התכונה 'קריאה לפונקציה' מאפשרת לכם לחבר מודלים לכלים ולממשקי API חיצוניים. במקום ליצור תשובות טקסטואליות, המודל קובע מתי לקרוא לפונקציות ספציפיות ומספק את הפרמטרים הנדרשים לביצוע פעולות בעולם האמיתי. כך המודל יכול לשמש כגשר בין שפה טבעית לבין פעולות ונתונים בעולם האמיתי. יש 3 תרחישי שימוש עיקריים לבקשה להפעלת פונקציה:
- ביצוע פעולות: אינטראקציה עם מערכות חיצוניות באמצעות ממשקי API, כמו קביעת פגישות, יצירת חשבוניות, שליחת אימיילים או שליטה במכשירים חכמים לבית.
- העשרת הידע: גישה למידע ממקורות חיצוניים כמו מסדי נתונים, ממשקי API ומאגרי מידע.
- הרחבת היכולות: אפשר להשתמש בכלים חיצוניים כדי לבצע חישובים ולהרחיב את המגבלות של המודל, למשל באמצעות מחשבון או יצירת תרשימים.
בהמשך מופיעות דוגמאות לתרחישי שימוש כאלה:
קביעת פגישה
בדוגמה הזו מוסבר איך להגדיר פונקציה שמתזמנת פגישה עם משתתפים בשעה ספציפית, כדי לאפשר למודל לנתח בקשות של משתמשים ולהחזיר ארגומנטים מובנים להפעלת פעולות במערכות חיצוניות.
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"]
}
}]
}'
קבלת מידע על מזג האוויר
בדוגמה הזו מוסבר איך להגדיר פונקציה שמחלצת נתוני טמפרטורה של מיקום מסוים, וכך מאפשרת למודל להפעיל ממשקי API חיצוניים כדי לענות על שאילתות שדורשות מידע בזמן אמת או מידע חיצוני.
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"]
}
}]
}'
יצירת תרשים
בדוגמה הזו מוגדרת פונקציה שמייצרת תרשים עמודות מנתונים מובְנים. הדוגמה הזו ממחישה איך המודל יכול להשתמש בכלים חיצוניים כדי לבצע חישובים או ליצור נכסים חזותיים:
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"]
}
}]
}'
איך פועלת פונקציית ההתקשרות
השימוש בפונקציות כולל אינטראקציה מובנית בין האפליקציה, המודל ופונקציות חיצוניות:
- הגדרת הצהרת פונקציה: מגדירים למודל את השם, הפרמטרים והמטרה של הפונקציה.
- קוראים למודל LLM עם הצהרות על פונקציות: שולחים את ההנחיה של המשתמש יחד עם ההצהרות על הפונקציות למודל.
- הפעלת קוד הפונקציה (באחריותכם): המודל לא מפעיל את הפונקציה בעצמו. מחלקים את השם והארגומנטים ומבצעים את הפעולה באפליקציה.
- יצירת תשובה ידידותית למשתמש: שליחת התוצאה בחזרה למודל כדי לקבל תשובה סופית וידידותית למשתמש.
אפשר לחזור על התהליך הזה כמה פעמים. המודל תומך בהפעלת כמה פונקציות בתור אחד (קריאה להפעלת פונקציות במקביל) וברצף (קריאה להפעלת פונקציות בהרכבה).
שלב 1: מגדירים הצהרה על פונקציה
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}
}
שלב 2: קוראים למודל עם הצהרות על פונקציות
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])
המודל מחזיר שלב function_call עם type, name ו-arguments:
type='function_call'
name='set_light_values'
arguments={'color_temp': 'warm', 'brightness': 25}
שלב 3: מריצים את הפונקציה
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)
}
שלב 4: שליחת התוצאה בחזרה למודל
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())
בקשה להפעלת פונקציה ללא שמירת מצב
אפשר גם להשתמש בהפעלת פונקציות במצב חסר מצב (stateless) על ידי ניהול היסטוריית השיחות בצד הלקוח והגדרת store=false.
במצב חסר מצב, צריך להעביר את ההיסטוריה המלאה של השיחה בשדה input של כל בקשה עוקבת. ההיסטוריה הזו צריכה לכלול:
1. השלב הראשוני user_input.
2. כל השלבים שנוצרו על ידי המודל והוחזרו בתור 1 (כולל השלבים thought ו-function_call) בדיוק כפי שהתקבלו.
3. השלב function_result שמכיל את הפלט של הפונקציה שהופעלה.
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\"]
}
}]
}"
הצהרות על פונקציות
הצהרה על פונקציה מועברת ככלי וכוללת:
-
type(מחרוזת): צריך להיות"function"עבור פונקציות בהתאמה אישית. -
name(מחרוזת): שם ייחודי של הפונקציה (אפשר להשתמש בקו תחתון או ב-camelCase). -
description(string): הסבר ברור על מטרת הפונקציה. -
parameters(אובייקט): פרמטרי הקלט שהפונקציה מצפה לקבל.-
type(string): סוג הנתונים הכולל, כמוobject. -
properties(אובייקט): פרמטרים נפרדים עם סוג ותיאור. -
required(מערך): שמות פרמטרים נדרשים.
-
בקשה להפעלת פונקציה עם מודלים של חשיבה
מודלים מסדרת Gemini 3 משתמשים בתהליך פנימי של "חשיבה" שמשפר את השימוש בפונקציות. ערכות ה-SDK מטפלות אוטומטית בחתימות מחשבה בשבילכם.
קריאה להפעלת פונקציות במקביל
הפעלת כמה פונקציות בבת אחת כשהן בלתי תלויות:
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"]
}
}
]
}'
קריאה להפעלת פונקציות בהרכבה
אפשר לשרשר כמה קריאות לפונקציות כדי לבצע בקשות מורכבות (למשל, קודם לקבל את המיקום ואז לקבל את נתוני מזג האוויר במיקום הזה).
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"]
}
}
]
}'
מצבים של בקשה להפעלת פונקציה
שליטה באופן השימוש של המודל בכלים באמצעות tool_choice ב-generation_config:
-
auto(ברירת מחדל): המודל מחליט אם להפעיל פונקציה או להגיב ישירות. -
any: המודל מוגבל כך שתמיד יחזה קריאה לפונקציה. -
none: המודל לא יכול לבצע קריאות לפונקציות.
validated: המודל מוודא שהפונקציה תואמת לסכימה.
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"]
}
}
}
}'
שימוש במולטיטול
אפשר להפעיל כמה כלים ולשלב בין כלים מובנים לבין קריאות לפונקציות באותה בקשה. מודלים של Gemini 3 יכולים לשלב כלים מובנים עם קריאה לפונקציות (function calling) מחוץ לקופסה באינטראקציות. העברת previous_interaction_id
תפיץ אוטומטית את ההקשר של הכלי המובנה.
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.\"}"}]
}
]
}'
תשובות פונקציה מולטי-מודאליות
במודלים מסדרת Gemini 3, אפשר לכלול תוכן מולטימודאלי בחלקים של תגובת הפונקציה ששולחים למודל. המודל יכול לעבד את התוכן הרב-מודאלי הזה בתור הבא כדי לספק תשובה מושכלת יותר.
כדי לכלול נתונים מרובי-אופנים בתשובה של פונקציה, צריך לכלול אותם כאחד או יותר בלוקים של תוכן בשדה result של שלב function_result. בכל בלוק תוכן צריך לציין את type (למשל, "text", "image").
בדוגמה הבאה מוצג איך לשלוח בחזרה למודל בתגובה לפונקציה נתונים של תמונה במהלך אינטראקציה:
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"
}
]
}
]
}'
בקשה להפעלת פונקציה עם פלט מובנה
במודלים מסדרת Gemini 3, אפשר לשלב קריאה לפונקציה עם פלט מובנה כדי לקבל תשובות בפורמט עקבי.
MCP (Model Context Protocol) מרוחק
Interactions API תומך בחיבור לשרתי MCP מרוחקים כדי לתת למודל גישה לכלים ולשירותים חיצוניים. אתם מספקים את השרת name ואת url בהגדרת הכלים.
כשמשתמשים ב-Remote MCP, חשוב לשים לב למגבלות הבאות:
- סוגי שרתים: שרת MCP מרוחק פועל רק עם שרתי HTTP שניתן להזרים מהם. אין תמיכה בשרתי SSE (אירועים שנשלחים מהשרת).
- שמות: שמות של שרתי MCP לא יכולים לכלול את התו
-. במקום זאת, צריך להשתמש בשמות השרתיםsnake_case.
| שדה | סוג | נדרש | תיאור |
|---|---|---|---|
type |
string |
כן | חייב להיות "mcp_server". |
name |
string |
לא | השם המוצג של שרת ה-MCP. |
url |
string |
לא | כתובת ה-URL המלאה של נקודת הקצה של שרת ה-MCP. |
headers |
object |
לא | צמדי מפתח/ערך שנשלחים ככותרות HTTP עם כל בקשה לשרת (לדוגמה, אסימוני אימות). |
allowed_tools |
array |
לא | הגבלת הכלים בשרת שהסוכן יכול להשתמש בהם. |
דוגמה
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"
}
]
}'
העברת קריאות לכלי בסטרימינג
כשמשתמשים בכלים עם סטרימינג, המודל יוצר קריאות לפונקציות כרצף של
step.delta אירועים בסטרימינג. אפשר להזרים ארגומנטים של כלים כארגומנטים חלקיים באמצעות arguments. כדי להפעיל את קריאות הכלים, צריך לצבור את ערכי הדלתא האלה כדי לשחזר את קריאות הכלים המלאות.
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
}'
שיטות מומלצות
- תיאורים של פונקציות ופרמטרים: הקפידו על בהירות וספציפיות.
- שמות: צריך להשתמש בשמות תיאוריים ללא רווחים או תווים מיוחדים.
- הקלדה חזקה: שימוש בסוגים ספציפיים (מספר שלם, מחרוזת, enum).
- בחירת כלים: כדאי להגדיר את האפשרות 'פעיל' ל-10 עד 20 כלים לכל היותר.
- הנדסת הנחיות: מספקים הקשר והוראות.
- אימות: אימות של קריאות לפונקציות לפני ההפעלה.
- טיפול בשגיאות: צריך להטמיע טיפול בשגיאות בצורה חזקה.
- אבטחה: השתמשו באימות מתאים לממשקי API חיצוניים.
פתרונות עקיפים לדרישות הטקסט של כלי ההכנה
בעיה: אם ההנחיה שלכם מחייבת את המודל להפיק טקסט מובנה (XML, YAML, JSON וכו') (לדוגמה, <UPDATE>...</UPDATE>) מיד לפני ביצוע קריאה לכלי, יכול להיות שהקריאה לכלי תיכשל מדי פעם עם Malformed_Function_Call.
פתרונות: הפתרונות הבאים יעזרו לכם לפתור את הבעיה:
- מומלץ: מנחים את המודל להוסיף את ההערות שלו לפני השימוש בכלי בתוך קריאה ייעודית לפונקציה
update()במקום בטקסט גולמי (פרטים בהמשך). - מנחים את המודל לכתוב הערות ככותרות Markdown (
# UPDATE,## PLAN) במקום כטקסט מובנה. - אל תדרשו מהמודל להפיק טקסט לפני קריאות לכלים.
פתרון עדיף: עטיפת הערות העבודה בקריאה ייעודית לפונקציה
במקום ההוראה המקורית:
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>`.
צריך להשתמש בהוראה המעודכנת הזו:
Before calling any other tool, in every response you MUST first call `update` with all required parameters (previous_step, plan, next_step, external).
בנוסף, צריך לעדכן את כל ההפניות לפורמט ה-XML הישן של <UPDATE> בבקשת הלקוח. לאחר מכן מוסיפים את הצהרת הפונקציה המתאימה לפונקציית העדכון:
{
"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"
]
}
}
לאחר מכן, המודל יבצע שתי קריאות באותו השלב: קריאת update() שמחליפה את ה-XML המובנה, וקריאת הפונקציה בפועל שהוא רוצה לבצע.
הערות ומגבלות
- יש תמיכה רק בקבוצת משנה של סכימת OpenAPI.
- במצב
any, יכול להיות שה-API ידחה סכימות גדולות מאוד או סכימות עם קינון עמוק. - סוגי הפרמטרים הנתמכים ב-Python מוגבלים.