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>\.ollama\models

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@Resourceprivate 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;@RestControllerpublic 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;@RestControllerpublic 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(); }}