SpringAI调用本地ollama大模型

pom文件

<?xml version="1.0" encoding="UTF-8"?> <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http:// .w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 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>3.2.4</version> <relativePath/> <!-- lookup parent from repository --> </parent> <groupId>com.bjpowernode</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>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> <!--配置本项目的仓库：因为maven中心仓库还没有更新spring ai的jar包--> <repositories> <!--快照版本的仓库--> <repository> <id>spring-snapshot</id> <name>Spring Snapshots</name> <url> repo.spring.io/snapshot</url> <releases> <enabled>false</enabled> </releases> </repository> </repositories> </project>

配置文件：application.yml

spring: application: name: spring-ai-ollama ai: ollama: base-url: http://localhost:11434 chat: options: model: qwen2.5-coder:7b

Demo

package com.bjpowernode.controller; import jakarta.annotation.Resource; import org.springframework.ai.chat.model.ChatModel; 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 ollamaChatClient; @Resource private ChatModel chatClient; @RequestMapping(value = "/ai/ollama") public Object ollama(@RequestParam(value = "msg") String msg) { String called = ollamaChatClient.call(msg); System.out.println(called); return called; } @RequestMapping(value = "/ai/ollama2") public Object ollama2(@RequestParam(value = "msg") String msg) { ChatResponse chatResponse = ollamaChatClient.call(new Prompt(msg, OllamaOptions.builder() .model("qwen2.5-coder:7b") //使用哪个大模型 .temperature(0.4).build())); //温度，温度值越高，准确率下降，温度值越低，准确率会提高 System.out.println(chatResponse.getResult().getOutput().getText()); return chatResponse.getResult().getOutput().getText(); } }

运行项目 测试demo

我这里ollama部署的是 qwen2.5-coder:7b 你们可以根据自己部署的模型更改代码中的配置进行访问

前文： Windows部署千问大模型 需要调用其他模型的可以根据下面地址查看API Spring ：官网 接口文档查看： AI Models就是可以调用的所有模型 Chat Models就是对话模型

SpringAI可以调用的对话模型： docs.spring.io/spring-ai/reference/api/chat/qianfan-chat.html Spring AI支持： 1、Chat Models 聊天模型 2、Text-to-image Models 文本到图像模型： 3、Transcription (audio to text) Models 转录（音频到文本）模型 4、Embedding Models 嵌入模型 5、矢量数据库 6、用于AI模型和矢量存储的Spring Boot自动配置和启动器； 7、函数调用 8、用于数据工程的ETL框架 9、广泛的参考文档、示例应用程序和研讨会/课程材料