Gemini API יכול ליצור פלט של טקסט מקלט מסוגים שונים, כולל טקסט, תמונות, סרטונים ואודיו, באמצעות מודלים של Gemini.
זו דוגמה בסיסית שמקבלת קלט טקסט יחיד:
Python
from google import genai
client = genai.Client()
response = client.models.generate_content(
model="gemini-2.5-flash",
contents="How does AI work?"
)
print(response.text)
JavaScript
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({});
async function main() {
const response = await ai.models.generateContent({
model: "gemini-2.5-flash",
contents: "How does AI work?",
});
console.log(response.text);
}
await main();
Go
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash",
genai.Text("Explain how AI works in a few words"),
nil,
)
fmt.Println(result.Text())
}
REST
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-X POST \
-d '{
"contents": [
{
"parts": [
{
"text": "How does AI work?"
}
]
}
]
}'
Apps Script
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const payload = {
contents: [
{
parts: [
{ text: 'How AI does work?' },
],
},
],
};
const url = 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent';
const options = {
method: 'POST',
contentType: 'application/json',
headers: {
'x-goog-api-key': apiKey,
},
payload: JSON.stringify(payload)
};
const response = UrlFetchApp.fetch(url, options);
const data = JSON.parse(response);
const content = data['candidates'][0]['content']['parts'][0]['text'];
console.log(content);
}
חשיבה עם Gemini 2.5
במודלים 2.5 Flash ו-Pro, התכונה 'חשיבה' מופעלת כברירת מחדל כדי לשפר את האיכות. הפעלת התכונה הזו עשויה להאריך את זמן הריצה ולהגדיל את השימוש בטוקנים.
כשמשתמשים ב-2.5 Flash, אפשר להשבית את התכונה 'חשיבה' על ידי הגדרת תקציב החשיבה לאפס.
מידע נוסף זמין במדריך התכנון.
Python
from google import genai
from google.genai import types
client = genai.Client()
response = client.models.generate_content(
model="gemini-2.5-flash",
contents="How does AI work?",
config=types.GenerateContentConfig(
thinking_config=types.ThinkingConfig(thinking_budget=0) # Disables thinking
),
)
print(response.text)
JavaScript
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({});
async function main() {
const response = await ai.models.generateContent({
model: "gemini-2.5-flash",
contents: "How does AI work?",
config: {
thinkingConfig: {
thinkingBudget: 0, // Disables thinking
},
}
});
console.log(response.text);
}
await main();
Go
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash",
genai.Text("How does AI work?"),
&genai.GenerateContentConfig{
ThinkingConfig: &genai.ThinkingConfig{
ThinkingBudget: int32(0), // Disables thinking
},
}
)
fmt.Println(result.Text())
}
REST
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-X POST \
-d '{
"contents": [
{
"parts": [
{
"text": "How does AI work?"
}
]
}
],
"generationConfig": {
"thinkingConfig": {
"thinkingBudget": 0
}
}
}'
Apps Script
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const payload = {
contents: [
{
parts: [
{ text: 'How AI does work?' },
],
},
],
};
const url = 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent';
const options = {
method: 'POST',
contentType: 'application/json',
headers: {
'x-goog-api-key': apiKey,
},
payload: JSON.stringify(payload)
};
const response = UrlFetchApp.fetch(url, options);
const data = JSON.parse(response);
const content = data['candidates'][0]['content']['parts'][0]['text'];
console.log(content);
}
הוראות מערכת והגדרות אחרות
אתם יכולים להנחות את ההתנהגות של מודלים של Gemini באמצעות הוראות מערכת. כדי לעשות את זה, מעבירים אובייקט GenerateContentConfig
.
Python
from google import genai
from google.genai import types
client = genai.Client()
response = client.models.generate_content(
model="gemini-2.5-flash",
config=types.GenerateContentConfig(
system_instruction="You are a cat. Your name is Neko."),
contents="Hello there"
)
print(response.text)
JavaScript
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({});
async function main() {
const response = await ai.models.generateContent({
model: "gemini-2.5-flash",
contents: "Hello there",
config: {
systemInstruction: "You are a cat. Your name is Neko.",
},
});
console.log(response.text);
}
await main();
Go
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
config := &genai.GenerateContentConfig{
SystemInstruction: genai.NewContentFromText("You are a cat. Your name is Neko.", genai.RoleUser),
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash",
genai.Text("Hello there"),
config,
)
fmt.Println(result.Text())
}
REST
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"system_instruction": {
"parts": [
{
"text": "You are a cat. Your name is Neko."
}
]
},
"contents": [
{
"parts": [
{
"text": "Hello there"
}
]
}
]
}'
Apps Script
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const systemInstruction = {
parts: [{
text: 'You are a cat. Your name is Neko.'
}]
};
const payload = {
systemInstruction,
contents: [
{
parts: [
{ text: 'Hello there' },
],
},
],
};
const url = 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent';
const options = {
method: 'POST',
contentType: 'application/json',
headers: {
'x-goog-api-key': apiKey,
},
payload: JSON.stringify(payload)
};
const response = UrlFetchApp.fetch(url, options);
const data = JSON.parse(response);
const content = data['candidates'][0]['content']['parts'][0]['text'];
console.log(content);
}
אובייקט GenerateContentConfig
מאפשר גם לשנות פרמטרים של גנרציה שמוגדרים כברירת מחדל, כמו טמפרטורה.
Python
from google import genai
from google.genai import types
client = genai.Client()
response = client.models.generate_content(
model="gemini-2.5-flash",
contents=["Explain how AI works"],
config=types.GenerateContentConfig(
temperature=0.1
)
)
print(response.text)
JavaScript
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({});
async function main() {
const response = await ai.models.generateContent({
model: "gemini-2.5-flash",
contents: "Explain how AI works",
config: {
temperature: 0.1,
},
});
console.log(response.text);
}
await main();
Go
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
temp := float32(0.9)
topP := float32(0.5)
topK := float32(20.0)
config := &genai.GenerateContentConfig{
Temperature: &temp,
TopP: &topP,
TopK: &topK,
ResponseMIMEType: "application/json",
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash",
genai.Text("What is the average size of a swallow?"),
config,
)
fmt.Println(result.Text())
}
REST
curl https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-X POST \
-d '{
"contents": [
{
"parts": [
{
"text": "Explain how AI works"
}
]
}
],
"generationConfig": {
"stopSequences": [
"Title"
],
"temperature": 1.0,
"topP": 0.8,
"topK": 10
}
}'
Apps Script
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const generationConfig = {
temperature: 1,
topP: 0.95,
topK: 40,
responseMimeType: 'text/plain',
};
const payload = {
generationConfig,
contents: [
{
parts: [
{ text: 'Explain how AI works in a few words' },
],
},
],
};
const url = 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent';
const options = {
method: 'POST',
contentType: 'application/json',
headers: {
'x-goog-api-key': apiKey,
},
payload: JSON.stringify(payload)
};
const response = UrlFetchApp.fetch(url, options);
const data = JSON.parse(response);
const content = data['candidates'][0]['content']['parts'][0]['text'];
console.log(content);
}
רשימה מלאה של הפרמטרים שאפשר להגדיר והתיאורים שלהם מופיעה GenerateContentConfig
בחומר העזר בנושא API.
קלט מרובה מצבים
Gemini API תומך בקלט מרובה-אופנים, ומאפשר לכם לשלב טקסט עם קובצי מדיה. בדוגמה הבאה אפשר לראות איך מספקים תמונה:
Python
from PIL import Image
from google import genai
client = genai.Client()
image = Image.open("/path/to/organ.png")
response = client.models.generate_content(
model="gemini-2.5-flash",
contents=[image, "Tell me about this instrument"]
)
print(response.text)
JavaScript
import {
GoogleGenAI,
createUserContent,
createPartFromUri,
} from "@google/genai";
const ai = new GoogleGenAI({});
async function main() {
const image = await ai.files.upload({
file: "/path/to/organ.png",
});
const response = await ai.models.generateContent({
model: "gemini-2.5-flash",
contents: [
createUserContent([
"Tell me about this instrument",
createPartFromUri(image.uri, image.mimeType),
]),
],
});
console.log(response.text);
}
await main();
Go
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
imagePath := "/path/to/organ.jpg"
imgData, _ := os.ReadFile(imagePath)
parts := []*genai.Part{
genai.NewPartFromText("Tell me about this instrument"),
&genai.Part{
InlineData: &genai.Blob{
MIMEType: "image/jpeg",
Data: imgData,
},
},
}
contents := []*genai.Content{
genai.NewContentFromParts(parts, genai.RoleUser),
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.5-flash",
contents,
nil,
)
fmt.Println(result.Text())
}
REST
# Use a temporary file to hold the base64 encoded image data
TEMP_B64=$(mktemp)
trap 'rm -f "$TEMP_B64"' EXIT
base64 $B64FLAGS $IMG_PATH > "$TEMP_B64"
# Use a temporary file to hold the JSON payload
TEMP_JSON=$(mktemp)
trap 'rm -f "$TEMP_JSON"' EXIT
cat > "$TEMP_JSON" << EOF
{
"contents": [
{
"parts": [
{
"text": "Tell me about this instrument"
},
{
"inline_data": {
"mime_type": "image/jpeg",
"data": "$(cat "$TEMP_B64")"
}
}
]
}
]
}
EOF
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-X POST \
-d "@$TEMP_JSON"
Apps Script
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const imageUrl = 'http://image/url';
const image = getImageData(imageUrl);
const payload = {
contents: [
{
parts: [
{ image },
{ text: 'Tell me about this instrument' },
],
},
],
};
const url = 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent';
const options = {
method: 'POST',
contentType: 'application/json',
headers: {
'x-goog-api-key': apiKey,
},
payload: JSON.stringify(payload)
};
const response = UrlFetchApp.fetch(url, options);
const data = JSON.parse(response);
const content = data['candidates'][0]['content']['parts'][0]['text'];
console.log(content);
}
function getImageData(url) {
const blob = UrlFetchApp.fetch(url).getBlob();
return {
mimeType: blob.getContentType(),
data: Utilities.base64Encode(blob.getBytes())
};
}
שיטות חלופיות להוספת תמונות ומידע נוסף על עיבוד תמונות מתקדם זמינים במדריך שלנו להבנת תמונות. ממשק ה-API תומך גם בהזנות ובפענוח של מסמכים, סרטונים ואודיו.
הצגת התשובות באופן שוטף
כברירת מחדל, המודל מחזיר תשובה רק אחרי שתהליך היצירה כולו מסתיים.
כדי שהאינטראקציות יהיו חלקות יותר, אפשר להשתמש בסטרימינג כדי לקבל מופעים של GenerateContentResponse
באופן מצטבר בזמן שהם נוצרים.
Python
from google import genai
client = genai.Client()
response = client.models.generate_content_stream(
model="gemini-2.5-flash",
contents=["Explain how AI works"]
)
for chunk in response:
print(chunk.text, end="")
JavaScript
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({});
async function main() {
const response = await ai.models.generateContentStream({
model: "gemini-2.5-flash",
contents: "Explain how AI works",
});
for await (const chunk of response) {
console.log(chunk.text);
}
}
await main();
Go
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
stream := client.Models.GenerateContentStream(
ctx,
"gemini-2.5-flash",
genai.Text("Write a story about a magic backpack."),
nil,
)
for chunk, _ := range stream {
part := chunk.Candidates[0].Content.Parts[0]
fmt.Print(part.Text)
}
}
REST
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:streamGenerateContent?alt=sse" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
--no-buffer \
-d '{
"contents": [
{
"parts": [
{
"text": "Explain how AI works"
}
]
}
]
}'
Apps Script
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const payload = {
contents: [
{
parts: [
{ text: 'Explain how AI works' },
],
},
],
};
const url = 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:streamGenerateContent';
const options = {
method: 'POST',
contentType: 'application/json',
headers: {
'x-goog-api-key': apiKey,
},
payload: JSON.stringify(payload)
};
const response = UrlFetchApp.fetch(url, options);
const data = JSON.parse(response);
const content = data['candidates'][0]['content']['parts'][0]['text'];
console.log(content);
}
שיחות עם זיכרון (Chat)
ערכות ה-SDK שלנו מספקות פונקציונליות לאיסוף של כמה סבבים של הנחיות ותשובות בצ'אט, וכך מאפשרות לכם לעקוב בקלות אחרי היסטוריית השיחות.
Python
from google import genai
client = genai.Client()
chat = client.chats.create(model="gemini-2.5-flash")
response = chat.send_message("I have 2 dogs in my house.")
print(response.text)
response = chat.send_message("How many paws are in my house?")
print(response.text)
for message in chat.get_history():
print(f'role - {message.role}',end=": ")
print(message.parts[0].text)
JavaScript
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({});
async function main() {
const chat = ai.chats.create({
model: "gemini-2.5-flash",
history: [
{
role: "user",
parts: [{ text: "Hello" }],
},
{
role: "model",
parts: [{ text: "Great to meet you. What would you like to know?" }],
},
],
});
const response1 = await chat.sendMessage({
message: "I have 2 dogs in my house.",
});
console.log("Chat response 1:", response1.text);
const response2 = await chat.sendMessage({
message: "How many paws are in my house?",
});
console.log("Chat response 2:", response2.text);
}
await main();
Go
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
history := []*genai.Content{
genai.NewContentFromText("Hi nice to meet you! I have 2 dogs in my house.", genai.RoleUser),
genai.NewContentFromText("Great to meet you. What would you like to know?", genai.RoleModel),
}
chat, _ := client.Chats.Create(ctx, "gemini-2.5-flash", nil, history)
res, _ := chat.SendMessage(ctx, genai.Part{Text: "How many paws are in my house?"})
if len(res.Candidates) > 0 {
fmt.Println(res.Candidates[0].Content.Parts[0].Text)
}
}
REST
curl https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-X POST \
-d '{
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello"
}
]
},
{
"role": "model",
"parts": [
{
"text": "Great to meet you. What would you like to know?"
}
]
},
{
"role": "user",
"parts": [
{
"text": "I have two dogs in my house. How many paws are in my house?"
}
]
}
]
}'
Apps Script
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const payload = {
contents: [
{
role: 'user',
parts: [
{ text: 'Hello' },
],
},
{
role: 'model',
parts: [
{ text: 'Great to meet you. What would you like to know?' },
],
},
{
role: 'user',
parts: [
{ text: 'I have two dogs in my house. How many paws are in my house?' },
],
},
],
};
const url = 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent';
const options = {
method: 'POST',
contentType: 'application/json',
headers: {
'x-goog-api-key': apiKey,
},
payload: JSON.stringify(payload)
};
const response = UrlFetchApp.fetch(url, options);
const data = JSON.parse(response);
const content = data['candidates'][0]['content']['parts'][0]['text'];
console.log(content);
}
אפשר להשתמש בסטרימינג גם בשיחות מרובות תפניות.
Python
from google import genai
client = genai.Client()
chat = client.chats.create(model="gemini-2.5-flash")
response = chat.send_message_stream("I have 2 dogs in my house.")
for chunk in response:
print(chunk.text, end="")
response = chat.send_message_stream("How many paws are in my house?")
for chunk in response:
print(chunk.text, end="")
for message in chat.get_history():
print(f'role - {message.role}', end=": ")
print(message.parts[0].text)
JavaScript
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({});
async function main() {
const chat = ai.chats.create({
model: "gemini-2.5-flash",
history: [
{
role: "user",
parts: [{ text: "Hello" }],
},
{
role: "model",
parts: [{ text: "Great to meet you. What would you like to know?" }],
},
],
});
const stream1 = await chat.sendMessageStream({
message: "I have 2 dogs in my house.",
});
for await (const chunk of stream1) {
console.log(chunk.text);
console.log("_".repeat(80));
}
const stream2 = await chat.sendMessageStream({
message: "How many paws are in my house?",
});
for await (const chunk of stream2) {
console.log(chunk.text);
console.log("_".repeat(80));
}
}
await main();
Go
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, err := genai.NewClient(ctx, nil)
if err != nil {
log.Fatal(err)
}
history := []*genai.Content{
genai.NewContentFromText("Hi nice to meet you! I have 2 dogs in my house.", genai.RoleUser),
genai.NewContentFromText("Great to meet you. What would you like to know?", genai.RoleModel),
}
chat, _ := client.Chats.Create(ctx, "gemini-2.5-flash", nil, history)
stream := chat.SendMessageStream(ctx, genai.Part{Text: "How many paws are in my house?"})
for chunk, _ := range stream {
part := chunk.Candidates[0].Content.Parts[0]
fmt.Print(part.Text)
}
}
REST
curl https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:streamGenerateContent?alt=sse \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-X POST \
-d '{
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello"
}
]
},
{
"role": "model",
"parts": [
{
"text": "Great to meet you. What would you like to know?"
}
]
},
{
"role": "user",
"parts": [
{
"text": "I have two dogs in my house. How many paws are in my house?"
}
]
}
]
}'
Apps Script
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const payload = {
contents: [
{
role: 'user',
parts: [
{ text: 'Hello' },
],
},
{
role: 'model',
parts: [
{ text: 'Great to meet you. What would you like to know?' },
],
},
{
role: 'user',
parts: [
{ text: 'I have two dogs in my house. How many paws are in my house?' },
],
},
],
};
const url = 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:streamGenerateContent';
const options = {
method: 'POST',
contentType: 'application/json',
headers: {
'x-goog-api-key': apiKey,
},
payload: JSON.stringify(payload)
};
const response = UrlFetchApp.fetch(url, options);
const data = JSON.parse(response);
const content = data['candidates'][0]['content']['parts'][0]['text'];
console.log(content);
}
מודלים נתמכים
כל המודלים במשפחת Gemini תומכים ביצירת טקסט. מידע נוסף על המודלים והיכולות שלהם זמין בדף מודלים.
שיטות מומלצות
טיפים לכתיבת הנחיות
כדי ליצור טקסט בסיסי, לעיתים קרובות מספיק להשתמש בהנחיה מסוג zero-shot בלי צורך בדוגמאות, בהוראות מערכת או בעיצוב ספציפי.
כדי לקבל פלט מותאם יותר:
- כדי להנחות את המודל, אפשר להשתמש בהוראות מערכת.
- מספקים כמה דוגמאות של קלט ופלט כדי להנחות את המודל. השיטה הזו נקראת בדרך כלל few-shot prompting.
במדריך שלנו ליצירת הנחיות מופיעים טיפים נוספים.
פלט מובנה
במקרים מסוימים, יכול להיות שתצטרכו פלט מובנה, כמו JSON. במדריך שלנו בנושא פלט מובנה מוסבר איך עושים את זה.
המאמרים הבאים
- כדאי לנסות את המדריך לתחילת העבודה עם Gemini API ב-Colab.
- אתם יכולים לנסות את היכולות של Gemini להבנת תמונות, סרטונים, אודיו ומסמכים.
- מידע על אסטרטגיות להנפקת הנחיות לקבצים