The User Prompt has User role and it provides placeholders which allows to append Users Messages.The Spring Ai Prompt Template with Message allows to pass System Prompt with System Role.
package com.example.springai.controller;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.messages.Message;
import org.springframework.ai.chat.messages.UserMessage;
import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.ai.chat.prompt.SystemPromptTemplate;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestParam;
import org.springframework.web.bind.annotation.RestController;
import java.util.List;
import java.util.Map;
@RestController
public class SpringAiController {
private final ChatClient chatClient;
public SpringAiController(ChatClient.Builder chatClient) {
this.chatClient = chatClient.build();
}
@GetMapping("/hello")
String hello(@RequestParam(value = "topic", required = false, defaultValue = "Ai with Spring") String topic) {
Message userMessage = new UserMessage("Hello, I am learning {topic}.");
SystemPromptTemplate systemPromptTemplate = new SystemPromptTemplate("You are a friendly chat bot that answers question in very detail with example in a story format.");
Message systemMessage = systemPromptTemplate.createMessage(Map.of("topic", topic));
Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
return chatClient.prompt(prompt).call().content();
}
}
package com.example.springai;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
@SpringBootApplication
public class SpringAiApplication {
public static void main(String[] args) {
SpringApplication.run(SpringAiApplication.class, args);
}
}
spring.application.name=SpringAi
spring.docker.compose.lifecycle-management=start-only
spring.threads.virtual.enabled=true
# The default Ollama Model in Spring Ai is mistral, but it can be changed by setting the below property. make sure to download the same model in entrypoint.sh file
#spring.ai.ollama.chat.options.model=llama3.1
# If running the Ollama Docker Instance separately, then set this property
spring.docker.compose.enabled=false
services:
ollama-model:
image: ollama/ollama:latest
container_name: ollama_container
ports:
- 11434:11434/tcp
healthcheck:
test: ollama --version || exit 1
command: serve
volumes:
- ./ollama/ollama:/root/.ollama
- ./entrypoint.sh:/entrypoint.sh
pull_policy: missing
tty: true
restart: no
entrypoint: [ "/usr/bin/bash", "/entrypoint.sh" ]
open-webui:
image: ghcr.io/open-webui/open-webui:main
container_name: open_webui_container
environment:
WEBUI_AUTH: false
ports:
- "8081:8080"
extra_hosts:
- "host.docker.internal:host-gateway"
volumes:
- open-webui:/app/backend/data
restart: no
volumes:
open-webui:
#!/bin/bash
# Start Ollama in the background.
/bin/ollama serve &
# Record Process ID.
pid=$!
# Pause for Ollama to start.
sleep 5
# The default Ollama Model in Spring Ai is mistral, but it can be changed in the applications property file. Make sure to download the same Model here
echo "🔴 Retrieve LLAMA3 model..."
ollama pull mistral
echo "🟢 Done!"
# Wait for the Ollama process to finish.
wait $pid
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://maven.apache.org/POM/4.0.0"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>3.3.2</version>
<relativePath/>
</parent>
<groupId>com.example.springai</groupId>
<artifactId>prompt-template-message</artifactId>
<version>0.0.1-SNAPSHOT</version>
<name>Prompt Template Message</name>
<description>Demo project for Spring Boot</description>
<properties>
<java.version>21</java.version>
<spring-ai.version>1.0.0-SNAPSHOT</spring-ai.version>
</properties>
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-ollama-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-docker-compose</artifactId>
<scope>runtime</scope>
<optional>true</optional>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-bom</artifactId>
<version>${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>
<mainClass>com.example.springai.SpringAiApplication</mainClass>
<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>
<repository>
<id>spring-snapshots</id>
<name>Spring Snapshots</name>
<url>https://repo.spring.io/snapshot</url>
<releases>
<enabled>false</enabled>
</releases>
</repository>
</repositories>
</project>
Run the curl to see the Spring Ai Prompt Template with Message
curl --location 'localhost:8080/hello?topic=Ai with Spring'
