ollama

install

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

get model

ollama run deepseek-r1:14b

install nvidia docker

curl -s -L https://nvidia.github.io/libnvidia-container/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/libnvidia-container/ubuntu20.04/libnvidia-container.list | \
sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update
sudo apt-get install -y nvidia-container-toolkit
sudo nvidia-ctk runtime configure
sudo systemctl restart docker
docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi
ollama run llama3.3
//see gpu use
nvidia-smi

install open-webui

docker run -d -p 3000:8080  -v open-webui:/app/backend/data --name open-webui dyrnq/open-webui

use docker-compose

services:
  open-webui:
    image: dyrnq/open-webui:main
    container_name: open-webui
    restart: always
    ports:
      - "3000:8080"
    volumes:
      - open-webui:/app/backend/data
    extra_hosts:
      - "host.docker.internal:host-gateway"
    environment:
      - OLLAMA_API_BASE_URL=http://host.docker.internal:11434
    networks:
      - my-network
networks:
  my-network:
    driver: bridge

volumes:
  open-webui:

ollama config

sudo vi /etc/systemd/system/ollama.service

edit service

[Unit]
Description=Ollama Service
After=network-online.target

[Service]
ExecStart=/usr/local/bin/ollama serve
User=ollama
Group=ollama
Restart=always
RestartSec=3
Environment="PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin"

[Install]
WantedBy=default.target

reload service

sudo systemctl daemon-reload
sudo systemctl restart ollama.service
ps aux | grep ollama

chat ui

open-webui

MaxKB

python use

install package

shell

pip install ollama

run by python

python

from ollama import Client

client = Client(
    host='http://127.0.0.1:11434',
)
def chat_with_model():
    print("欢迎使用 AI 助手！输入 'exit' 退出对话。\n")

    # 设置用户角色
    messages = [
        {'role': 'system', 'content': '你是一个linux下python专家'}
    ]

    while True:
        try:
            # 获取用户输入
            user_input = input("你: ")
            if user_input.lower() == 'exit':
                print("对话已结束。")
                break

            # 添加用户消息到对话历史
            messages.append({'role': 'user', 'content': user_input})

            # 调用模型，开启流式输出
            stream = client.chat(model='deepseek-r1:32b', messages=messages, stream=True)
            print("助手: ", end="", flush=True)

            # 收集助手的响应
            assistant_response = ""
            for chunk in stream:
                if 'message' in chunk and 'content' in chunk['message']:
                    content = chunk['message']['content']
                    assistant_response += content
                    print(content, end="", flush=True)

            print()  # 换行

            # 将助手响应添加到对话历史
            messages.append({'role': 'assistant', 'content': assistant_response})

        except Exception as e:
            print(f"发生错误: {e}")


if __name__ == "__main__":
    chat_with_model()

ai助手

https://github.com/ibiteam/assistant

ollama ​

python use ​

ollama

python use