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Ollama使用

Ollama是一个用于在本地计算机上运行大模型的软件
软件运行后监听11434端口，自己写的程序要调大模型就用这个端口

ollama命令
ollama list：显示模型列表
ollama show：显示模型的信息
ollama pull：拉取模型
ollama push：推送模型
ollama cp：拷贝一个模型
ollama rm：删除一个模型
ollama run：运行一个模型

ollama全是命令行下操作，所以结合web客户端界面使用【安装可选】
主流的web工具
1 Openwebui
2 LobeChat,功能强大，可调用Ollama的模型，也可调用openai,google的等，在设置界面中配置url和key即可

spring Ai框架调用

1 pom.xml，注意添加的依赖和配置了仓库

<?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>3.2.5</version><relativePath/> <!-- lookup parent from repository --></parent><groupId>com.example</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><spring-ai.version>0.8.1</spring-ai.version></properties><dependencies><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-web</artifactId></dependency><dependency><groupId>io.springboot.ai</groupId><artifactId>spring-ai-ollama-spring-boot-starter</artifactId><version>1.0.0</version></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><repositories><repository><id>spring-milestones</id><name>Spring Milestones</name><url>https://repo.spring.io/milestone</url><snapshots><enabled>false</enabled></snapshots></repository></repositories></project>

2 yml配置，写自己的 Ollama 地址，模型用哪个，先用Ollama去下载

spring:application:name: spring-ai-ollamaai:ollama:base-url: http://120.55.99.218:11434chat:options:model: gemma:7b

3 测试

import org.springframework.ai.chat.ChatResponse;
import org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.ai.chat.prompt.PromptTemplate;
import org.springframework.ai.ollama.OllamaChatClient;
import org.springframework.ai.ollama.api.OllamaOptions;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.*;@RestController
public class AiController {@Autowiredprivate OllamaChatClient ollamaChatClient;@GetMapping(value = "/chat_1")public String chat_1(@RequestParam(value = "message") String message) {String call = ollamaChatClient.call(message);System.out.println("模型回答 = " + call);return call;}@GetMapping(value = "/chat_2")public Object chat_2(@RequestParam(value = "message") String message) {Prompt prompt = new Prompt(message,OllamaOptions.create()//代码中配置，会覆盖application.yml中的配置.withModel("gemma:7b") //使用什么大模型.withTemperature(0.9F) //温度高，更发散,准确性降低，温度低，更保守，准确性高);ChatResponse call = ollamaChatClient.call(prompt);AssistantMessage output = call.getResult().getOutput();System.out.println("模型回答 = " + output.getContent());return output;}@GetMapping("/chat_3/{size}")public String chatYear(@PathVariable("size") Integer size) {String message = "随便写一句话,{size} 字以内";PromptTemplate promptTemplate = new PromptTemplate(message);promptTemplate.add("size", size);System.out.println(promptTemplate.render());return ollamaChatClient.call(promptTemplate.render());}
}