大模型工具Ollama
官网:https://ollama.com/
Ollama是一个用于部署和运行各种开源大模型的工具;
它能够帮助用户快速在本地运行各种大模型，极大地简化了大模型在本地运行的过程。用户通过执行几条命令就能在本地运行开源大模型，如Lama 2等;
综上，Ollama是一个大模型部署运行工具，在该工具里面可以部署运行各种大模型，方便开发者在本地搭建一套大模型运行环境;
下载:https://ollama.com/download
下载Ollama
说明:Ollama的运行会受到所使用模型大小的影响;
1、例如，运行一个7B(70亿参数)的模型至少需要8GB的可用内存(RAM)，而运行一个13B(130亿参数)的模型需要16GB的内存，33B(330亿参数)的型需要32GB的内存;
2、需要考虑有足够的磁盘空间，大模型的文件大小可能比较大，建议至少为Ollama和其模型预留50GB的磁盘空间3、性能较高的CPU可以提供更好的运算速度和效率，多核处理器能够更好地处理并行任务，选择具有足够核心数的CPU:
4、显卡(GPU):Ollama支持纯CPU运行，但如果电脑配备了NVIDIA GPU，可以利用GPU进行加速，提高模型的运行速度和性能;
命令行使用ollama 打开终端，输入ollama -h,查看到所有的命令
service ollama start启动allama
输入ollama -v查看当前版本，能输出版本则安装成功
运行模型单行对话
拉取并运行llama2模型
ollama run llama2
直接输入该命令会检查目录下是否有该模型，没有会自动下载，下载好后自动运行该模型
其他模型见library (ollama.com)
# 查看 Ollama 版本
ollama -v
# 查看已安装的模型
ollama list
# 删除指定模型
ollama rm [modelname]
# 模型存储路径
# C:Users<username>.ollamamodels
ollama run qwen:0.5b
默认Ollama api会监听11434端口，可以使用命令进行查看netstat -ano |findstr 114341
//加依赖
<dependency>
<groupld>org.springframework,ai</groupld>
<artifactld>spring-ai-ollama-spring-boot-starter</artifactld>
</dependency>
//写代码
注入OllamaChatClient
@Resource
private OllamaChatClient ollamaChatClient,
//调用call方法
ollamaChatClient.call(msg);
完整pom文件
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>3.3.0</version>
<relativePath/> <!-- lookup parent from repository -->
</parent>
<groupId>com.zzq</groupId>
<artifactId>spring-ai-ollama</artifactId>
<version>0.0.1-SNAPSHOT</version>
<name>spring-ai-ollama</name>
<description>spring-ai-ollama</description>
<properties>
<java.version>17</java.version>
<!-- 快照版本-->
<spring-ai.version>1.0.0-SNAPSHOT</spring-ai.version>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-ollama-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-devtools</artifactId>
<scope>runtime</scope>
<optional>true</optional>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<optional>true</optional>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-bom</artifactId>
<version>${spring-ai.version}</version>
<type>pom</type>
<scope>import</scope>
</dependency>
</dependencies>
</dependencyManagement>
<build>
<plugins>
<plugin>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-maven-plugin</artifactId>
<configuration>
<excludes>
<exclude>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
</exclude>
</excludes>
</configuration>
</plugin>
</plugins>
</build>
<!-- 快照版本-->
<repositories>
<repository>
<id>spring-snapshot</id>
<name>Spring Snapshots</name>
<url>https://repo.spring.io/snapshot</url>
<releases>
<enabled>false</enabled>
</releases>
</repository>
</repositories>
</project>
application文件内容
spring:
application:
name:spring-ai-05-ollama
ai:
ollama:
base-url: http://localhost:11434
chat:
options:
model: qwen:0.5b
controller
package com.zzq.controller;
import jakarta.annotation.Resource;
import org.springframework.ai.ollama.OllamaChatModel;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
@RestController
public class OllamaController {
@Resource
private OllamaChatModel ollamaChatModel;
@RequestMapping(value = "/ai/ollama")
public Object ollama(@RequestParam(value = "msg")String msg){
String called=ollamaChatModel.call(msg);
System.out.println(called);
return called;
}
}
package com.zzq.controller;
import jakarta.annotation.Resource;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.ai.ollama.OllamaChatModel;
import org.springframework.ai.ollama.api.OllamaOptions;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
@RestController
public class OllamaController {
@Resource
private OllamaChatModel ollamaChatModel;
@RequestMapping(value = "/ai/ollama")
public Object ollama(@RequestParam(value = "msg")String msg){
String called=ollamaChatModel.call(msg);
System.out.println(called);
return called;
}
@RequestMapping(value = "/ai/ollama2")
public Object ollama2(@RequestParam(value = "msg")String msg){
ChatResponse chatResponse=ollamaChatModel.call(new Prompt(msg, OllamaOptions.create()
.withModel("qwen:0.5b")//使用哪个大模型
.withTemperature(0.4F)));//温度，温度值越高，准确率下降，温度值越低，准确率上升
System.out.println(chatResponse.getResult().getOutput().getContent());
return chatResponse.getResult().getOutput().getContent();
}
}
