ollama.chat.options.model=qwen:0.5b
第三步，使用OllamaChatClient进行文字生成或者对话：
import org.springframework.ai.chat.ChatResponse;
import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.ai.ollama.OllamaChatClient;
import org.springframework.ai.ollama.api.OllamaOptions;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;@RestController
public class OllamaClientController {@Autowired@Qualifier("ollamaChatClient")private OllamaChatClient ollamaChatClient;/*** http://localhost:8088/ollama/chat/v1?msg=天空为什么是蓝色的？*/@GetMapping("/ollama/chat/v1")public String ollamaChat(@RequestParam String msg) {return this.ollamaChatClient.call(msg);}/*** http://localhost:8088/ollama/chat/v2?msg=人为什么要不断的追求卓越？*/@GetMapping("/ollama/chat/v2")public Object ollamaChatV2(@RequestParam String msg) {Prompt prompt = new Prompt(msg);ChatResponse chatResponse = ollamaChatClient.call(prompt);return chatResponse;}/*** http://localhost:8088/ollama/chat/v3?msg=你认为老牛同学的文章如何？*/@GetMapping("/ollama/chat/v3")public Object ollamaChatV3(@RequestParam String msg) {Prompt prompt = new Prompt(msg,OllamaOptions.create().withModel("qwen:0.5b").withTemperature(0.4F));ChatResponse chatResponse = ollamaChatClient.call(prompt);return chatResponse.getResult().getOutput().getContent();}
}
