La chiamata di funzioni consente di collegare i modelli a strumenti e API esterni. Anziché generare risposte di testo, il modello determina quando chiamare funzioni specifiche e fornisce i parametri necessari per eseguire azioni nel mondo reale. Ciò consente al modello di fungere da ponte tra il linguaggio naturale e le azioni e i dati del mondo reale. Le chiamate di funzione hanno tre casi d'uso principali:
- Esegui azioni:interagisci con sistemi esterni utilizzando API, ad esempio pianificare appuntamenti, creare fatture, inviare email o controllare dispositivi per la smart home.
- Aumenta le conoscenze:accedi alle informazioni da fonti esterne come database, API e knowledge base.
- Estendi le funzionalità:utilizza strumenti esterni per eseguire calcoli ed estendere i limiti del modello, ad esempio utilizzando una calcolatrice o creando grafici.
Di seguito puoi sfogliare alcuni esempi di questi casi d'uso:
Pianifica riunione
Questo esempio mostra come definire una funzione che pianifica una riunione con i partecipanti a un'ora specifica, consentendo al modello di analizzare le richieste degli utenti e restituire argomenti strutturati per attivare azioni in sistemi esterni.
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}")
JavaScript
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)}`);
}
}
Java
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"]
}
}]
}'
Visualizza meteo
Questo esempio mostra come definire una funzione che recupera i dati di temperatura per una località, consentendo al modello di chiamare API esterne per rispondere a query che richiedono informazioni esterne o in tempo reale.
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}")
JavaScript
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)}`);
}
}
Java
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"]
}
}]
}'
Crea grafico
Questo esempio mostra come definire una funzione che genera un grafico a barre da dati strutturati, dimostrando come il modello può utilizzare strumenti esterni per eseguire calcoli o creare asset visivi:
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}")
JavaScript
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)})`);
}
}
Java
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"]
}
}]
}'
Come funziona la chiamata di funzioni
La chiamata di funzioni prevede un'interazione strutturata tra l'applicazione, il modello e le funzioni esterne:
- Definisci la dichiarazione di funzione:definisci il nome, i parametri e lo scopo della funzione per il modello.
- Chiama LLM con dichiarazioni di funzione: invia il prompt dell'utente insieme alle dichiarazioni di funzione al modello.
- Esecuzione del codice della funzione (tua responsabilità): il modello non esegue la funzione stessa. Estrai il nome e gli argomenti ed esegui nell'applicazione.
- Crea una risposta intuitiva: invia il risultato al modello per una risposta finale e intuitiva.
Questa procedura può essere ripetuta in più turni. Il modello supporta la chiamata di più funzioni in un singolo turno (chiamata di funzione parallela) e in sequenza (chiamata di funzione compositiva).
Passaggio 1: definisci una dichiarazione di funzione
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}
JavaScript
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 };
}
Java
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}
}
Passaggio 2: chiama il modello con le dichiarazioni di funzione
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)
JavaScript
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);
Java
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])
Il modello restituisce un passaggio function_call con type, name e arguments:
type='function_call'
name='set_light_values'
arguments={'color_temp': 'warm', 'brightness': 25}
Passaggio 3: esegui la funzione
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}")
JavaScript
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)}`);
}
Java
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)
}
Passaggio 4: invia il risultato al modello
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)
JavaScript
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);
Java
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())
Chiamata di funzione stateless
Puoi anche utilizzare la chiamata di funzioni in modalità stateless gestendo la cronologia della conversazione sul lato client e impostando store=false.
In modalità stateless, devi trasmettere la cronologia completa della conversazione nel campo input di ogni richiesta successiva. Questa cronologia deve includere:
1. Il passaggio iniziale user_input.
2. Tutti i passaggi generati dal modello restituiti nel Turno 1 (inclusi i passaggi thought e function_call) esattamente come ricevuti.
3. Il passaggio function_result contenente l'output della funzione eseguita.
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)
JavaScript
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();
Java
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\"]
}
}]
}"
Dichiarazioni di funzione
Una dichiarazione di funzione viene passata come strumento e include:
type(stringa): deve essere"function"per le funzioni personalizzate.name(stringa): nome univoco della funzione (utilizza trattini bassi o camelCase).description(stringa): spiegazione chiara dello scopo della funzione.parameters(oggetto): parametri di input previsti dalla funzione.type(stringa): tipo di dati complessivo, ad esempioobject.properties(oggetto): singoli parametri con tipo e descrizione.required(array): nomi dei parametri obbligatori.
Chiamata di funzione con modelli di ragionamento
I modelli della serie Gemini 3 utilizzano un processo interno di "pensiero" che migliora la chiamata di funzioni. Gli SDK gestiscono automaticamente le firme del pensiero.
Chiamata di funzione parallela
Chiama più funzioni contemporaneamente quando sono indipendenti:
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})")
JavaScript
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)})`);
}
}
Java
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"]
}
}
]
}'
Chiamata di funzione compositiva
Concatenare più chiamate di funzione per richieste complesse (ad es. prima ottenere la posizione, poi le previsioni meteo per quella posizione).
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)
JavaScript
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);
}
}
}
}
Java
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"]
}
}
]
}'
Modalità di chiamata di funzione
Controlla il modo in cui il modello utilizza gli strumenti utilizzando tool_choice in generation_config:
auto(predefinito): il modello decide se chiamare una funzione o rispondere direttamente.any: il modello è vincolato a prevedere sempre una chiamata di funzione.none: Il modello non può effettuare chiamate di funzione.validated: Il modello garantisce il rispetto dello schema della funzione.
Python
generation_config = {
"tool_choice": {
"allowed_tools": {
"mode": "any",
"tools": ["get_current_temperature"]
}
}
}
JavaScript
const generation_config = {
tool_choice: {
allowed_tools: {
mode: 'any',
tools: ['get_current_temperature']
}
}
};
Java
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"]
}
}
}
}'
Utilizzo di multiutensili
Puoi attivare più strumenti, combinando quelli integrati con la chiamata a funzioni nella stessa richiesta. I modelli Gemini 3 possono combinare strumenti integrati con la chiamata di funzioni
pronte all'uso in Interazioni. Il passaggio di previous_interaction_id
fa circolare automaticamente il contesto dello strumento integrato.
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)
JavaScript
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);
}
}
Java
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.\"}"}]
}
]
}'
Risposte di funzioni multimodali
Per i modelli della serie Gemini 3, puoi includere contenuti multimodali nelle parti della risposta della funzione che invii al modello. Il modello può elaborare questo contenuto multimodale nel turno successivo per produrre una risposta più informata.
Per includere dati multimodali in una risposta della funzione, includili come uno o più blocchi di contenuti nel campo result del passaggio function_result. Ogni blocco di contenuti deve specificare il relativo type (ad es. "text", "image").
Il seguente esempio mostra come inviare una risposta della funzione contenente dati immagine al modello in un'interazione:
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)
JavaScript
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);
Java
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"
}
]
}
]
}'
Chiamata di funzione con output strutturato
Per i modelli della serie Gemini 3, combina la chiamata di funzione con l'output strutturato per risposte formattate in modo coerente.
MCP (Model Context Protocol) remoto
L'API Interactions supporta la connessione a server MCP remoti per consentire al modello di accedere a strumenti e servizi esterni. Fornisci il server name e url nella configurazione degli strumenti.
Quando utilizzi Remote MCP, tieni presente i seguenti vincoli:
- Tipi di server: l'MCP remoto funziona solo con i server HTTP riproducibili in streaming. I server SSE (Server-Sent Events) non sono supportati.
- Denominazione: i nomi dei server MCP non devono includere il carattere
-. Utilizza invece i nomi dei serversnake_case.
| Campo | Tipo | Obbligatorio | Descrizione |
|---|---|---|---|
type |
string |
Sì | Deve essere "mcp_server". |
name |
string |
No | Un nome visualizzato per il server MCP. |
url |
string |
No | L'URL completo dell'endpoint del server MCP. |
headers |
object |
No | Coppie chiave-valore inviate come intestazioni HTTP con ogni richiesta al server (ad esempio, token di autenticazione). |
allowed_tools |
array |
No | Limita gli strumenti del server che l'agente può chiamare. |
Esempio
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",
}
]
)
JavaScript
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'
}
]
});
Java
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"
}
]
}'
Chiamate allo strumento di streaming
Quando utilizzi strumenti con lo streaming, il modello genera chiamate di funzione come
sequenza di eventi step.delta nello stream. Gli argomenti dello strumento possono essere trasmessi in streaming
come argomenti parziali utilizzando arguments. Devi aggregare questi delta per
ricostruire le chiamate agli strumenti complete prima di eseguirle.
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))
JavaScript
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));
}
}
Java
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
}'
Best practice
- Descrizioni di funzioni e parametri:sii chiaro e specifico.
- Denominazione:utilizza nomi descrittivi senza spazi o caratteri speciali.
- Tipizzazione forte:utilizza tipi specifici (numero intero, stringa, enum).
- Selezione degli strumenti:mantieni attivo un massimo di 10-20 strumenti.
- Prompt engineering: fornisci il contesto e le istruzioni.
- Convalida:convalida le chiamate di funzioni prima dell'esecuzione.
- Gestione degli errori:implementa una gestione degli errori efficace.
- Sicurezza:utilizza l'autenticazione appropriata per le API esterne.
Soluzioni alternative per i requisiti di testo pre-strumento
Problema:se il prompt richiede al modello di restituire testo strutturato (XML, YAML, JSON e così via) (ad es. <UPDATE>...</UPDATE>) immediatamente prima di effettuare una chiamata allo strumento, la chiamata allo strumento potrebbe occasionalmente non riuscire con Malformed_Function_Call.
Soluzioni:le seguenti soluzioni alternative risolvono il problema:
- PREFERITO: indica al modello di inserire le note pre-strumento all'interno di una chiamata di funzione
update()dedicata anziché in testo non elaborato (dettagli di seguito). - Chiedi al modello di scrivere le note come intestazioni Markdown (
# UPDATE,## PLAN) anziché come testo strutturato. - Non richiedere al modello di generare testo prima delle chiamate di strumenti.
Soluzione alternativa preferita: racchiudi le note di lavoro in una chiamata di funzione dedicata
Invece dell'istruzione originale:
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>`.
Utilizza questa istruzione aggiornata:
Before calling any other tool, in every response you MUST first call `update` with all required parameters (previous_step, plan, next_step, external).
Aggiorna tutti i riferimenti al vecchio formato XML <UPDATE> nella richiesta del cliente. Poi aggiungi la dichiarazione di funzione corrispondente per la funzione di aggiornamento:
{
"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"
]
}
}
Il modello effettuerà quindi due chiamate nello stesso passaggio: la chiamata update() che sostituisce l'XML strutturato e la chiamata di funzione effettiva che vuole effettuare.
Note e limitazioni
- È supportato solo un sottoinsieme dello schema OpenAPI.
- Per la modalità
any, l'API potrebbe rifiutare schemi molto grandi o con molti livelli di nidificazione. - I tipi di parametri supportati in Python sono limitati.