함수 호출을 사용하면 모델을 외부 도구 및 API에 연결할 수 있습니다. 모델은 텍스트 응답을 생성하는 대신 특정 함수를 호출할 시기를 결정하고 실제 작업을 실행하는 데 필요한 파라미터를 제공합니다. 이를 통해 모델은 자연어와 실제 작업 및 데이터 간의 다리 역할을 할 수 있습니다. 함수 호출에는 3가지 주요 사용 사례가 있습니다.
- 작업 수행: 약속 일정 예약, 인보이스 생성, 이메일 전송, 스마트 홈 기기 제어 등 API를 사용하여 외부 시스템과 상호작용합니다.
- 지식 보강: 데이터베이스, API, 기술 자료와 같은 외부 소스의 정보에 액세스합니다.
- 기능 확장: 외부 도구를 사용하여 계산을 수행하고 계산기 사용이나 차트 생성과 같은 모델의 제한사항을 확장합니다.
아래에서 이러한 사용 사례의 예를 살펴볼 수 있습니다.
회의 일정 예약
이 예에서는 특정 시간에 참석자와 회의를 예약하는 함수를 정의하여 모델이 사용자 요청을 파싱하고 구조화된 인수를 반환하여 외부 시스템에서 작업을 트리거할 수 있도록 하는 방법을 보여줍니다.
Python
from google import genai
schedule_meeting_function = {
"type": "function",
"name": "schedule_meeting",
"description": "Schedules a meeting with specified attendees at a given time and date.",
"parameters": {
"type": "object",
"properties": {
"attendees": {"type": "array", "items": {"type": "string"}},
"date": {"type": "string", "description": "Date (e.g., '2024-07-29')"},
"time": {"type": "string", "description": "Time (e.g., '15:00')"},
"topic": {"type": "string", "description": "The meeting topic."},
},
"required": ["attendees", "date", "time", "topic"],
},
}
client = genai.Client()
interaction = client.interactions.create(
model="gemini-3.8-flash",
input="Schedule a meeting with Bob and Alice for 03/14/2025 at 10:00 AM about Q3 planning.",
tools=[{"type": "function", **schedule_meeting_function}],
)
for step in interaction.steps:
if step.type == "function_call":
print(f"Function to call: {step.name}")
print(f"Arguments: {step.arguments}")
자바스크립트
import { GoogleGenAI } from '@google/genai';
const client = new GoogleGenAI({});
const scheduleMeetingFunction = {
type: 'function',
name: 'schedule_meeting',
description: 'Schedules a meeting with specified attendees at a given time and date.',
parameters: {
type: 'object',
properties: {
attendees: { type: 'array', items: { type: 'string' } },
date: { type: 'string', description: 'Date (e.g., "2024-07-29")' },
time: { type: 'string', description: 'Time (e.g., "15:00")' },
topic: { type: 'string', description: 'The meeting topic.' },
},
required: ['attendees', 'date', 'time', 'topic'],
},
};
const interaction = await client.interactions.create({
model: 'gemini-3.8-flash',
input: 'Schedule a meeting with Bob and Alice for 03/27/2025 at 10:00 AM about Q3 planning.',
tools: [scheduleMeetingFunction],
});
for (const step of interaction.steps) {
if (step.type === 'function_call') {
console.log(`Function to call: ${step.name}`);
console.log(`Arguments: ${JSON.stringify(step.arguments)}`);
}
}
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Function;
import com.google.genai.gaos.models.interactions.FunctionCallStep;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.Map;
Client client = new Client();
Map<String, Object> attendeesProp = new HashMap<>();
attendeesProp.put("type", "array");
attendeesProp.put("items", Collections.singletonMap("type", "string"));
Map<String, Object> dateProp = new HashMap<>();
dateProp.put("type", "string");
dateProp.put("description", "Date (e.g., '2024-07-29')");
Map<String, Object> timeProp = new HashMap<>();
timeProp.put("type", "string");
timeProp.put("description", "Time (e.g., '15:00')");
Map<String, Object> topicProp = new HashMap<>();
topicProp.put("type", "string");
topicProp.put("description", "The meeting topic.");
Map<String, Object> properties = new HashMap<>();
properties.put("attendees", attendeesProp);
properties.put("date", dateProp);
properties.put("time", timeProp);
properties.put("topic", topicProp);
Map<String, Object> parameters = new HashMap<>();
parameters.put("type", "object");
parameters.put("properties", properties);
parameters.put("required", Arrays.asList("attendees", "date", "time", "topic"));
Function scheduleMeetingFunction =
Function.builder()
.name("schedule_meeting")
.description("Schedules a meeting with specified attendees at a given time and date.")
.parameters(parameters)
.build();
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(
InteractionsInput.of(
"Schedule a meeting with Bob and Alice for 03/14/2025 at 10:00 AM about Q3 planning."))
.tools(Arrays.asList(scheduleMeetingFunction))
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
if (interaction.steps().isPresent()) {
for (Step step : interaction.steps().get()) {
if (step instanceof FunctionCallStep) {
FunctionCallStep functionCall = (FunctionCallStep) step;
System.out.println("Function to call: " + functionCall.name().orElse(""));
System.out.println("Arguments: " + functionCall.arguments().orElse(null));
}
}
}
Go
package main
import (
"context"
"fmt"
"log"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
// Define the function declaration for the model
scheduleMeetingFunc := &genai.FunctionDeclaration{
Name: "schedule_meeting",
Description: "Schedules a meeting with specified attendees at a given time and date.",
Parameters: &genai.Schema{
Type: genai.TypeObject,
Properties: map[string]*genai.Schema{
"attendees": {
Type: genai.TypeArray,
Items: &genai.Schema{Type: genai.TypeString},
Description: "List of people attending the meeting.",
},
"date": {
Type: genai.TypeString,
Description: "Date (e.g., '2024-07-29')",
},
"time": {
Type: genai.TypeString,
Description: "Time (e.g., '15:00')",
},
"topic": {
Type: genai.TypeString,
Description: "The meeting topic.",
},
},
Required: []string{"attendees", "date", "time", "topic"},
},
}
config := &genai.GenerateContentConfig{
Tools: []*genai.Tool{
{FunctionDeclarations: []*genai.FunctionDeclaration{scheduleMeetingFunc}},
},
}
// Send request with function declarations
response, err := client.Models.GenerateContent(
ctx,
"gemini-3.8-flash",
genai.Text("Schedule a meeting with Bob and Alice for 03/14/2025 at 10:00 AM about Q3 planning."),
config,
)
if err != nil {
log.Fatal(err)
}
// Check for a function call
if len(response.FunctionCalls()) > 0 {
functionCall := response.FunctionCalls()[0]
fmt.Printf("Function to call: %s\n", functionCall.Name)
fmt.Printf("Arguments: %v\n", functionCall.Args)
} else {
fmt.Println("No function call found in the response.")
fmt.Println(response.Text())
}
}
REST
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "gemini-3.8-flash",
"input": "Schedule a meeting with Bob and Alice for 03/27/2025 at 10:00 AM about Q3 planning.",
"tools": [{
"type": "function",
"name": "schedule_meeting",
"description": "Schedules a meeting with specified attendees at a given time and date.",
"parameters": {
"type": "object",
"properties": {
"attendees": {"type": "array", "items": {"type": "string"}},
"date": {"type": "string"},
"time": {"type": "string"},
"topic": {"type": "string"}
},
"required": ["attendees", "date", "time", "topic"]
}
}]
}'
날씨 확인
이 예시에서는 위치의 온도 데이터를 가져오는 함수를 정의하여 모델이 실시간 또는 외부 정보가 필요한 질문에 답변하기 위해 외부 API를 호출할 수 있도록 하는 방법을 보여줍니다.
Python
from google import genai
weather_function = {
"type": "function",
"name": "get_current_temperature",
"description": "Gets the current temperature for a given location.",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city name, e.g. San Francisco",
},
},
"required": ["location"],
},
}
client = genai.Client()
interaction = client.interactions.create(
model="gemini-3.8-flash",
input="What's the temperature in London?",
tools=[weather_function],
)
for step in interaction.steps:
if step.type == "function_call":
print(f"Function to call: {step.name}")
print(f"Arguments: {step.arguments}")
자바스크립트
import { GoogleGenAI } from '@google/genai';
const client = new GoogleGenAI({});
const weatherFunctionDeclaration = {
type: 'function',
name: 'get_current_temperature',
description: 'Gets the current temperature for a given location.',
parameters: {
type: 'object',
properties: {
location: {
type: 'string',
description: 'The city name, e.g. San Francisco',
},
},
required: ['location'],
},
};
const interaction = await client.interactions.create({
model: 'gemini-3.8-flash',
input: "What's the temperature in London?",
tools: [weatherFunctionDeclaration],
});
for (const step of interaction.steps) {
if (step.type === 'function_call') {
console.log(`Function to call: ${step.name}`);
console.log(`Arguments: ${JSON.stringify(step.arguments)}`);
}
}
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Function;
import com.google.genai.gaos.models.interactions.FunctionCallStep;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;
Client client = new Client();
Map<String, Object> locationProp = new HashMap<>();
locationProp.put("type", "string");
locationProp.put("description", "The city name, e.g. San Francisco");
Map<String, Object> properties = new HashMap<>();
properties.put("location", locationProp);
Map<String, Object> parameters = new HashMap<>();
parameters.put("type", "object");
parameters.put("properties", properties);
parameters.put("required", Arrays.asList("location"));
Function weatherFunction =
Function.builder()
.name("get_current_temperature")
.description("Gets the current temperature for a given location.")
.parameters(parameters)
.build();
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(InteractionsInput.of("What's the temperature in London?"))
.tools(Arrays.asList(weatherFunction))
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
if (interaction.steps().isPresent()) {
for (Step step : interaction.steps().get()) {
if (step instanceof FunctionCallStep) {
FunctionCallStep functionCall = (FunctionCallStep) step;
System.out.println("Function to call: " + functionCall.name().orElse(""));
System.out.println("Arguments: " + functionCall.arguments().orElse(null));
}
}
}
Go
package main
import (
"context"
"fmt"
"log"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
// Define the function declaration for the model
weatherFunc := &genai.FunctionDeclaration{
Name: "get_current_temperature",
Description: "Gets the current temperature for a given location.",
Parameters: &genai.Schema{
Type: genai.TypeObject,
Properties: map[string]*genai.Schema{
"location": {
Type: genai.TypeString,
Description: "The city name, e.g. San Francisco",
},
},
Required: []string{"location"},
},
}
config := &genai.GenerateContentConfig{
Tools: []*genai.Tool{
{FunctionDeclarations: []*genai.FunctionDeclaration{weatherFunc}},
},
}
// Send request with function declarations
response, err := client.Models.GenerateContent(
ctx,
"gemini-3.8-flash",
genai.Text("What's the temperature in London?"),
config,
)
if err != nil {
log.Fatal(err)
}
// Check for a function call
if len(response.FunctionCalls()) > 0 {
functionCall := response.FunctionCalls()[0]
fmt.Printf("Function to call: %s\n", functionCall.Name)
fmt.Printf("Arguments: %v\n", functionCall.Args)
} else {
fmt.Println("No function call found in the response.")
fmt.Println(response.Text())
}
}
REST
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "gemini-3.8-flash",
"input": "What'\''s the temperature in London?",
"tools": [{
"type": "function",
"name": "get_current_temperature",
"description": "Gets the current temperature for a given location.",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "The city name"}
},
"required": ["location"]
}
}]
}'
차트 만들기
이 예에서는 구조화된 데이터에서 막대 그래프를 생성하는 함수를 정의하여 모델이 외부 도구를 사용하여 계산을 수행하거나 시각적 애셋을 만드는 방법을 보여줍니다.
Python
from google import genai
create_chart_function = {
"type": "function",
"name": "create_bar_chart",
"description": "Creates a bar chart given a title, labels, and values.",
"parameters": {
"type": "object",
"properties": {
"title": {"type": "string", "description": "The title for the chart."},
"labels": {"type": "array", "items": {"type": "string"}},
"values": {"type": "array", "items": {"type": "number"}},
},
"required": ["title", "labels", "values"],
},
}
client = genai.Client()
interaction = client.interactions.create(
model="gemini-3.8-flash",
input="Create a bar chart titled 'Quarterly Sales' with Q1: 50000, Q2: 75000, Q3: 60000.",
tools=[create_chart_function],
)
for step in interaction.steps:
if step.type == "function_call":
print(f"Function to call: {step.name}")
print(f"Arguments: {step.arguments}")
자바스크립트
import { GoogleGenAI } from '@google/genai';
const client = new GoogleGenAI({});
const createChartFunctionDeclaration = {
type: 'function',
name: 'create_bar_chart',
description: 'Creates a bar chart given a title, labels, and values.',
parameters: {
type: 'object',
properties: {
title: { type: 'string', description: 'The title for the chart.' },
labels: { type: 'array', items: { type: 'string' } },
values: { type: 'array', items: { type: 'number' } },
},
required: ['title', 'labels', 'values'],
},
};
const interaction = await client.interactions.create({
model: 'gemini-3.8-flash',
input: "Create a bar chart titled 'Quarterly Sales' with Q1: 50000, Q2: 75000, Q3: 60000.",
tools: [createChartFunctionDeclaration],
});
for (const step of interaction.steps) {
if (step.type === 'function_call') {
console.log(`${step.name}(${JSON.stringify(step.arguments)})`);
}
}
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Function;
import com.google.genai.gaos.models.interactions.FunctionCallStep;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.Map;
Client client = new Client();
Map<String, Object> properties = new HashMap<>();
Map<String, Object> titleMap = new HashMap<>();
titleMap.put("type", "string");
titleMap.put("description", "The title for the chart.");
properties.put("title", titleMap);
Map<String, Object> labelsMap = new HashMap<>();
labelsMap.put("type", "array");
labelsMap.put("items", Collections.singletonMap("type", "string"));
properties.put("labels", labelsMap);
Map<String, Object> valuesMap = new HashMap<>();
valuesMap.put("type", "array");
valuesMap.put("items", Collections.singletonMap("type", "number"));
properties.put("values", valuesMap);
Map<String, Object> parameters = new HashMap<>();
parameters.put("type", "object");
parameters.put("properties", properties);
parameters.put("required", Arrays.asList("title", "labels", "values"));
Function createChartFunction =
Function.builder()
.name("create_bar_chart")
.description("Creates a bar chart given a title, labels, and values.")
.parameters(parameters)
.build();
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(
InteractionsInput.of(
"Create a bar chart titled 'Quarterly Sales' with Q1: 50000, Q2: 75000, Q3: 60000."))
.tools(Arrays.asList(createChartFunction))
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
if (interaction.steps().isPresent()) {
for (Step step : interaction.steps().get()) {
if (step instanceof FunctionCallStep) {
FunctionCallStep functionCall = (FunctionCallStep) step;
System.out.println("Function to call: " + functionCall.name().orElse(""));
System.out.println("Arguments: " + functionCall.arguments().orElse(null));
}
}
}
Go
package main
import (
"context"
"fmt"
"log"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
// Define the function declaration for the model
createChartFunc := &genai.FunctionDeclaration{
Name: "create_bar_chart",
Description: "Creates a bar chart given a title, labels, and values.",
Parameters: &genai.Schema{
Type: genai.TypeObject,
Properties: map[string]*genai.Schema{
"title": {
Type: genai.TypeString,
Description: "The title for the chart.",
},
"labels": {
Type: genai.TypeArray,
Items: &genai.Schema{Type: genai.TypeString},
},
"values": {
Type: genai.TypeArray,
Items: &genai.Schema{Type: genai.TypeNumber},
},
},
Required: []string{"title", "labels", "values"},
},
}
config := &genai.GenerateContentConfig{
Tools: []*genai.Tool{
{FunctionDeclarations: []*genai.FunctionDeclaration{createChartFunc}},
},
}
// Send request with function declarations
response, err := client.Models.GenerateContent(
ctx,
"gemini-3.8-flash",
genai.Text("Create a bar chart titled 'Quarterly Sales' with Q1: 50000, Q2: 75000, Q3: 60000."),
config,
)
if err != nil {
log.Fatal(err)
}
// Check for a function call
if len(response.FunctionCalls()) > 0 {
functionCall := response.FunctionCalls()[0]
fmt.Printf("Function to call: %s\n", functionCall.Name)
fmt.Printf("Arguments: %v\n", functionCall.Args)
} else {
fmt.Println("No function call found in the response.")
fmt.Println(response.Text())
}
}
REST
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "gemini-3.8-flash",
"input": "Create a bar chart titled '\''Quarterly Sales'\'' with Q1: 50000, Q2: 75000, Q3: 60000.",
"tools": [{
"type": "function",
"name": "create_bar_chart",
"description": "Creates a bar chart given a title, labels, and values.",
"parameters": {
"type": "object",
"properties": {
"title": {"type": "string"},
"labels": {"type": "array", "items": {"type": "string"}},
"values": {"type": "array", "items": {"type": "number"}}
},
"required": ["title", "labels", "values"]
}
}]
}'
함수 호출 작동 방식
함수 호출은 애플리케이션, 모델, 외부 함수 간의 구조화된 상호작용을 포함합니다.
- 함수 선언 정의: 모델에 함수의 이름, 매개변수, 목적을 정의합니다.
- 함수 선언으로 LLM 호출: 사용자 프롬프트와 함수 선언을 모델에 전송합니다.
- 함수 코드 실행 (사용자 책임): 모델이 함수 자체를 실행하지 않습니다. 이름과 인수를 추출하고 애플리케이션에서 실행합니다.
- 사용자 친화적인 응답 만들기: 최종 사용자 친화적인 응답을 위해 결과를 모델에 다시 전송합니다.
이 프로세스는 여러 턴에 걸쳐 반복될 수 있습니다. 모델은 단일 턴에서 여러 함수를 병렬 (병렬 함수 호출) 및 순차적 (구성 함수 호출)으로 호출하는 것을 지원합니다.
1단계: 함수 선언 정의
Python
set_light_values_declaration = {
"type": "function",
"name": "set_light_values",
"description": "Sets the brightness and color temperature of a light.",
"parameters": {
"type": "object",
"properties": {
"brightness": {
"type": "integer",
"description": "Light level from 0 to 100",
},
"color_temp": {
"type": "string",
"enum": ["daylight", "cool", "warm"],
"description": "Color temperature",
},
},
"required": ["brightness", "color_temp"],
},
}
def set_light_values(brightness: int, color_temp: str) -> dict:
"""Set the brightness and color temperature of a room light."""
return {"brightness": brightness, "colorTemperature": color_temp}
자바스크립트
const setLightValuesTool = {
type: 'function',
name: 'set_light_values',
description: 'Sets the brightness and color temperature of a light.',
parameters: {
type: 'object',
properties: {
brightness: { type: 'number', description: 'Light level from 0 to 100' },
color_temp: { type: 'string', enum: ['daylight', 'cool', 'warm'] },
},
required: ['brightness', 'color_temp'],
},
};
function setLightValues(brightness, color_temp) {
return { brightness: brightness, colorTemperature: color_temp };
}
자바
import com.google.genai.gaos.models.interactions.Function;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;
import java.util.function.BiFunction;
Map<String, Object> brightnessProp = new HashMap<>();
brightnessProp.put("type", "integer");
brightnessProp.put("description", "Light level from 0 to 100");
Map<String, Object> colorTempProp = new HashMap<>();
colorTempProp.put("type", "string");
colorTempProp.put("enum", Arrays.asList("daylight", "cool", "warm"));
colorTempProp.put("description", "Color temperature");
Map<String, Object> properties = new HashMap<>();
properties.put("brightness", brightnessProp);
properties.put("color_temp", colorTempProp);
Map<String, Object> parameters = new HashMap<>();
parameters.put("type", "object");
parameters.put("properties", properties);
parameters.put("required", Arrays.asList("brightness", "color_temp"));
Function setLightValuesDeclaration =
Function.builder()
.name("set_light_values")
.description("Sets the brightness and color temperature of a light.")
.parameters(parameters)
.build();
BiFunction<Integer, String, Map<String, Object>> setLightValues =
(brightness, colorTemp) -> {
Map<String, Object> result = new HashMap<>();
result.put("brightness", brightness);
result.put("colorTemperature", colorTemp);
return result;
};
Go
package main
import "google.golang.org/genai"
var setLightValuesDeclaration = &genai.FunctionDeclaration{
Name: "set_light_values",
Description: "Sets the brightness and color temperature of a light.",
Parameters: &genai.Schema{
Type: genai.TypeObject,
Properties: map[string]*genai.Schema{
"brightness": {
Type: genai.TypeInteger,
Description: "Light level from 0 to 100",
},
"color_temp": {
Type: genai.TypeString,
Enum: []string{"daylight", "cool", "warm"},
Description: "Color temperature",
},
},
Required: []string{"brightness", "color_temp"},
},
}
func setLightValues(brightness int, colorTemp string) map[string]any {
return map[string]any{"brightness": brightness, "colorTemperature": colorTemp}
}
2단계: 함수 선언으로 모델 호출
Python
from google import genai
client = genai.Client()
interaction = client.interactions.create(
model="gemini-3.8-flash",
input="Turn the lights down to a romantic level",
tools=[set_light_values_declaration],
)
fc_step = next(s for s in interaction.steps if s.type == "function_call")
print(fc_step)
자바스크립트
import { GoogleGenAI } from '@google/genai';
const client = new GoogleGenAI({});
const interaction = await client.interactions.create({
model: 'gemini-3.8-flash',
input: 'Turn the lights down to a romantic level',
tools: [setLightValuesTool],
});
const fcStep = interaction.steps.find(s => s.type === 'function_call');
console.log(fcStep);
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Function;
import com.google.genai.gaos.models.interactions.FunctionCallStep;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;
Client client = new Client();
Map<String, Object> brightnessProp = new HashMap<>();
brightnessProp.put("type", "integer");
brightnessProp.put("description", "Light level from 0 to 100");
Map<String, Object> colorTempProp = new HashMap<>();
colorTempProp.put("type", "string");
colorTempProp.put("enum", Arrays.asList("daylight", "cool", "warm"));
colorTempProp.put("description", "Color temperature");
Map<String, Object> properties = new HashMap<>();
properties.put("brightness", brightnessProp);
properties.put("color_temp", colorTempProp);
Map<String, Object> parameters = new HashMap<>();
parameters.put("type", "object");
parameters.put("properties", properties);
parameters.put("required", Arrays.asList("brightness", "color_temp"));
Function setLightValuesDeclaration =
Function.builder()
.name("set_light_values")
.description("Sets the brightness and color temperature of a light.")
.parameters(parameters)
.build();
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(InteractionsInput.of("Turn the lights down to a romantic level"))
.tools(Arrays.asList(setLightValuesDeclaration))
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
FunctionCallStep fcStep = null;
if (interaction.steps().isPresent()) {
for (Step step : interaction.steps().get()) {
if (step instanceof FunctionCallStep) {
fcStep = (FunctionCallStep) step;
break;
}
}
}
System.out.println(fcStep);
Go
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
config := &genai.GenerateContentConfig{
Tools: []*genai.Tool{
{FunctionDeclarations: []*genai.FunctionDeclaration{setLightValuesDeclaration}},
},
}
contents := []*genai.Content{
genai.NewContentFromText("Turn the lights down to a romantic level", genai.RoleUser),
}
response, err := client.Models.GenerateContent(ctx, "gemini-3.8-flash", contents, config)
if err != nil {
log.Fatal(err)
}
fmt.Println(response.FunctionCalls()[0])
모델은 type, name, arguments이 포함된 function_call 단계를 반환합니다.
type='function_call'
name='set_light_values'
arguments={'color_temp': 'warm', 'brightness': 25}
3단계: 함수 실행
Python
fc_step = next(s for s in interaction.steps if s.type == "function_call")
if fc_step.name == "set_light_values":
result = set_light_values(**fc_step.arguments)
print(f"Function execution result: {result}")
자바스크립트
const fcStep = interaction.steps.find(s => s.type === 'function_call');
let result;
if (fcStep.name === 'set_light_values') {
result = setLightValues(fcStep.arguments.brightness, fcStep.arguments.color_temp);
console.log(`Function execution result: ${JSON.stringify(result)}`);
}
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Function;
import com.google.genai.gaos.models.interactions.FunctionCallStep;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.Map;
import java.util.function.BiFunction;
Client client = new Client();
Map<String, Object> brightnessProp = new HashMap<>();
brightnessProp.put("type", "integer");
brightnessProp.put("description", "Light level from 0 to 100");
Map<String, Object> colorTempProp = new HashMap<>();
colorTempProp.put("type", "string");
colorTempProp.put("enum", Arrays.asList("daylight", "cool", "warm"));
colorTempProp.put("description", "Color temperature");
Map<String, Object> properties = new HashMap<>();
properties.put("brightness", brightnessProp);
properties.put("color_temp", colorTempProp);
Map<String, Object> parameters = new HashMap<>();
parameters.put("type", "object");
parameters.put("properties", properties);
parameters.put("required", Arrays.asList("brightness", "color_temp"));
Function setLightValuesDeclaration =
Function.builder()
.name("set_light_values")
.description("Sets the brightness and color temperature of a light.")
.parameters(parameters)
.build();
BiFunction<Integer, String, Map<String, Object>> setLightValues =
(brightness, colorTemp) -> {
Map<String, Object> result = new HashMap<>();
result.put("brightness", brightness);
result.put("colorTemperature", colorTemp);
return result;
};
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(InteractionsInput.of("Turn the lights down to a romantic level"))
.tools(Arrays.asList(setLightValuesDeclaration))
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
if (interaction.steps().isPresent()) {
for (Step step : interaction.steps().get()) {
if (step instanceof FunctionCallStep) {
FunctionCallStep fcStep = (FunctionCallStep) step;
if ("set_light_values".equals(fcStep.name().orElse(""))) {
Map<String, Object> args = fcStep.arguments().orElse(Collections.emptyMap());
int brightness = ((Number) args.getOrDefault("brightness", 25)).intValue();
String colorTemp = (String) args.getOrDefault("color_temp", "warm");
Map<String, Object> result = setLightValues.apply(brightness, colorTemp);
System.out.println("Function execution result: " + result);
}
}
}
}
Go
toolCall := response.FunctionCalls()[0]
var result map[string]any
if toolCall.Name == "set_light_values" {
brightness := int(toolCall.Args["brightness"].(float64))
colorTemp := toolCall.Args["color_temp"].(string)
result = setLightValues(brightness, colorTemp)
fmt.Printf("Function execution result: %v\n", result)
}
4단계: 결과를 모델에 다시 전송
Python
final_interaction = client.interactions.create(
model="gemini-3.8-flash",
input=[
{
"type": "function_result",
"name": fc_step.name,
"call_id": fc_step.id,
"result": [{"type": "text", "text": json.dumps(result)}],
}
],
tools=[set_light_values_declaration],
previous_interaction_id=interaction.id,
)
print(final_interaction.output_text)
자바스크립트
const finalInteraction = await client.interactions.create({
model: 'gemini-3.8-flash',
input: [{
type: 'function_result',
name: fcStep.name,
call_id: fcStep.id,
result: [{ type: 'text', text: JSON.stringify(result) }]
}],
tools: [setLightValuesTool],
previous_interaction_id: interaction.id,
});
console.log(finalInteraction.output_text);
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Function;
import com.google.genai.gaos.models.interactions.FunctionCallStep;
import com.google.genai.gaos.models.interactions.FunctionResultStep;
import com.google.genai.gaos.models.interactions.FunctionResultStepResultUnion;
import com.google.genai.gaos.models.interactions.FunctionResultSubcontent;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.interactions.TextContent;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;
Client client = new Client();
Map<String, Object> brightnessProp = new HashMap<>();
brightnessProp.put("type", "integer");
brightnessProp.put("description", "Light level from 0 to 100");
Map<String, Object> colorTempProp = new HashMap<>();
colorTempProp.put("type", "string");
colorTempProp.put("enum", Arrays.asList("daylight", "cool", "warm"));
colorTempProp.put("description", "Color temperature");
Map<String, Object> properties = new HashMap<>();
properties.put("brightness", brightnessProp);
properties.put("color_temp", colorTempProp);
Map<String, Object> parameters = new HashMap<>();
parameters.put("type", "object");
parameters.put("properties", properties);
parameters.put("required", Arrays.asList("brightness", "color_temp"));
Function setLightValuesDeclaration =
Function.builder()
.name("set_light_values")
.description("Sets the brightness and color temperature of a light.")
.parameters(parameters)
.build();
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(InteractionsInput.of("Turn the lights down to a romantic level"))
.tools(Arrays.asList(setLightValuesDeclaration))
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
FunctionCallStep fcStep = null;
if (interaction.steps().isPresent()) {
for (Step step : interaction.steps().get()) {
if (step instanceof FunctionCallStep) {
fcStep = (FunctionCallStep) step;
break;
}
}
}
if (fcStep != null) {
String resultJson = "{\"brightness\": 25, \"colorTemperature\": \"warm\"}";
FunctionResultStep resultStep =
FunctionResultStep.builder()
.name(fcStep.name().orElse(""))
.callId(fcStep.id().orElse(""))
.result(
FunctionResultStepResultUnion.of(
Arrays.<FunctionResultSubcontent>asList(
TextContent.builder().text(resultJson).build())))
.build();
CreateModelInteraction finalParams =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.previousInteractionId(interaction.id().orElse(""))
.tools(Arrays.asList(setLightValuesDeclaration))
.input(InteractionsInput.ofStep(Arrays.<Step>asList(resultStep)))
.build();
Interaction finalInteraction =
client
.interactions
.create(CreateInteractionRequestBody.of(finalParams))
.interaction()
.get();
System.out.println(finalInteraction.outputText().orElse(""));
}
Go
functionResponsePart := &genai.Part{
FunctionResponse: &genai.FunctionResponse{
ID: toolCall.ID,
Name: toolCall.Name,
Response: result,
},
}
contents = append(contents, response.Candidates[0].Content)
contents = append(contents, &genai.Content{
Role: genai.RoleUser,
Parts: []*genai.Part{functionResponsePart},
})
finalResponse, err := client.Models.GenerateContent(ctx, "gemini-3.8-flash", contents, config)
if err != nil {
log.Fatal(err)
}
fmt.Println(finalResponse.Text())
스테이트리스 함수 호출
클라이언트 측에서 대화 기록을 관리하고 store=false를 설정하여 상태 비저장 모드에서 함수 호출을 사용할 수도 있습니다.
스테이트리스(Stateless) 모드에서는 각 후속 요청의 input 필드에 대화의 전체 기록을 전달해야 합니다. 이 기록에는 다음이 포함되어야 합니다.
1. 초기 user_input 단계입니다.
2. 턴 1에서 반환된 모든 모델 생성 단계 (thought 및 function_call 단계 포함)가 수신된 그대로입니다.
3. 실행된 함수의 출력이 포함된 function_result 단계
Python
from google import genai
import json
client = genai.Client()
history = [
{
"type": "user_input",
"content": [{"type": "text", "text": "Turn the lights down to a romantic level"}]
}
]
interaction = client.interactions.create(
model="gemini-3.8-flash",
store=False,
input=history,
tools=[set_light_values_declaration],
)
for step in interaction.steps:
history.append(step.model_dump())
fc_step = next(s for s in interaction.steps if s.type == "function_call")
if fc_step.name == "set_light_values":
result = set_light_values(**fc_step.arguments)
history.append({
"type": "function_result",
"name": fc_step.name,
"call_id": fc_step.id,
"result": [{"type": "text", "text": json.dumps(result)}],
})
final_interaction = client.interactions.create(
model="gemini-3.8-flash",
store=False,
input=history,
tools=[set_light_values_declaration],
)
print(final_interaction.output_text)
자바스크립트
import { GoogleGenAI } from "@google/genai";
const client = new GoogleGenAI({});
async function main() {
const history = [
{
type: "user_input",
content: [{ type: "text", text: "Turn the lights down to a romantic level" }]
}
];
const interaction = await client.interactions.create({
model: "gemini-3.8-flash",
store: false,
input: history,
tools: [setLightValuesTool],
});
history.push(...interaction.steps);
const fcStep = interaction.steps.find(s => s.type === 'function_call');
let result;
if (fcStep.name === 'set_light_values') {
result = setLightValues(fcStep.arguments.brightness, fcStep.arguments.color_temp);
}
history.push({
type: 'function_result',
name: fcStep.name,
call_id: fcStep.id,
result: [{ type: 'text', text: JSON.stringify(result) }]
});
const finalInteraction = await client.interactions.create({
model: 'gemini-3.8-flash',
store: false,
input: history,
tools: [setLightValuesTool],
});
console.log(finalInteraction.output_text);
}
await main();
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Function;
import com.google.genai.gaos.models.interactions.FunctionCallStep;
import com.google.genai.gaos.models.interactions.FunctionResultStep;
import com.google.genai.gaos.models.interactions.FunctionResultStepResultUnion;
import com.google.genai.gaos.models.interactions.FunctionResultSubcontent;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.interactions.TextContent;
import com.google.genai.gaos.models.interactions.UserInputStep;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
Client client = new Client();
Map<String, Object> brightnessProp = new HashMap<>();
brightnessProp.put("type", "integer");
brightnessProp.put("description", "Light level from 0 to 100");
Map<String, Object> colorTempProp = new HashMap<>();
colorTempProp.put("type", "string");
colorTempProp.put("enum", Arrays.asList("daylight", "cool", "warm"));
colorTempProp.put("description", "Color temperature");
Map<String, Object> properties = new HashMap<>();
properties.put("brightness", brightnessProp);
properties.put("color_temp", colorTempProp);
Map<String, Object> parameters = new HashMap<>();
parameters.put("type", "object");
parameters.put("properties", properties);
parameters.put("required", Arrays.asList("brightness", "color_temp"));
Function setLightValuesDeclaration =
Function.builder()
.name("set_light_values")
.description("Sets the brightness and color temperature of a light.")
.parameters(parameters)
.build();
List<Step> history = new ArrayList<>();
history.add(
UserInputStep.builder()
.content(
Arrays.asList(
TextContent.builder()
.text("Turn the lights down to a romantic level")
.build()))
.build());
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.store(false)
.input(InteractionsInput.ofStep(history))
.tools(Arrays.asList(setLightValuesDeclaration))
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
FunctionCallStep fcStep = null;
if (interaction.steps().isPresent()) {
history.addAll(interaction.steps().get());
for (Step step : interaction.steps().get()) {
if (step instanceof FunctionCallStep) {
fcStep = (FunctionCallStep) step;
break;
}
}
}
if (fcStep != null) {
String resultJson = "{\"brightness\": 25, \"colorTemperature\": \"warm\"}";
history.add(
FunctionResultStep.builder()
.name(fcStep.name().orElse(""))
.callId(fcStep.id().orElse(""))
.result(
FunctionResultStepResultUnion.of(
Arrays.<FunctionResultSubcontent>asList(
TextContent.builder().text(resultJson).build())))
.build());
CreateModelInteraction finalParams =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.store(false)
.input(InteractionsInput.ofStep(history))
.tools(Arrays.asList(setLightValuesDeclaration))
.build();
Interaction finalInteraction =
client
.interactions
.create(CreateInteractionRequestBody.of(finalParams))
.interaction()
.get();
System.out.println(finalInteraction.outputText().orElse(""));
}
Go
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
config := &genai.GenerateContentConfig{
Tools: []*genai.Tool{
{FunctionDeclarations: []*genai.FunctionDeclaration{setLightValuesDeclaration}},
},
}
history := []*genai.Content{
genai.NewContentFromText("Turn the lights down to a romantic level", genai.RoleUser),
}
response, err := client.Models.GenerateContent(ctx, "gemini-3.8-flash", history, config)
if err != nil {
log.Fatal(err)
}
toolCall := response.FunctionCalls()[0]
brightness := int(toolCall.Args["brightness"].(float64))
colorTemp := toolCall.Args["color_temp"].(string)
result := setLightValues(brightness, colorTemp)
history = append(history, response.Candidates[0].Content)
history = append(history, &genai.Content{
Role: genai.RoleUser,
Parts: []*genai.Part{
{
FunctionResponse: &genai.FunctionResponse{
ID: toolCall.ID,
Name: toolCall.Name,
Response: result,
},
},
},
})
finalResponse, err := client.Models.GenerateContent(ctx, "gemini-3.8-flash", history, config)
if err != nil {
log.Fatal(err)
}
fmt.Println(finalResponse.Text())
REST
# Turn 1: Send request with tools and store: false
RESPONSE1=$(curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "gemini-3.8-flash",
"store": false,
"input": [
{
"type": "user_input",
"content": "Turn the lights down to a romantic level"
}
],
"tools": [{
"type": "function",
"name": "set_light_values",
"description": "Sets the brightness and color temperature of a light.",
"parameters": {
"type": "object",
"properties": {
"brightness": {"type": "integer", "description": "Light level from 0 to 100"},
"color_temp": {"type": "string", "enum": ["daylight", "cool", "warm"]}
},
"required": ["brightness", "color_temp"]
}
}]
}')
# Extract model steps (thought, function_call)
MODEL_STEPS=$(echo "$RESPONSE1" | jq '.steps')
# Extract function call details to execute
FC_NAME=$(echo "$RESPONSE1" | jq -r '.steps[] | select(.type=="function_call") | .name')
FC_ID=$(echo "$RESPONSE1" | jq -r '.steps[] | select(.type=="function_call") | .id')
# Assume local execution returns: {"brightness": 25, "colorTemperature": "warm"}
RESULT="{\"brightness\": 25, \"colorTemperature\": \"warm\"}"
# Reconstruct history for Turn 2
HISTORY=$(jq -n \
--argjson first_input '[{"type": "user_input", "content": "Turn the lights down to a romantic level"}]' \
--argjson model_steps "$MODEL_STEPS" \
--arg fc_name "$FC_NAME" \
--arg fc_id "$FC_ID" \
--arg result "$RESULT" \
'$first_input + $model_steps + [{"type": "function_result", "name": $fc_name, "call_id": $fc_id, "result": [{"type": "text", "text": $result}]}]')
# Turn 2: Send the full history
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d "{
\"model\": \"gemini-3.8-flash\",
\"store\": false,
\"input\": $HISTORY,
\"tools\": [{
\"type\": \"function\",
\"name\": \"set_light_values\",
\"description\": \"Sets the brightness and color temperature of a light.\",
\"parameters\": {
\"type\": \"object\",
\"properties\": {
\"brightness\": {\"type\": \"integer\"},
\"color_temp\": {\"type\": \"string\"}
},
\"required\": [\"brightness\", \"color_temp\"]
}
}]
}"
함수 선언
함수 선언은 도구로 전달되며 다음을 포함합니다.
type(문자열): 맞춤 함수의 경우"function"여야 합니다.name(문자열): 고유한 함수 이름 (밑줄 또는 카멜 표기법 사용)description(문자열): 함수의 목적에 관한 명확한 설명입니다.parameters(객체): 함수에서 예상하는 입력 매개변수입니다.type(문자열):object과 같은 전체 데이터 유형입니다.properties(객체): 유형과 설명이 있는 개별 매개변수입니다.required(배열): 필수 매개변수 이름입니다.
사고 모델을 사용한 함수 호출
Gemini 3 시리즈 모델은 함수 호출을 개선하는 내부 '사고' 프로세스를 사용합니다. SDK는 생각 서명을 자동으로 처리합니다.
병렬 함수 호출
독립적인 경우 한 번에 여러 함수 호출:
Python
power_disco_ball = {"type": "function", "name": "power_disco_ball", "description": "Powers the disco ball.",
"parameters": {"type": "object", "properties": {"power": {"type": "boolean"}}, "required": ["power"]}}
start_music = {"type": "function", "name": "start_music", "description": "Play music.",
"parameters": {"type": "object", "properties": {"energetic": {"type": "boolean"}, "loud": {"type": "boolean"}}, "required": ["energetic", "loud"]}}
dim_lights = {"type": "function", "name": "dim_lights", "description": "Dim the lights.",
"parameters": {"type": "object", "properties": {"brightness": {"type": "number"}}, "required": ["brightness"]}}
client = genai.Client()
interaction = client.interactions.create(
model="gemini-3.8-flash",
input="Turn this place into a party!",
tools=[power_disco_ball, start_music, dim_lights],
generation_config={"tool_choice": "any"},
)
for step in interaction.steps:
if step.type == "function_call":
args = ", ".join(f"{key}={val}" for key, val in step.arguments.items())
print(f"{step.name}({args})")
자바스크립트
const powerDiscoBall = { type: 'function', name: 'power_disco_ball', description: 'Powers the disco ball.',
parameters: { type: 'object', properties: { power: { type: 'boolean' } }, required: ['power'] } };
const startMusic = { type: 'function', name: 'start_music', description: 'Play music.',
parameters: { type: 'object', properties: { energetic: { type: 'boolean' }, loud: { type: 'boolean' } }, required: ['energetic', 'loud'] } };
const dimLights = { type: 'function', name: 'dim_lights', description: 'Dim the lights.',
parameters: { type: 'object', properties: { brightness: { type: 'number' } }, required: ['brightness'] } };
const interaction = await client.interactions.create({
model: 'gemini-3.8-flash',
input: 'Turn this place into a party!',
tools: [powerDiscoBall, startMusic, dimLights],
generation_config: { tool_choice: 'any' },
});
for (const step of interaction.steps) {
if (step.type === 'function_call') {
console.log(`${step.name}(${JSON.stringify(step.arguments)})`);
}
}
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Function;
import com.google.genai.gaos.models.interactions.FunctionCallStep;
import com.google.genai.gaos.models.interactions.GenerationConfig;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.interactions.ToolChoice;
import com.google.genai.gaos.models.interactions.ToolChoiceType;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.Arrays;
import java.util.Collections;
import java.util.HashMap;
import java.util.Map;
Client client = new Client();
Map<String, Object> discoParams = new HashMap<>();
discoParams.put("type", "object");
discoParams.put(
"properties", Collections.singletonMap("power", Collections.singletonMap("type", "boolean")));
discoParams.put("required", Arrays.asList("power"));
Function powerDiscoBall =
Function.builder()
.name("power_disco_ball")
.description("Powers the disco ball.")
.parameters(discoParams)
.build();
Map<String, Object> musicProps = new HashMap<>();
musicProps.put("energetic", Collections.singletonMap("type", "boolean"));
musicProps.put("loud", Collections.singletonMap("type", "boolean"));
Map<String, Object> musicParams = new HashMap<>();
musicParams.put("type", "object");
musicParams.put("properties", musicProps);
musicParams.put("required", Arrays.asList("energetic", "loud"));
Function startMusic =
Function.builder()
.name("start_music")
.description("Play music.")
.parameters(musicParams)
.build();
Map<String, Object> lightsParams = new HashMap<>();
lightsParams.put("type", "object");
lightsParams.put(
"properties",
Collections.singletonMap("brightness", Collections.singletonMap("type", "number")));
lightsParams.put("required", Arrays.asList("brightness"));
Function dimLights =
Function.builder()
.name("dim_lights")
.description("Dim the lights.")
.parameters(lightsParams)
.build();
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(InteractionsInput.of("Turn this place into a party!"))
.tools(Arrays.asList(powerDiscoBall, startMusic, dimLights))
.generationConfig(
GenerationConfig.builder().toolChoice(ToolChoice.of(ToolChoiceType.ANY)).build())
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
if (interaction.steps().isPresent()) {
for (Step step : interaction.steps().get()) {
if (step instanceof FunctionCallStep) {
FunctionCallStep fc = (FunctionCallStep) step;
System.out.println(fc.name().orElse("") + "(" + fc.arguments().orElse(null) + ")");
}
}
}
Go
package main
import (
"context"
"fmt"
"log"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
powerDiscoBall := &genai.FunctionDeclaration{
Name: "power_disco_ball",
Description: "Powers the disco ball.",
Parameters: &genai.Schema{
Type: genai.TypeObject,
Properties: map[string]*genai.Schema{
"power": {Type: genai.TypeBoolean},
},
Required: []string{"power"},
},
}
startMusic := &genai.FunctionDeclaration{
Name: "start_music",
Description: "Play music.",
Parameters: &genai.Schema{
Type: genai.TypeObject,
Properties: map[string]*genai.Schema{
"energetic": {Type: genai.TypeBoolean},
"loud": {Type: genai.TypeBoolean},
},
Required: []string{"energetic", "loud"},
},
}
dimLights := &genai.FunctionDeclaration{
Name: "dim_lights",
Description: "Dim the lights.",
Parameters: &genai.Schema{
Type: genai.TypeObject,
Properties: map[string]*genai.Schema{
"brightness": {Type: genai.TypeNumber},
},
Required: []string{"brightness"},
},
}
config := &genai.GenerateContentConfig{
Tools: []*genai.Tool{
{FunctionDeclarations: []*genai.FunctionDeclaration{powerDiscoBall, startMusic, dimLights}},
},
ToolConfig: &genai.ToolConfig{
FunctionCallingConfig: &genai.FunctionCallingConfig{
Mode: genai.FunctionCallingConfigModeAny,
},
},
}
response, err := client.Models.GenerateContent(
ctx,
"gemini-3.8-flash",
genai.Text("Turn this place into a party!"),
config,
)
if err != nil {
log.Fatal(err)
}
for _, fn := range response.FunctionCalls() {
fmt.Printf("%s(%v)\n", fn.Name, fn.Args)
}
}
REST
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "gemini-3.8-flash",
"input": "Turn this place into a party!",
"tools": [
{
"type": "function",
"name": "power_disco_ball",
"description": "Powers the disco ball.",
"parameters": {
"type": "object",
"properties": {
"power": {"type": "boolean"}
},
"required": ["power"]
}
},
{
"type": "function",
"name": "start_music",
"description": "Play music.",
"parameters": {
"type": "object",
"properties": {
"energetic": {"type": "boolean"},
"loud": {"type": "boolean"}
},
"required": ["energetic", "loud"]
}
},
{
"type": "function",
"name": "dim_lights",
"description": "Dim the lights.",
"parameters": {
"type": "object",
"properties": {
"brightness": {"type": "number"}
},
"required": ["brightness"]
}
}
]
}'
구성 함수 호출
복잡한 요청을 위해 여러 함수 호출을 함께 연결합니다 (예: 먼저 위치를 가져온 다음 해당 위치의 날씨를 가져옴).
Python
get_weather_forecast_declaration = {
"type": "function",
"name": "get_weather_forecast",
"description": "Gets the current weather temperature for a given location.",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "The location"},
},
"required": ["location"],
},
}
set_thermostat_temperature_declaration = {
"type": "function",
"name": "set_thermostat_temperature",
"description": "Sets the thermostat to a desired temperature.",
"parameters": {
"type": "object",
"properties": {
"temperature": {
"type": "integer",
"description": "The temperature in Celsius",
},
},
"required": ["temperature"],
},
}
client = genai.Client()
interaction = client.interactions.create(
model="gemini-3.8-flash",
input="If it's warmer than 20°C in London, set the thermostat to 20°C, otherwise 18°C.",
tools=[
get_weather_forecast_declaration,
set_thermostat_temperature_declaration,
],
)
for step in interaction.steps:
if step.type == "function_call":
print(f"Function to call: {step.name}")
print(f"Arguments: {step.arguments}")
elif hasattr(step, "content") and step.content:
for part in step.content:
if hasattr(part, "text"):
print(part.text)
자바스크립트
import { GoogleGenAI } from '@google/genai';
const client = new GoogleGenAI({});
const getWeatherForecastTool = {
type: 'function',
name: 'get_weather_forecast',
description: 'Gets the current weather temperature for a given location.',
parameters: {
type: 'object',
properties: {
location: { type: 'string', description: 'The location' },
},
required: ['location'],
},
};
const setThermostatTemperatureTool = {
type: 'function',
name: 'set_thermostat_temperature',
description: 'Sets the thermostat to a desired temperature.',
parameters: {
type: 'object',
properties: {
temperature: {
type: 'integer',
description: 'The temperature in Celsius',
},
},
required: ['temperature'],
},
};
const interaction = await client.interactions.create({
model: 'gemini-3.8-flash',
input: "If it's warmer than 20°C in London, set the thermostat to 20°C, otherwise 18°C.",
tools: [
getWeatherForecastTool,
setThermostatTemperatureTool,
],
});
for (const step of interaction.steps) {
if (step.type === 'function_call') {
console.log(`Function to call: ${step.name}`);
console.log(`Arguments: ${JSON.stringify(step.arguments)}`);
} else if (step.content) {
for (const part of step.content) {
if (part.text) {
console.log(part.text);
}
}
}
}
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.Content;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Function;
import com.google.genai.gaos.models.interactions.FunctionCallStep;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.ModelOutputStep;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.interactions.TextContent;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;
Client client = new Client();
Map<String, Object> locationProp = new HashMap<>();
locationProp.put("type", "string");
locationProp.put("description", "The location");
Map<String, Object> weatherProps = new HashMap<>();
weatherProps.put("location", locationProp);
Map<String, Object> weatherParams = new HashMap<>();
weatherParams.put("type", "object");
weatherParams.put("properties", weatherProps);
weatherParams.put("required", Arrays.asList("location"));
Function getWeatherForecastDeclaration =
Function.builder()
.name("get_weather_forecast")
.description("Gets the current weather temperature for a given location.")
.parameters(weatherParams)
.build();
Map<String, Object> tempProp = new HashMap<>();
tempProp.put("type", "integer");
tempProp.put("description", "The temperature in Celsius");
Map<String, Object> thermostatProps = new HashMap<>();
thermostatProps.put("temperature", tempProp);
Map<String, Object> thermostatParams = new HashMap<>();
thermostatParams.put("type", "object");
thermostatParams.put("properties", thermostatProps);
thermostatParams.put("required", Arrays.asList("temperature"));
Function setThermostatTemperatureDeclaration =
Function.builder()
.name("set_thermostat_temperature")
.description("Sets the thermostat to a desired temperature.")
.parameters(thermostatParams)
.build();
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(
InteractionsInput.of(
"If it's warmer than 20°C in London, set the thermostat to 20°C, otherwise 18°C."))
.tools(Arrays.asList(getWeatherForecastDeclaration, setThermostatTemperatureDeclaration))
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
if (interaction.steps().isPresent()) {
for (Step step : interaction.steps().get()) {
if (step instanceof FunctionCallStep) {
FunctionCallStep fc = (FunctionCallStep) step;
System.out.println("Function to call: " + fc.name().orElse(""));
System.out.println("Arguments: " + fc.arguments().orElse(null));
} else if (step instanceof ModelOutputStep) {
ModelOutputStep outputStep = (ModelOutputStep) step;
if (outputStep.content().isPresent()) {
for (Content part : outputStep.content().get()) {
if (part instanceof TextContent) {
System.out.println(((TextContent) part).text().orElse(""));
}
}
}
}
}
}
Go
package main
import (
"context"
"fmt"
"log"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
getWeatherForecastDecl := &genai.FunctionDeclaration{
Name: "get_weather_forecast",
Description: "Gets the current weather temperature for a given location.",
Parameters: &genai.Schema{
Type: genai.TypeObject,
Properties: map[string]*genai.Schema{
"location": {Type: genai.TypeString, Description: "The location"},
},
Required: []string{"location"},
},
}
setThermostatTemperatureDecl := &genai.FunctionDeclaration{
Name: "set_thermostat_temperature",
Description: "Sets the thermostat to a desired temperature.",
Parameters: &genai.Schema{
Type: genai.TypeObject,
Properties: map[string]*genai.Schema{
"temperature": {Type: genai.TypeInteger, Description: "The temperature in Celsius"},
},
Required: []string{"temperature"},
},
}
config := &genai.GenerateContentConfig{
Tools: []*genai.Tool{
{FunctionDeclarations: []*genai.FunctionDeclaration{getWeatherForecastDecl, setThermostatTemperatureDecl}},
},
}
response, err := client.Models.GenerateContent(
ctx,
"gemini-3.8-flash",
genai.Text("If it's warmer than 20°C in London, set the thermostat to 20°C, otherwise 18°C."),
config,
)
if err != nil {
log.Fatal(err)
}
for _, fn := range response.FunctionCalls() {
fmt.Printf("Function to call: %s\n", fn.Name)
fmt.Printf("Arguments: %v\n", fn.Args)
}
}
REST
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "gemini-3.8-flash",
"input": "If it'\''s warmer than 20°C in London, set the thermostat to 20°C, otherwise 18°C.",
"tools": [
{
"type": "function",
"name": "get_weather_forecast",
"description": "Gets the current weather temperature for a given location.",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string"}
},
"required": ["location"]
}
},
{
"type": "function",
"name": "set_thermostat_temperature",
"description": "Sets the thermostat to a desired temperature.",
"parameters": {
"type": "object",
"properties": {
"temperature": {"type": "integer"}
},
"required": ["temperature"]
}
}
]
}'
함수 호출 모드
generation_config에서 tool_choice를 사용하여 모델이 도구를 사용하는 방식 제어:
auto(기본값): 모델이 함수를 호출할지 아니면 직접 응답할지 결정합니다.any: 모델이 항상 함수 호출을 예측하도록 제한됩니다.none: 모델이 함수 호출을 실행하는 것이 금지됩니다.validated: 모델이 함수 스키마 준수를 보장합니다.
Python
generation_config = {
"tool_choice": {
"allowed_tools": {
"mode": "any",
"tools": ["get_current_temperature"]
}
}
}
자바스크립트
const generation_config = {
tool_choice: {
allowed_tools: {
mode: 'any',
tools: ['get_current_temperature']
}
}
};
자바
import com.google.genai.gaos.models.interactions.AllowedTools;
import com.google.genai.gaos.models.interactions.GenerationConfig;
import com.google.genai.gaos.models.interactions.ToolChoice;
import com.google.genai.gaos.models.interactions.ToolChoiceConfig;
import com.google.genai.gaos.models.interactions.ToolChoiceType;
import java.util.Arrays;
GenerationConfig generationConfig =
GenerationConfig.builder()
.toolChoice(
ToolChoice.of(
ToolChoiceConfig.builder()
.allowedTools(
AllowedTools.builder()
.mode(ToolChoiceType.ANY)
.tools(Arrays.asList("get_current_temperature"))
.build())
.build()))
.build();
Go
// Configure function calling mode
toolConfig := &genai.ToolConfig{
FunctionCallingConfig: &genai.FunctionCallingConfig{
Mode: genai.FunctionCallingConfigModeAny,
AllowedFunctionNames: []string{"get_current_temperature"},
},
}
// Create the generation config
config := &genai.GenerateContentConfig{
Tools: tools, // not defined here.
ToolConfig: toolConfig,
}
REST
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "gemini-3.8-flash",
"input": "What is the temperature in Boston?",
"tools": [{
"type": "function",
"name": "get_current_temperature",
"description": "Gets the current temperature for a given location.",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string"}
},
"required": ["location"]
}
}],
"generation_config": {
"tool_choice": {
"allowed_tools": {
"mode": "any",
"tools": ["get_current_temperature"]
}
}
}
}'
멀티 도구 사용
동일한 요청에서 기본 제공 도구와 함수 호출을 결합하여 여러 도구를 사용 설정할 수 있습니다. Gemini 3 모델은 상호작용에서 기본 제공 도구와 함수 호출을 즉시 결합할 수 있습니다. previous_interaction_id를 전달하면 기본 제공 도구 컨텍스트가 자동으로 순환됩니다.
Python
from google import genai
import json
client = genai.Client()
get_weather = {
"type": "function",
"name": "get_weather",
"description": "Gets the weather for a requested city.",
"parameters": {
"type": "object",
"properties": {
"city": {
"type": "string",
"description": "The city and state, e.g. Utqiaġvik, Alaska",
},
},
"required": ["city"],
},
}
tools = [
{"type": "google_search"},
get_weather
]
interaction = client.interactions.create(
model="gemini-3.8-flash",
input="What is the northernmost city in the United States? What's the weather like there today?",
tools=tools
)
for step in interaction.steps:
if step.type == "function_call":
print(f"Function call: {step.name} (ID: {step.id})")
result = {"response": "Very cold. 22 degrees Fahrenheit."}
interaction_2 = client.interactions.create(
model="gemini-3.8-flash",
previous_interaction_id=interaction.id,
tools=tools,
input=[{
"type": "function_result",
"name": step.name,
"call_id": step.id,
"result": [{"type": "text", "text": json.dumps(result)}]
}]
)
print(interaction_2.output_text)
자바스크립트
import { GoogleGenAI } from '@google/genai';
const client = new GoogleGenAI({});
const weatherTool = {
type: 'function',
name: 'get_weather',
description: 'Gets the weather for a given location.',
parameters: {
type: 'object',
properties: {
location: {
type: 'string',
description: 'The city and state, e.g. San Francisco, CA',
},
},
required: ['location'],
},
};
const tools = [
{ type: 'google_search' }, // Built-in tool
weatherTool,
];
const interaction = await client.interactions.create({
model: 'gemini-3.8-flash',
input: "What is the northernmost city in the United States? What's the weather like there today?",
tools: tools,
});
for (const step of interaction.steps) {
if (step.type === 'function_call') {
console.log(`Function call: ${step.name} (ID: ${step.id})`);
const result = { response: 'Very cold. 22 degrees Fahrenheit.' };
const interaction_2 = await client.interactions.create({
model: 'gemini-3.8-flash',
previous_interaction_id: interaction.id,
tools: tools,
input: [
{
type: 'function_result',
name: step.name,
call_id: step.id,
result: [{ type: 'text', text: JSON.stringify(result) }],
},
],
});
console.log(interaction_2.output_text);
}
}
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Function;
import com.google.genai.gaos.models.interactions.FunctionCallStep;
import com.google.genai.gaos.models.interactions.FunctionResultStep;
import com.google.genai.gaos.models.interactions.FunctionResultStepResultUnion;
import com.google.genai.gaos.models.interactions.FunctionResultSubcontent;
import com.google.genai.gaos.models.interactions.GoogleSearch;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.interactions.TextContent;
import com.google.genai.gaos.models.interactions.Tool;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
Client client = new Client();
Map<String, Object> cityProp = new HashMap<>();
cityProp.put("type", "string");
cityProp.put("description", "The city and state, e.g. Utqiaġvik, Alaska");
Map<String, Object> properties = new HashMap<>();
properties.put("city", cityProp);
Map<String, Object> parameters = new HashMap<>();
parameters.put("type", "object");
parameters.put("properties", properties);
parameters.put("required", Arrays.asList("city"));
Function getWeather =
Function.builder()
.name("get_weather")
.description("Gets the weather for a requested city.")
.parameters(parameters)
.build();
List<Tool> tools = Arrays.asList(GoogleSearch.builder().build(), getWeather);
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(
InteractionsInput.of(
"What is the northernmost city in the United States? What's the weather like there today?"))
.tools(tools)
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
if (interaction.steps().isPresent()) {
for (Step step : interaction.steps().get()) {
if (step instanceof FunctionCallStep) {
FunctionCallStep fcStep = (FunctionCallStep) step;
System.out.printf(
"Function call: %s (ID: %s)%n", fcStep.name().orElse(""), fcStep.id().orElse(""));
String resultJson = "{\"response\": \"Very cold. 22 degrees Fahrenheit.\"}";
FunctionResultStep resultStep =
FunctionResultStep.builder()
.name(fcStep.name().orElse(""))
.callId(fcStep.id().orElse(""))
.result(
FunctionResultStepResultUnion.of(
Arrays.<FunctionResultSubcontent>asList(
TextContent.builder().text(resultJson).build())))
.build();
CreateModelInteraction params2 =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.previousInteractionId(interaction.id().orElse(""))
.tools(tools)
.input(InteractionsInput.ofStep(Arrays.<Step>asList(resultStep)))
.build();
Interaction interaction2 =
client
.interactions
.create(CreateInteractionRequestBody.of(params2))
.interaction()
.get();
System.out.println(interaction2.outputText().orElse(""));
}
}
}
Go
package main
import (
"context"
"fmt"
"log"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
getWeather := &genai.FunctionDeclaration{
Name: "get_weather",
Description: "Gets the weather for a given location.",
Parameters: &genai.Schema{
Type: genai.TypeObject,
Properties: map[string]*genai.Schema{
"location": {
Type: genai.TypeString,
Description: "The city and state, e.g. San Francisco, CA",
},
},
Required: []string{"location"},
},
}
tools := []*genai.Tool{
{GoogleSearch: &genai.GoogleSearch{}},
{FunctionDeclarations: []*genai.FunctionDeclaration{getWeather}},
}
config := &genai.GenerateContentConfig{
Tools: tools,
}
prompt := "What is the northernmost city in the United States? What's the weather like there today?"
response1, err := client.Models.GenerateContent(ctx, "gemini-3.8-flash", genai.Text(prompt), config)
if err != nil {
log.Fatal(err)
}
toolCall := response1.FunctionCalls()[0]
fmt.Printf("Function call: %s (ID: %s)\n", toolCall.Name, toolCall.ID)
history := []*genai.Content{
genai.NewContentFromText(prompt, genai.RoleUser),
response1.Candidates[0].Content,
{
Role: genai.RoleUser,
Parts: []*genai.Part{
{
FunctionResponse: &genai.FunctionResponse{
ID: toolCall.ID,
Name: toolCall.Name,
Response: map[string]any{"response": "Very cold. 22 degrees Fahrenheit."},
},
},
},
},
}
response2, err := client.Models.GenerateContent(ctx, "gemini-3.8-flash", history, config)
if err != nil {
log.Fatal(err)
}
fmt.Println(response2.Text())
}
REST
# Turn 1: Send request with built-in google_search tool and custom weather tool
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "gemini-3.8-flash",
"input": "What is the northernmost city in the United States? What'\''s the weather like there today?",
"tools": [
{"type": "google_search"},
{
"type": "function",
"name": "get_weather",
"description": "Gets the weather for a given location.",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "The city and state, e.g. San Francisco, CA"}
},
"required": ["location"]
}
}
]
}'
# Turn 2: Provide function result and pass previous_interaction_id
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "gemini-3.8-flash",
"previous_interaction_id": "INTERACTION_ID",
"tools": [
{"type": "google_search"},
{
"type": "function",
"name": "get_weather",
"description": "Gets the weather for a given location.",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "The city and state, e.g. San Francisco, CA"}
},
"required": ["location"]
}
}
],
"input": [
{
"type": "function_result",
"name": "get_weather",
"call_id": "call_123",
"result": [{"type": "text", "text": "{\"response\": \"Very cold. 22 degrees Fahrenheit.\"}"}]
}
]
}'
멀티모달 함수 응답
Gemini 3 시리즈 모델의 경우 모델에 전송하는 함수 응답 부분에 멀티모달 콘텐츠를 포함할 수 있습니다. 모델은 다음 차례에 이 멀티모달 콘텐츠를 처리하여 더 많은 정보를 바탕으로 응답을 생성할 수 있습니다.
함수 응답에 멀티모달 데이터를 포함하려면 function_result 단계의 result 필드에 하나 이상의 콘텐츠 블록으로 포함하세요. 각 콘텐츠 블록은 type (예: "text", "image")를 지정해야 합니다.
다음 예시는 상호작용에서 이미지 데이터가 포함된 함수 응답을 모델에 다시 전송하는 방법을 보여줍니다.
Python
import base64
from google import genai
import requests
client = genai.Client()
tool_call = next(s for s in interaction.steps if s.type == "function_call")
image_path = "https://goo.gle/instrument-img"
image_bytes = requests.get(image_path).content
base64_image_data = base64.b64encode(image_bytes).decode("utf-8")
final_interaction = client.interactions.create(
model="gemini-3.8-flash",
previous_interaction_id=interaction.id,
input=[
{
"type": "function_result",
"name": tool_call.name,
"call_id": tool_call.id,
"result": [
{"type": "text", "text": "instrument.jpg"},
{
"type": "image",
"mime_type": "image/jpeg",
"data": base64_image_data,
},
],
}
],
)
print(final_interaction.output_text)
자바스크립트
import { GoogleGenAI } from "@google/genai";
const client = new GoogleGenAI({});
const toolCall = interaction.steps.find(s => s.type === 'function_call');
const base64ImageData = "BASE64_IMAGE_DATA";
const finalInteraction = await client.interactions.create({
model: 'gemini-3.8-flash',
previous_interaction_id: interaction.id,
input: [{
type: 'function_result',
name: toolCall.name,
call_id: toolCall.id,
result: [
{ type: 'text', text: 'instrument.jpg' },
{
type: 'image',
mime_type: 'image/jpeg',
data: base64ImageData,
}
]
}]
});
console.log(finalInteraction.output_text);
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Function;
import com.google.genai.gaos.models.interactions.FunctionCallStep;
import com.google.genai.gaos.models.interactions.FunctionResultStep;
import com.google.genai.gaos.models.interactions.FunctionResultStepResultUnion;
import com.google.genai.gaos.models.interactions.FunctionResultSubcontent;
import com.google.genai.gaos.models.interactions.ImageContent;
import com.google.genai.gaos.models.interactions.ImageContentMimeType;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.interactions.TextContent;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;
Client client = new Client();
Map<String, Object> parameters = new HashMap<>();
parameters.put("type", "object");
Function getInstrumentImage =
Function.builder()
.name("get_instrument_image")
.description("Gets an image of an instrument.")
.parameters(parameters)
.build();
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(InteractionsInput.of("Show me the instrument."))
.tools(Arrays.asList(getInstrumentImage))
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
FunctionCallStep toolCall = null;
if (interaction.steps().isPresent()) {
for (Step step : interaction.steps().get()) {
if (step instanceof FunctionCallStep) {
toolCall = (FunctionCallStep) step;
break;
}
}
}
if (toolCall != null) {
String base64ImageData = "BASE64_IMAGE_DATA";
FunctionResultStep resultStep =
FunctionResultStep.builder()
.name(toolCall.name().orElse(""))
.callId(toolCall.id().orElse(""))
.result(
FunctionResultStepResultUnion.of(
Arrays.<FunctionResultSubcontent>asList(
TextContent.builder().text("instrument.jpg").build(),
ImageContent.builder()
.mimeType(ImageContentMimeType.IMAGE_JPEG)
.data(base64ImageData)
.build())))
.build();
CreateModelInteraction finalParams =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.previousInteractionId(interaction.id().orElse(""))
.input(InteractionsInput.ofStep(Arrays.<Step>asList(resultStep)))
.build();
Interaction finalInteraction =
client
.interactions
.create(CreateInteractionRequestBody.of(finalParams))
.interaction()
.get();
System.out.println(finalInteraction.outputText().orElse(""));
}
Go
package main
import (
"context"
"fmt"
"io"
"log"
"net/http"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
// 1. Define the function tool
getImageDeclaration := &genai.FunctionDeclaration{
Name: "get_image",
Description: "Retrieves the image file reference for a specific order item.",
Parameters: &genai.Schema{
Type: genai.TypeObject,
Properties: map[string]*genai.Schema{
"item_name": {
Type: genai.TypeString,
Description: "The name or description of the item ordered (e.g., 'instrument').",
},
},
Required: []string{"item_name"},
},
}
tools := []*genai.Tool{
{FunctionDeclarations: []*genai.FunctionDeclaration{getImageDeclaration}},
}
// 2. Send a message that triggers the tool
prompt := "Show me the instrument I ordered last month."
response1, err := client.Models.GenerateContent(ctx, "gemini-3.8-flash", genai.Text(prompt), &genai.GenerateContentConfig{
Tools: tools,
})
if err != nil {
log.Fatal(err)
}
// 3. Handle the function call
functionCall := response1.FunctionCalls()[0]
requestedItem := functionCall.Args["item_name"]
fmt.Printf("Model wants to call: %s\n", functionCall.Name)
fmt.Printf("Calling external tool for: %v\n", requestedItem)
resp, err := http.Get("https://goo.gle/instrument-img")
if err != nil {
log.Fatal(err)
}
defer resp.Body.Close()
imageBytes, err := io.ReadAll(resp.Body)
if err != nil {
log.Fatal(err)
}
functionResponseData := map[string]any{
"image_ref": map[string]any{"$ref": "instrument.jpg"},
}
functionResponseMultimodalData := &genai.FunctionResponsePart{
InlineData: &genai.FunctionResponseBlob{
MIMEType: "image/jpeg",
DisplayName: "instrument.jpg",
Data: imageBytes,
},
}
// 4. Send the tool's result back
history := []*genai.Content{
genai.NewContentFromText(prompt, genai.RoleUser),
response1.Candidates[0].Content,
{
Role: genai.RoleUser,
Parts: []*genai.Part{
{
FunctionResponse: &genai.FunctionResponse{
ID: functionCall.ID,
Name: functionCall.Name,
Response: functionResponseData,
Parts: []*genai.FunctionResponsePart{functionResponseMultimodalData},
},
},
},
},
}
response2, err := client.Models.GenerateContent(ctx, "gemini-3.8-flash", history, &genai.GenerateContentConfig{
Tools: tools,
ThinkingConfig: &genai.ThinkingConfig{
IncludeThoughts: true,
},
})
if err != nil {
log.Fatal(err)
}
fmt.Printf("\nFinal model response: %s\n", response2.Text())
}
REST
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "gemini-3.8-flash",
"previous_interaction_id": "INTERACTION_ID",
"input": [
{
"type": "function_result",
"name": "get_image",
"call_id": "call_123",
"result": [
{"type": "text", "text": "instrument.jpg"},
{
"type": "image",
"mime_type": "image/jpeg",
"data": "BASE64_IMAGE_DATA"
}
]
}
]
}'
구조화된 출력을 사용한 함수 호출
Gemini 3 시리즈 모델의 경우 함수 호출을 구조화된 출력과 결합하여 일관된 형식의 응답을 얻으세요.
원격 MCP (모델 컨텍스트 프로토콜)
상호작용 API는 원격 MCP 서버에 연결하여 모델이 외부 도구 및 서비스에 액세스할 수 있도록 지원합니다. 도구 구성에서 서버 name 및 url을 제공합니다.
원격 MCP를 사용할 때는 다음 제약 조건에 유의하세요.
- 서버 유형: 원격 MCP는 스트리밍 가능 HTTP 서버에서만 작동합니다. SSE (서버 전송 이벤트) 서버는 지원되지 않습니다.
- 이름 지정: MCP 서버 이름에
-문자를 포함하면 안 됩니다. 대신snake_case서버 이름을 사용하세요.
| 필드 | 유형 | 필수 | 설명 |
|---|---|---|---|
type |
string |
예 | "mcp_server"이어야 합니다. |
name |
string |
아니요 | MCP 서버의 표시 이름입니다. |
url |
string |
아니요 | MCP 서버 엔드포인트의 전체 URL입니다. |
headers |
object |
아니요 | 서버에 대한 모든 요청과 함께 HTTP 헤더로 전송되는 키-값 쌍 (예: 인증 토큰)입니다. |
allowed_tools |
array |
아니요 | 에이전트가 호출할 수 있는 서버의 도구를 제한합니다. |
예
Python
from google import genai
client = genai.Client()
interaction = client.interactions.create(
model="gemini-3.8-flash",
input="Check the weather in San Francisco.",
tools=[
{
"type": "mcp_server",
"name": "weather",
"url": "https://gemini-api-demos.uc.r.appspot.com/mcp",
}
]
)
자바스크립트
import { GoogleGenAI } from '@google/genai';
const client = new GoogleGenAI({});
const interaction = await client.interactions.create({
model: 'gemini-3.8-flash',
input: 'Check the weather in San Francisco.',
tools: [
{
type: 'mcp_server',
name: 'weather',
url: 'https://gemini-api-demos.uc.r.appspot.com/mcp'
}
]
});
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Interaction;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.MCPServer;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import java.util.Arrays;
Client client = new Client();
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(InteractionsInput.of("Check the weather in San Francisco."))
.tools(
Arrays.asList(
MCPServer.builder()
.name("weather")
.url("https://gemini-api-demos.uc.r.appspot.com/mcp")
.build()))
.build();
Interaction interaction =
client.interactions.create(CreateInteractionRequestBody.of(params)).interaction().get();
REST
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-d '{
"model": "gemini-3.8-flash",
"input": "Check the weather in San Francisco.",
"tools": [
{
"type": "mcp_server",
"name": "weather",
"url": "https://gemini-api-demos.uc.r.appspot.com/mcp"
}
]
}'
스트림 도구 호출
스트리밍과 함께 도구를 사용하면 모델은 스트림에서 step.delta 이벤트 시퀀스로 함수 호출을 생성합니다. 도구 인수는 arguments를 사용하여 부분 인수로 스트리밍할 수 있습니다. 이러한 델타를 집계하여 실행하기 전에 전체 도구 호출을 재구성해야 합니다.
Python
import json
from google import genai
client = genai.Client()
weather_tool = {
"type": "function",
"name": "get_weather",
"description": "Gets the weather for a given location.",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "The city and state"}
},
"required": ["location"]
}
}
stream = client.interactions.create(
model="gemini-3.8-flash",
input="What is the weather in Paris?",
tools=[weather_tool],
stream=True
)
current_calls = {}
tool_calls = []
for event in stream:
if event.event_type == "step.start":
if event.step.type == "function_call":
current_calls[event.index] = {
"id": event.step.id,
"name": event.step.name,
"arguments": ""
}
if hasattr(event.step, "arguments") and event.step.arguments:
if isinstance(event.step.arguments, dict):
current_calls[event.index]["arguments"] = json.dumps(event.step.arguments)
else:
current_calls[event.index]["arguments"] = event.step.arguments
elif event.event_type == "step.delta":
if event.delta.type == "arguments":
if event.index in current_calls:
current_calls[event.index]["arguments"] += event.delta.partial_arguments
elif event.delta.type == "text":
print(event.delta.text, end="", flush=True)
elif event.event_type == "interaction.completed":
for index, call in current_calls.items():
args = call["arguments"]
if args:
args = json.loads(args)
else:
args = {}
tool_calls.append({
"type": "function_call",
"id": call["id"],
"name": call["name"],
"arguments": args
})
print(f"\nFinal tool calls ready to execute:")
print(json.dumps(tool_calls, indent=2))
자바스크립트
import { GoogleGenAI } from '@google/genai';
const client = new GoogleGenAI({});
const weatherTool = {
type: 'function',
name: 'get_weather',
description: 'Gets the weather for a given location.',
parameters: {
type: 'object',
properties: {
location: { type: 'string', description: 'The city and state' }
},
required: ['location']
}
};
const stream = await client.interactions.create({
model: 'gemini-3.8-flash',
input: 'What is the weather in Paris?',
tools: [weatherTool],
stream: true,
});
const currentCalls = new Map();
let toolCalls = [];
for await (const event of stream) {
const evType = event.event_type;
if (evType === 'step.start') {
if (event.step.type === 'function_call') {
currentCalls.set(event.index, {
id: event.step.id,
name: event.step.name,
arguments: ''
});
if (event.step.arguments) {
if (typeof event.step.arguments === 'object') {
currentCalls.get(event.index).arguments = JSON.stringify(event.step.arguments);
} else {
currentCalls.get(event.index).arguments = event.step.arguments;
}
}
}
} else if (evType === 'step.delta') {
if (event.delta.type === 'arguments') {
if (currentCalls.has(event.index)) {
currentCalls.get(event.index).arguments += event.delta.partial_arguments;
}
} else if (event.delta.type === 'text') {
process.stdout.write(event.delta.text);
}
} else if (evType === 'interaction.completed' || evType === 'interaction.complete') {
toolCalls = Array.from(currentCalls.values()).map(call => ({
type: 'function_call',
id: call.id,
name: call.name,
arguments: call.arguments ? JSON.parse(call.arguments) : {}
}));
console.log('\nFinal tool calls ready to execute:');
console.log(JSON.stringify(toolCalls, null, 2));
}
}
자바
import com.google.genai.Client;
import com.google.genai.gaos.models.interactions.ArgumentsDelta;
import com.google.genai.gaos.models.interactions.CreateModelInteraction;
import com.google.genai.gaos.models.interactions.Function;
import com.google.genai.gaos.models.interactions.FunctionCallStep;
import com.google.genai.gaos.models.interactions.InteractionCompletedEvent;
import com.google.genai.gaos.models.interactions.InteractionSSEEvent;
import com.google.genai.gaos.models.interactions.InteractionSSEStreamEvent;
import com.google.genai.gaos.models.interactions.InteractionsInput;
import com.google.genai.gaos.models.interactions.Model;
import com.google.genai.gaos.models.interactions.Step;
import com.google.genai.gaos.models.interactions.StepDelta;
import com.google.genai.gaos.models.interactions.StepDeltaData;
import com.google.genai.gaos.models.interactions.StepStart;
import com.google.genai.gaos.models.interactions.TextDelta;
import com.google.genai.gaos.models.operations.CreateInteractionRequestBody;
import com.google.genai.gaos.models.operations.CreateInteractionResponse;
import com.google.genai.gaos.utils.EventStream;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
Client client = new Client();
Map<String, Object> locationProp = new HashMap<>();
locationProp.put("type", "string");
locationProp.put("description", "The city and state");
Map<String, Object> properties = new HashMap<>();
properties.put("location", locationProp);
Map<String, Object> parameters = new HashMap<>();
parameters.put("type", "object");
parameters.put("properties", properties);
parameters.put("required", Arrays.asList("location"));
Function weatherTool =
Function.builder()
.name("get_weather")
.description("Gets the weather for a given location.")
.parameters(parameters)
.build();
CreateModelInteraction params =
CreateModelInteraction.builder()
.model(Model.of("gemini-3.8-flash"))
.input(InteractionsInput.of("What is the weather in Paris?"))
.tools(Arrays.asList(weatherTool))
.stream(true)
.build();
CreateInteractionResponse response =
client.interactions.create(CreateInteractionRequestBody.of(params));
Map<Integer, Map<String, Object>> currentCalls = new HashMap<>();
List<Map<String, Object>> toolCalls = new ArrayList<>();
try (EventStream<InteractionSSEStreamEvent> events = response.events()) {
for (InteractionSSEStreamEvent streamEvent : events) {
InteractionSSEEvent event = streamEvent.data().orElse(null);
if (event instanceof StepStart) {
StepStart stepStart = (StepStart) event;
Step step = stepStart.step().orElse(null);
if (step instanceof FunctionCallStep) {
FunctionCallStep fcStep = (FunctionCallStep) step;
int idx = stepStart.index().orElse(0);
Map<String, Object> callInfo = new HashMap<>();
callInfo.put("id", fcStep.id().orElse(""));
callInfo.put("name", fcStep.name().orElse(""));
callInfo.put("arguments", new StringBuilder());
if (fcStep.arguments().isPresent() && !fcStep.arguments().get().isEmpty()) {
((StringBuilder) callInfo.get("arguments")).append(fcStep.arguments().get().toString());
}
currentCalls.put(idx, callInfo);
}
} else if (event instanceof StepDelta) {
StepDelta stepDelta = (StepDelta) event;
StepDeltaData delta = stepDelta.delta().orElse(null);
int idx = stepDelta.index().orElse(0);
if (delta instanceof ArgumentsDelta) {
String partialArgs = ((ArgumentsDelta) delta).arguments().orElse("");
if (currentCalls.containsKey(idx)) {
((StringBuilder) currentCalls.get(idx).get("arguments")).append(partialArgs);
}
} else if (delta instanceof TextDelta) {
((TextDelta) delta).text().ifPresent(System.out::print);
}
} else if (event instanceof InteractionCompletedEvent) {
for (Map<String, Object> call : currentCalls.values()) {
Map<String, Object> finishedCall = new HashMap<>();
finishedCall.put("type", "function_call");
finishedCall.put("id", call.get("id"));
finishedCall.put("name", call.get("name"));
finishedCall.put("arguments", call.get("arguments").toString());
toolCalls.add(finishedCall);
}
System.out.println("\nFinal tool calls ready to execute:");
System.out.println(toolCalls);
}
}
}
Go
package main
import (
"context"
"fmt"
"log"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
getWeather := &genai.FunctionDeclaration{
Name: "get_weather",
Description: "Gets the weather for a given location.",
Parameters: &genai.Schema{
Type: genai.TypeObject,
Properties: map[string]*genai.Schema{
"location": {
Type: genai.TypeString,
Description: "The city and state",
},
},
Required: []string{"location"},
},
}
config := &genai.GenerateContentConfig{
Tools: []*genai.Tool{
{FunctionDeclarations: []*genai.FunctionDeclaration{getWeather}},
},
}
for resp, err := range client.Models.GenerateContentStream(
ctx,
"gemini-3.8-flash",
genai.Text("What is the weather in Paris?"),
config,
) {
if err != nil {
log.Fatal(err)
}
for _, fc := range resp.FunctionCalls() {
fmt.Printf("Function to call: %s\n", fc.Name)
fmt.Printf("Arguments: %v\n", fc.Args)
}
}
}
REST
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?alt=sse" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-d '{
"model": "gemini-3.8-flash",
"input": "What is the weather in Paris?",
"tools": [{
"type": "function",
"name": "get_weather",
"description": "Gets the weather for a given location.",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "The city and state"}
},
"required": ["location"]
}
}],
"stream": true
}'
권장사항
- 함수 및 파라미터 설명: 명확하고 구체적으로 작성하세요.
- 이름 지정: 공백이나 특수문자가 없는 설명적인 이름을 사용합니다.
- 강한 타이핑: 구체적인 유형 (정수, 문자열, enum)을 사용합니다.
- 도구 선택: 활성 도구 세트를 최대 10~20개로 유지합니다.
- 프롬프트 엔지니어링: 컨텍스트와 요청 사항을 제공합니다.
- 유효성 검사: 실행 전에 함수 호출을 검증합니다.
- 오류 처리: 강력한 오류 처리를 구현합니다.
- 보안: 외부 API에 적절한 인증을 사용합니다.
사전 도구 텍스트 요구사항 해결 방법
문제: 프롬프트에서 모델이 구조화된 텍스트 (XML, YAML, JSON 등)를 출력해야 하는 경우 (예: <UPDATE>...</UPDATE>)을 호출하면 도구 호출이 Malformed_Function_Call로 인해 가끔 실패할 수 있습니다.
해결 방법: 다음 해결 방법으로 이 문제를 해결할 수 있습니다.
- 권장: 모델이 도구 전 메모를 원시 텍스트 대신 전용
update()함수 호출 내에 넣도록 지시합니다 (자세한 내용은 아래 참고). - 구조화된 텍스트 대신 마크다운 헤더 (
# UPDATE,## PLAN)로 메모를 작성하도록 모델에 지시합니다. - 모델이 도구 호출 전에 텍스트를 출력하도록 요구하지 마세요.
권장 해결 방법: 전용 함수 호출로 작업 메모 래핑
원래 지침 대신 다음을 사용하세요.
Before calling a tool, in every response you MUST first output a single `<UPDATE>` part as specified, don't skip this part or any of required sub-tags within `<UPDATE>`.
업데이트된 안내를 사용하세요.
Before calling any other tool, in every response you MUST first call `update` with all required parameters (previous_step, plan, next_step, external).
고객 요청에서 이전 <UPDATE> XML 형식에 대한 모든 참조를 업데이트합니다. 그런 다음 업데이트 함수의 해당 함수 선언을 추가합니다.
{
"name": "update",
"description": "Update working notes (previous step analysis, plan, next step, external note).",
"parameters": {
"type": "OBJECT",
"properties": {
"previous_step": {
"type": "STRING",
"description": "Key findings and outcomes since the previous step."
},
"plan": {
"type": "STRING",
"description": "The current status of the plan."
},
"next_step": {
"type": "STRING",
"description": "Brief explanation of the immediate next action according to the plan."
},
"external": {
"type": "STRING",
"description": "A short, plain-language note shown to the User about what you are ABOUT TO DO next."
}
},
"required": [
"previous_step",
"plan",
"next_step",
"external"
]
}
}
그러면 모델은 동일한 단계에서 구조화된 XML을 대체하는 update() 호출과 실행하려는 실제 함수 호출이라는 두 가지 호출을 실행합니다.
참고사항 및 제한사항
- OpenAPI 스키마의 하위 집합만 지원됩니다.
any모드의 경우 API에서 매우 크거나 깊이 중첩된 스키마를 거부할 수 있습니다.- Python에서 지원되는 매개변수 유형은 제한적입니다.