يمكن لواجهة برمجة التطبيقات Gemini API إنشاء إخراج نصي من إدخالات مختلفة، بما في ذلك النصوص والصور والفيديوهات والصوت، وذلك من خلال الاستفادة من نماذج Gemini.
في ما يلي مثال أساسي يأخذ إدخال نصي واحدًا:
from google import genai
client = genai.Client(api_key="GEMINI_API_KEY")
response = client.models.generate_content(
model="gemini-2.0-flash",
contents=["How does AI work?"]
)
print(response.text)
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });
async function main() {
const response = await ai.models.generateContent({
model: "gemini-2.0-flash",
contents: "How does AI work?",
});
console.log(response.text);
}
await main();
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, _ := genai.NewClient(ctx, &genai.ClientConfig{
APIKey: os.Getenv("GEMINI_API_KEY"),
Backend: genai.BackendGeminiAPI,
})
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.0-flash",
genai.Text("Explain how AI works in a few words"),
nil,
)
fmt.Println(result.Text())
}
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-X POST \
-d '{
"contents": [
{
"parts": [
{
"text": "How does AI work?"
}
]
}
]
}'
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const payload = {
contents: [
{
parts: [
{ text: 'How AI does work?' },
],
},
],
};
const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=${apiKey}`;
const options = {
method: 'POST',
contentType: 'application/json',
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);
}
تعليمات النظام وإعداداته
يمكنك توجيه سلوك نماذج Gemini باستخدام تعليمات النظام. لإجراء ذلك،
أرسِل عنصر GenerateContentConfig
.
from google import genai
from google.genai import types
client = genai.Client(api_key="GEMINI_API_KEY")
response = client.models.generate_content(
model="gemini-2.0-flash",
config=types.GenerateContentConfig(
system_instruction="You are a cat. Your name is Neko."),
contents="Hello there"
)
print(response.text)
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });
async function main() {
const response = await ai.models.generateContent({
model: "gemini-2.0-flash",
contents: "Hello there",
config: {
systemInstruction: "You are a cat. Your name is Neko.",
},
});
console.log(response.text);
}
await main();
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, _ := genai.NewClient(ctx, &genai.ClientConfig{
APIKey: os.Getenv("GEMINI_API_KEY"),
Backend: genai.BackendGeminiAPI,
})
config := &genai.GenerateContentConfig{
SystemInstruction: genai.NewContentFromText("You are a cat. Your name is Neko.", genai.RoleUser),
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.0-flash",
genai.Text("Hello there"),
config,
)
fmt.Println(result.Text())
}
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"system_instruction": {
"parts": [
{
"text": "You are a cat. Your name is Neko."
}
]
},
"contents": [
{
"parts": [
{
"text": "Hello there"
}
]
}
]
}'
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const systemInstruction = {
parts: [{
text: 'You are a cat. Your name is Neko.'
}]
};
const payload = {
systemInstruction,
contents: [
{
parts: [
{ text: 'Hello there' },
],
},
],
};
const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=${apiKey}`;
const options = {
method: 'POST',
contentType: 'application/json',
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);
}
يتيح لك عنصر GenerateContentConfig
أيضًا إلغاء مَعلمات الإنشاء التلقائية، مثل
temperature.
from google import genai
from google.genai import types
client = genai.Client(api_key="GEMINI_API_KEY")
response = client.models.generate_content(
model="gemini-2.0-flash",
contents=["Explain how AI works"],
config=types.GenerateContentConfig(
max_output_tokens=500,
temperature=0.1
)
)
print(response.text)
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });
async function main() {
const response = await ai.models.generateContent({
model: "gemini-2.0-flash",
contents: "Explain how AI works",
config: {
maxOutputTokens: 500,
temperature: 0.1,
},
});
console.log(response.text);
}
await main();
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, _ := genai.NewClient(ctx, &genai.ClientConfig{
APIKey: os.Getenv("GEMINI_API_KEY"),
Backend: genai.BackendGeminiAPI,
})
temp := float32(0.9)
topP := float32(0.5)
topK := float32(20.0)
maxOutputTokens := int32(100)
config := &genai.GenerateContentConfig{
Temperature: &temp,
TopP: &topP,
TopK: &topK,
MaxOutputTokens: maxOutputTokens,
ResponseMIMEType: "application/json",
}
result, _ := client.Models.GenerateContent(
ctx,
"gemini-2.0-flash",
genai.Text("What is the average size of a swallow?"),
config,
)
fmt.Println(result.Text())
}
curl https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{
"contents": [
{
"parts": [
{
"text": "Explain how AI works"
}
]
}
],
"generationConfig": {
"stopSequences": [
"Title"
],
"temperature": 1.0,
"maxOutputTokens": 800,
"topP": 0.8,
"topK": 10
}
}'
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const generationConfig = {
temperature: 1,
topP: 0.95,
topK: 40,
maxOutputTokens: 8192,
responseMimeType: 'text/plain',
};
const payload = {
generationConfig,
contents: [
{
parts: [
{ text: 'Explain how AI works in a few words' },
],
},
],
};
const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=${apiKey}`;
const options = {
method: 'POST',
contentType: 'application/json',
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);
}
يُرجى الرجوع إلى GenerateContentConfig
في مرجع واجهة برمجة التطبيقات للحصول على قائمة كاملة بالمَعلمات القابلة للضبط و
أوصافها.
المدخلات المتعددة الوسائط
تتيح لك Gemini API إدخالات متعددة الوسائط، ما يتيح لك دمج النص مع ملفات الوسائط. يوضّح المثال التالي كيفية تقديم صورة:
from PIL import Image
from google import genai
client = genai.Client(api_key="GEMINI_API_KEY")
image = Image.open("/path/to/organ.png")
response = client.models.generate_content(
model="gemini-2.0-flash",
contents=[image, "Tell me about this instrument"]
)
print(response.text)
import {
GoogleGenAI,
createUserContent,
createPartFromUri,
} from "@google/genai";
const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });
async function main() {
const image = await ai.files.upload({
file: "/path/to/organ.png",
});
const response = await ai.models.generateContent({
model: "gemini-2.0-flash",
contents: [
createUserContent([
"Tell me about this instrument",
createPartFromUri(image.uri, image.mimeType),
]),
],
});
console.log(response.text);
}
await main();
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, _ := genai.NewClient(ctx, &genai.ClientConfig{
APIKey: os.Getenv("GEMINI_API_KEY"),
Backend: genai.BackendGeminiAPI,
})
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-2.0-flash",
contents,
nil,
)
fmt.Println(result.Text())
}
# 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 "$TEMP_B64")"
}
}
]
}
]
}
EOF
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY" \
-H 'Content-Type: application/json' \
-X POST \
-d "@$TEMP_JSON"
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const imageUrl = 'http://image/url';
const image = getImageData(imageUrl);
const payload = {
contents: [
{
parts: [
{ image },
{ text: 'Tell me about this instrument' },
],
},
],
};
const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=${apiKey}`;
const options = {
method: 'POST',
contentType: 'application/json',
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())
};
}
للاطّلاع على طرق بديلة لتقديم الصور ومعالجة الصور بشكل أكثر تقدمًا، يمكنك الاطّلاع على دليل فهم الصور. تتيح واجهة برمجة التطبيقات أيضًا إدخال مستند وفيديو وصوت وفهمها.
عرض الردود تدريجيًا
لا يعرض النموذج استجابة تلقائيًا إلا بعد اكتمال عملية الإنشاء بالكامل.
للحصول على تفاعلات أكثر سلاسة، استخدِم ميزة البث لتلقّي نُسخ GenerateContentResponse
بشكل تدريجي
أثناء إنشائها.
from google import genai
client = genai.Client(api_key="GEMINI_API_KEY")
response = client.models.generate_content_stream(
model="gemini-2.0-flash",
contents=["Explain how AI works"]
)
for chunk in response:
print(chunk.text, end="")
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });
async function main() {
const response = await ai.models.generateContentStream({
model: "gemini-2.0-flash",
contents: "Explain how AI works",
});
for await (const chunk of response) {
console.log(chunk.text);
}
}
await main();
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, _ := genai.NewClient(ctx, &genai.ClientConfig{
APIKey: os.Getenv("GEMINI_API_KEY"),
Backend: genai.BackendGeminiAPI,
})
stream := client.Models.GenerateContentStream(
ctx,
"gemini-2.0-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)
}
}
curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:streamGenerateContent?alt=sse&key=${GEMINI_API_KEY}" \
-H 'Content-Type: application/json' \
--no-buffer \
-d '{
"contents": [
{
"parts": [
{
"text": "Explain how AI works"
}
]
}
]
}'
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const payload = {
contents: [
{
parts: [
{ text: 'Explain how AI works' },
],
},
],
};
const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:streamGenerateContent?key=${apiKey}`;
const options = {
method: 'POST',
contentType: 'application/json',
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);
}
المحادثات المتعدّدة المقاطع (Chat)
توفّر حِزم تطوير البرامج (SDK) لدينا وظائف لجمع جولات متعدّدة من الطلبات والمناقشات في محادثة، ما يمنحك طريقة سهلة لتتبُّع سجلّ المحادثة.
from google import genai
client = genai.Client(api_key="GEMINI_API_KEY")
chat = client.chats.create(model="gemini-2.0-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)
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });
async function main() {
const chat = ai.chats.create({
model: "gemini-2.0-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();
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, _ := genai.NewClient(ctx, &genai.ClientConfig{
APIKey: os.Getenv("GEMINI_API_KEY"),
Backend: genai.BackendGeminiAPI,
})
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-2.0-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)
}
}
curl https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello"
}
]
},
{
"role": "model",
"parts": [
{
"text": "Great to meet you. What would you like to know?"
}
]
},
{
"role": "user",
"parts": [
{
"text": "I have two dogs in my house. How many paws are in my house?"
}
]
}
]
}'
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const payload = {
contents: [
{
role: 'user',
parts: [
{ text: 'Hello' },
],
},
{
role: 'model',
parts: [
{ text: 'Great to meet you. What would you like to know?' },
],
},
{
role: 'user',
parts: [
{ text: 'I have two dogs in my house. How many paws are in my house?' },
],
},
],
};
const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=${apiKey}`;
const options = {
method: 'POST',
contentType: 'application/json',
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);
}
يمكن أيضًا استخدام البث للمحادثات التي تتضمّن عدّة أدوار.
from google import genai
client = genai.Client(api_key="GEMINI_API_KEY")
chat = client.chats.create(model="gemini-2.0-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)
import { GoogleGenAI } from "@google/genai";
const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });
async function main() {
const chat = ai.chats.create({
model: "gemini-2.0-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();
package main
import (
"context"
"fmt"
"os"
"google.golang.org/genai"
)
func main() {
ctx := context.Background()
client, _ := genai.NewClient(ctx, &genai.ClientConfig{
APIKey: os.Getenv("GEMINI_API_KEY"),
Backend: genai.BackendGeminiAPI,
})
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-2.0-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)
}
}
curl https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:streamGenerateContent?alt=sse&key=$GEMINI_API_KEY \
-H 'Content-Type: application/json' \
-X POST \
-d '{
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello"
}
]
},
{
"role": "model",
"parts": [
{
"text": "Great to meet you. What would you like to know?"
}
]
},
{
"role": "user",
"parts": [
{
"text": "I have two dogs in my house. How many paws are in my house?"
}
]
}
]
}'
// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');
function main() {
const payload = {
contents: [
{
role: 'user',
parts: [
{ text: 'Hello' },
],
},
{
role: 'model',
parts: [
{ text: 'Great to meet you. What would you like to know?' },
],
},
{
role: 'user',
parts: [
{ text: 'I have two dogs in my house. How many paws are in my house?' },
],
},
],
};
const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:streamGenerateContent?key=${apiKey}`;
const options = {
method: 'POST',
contentType: 'application/json',
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);
}
النماذج المتوافقة
تتيح جميع النماذج في عائلة Gemini إنشاء النصوص. للاطّلاع على مزيد من المعلومات عن النماذج وإمكاناتها، يُرجى الانتقال إلى صفحة النماذج.
أفضل الممارسات
نصائح حول صياغة الطلبات
بالنسبة إلى إنشاء النصوص الأساسية، غالبًا ما يكفي طلب بدون تدريب بدون الحاجة إلى أمثلة أو تعليمات النظام أو تنسيق محدّد.
للحصول على نتائج أكثر تخصيصًا:
- استخدِم تعليمات النظام لتوجيه النموذج.
- قدِّم بعض الأمثلة على المدخلات والنواتج لتوجيه النموذج. يُشار إلى ذلك غالبًا باسم طلبات قليلة.
- ننصحك بإجراء تحسينات دقيقة لحالات الاستخدام المتقدّمة.
يمكنك الرجوع إلى دليل الهندسة المتعلّقة بالطلبات للحصول على مزيد من النصائح.
الإخراج المنظَّم
في بعض الحالات، قد تحتاج إلى إخراج منظَّم، مثل تنسيق JSON. يُرجى الرجوع إلى دليل النتائج من الموقع الإلكتروني لمعرفة كيفية إجراء ذلك.
الخطوات التالية
- جرِّب البدء باستخدام Gemini API في Colab.
- استكشِف إمكانات فهم الصور، الفيديوهات، الصوت والمستندات في Gemini.
- اطّلِع على معلومات عن استراتيجيات طلب الملفات باستخدام الوسائط المتعددة.