Ollama Ai Model provides a lot of functionality, along with it, Ollama allows to registration of custom Funtions, tools and external API for enhancing the Model capability. The AI Model can intelligently choose to call one or many functions. The Spring Ai Ollama Function calling can easily integrate with the Ai Models.
The function needs to register as a Spring Bean with the name, description, and call signature that will tell the Model about the required arguments. The description helps the Model to decide when to call the function.
package com.example.springai.config;
import com.example.springai.service.WeatherService;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.context.annotation.Description;
import java.util.function.Function;
@Configuration
public class FunctionConfiguration {
@Bean
@Description("Get the current weather condition for the given city")
public Function<WeatherService.Request, WeatherService.Response> currentWeatherFunction() {
return new WeatherService();
}
}
package com.example.springai.controller;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.messages.SystemMessage;
import org.springframework.ai.chat.messages.UserMessage;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.chat.prompt.Prompt;
import org.springframework.ai.ollama.api.OllamaOptions;
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;
@RestController
public class SpringAiController {
private final ChatClient chatClient;
public SpringAiController(ChatClient.Builder chatClient) {
this.chatClient = chatClient.build();
}
@GetMapping("/function")
public String function(@RequestParam(value = "question") String question) {
SystemMessage systemMessage = new SystemMessage("You are a helpful AI assistant answering questions about cities around the world and their current weather in very detail.");
UserMessage userMessage = new UserMessage(question);
OllamaOptions currentWeatherFunction = OllamaOptions.builder().function("currentWeatherFunction").build();
Prompt prompt = new Prompt(List.of(systemMessage, userMessage), currentWeatherFunction);
ChatResponse chatResponse = chatClient.prompt(prompt).call().chatResponse();
return chatResponse.getResult().getOutput().getContent();
}
}
package com.example.springai.service;
import com.google.gson.Gson;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Configuration;
import org.springframework.core.io.Resource;
import java.io.IOException;
import java.nio.charset.StandardCharsets;
import java.util.function.Function;
@Configuration
public class WeatherService implements Function<WeatherService.Request, WeatherService.Response> {
@Value("classpath:weather.json")
Resource resourceFile;
private @Autowired Gson gson;
@Override
public Response apply(Request request) {
System.out.println("WeatherService.apply request = " + request);
try {
return gson.fromJson(resourceFile.getContentAsString(StandardCharsets.UTF_8), Response.class);
} catch (IOException e) {
throw new RuntimeException("Unable to read weather json file " + e);
}
}
public record Request(String city) {
}
record AirQuality(double co, double no2, double o3, double so2, double pm2_5, double pm10) {
}
record Condition(String text, String icon, int code) {
}
record Current(int last_updated_epoch, String last_updated, int temp_c, double temp_f, int is_day,
Condition condition, double wind_mph, double wind_kph, int wind_degree, String wind_dir,
int pressure_mb, double pressure_in, double precip_mm, int precip_in, int humidity, int cloud,
double feelslike_c, double feelslike_f, int vis_km, int vis_miles, int uv, double gust_mph,
double gust_kph, AirQuality air_quality) {
}
record Location(String name, String region, String country, double lat, double lon, String tz_id,
int localtime_epoch, String localtime) {
}
public record Response(Location location, Current current) {
}
}
package com.example.springai;
import com.google.gson.Gson;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;
@SpringBootApplication
public class SpringAiApplication {
public static void main(String[] args) {
SpringApplication.run(SpringAiApplication.class, args);
}
@Bean
public Gson gson() {
return new Gson();
}
}
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
{
"location": {
"name": "London",
"region": "City of London, Greater London",
"country": "United Kingdom",
"lat": 51.52,
"lon": -0.11,
"tz_id": "Europe/London",
"localtime_epoch": 1613896955,
"localtime": "2024-02-21 8:42"
},
"current": {
"last_updated_epoch": 1613896210,
"last_updated": "2021-02-21 08:30",
"temp_c": 10,
"temp_f": 50.8,
"is_day": 1,
"condition": {
"text": "Partly cloudy",
"icon": "//cdn.weatherapi.com/weather/64x64/day/116.png",
"code": 1003
},
"wind_mph": 3.8,
"wind_kph": 6.1,
"wind_degree": 220,
"wind_dir": "SW",
"pressure_mb": 1009,
"pressure_in": 30.3,
"precip_mm": 0.1,
"precip_in": 0,
"humidity": 82,
"cloud": 75,
"feelslike_c": 9.5,
"feelslike_f": 49.2,
"vis_km": 10,
"vis_miles": 6,
"uv": 1,
"gust_mph": 10.5,
"gust_kph": 16.9,
"air_quality": {
"co": 230.3,
"no2": 13.5,
"o3": 54.3,
"so2": 7.9,
"pm2_5": 8.6,
"pm10": 11.3,
"us-epa-index": 1,
"gb-defra-index": 1
}
}
}
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 $pid
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://maven.apache.org/POM/4.0.0"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-parent</artifactId>
<version>3.3.2</version>
<relativePath/>
</parent>
<groupId>com.example.springai</groupId>
<artifactId>function-calling</artifactId>
<version>0.0.1-SNAPSHOT</version>
<name>Function calling</name>
<description>Demo project for Spring Boot</description>
<properties>
<java.version>21</java.version>
<spring-ai.version>1.0.0-SNAPSHOT</spring-ai.version>
</properties>
<dependencies>
<dependency>
<groupId>com.google.code.gson</groupId>
<artifactId>gson</artifactId>
<version>2.11.0</version>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-ollama-spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-docker-compose</artifactId>
<scope>runtime</scope>
<optional>true</optional>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.springframework.ai</groupId>
<artifactId>spring-ai-bom</artifactId>
<version>${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 Ollama Function Calling
curl --location 'localhost:8080/function?question=what%20is%20current%20weather%20in%20London'
