Text-to-image: generate an image from a text description
curl --request POST \
--url https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"contents": [
{
"parts": [
{
"text": "A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail"
}
]
}
],
"generationConfig": {
"responseModalities": [
"IMAGE"
],
"imageConfig": {
"aspectRatio": "16:9",
"imageSize": "1K"
}
}
}
'import requests
url = "https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent"
payload = {
"contents": [{ "parts": [{ "text": "A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail" }] }],
"generationConfig": {
"responseModalities": ["IMAGE"],
"imageConfig": {
"aspectRatio": "16:9",
"imageSize": "1K"
}
}
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
contents: [
{
parts: [
{
text: 'A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail'
}
]
}
],
generationConfig: {
responseModalities: ['IMAGE'],
imageConfig: {aspectRatio: '16:9', imageSize: '1K'}
}
})
};
fetch('https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'contents' => [
[
'parts' => [
[
'text' => 'A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail'
]
]
]
],
'generationConfig' => [
'responseModalities' => [
'IMAGE'
],
'imageConfig' => [
'aspectRatio' => '16:9',
'imageSize' => '1K'
]
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent"
payload := strings.NewReader("{\n \"contents\": [\n {\n \"parts\": [\n {\n \"text\": \"A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail\"\n }\n ]\n }\n ],\n \"generationConfig\": {\n \"responseModalities\": [\n \"IMAGE\"\n ],\n \"imageConfig\": {\n \"aspectRatio\": \"16:9\",\n \"imageSize\": \"1K\"\n }\n }\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"contents\": [\n {\n \"parts\": [\n {\n \"text\": \"A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail\"\n }\n ]\n }\n ],\n \"generationConfig\": {\n \"responseModalities\": [\n \"IMAGE\"\n ],\n \"imageConfig\": {\n \"aspectRatio\": \"16:9\",\n \"imageSize\": \"1K\"\n }\n }\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"contents\": [\n {\n \"parts\": [\n {\n \"text\": \"A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail\"\n }\n ]\n }\n ],\n \"generationConfig\": {\n \"responseModalities\": [\n \"IMAGE\"\n ],\n \"imageConfig\": {\n \"aspectRatio\": \"16:9\",\n \"imageSize\": \"1K\"\n }\n }\n}"
response = http.request(request)
puts response.read_body{
"candidates": [
{
"content": {
"parts": [
{
"inlineData": {
"mimeType": "image/png",
"data": "<string>"
}
}
]
},
"finishReason": "STOP"
}
],
"usageMetadata": {
"promptTokenCount": 10,
"candidatesTokenCount": 258
}
}Nano Banana Lite 이미지 생성
텍스트-이미지 API 레퍼런스
Nano Banana 2 Lite 텍스트-이미지 API 레퍼런스 및 대화형 플레이그라운드 — 텍스트 prompt로 이미지를 생성합니다
POST
/
v1beta
/
models
/
gemini-3.1-flash-lite-image:generateContent
Text-to-image: generate an image from a text description
curl --request POST \
--url https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"contents": [
{
"parts": [
{
"text": "A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail"
}
]
}
],
"generationConfig": {
"responseModalities": [
"IMAGE"
],
"imageConfig": {
"aspectRatio": "16:9",
"imageSize": "1K"
}
}
}
'import requests
url = "https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent"
payload = {
"contents": [{ "parts": [{ "text": "A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail" }] }],
"generationConfig": {
"responseModalities": ["IMAGE"],
"imageConfig": {
"aspectRatio": "16:9",
"imageSize": "1K"
}
}
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
contents: [
{
parts: [
{
text: 'A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail'
}
]
}
],
generationConfig: {
responseModalities: ['IMAGE'],
imageConfig: {aspectRatio: '16:9', imageSize: '1K'}
}
})
};
fetch('https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'contents' => [
[
'parts' => [
[
'text' => 'A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail'
]
]
]
],
'generationConfig' => [
'responseModalities' => [
'IMAGE'
],
'imageConfig' => [
'aspectRatio' => '16:9',
'imageSize' => '1K'
]
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent"
payload := strings.NewReader("{\n \"contents\": [\n {\n \"parts\": [\n {\n \"text\": \"A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail\"\n }\n ]\n }\n ],\n \"generationConfig\": {\n \"responseModalities\": [\n \"IMAGE\"\n ],\n \"imageConfig\": {\n \"aspectRatio\": \"16:9\",\n \"imageSize\": \"1K\"\n }\n }\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"contents\": [\n {\n \"parts\": [\n {\n \"text\": \"A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail\"\n }\n ]\n }\n ],\n \"generationConfig\": {\n \"responseModalities\": [\n \"IMAGE\"\n ],\n \"imageConfig\": {\n \"aspectRatio\": \"16:9\",\n \"imageSize\": \"1K\"\n }\n }\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"contents\": [\n {\n \"parts\": [\n {\n \"text\": \"A cute Shiba Inu sitting under cherry blossoms, watercolor style, high detail\"\n }\n ]\n }\n ],\n \"generationConfig\": {\n \"responseModalities\": [\n \"IMAGE\"\n ],\n \"imageConfig\": {\n \"aspectRatio\": \"16:9\",\n \"imageSize\": \"1K\"\n }\n }\n}"
response = http.request(request)
puts response.read_body{
"candidates": [
{
"content": {
"parts": [
{
"inlineData": {
"mimeType": "image/png",
"data": "<string>"
}
}
]
},
"finishReason": "STOP"
}
],
"usageMetadata": {
"promptTokenCount": 10,
"candidatesTokenCount": 258
}
}오른쪽의 대화형 Playground는 매개변수(종횡비, 응답 유형 등)에 대한 드롭다운 선택을 지원합니다. 테스트 요청을 원클릭으로 보내려면 Authorization 필드에 API Key를 입력하십시오(형식:
Bearer sk-xxx).범위: 이 페이지는 text-to-image generation용입니다. prompt만 입력하면 되며, 이미지 업로드는 필요하지 않습니다. 기존 이미지를 편집하려면 Image Editing endpoint를 사용하십시오.
🖥️ 브라우저 Playground 제한(중요)이 endpoint는 응답에 base64로 인코딩된 이미지(
inlineData.data, 보통 수 MB)를 반환합니다. 브라우저 렌더링 제한 때문에 오른쪽 Playground는 응답이 도착한 뒤 请求时发生错误: unable to complete request로 표시될 수 있습니다 — 실제로 요청은 성공한 것입니다; 브라우저가 그렇게 긴 base64 문자열을 렌더링하지 못할 뿐입니다.권장 작업 흐름(초보자 친화적):- 아래 Python / Node.js / cURL 샘플을 복사해 로컬에서 실행하십시오. 코드는 응답을 자동으로
base64.b64decodes하고 이미지를 파일로 저장합니다. - Nano Banana 2 Lite는 1K 캔버스에 초점을 맞추고 있으므로 응답 크기는 중간 정도이지만, 이미지를 저장하려면 로컬에서 실행하는 것이 여전히 가장 안전합니다.
모든 image API는 동기식입니다 — 폴링할 task ID가 없으며, 클라이언트가 연결을 끊으면 요청은 계속 과금되는 동안 결과는 사라집니다. 이 모델에는 넉넉한 타임아웃을 설정하십시오. Image API Essentials & Best Practices를 참조하십시오.
코드 예제
Python
import requests
import base64
API_KEY = "sk-your-api-key"
PROMPT = "A cute Shiba Inu sitting under cherry blossom trees, watercolor style, HD details"
response = requests.post(
"https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent",
headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
json={
"contents": [{"parts": [{"text": PROMPT}]}],
"generationConfig": {
"responseModalities": ["IMAGE"],
"imageConfig": {"aspectRatio": "16:9", "imageSize": "1K"}
}
},
timeout=300
).json()
img_data = response["candidates"][0]["content"]["parts"][0]["inlineData"]["data"]
with open("output.png", 'wb') as f:
f.write(base64.b64decode(img_data))
print("Image saved to output.png")
cURL
curl -X POST "https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent" \
-H "Authorization: Bearer sk-your-api-key" \
-H "Content-Type: application/json" \
-d '{
"contents": [{"parts": [{"text": "Futuristic city night view, neon lights, cyberpunk style"}]}],
"generationConfig": {
"responseModalities": ["IMAGE"],
"imageConfig": {"aspectRatio": "16:9", "imageSize": "1K"}
}
}'
Node.js
import fs from "fs";
const API_KEY = "sk-your-api-key";
const response = await fetch(
"https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent",
{
method: "POST",
headers: {
"Authorization": `Bearer ${API_KEY}`,
"Content-Type": "application/json"
},
body: JSON.stringify({
contents: [{ parts: [{ text: "Futuristic city night view, neon lights, cyberpunk style" }] }],
generationConfig: {
responseModalities: ["IMAGE"],
imageConfig: { aspectRatio: "16:9", imageSize: "1K" }
}
})
}
);
const data = await response.json();
const imgBase64 = data.candidates[0].content.parts[0].inlineData.data;
fs.writeFileSync("output.png", Buffer.from(imgBase64, "base64"));
OpenAI 호환 모드
from openai import OpenAI
client = OpenAI(api_key="sk-your-api-key", base_url="https://api.apiyi.com/v1")
response = client.chat.completions.create(
model="gemini-3.1-flash-lite-image",
stream=False,
messages=[{"role": "user", "content": "An autumn landscape painting with red leaves and birds in the distance"}]
)
print(response.choices[0].message.content)
파라미터 빠른 참조
| 파라미터 | 유형 | 필수 | 설명 |
|---|---|---|---|
contents[].parts[].text | string | 예 | 텍스트 prompt |
generationConfig.responseModalities | array | 예 | ["IMAGE"] 또는 ["TEXT","IMAGE"] |
generationConfig.imageConfig.aspectRatio | string | 아니요 | 14개 화면비, 기본값 1:1 |
generationConfig.imageConfig.imageSize | string | 아니요 | 1K 전용(Lite는 1K 캔버스에 초점을 맞춥니다) |
자세한 파라미터 문서, 허용 값, 기본값은 오른쪽 플레이그라운드의 필드 설명을 참고하십시오.
aspectRatio와 같은 모든 enum 유형 필드는 드롭다운 선택을 지원하므로 수동 입력이 필요하지 않습니다.Nano Banana 2에서 마이그레이션하는 경우: 모델 이름을
gemini-3.1-flash-image에서 gemini-3.1-flash-lite-image으로만 변경하고, 다른 파라미터는 그대로 유지하십시오. Lite는 1K만 지원하므로 2K/4K를 전달하는 경우 1K로 다시 전환하십시오.인증
API Key obtained from the APIYI console
본문
application/json
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