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画像生成
Text-to-Image API リファレンス
Nano Banana 2 Lite の text-to-image API リファレンスとインタラクティブなプレイグラウンド — text prompt から画像を生成します
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
}
}右側のインタラクティブな Playground では、パラメータ(アスペクト比、レスポンス形式など)をドロップダウンで選択できます。Authorization フィールドに API Key を入力し(形式:
Bearer sk-xxx)、ワンクリックでテストリクエストを送信できます。適用範囲: このページは テキストから画像生成 用です。prompt を入力するだけでよく、画像のアップロードは不要です。既存の画像を編集する場合は、Image Editing endpoint を使用してください。
🖥️ ブラウザ Playground の制限(重要)この endpoint は、レスポンス内で base64 エンコードされた画像(
inlineData.data、通常は数 MB)を返します。ブラウザのレンダリング制限により、右側の Playground ではレスポンス到着後に 请求时发生错误: unable to complete request と表示されることがありますが、リクエスト自体は実際には成功しています。ブラウザがそのような長い base64 文字列をレンダリングできないだけです。推奨ワークフロー(初心者向け):- 下の Python / Node.js / cURL サンプルをコピーしてローカルで実行してください。コードはレスポンスを自動的に
base64.b64decodesし、画像をファイルに書き込みます。 - Nano Banana 2 Lite は 1K キャンバスに最適化されているため、レスポンスサイズは比較的控えめですが、それでも画像を保存するにはローカル実行が最も安全です。
すべての image API は 同期式 です。ポーリングするタスク ID はなく、クライアントが切断されると、リクエストがまだ課金対象のままであっても結果は失われます。このモデルでは十分に長いタイムアウトを設定してください。Image API Essentials & Best Practices を参照してください。
コード例
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 互換モード
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)
パラメータのクイックリファレンス
| パラメータ | 型 | 必須 | 説明 |
|---|---|---|---|
contents[].parts[].text | 文字列 | はい | テキストプロンプト |
generationConfig.responseModalities | 配列 | はい | ["IMAGE"] または ["TEXT","IMAGE"] |
generationConfig.imageConfig.aspectRatio | 文字列 | いいえ | 14種類のアスペクト比、デフォルトは 1:1 |
generationConfig.imageConfig.imageSize | 文字列 | いいえ | 1K のみ(Liteは1Kキャンバスに重点を置いています) |
詳細なパラメータドキュメント、使用可能な値、デフォルトは右側のプレイグラウンドのフィールド説明をご覧ください。列挙型のすべてのフィールド(
aspectRatio など)はドロップダウン選択に対応しており、手動入力は不要です。Nano Banana 2 からの移行: モデル名を
gemini-3.1-flash-imageからgemini-3.1-flash-lite-imageに変更するだけで、他のパラメータは変更しないでください。Liteは1K のみをサポートしています。2K/4K を渡す場合は、1K に戻してください。承認
API Key obtained from the APIYI console
ボディ
application/json
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