用自己的服务器做网站网站开发开题报告范文

Github

• https://github.com/ollama/ollama

官网

• https://ollama.com/

简介

Ollama 是一个本地化大语言模型运行框架，主要特点包括：

• 支持在本地运行 Llama 3、Mistral、DeepSeek 等主流大模型
• 提供REST API接口（如您代码中的 base_url 配置）
• 支持多平台（MacOS/Linux/Windows）
• 内置模型库管理功能

安装

• 验证是否安装成功

ollama -v
# 监听 Ollama 服务端口
lsof -i :11434 | grep LISTEN

基础命令

# 下载模型到本地
ollama pull deepseek-r1:1.5b
# 列出已有的模型
ollama list
# 运行指定模型
ollama run deepseek-r1:1.5b
ollama run deepseek-r1:7b
# 删除本地模型
ollama rm deepseek-r1:7b

模型下载

• https://ollama.com/library/deepseek-r1
  
  

注：本地资源有限就只下载了 1.5b 版本。

运行模型

ollama list
ollama run deepseek-r1:1.5b

注：首次执行会先下载模型；按 Ctr + d 停止运行

测试模型

API文档

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

常用API

• http://127.0.0.1:11434
  
• http://127.0.0.1:11434/api/tags
  
• http://127.0.0.1:11434/api/ps
  

Generate 响应

• http://127.0.0.1:11434/api/generate

curl http://127.0.0.1:11434/api/generate \-H "Content-Type: application/json" \-d '{"model": "deepseek-r1:1.5b","prompt": "你好","stream": false}' \--max-time 30 \--no-buffer

Python Generate 示例

import requests
import jsonAPI_URL = "http://localhost:11434/api/generate"def Demo1():data = {"model": "deepseek-r1:1.5b","system": "You are a helpful assistant, and you only speak Chinese.","prompt": "你好","stream": False}response = requests.post(API_URL, json=data)print(response)json_response = response.json()print(json.dumps(json_response, indent=2, ensure_ascii=False))print(json_response.get("response", "").strip())if __name__ == "__main__":Demo1()

Chat 响应

• http://127.0.0.1:11434/api/chat

curl http://127.0.0.1:11434/api/chat \-H "Content-Type: application/json" \-d '{"model": "deepseek-r1:1.5b","messages": [{"role": "system", "content": "You are a helpful assistant, and you only speak Chinese."},{"role": "user", "content": "你好"}],"stream": false}' \--max-time 30 \--no-buffer

Python Chat 示例

import requests
import jsonAPI_URL = "http://localhost:11434/api/chat"def Demo1():data = {"model": "deepseek-r1:1.5b","messages": [{"role": "system", "content": "You are a helpful assistant, and you only speak Chinese."},{"role": "user", "content": "你好"}],"stream": False}response = requests.post(API_URL, json=data)print(response)json_response = response.json()print(json.dumps(json_response, indent=2, ensure_ascii=False))print(json_response['message']['content'])if __name__ == "__main__":Demo1()

• 响应内容

{"model": "deepseek-r1:1.5b","created_at": "2025-03-20T15:10:32.605318Z","message": {"role": "assistant","content": "<think>\n\n</think>\n\n你好！有什么我可以帮助你的吗？"},"done_reason": "stop","done": true,"total_duration": 1046775688,"load_duration": 25081968,"prompt_eval_count": 16,"prompt_eval_duration": 69998462,"eval_count": 13,"eval_duration": 950691930
}

Chatbox

• https://chatboxai.app/zh

Chatbox AI 是一款 AI 客户端应用和智能助手，支持众多先进的 AI 模型和 API，可在 Windows、MacOS、Android、iOS、Linux 和网页版上使用。

Mac 开放局域网访问

# 强制关闭 Ollama
sudo pkill -9 ollama 

• 使用正确的Ollama配置创建plist文件

echo '<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict><key>Label</key><string>ollama</string><key>ProgramArguments</key><array><string>/bin/bash</string><string>-c</string><string>export OLLAMA_HOST="0.0.0.0:11434" && /usr/local/bin/ollama serve</string></array><key>RunAtLoad</key><true/><key>KeepAlive</key><true/>
</dict>
</plist>' > ~/Library/LaunchAgents/ollama.plist

• 设置权限并重新加载服务

chmod 644 ~/Library/LaunchAgents/ollama.plist
launchctl unload ~/Library/LaunchAgents/ollama.plist 2>/dev/null
launchctl load ~/Library/LaunchAgents/ollama.plist

• 启启 Ollama 服务后

lsof -i :11434 | grep LISTEN

• 局域网内访问测试

curl http://192.168.0.100:11434/api/generate \-H "Content-Type: application/json" \-d '{"model": "deepseek-r1:1.5b","prompt": "你好","stream": false}' \--max-time 30 \--no-buffer