Image Editing API リファレンス

Image Editing: Edit an existing image with text instructions

curl --request POST \
  --url https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview:generateContent \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "contents": [
    {
      "parts": [
        {
          "text": "Combine the people from these two images into one office scene, making funny faces"
        },
        {
          "inlineData": {
            "mimeType": "image/png",
            "data": "<BASE64_DATA_IMG_1>"
          }
        },
        {
          "inlineData": {
            "mimeType": "image/png",
            "data": "<BASE64_DATA_IMG_2>"
          }
        }
      ]
    }
  ],
  "generationConfig": {
    "responseModalities": [
      "IMAGE"
    ],
    "imageConfig": {
      "aspectRatio": "16:9",
      "imageSize": "2K"
    }
  }
}
'

import requests

url = "https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview:generateContent"

payload = {
    "contents": [{ "parts": [{ "text": "Combine the people from these two images into one office scene, making funny faces" }, { "inlineData": {
                        "mimeType": "image/png",
                        "data": "<BASE64_DATA_IMG_1>"
                    } }, { "inlineData": {
                        "mimeType": "image/png",
                        "data": "<BASE64_DATA_IMG_2>"
                    } }] }],
    "generationConfig": {
        "responseModalities": ["IMAGE"],
        "imageConfig": {
            "aspectRatio": "16:9",
            "imageSize": "2K"
        }
    }
}
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: 'Combine the people from these two images into one office scene, making funny faces'
          },
          {inlineData: {mimeType: 'image/png', data: '<BASE64_DATA_IMG_1>'}},
          {inlineData: {mimeType: 'image/png', data: '<BASE64_DATA_IMG_2>'}}
        ]
      }
    ],
    generationConfig: {
      responseModalities: ['IMAGE'],
      imageConfig: {aspectRatio: '16:9', imageSize: '2K'}
    }
  })
};

fetch('https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview: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-pro-image-preview: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' => 'Combine the people from these two images into one office scene, making funny faces'
                                ],
                                [
                                                                'inlineData' => [
                                                                                                                                'mimeType' => 'image/png',
                                                                                                                                'data' => '<BASE64_DATA_IMG_1>'
                                                                ]
                                ],
                                [
                                                                'inlineData' => [
                                                                                                                                'mimeType' => 'image/png',
                                                                                                                                'data' => '<BASE64_DATA_IMG_2>'
                                                                ]
                                ]
                ]
        ]
    ],
    'generationConfig' => [
        'responseModalities' => [
                'IMAGE'
        ],
        'imageConfig' => [
                'aspectRatio' => '16:9',
                'imageSize' => '2K'
        ]
    ]
  ]),
  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-pro-image-preview:generateContent"

	payload := strings.NewReader("{\n  \"contents\": [\n    {\n      \"parts\": [\n        {\n          \"text\": \"Combine the people from these two images into one office scene, making funny faces\"\n        },\n        {\n          \"inlineData\": {\n            \"mimeType\": \"image/png\",\n            \"data\": \"<BASE64_DATA_IMG_1>\"\n          }\n        },\n        {\n          \"inlineData\": {\n            \"mimeType\": \"image/png\",\n            \"data\": \"<BASE64_DATA_IMG_2>\"\n          }\n        }\n      ]\n    }\n  ],\n  \"generationConfig\": {\n    \"responseModalities\": [\n      \"IMAGE\"\n    ],\n    \"imageConfig\": {\n      \"aspectRatio\": \"16:9\",\n      \"imageSize\": \"2K\"\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-pro-image-preview:generateContent")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"contents\": [\n    {\n      \"parts\": [\n        {\n          \"text\": \"Combine the people from these two images into one office scene, making funny faces\"\n        },\n        {\n          \"inlineData\": {\n            \"mimeType\": \"image/png\",\n            \"data\": \"<BASE64_DATA_IMG_1>\"\n          }\n        },\n        {\n          \"inlineData\": {\n            \"mimeType\": \"image/png\",\n            \"data\": \"<BASE64_DATA_IMG_2>\"\n          }\n        }\n      ]\n    }\n  ],\n  \"generationConfig\": {\n    \"responseModalities\": [\n      \"IMAGE\"\n    ],\n    \"imageConfig\": {\n      \"aspectRatio\": \"16:9\",\n      \"imageSize\": \"2K\"\n    }\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview: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\": \"Combine the people from these two images into one office scene, making funny faces\"\n        },\n        {\n          \"inlineData\": {\n            \"mimeType\": \"image/png\",\n            \"data\": \"<BASE64_DATA_IMG_1>\"\n          }\n        },\n        {\n          \"inlineData\": {\n            \"mimeType\": \"image/png\",\n            \"data\": \"<BASE64_DATA_IMG_2>\"\n          }\n        }\n      ]\n    }\n  ],\n  \"generationConfig\": {\n    \"responseModalities\": [\n      \"IMAGE\"\n    ],\n    \"imageConfig\": {\n      \"aspectRatio\": \"16:9\",\n      \"imageSize\": \"2K\"\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
  }
}

POST

v1beta

models

gemini-3-pro-image-preview:generateContent

Image Editing: Edit an existing image with text instructions

curl --request POST \
  --url https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview:generateContent \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "contents": [
    {
      "parts": [
        {
          "text": "Combine the people from these two images into one office scene, making funny faces"
        },
        {
          "inlineData": {
            "mimeType": "image/png",
            "data": "<BASE64_DATA_IMG_1>"
          }
        },
        {
          "inlineData": {
            "mimeType": "image/png",
            "data": "<BASE64_DATA_IMG_2>"
          }
        }
      ]
    }
  ],
  "generationConfig": {
    "responseModalities": [
      "IMAGE"
    ],
    "imageConfig": {
      "aspectRatio": "16:9",
      "imageSize": "2K"
    }
  }
}
'

import requests

url = "https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview:generateContent"

payload = {
    "contents": [{ "parts": [{ "text": "Combine the people from these two images into one office scene, making funny faces" }, { "inlineData": {
                        "mimeType": "image/png",
                        "data": "<BASE64_DATA_IMG_1>"
                    } }, { "inlineData": {
                        "mimeType": "image/png",
                        "data": "<BASE64_DATA_IMG_2>"
                    } }] }],
    "generationConfig": {
        "responseModalities": ["IMAGE"],
        "imageConfig": {
            "aspectRatio": "16:9",
            "imageSize": "2K"
        }
    }
}
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: 'Combine the people from these two images into one office scene, making funny faces'
          },
          {inlineData: {mimeType: 'image/png', data: '<BASE64_DATA_IMG_1>'}},
          {inlineData: {mimeType: 'image/png', data: '<BASE64_DATA_IMG_2>'}}
        ]
      }
    ],
    generationConfig: {
      responseModalities: ['IMAGE'],
      imageConfig: {aspectRatio: '16:9', imageSize: '2K'}
    }
  })
};

fetch('https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview: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-pro-image-preview: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' => 'Combine the people from these two images into one office scene, making funny faces'
                                ],
                                [
                                                                'inlineData' => [
                                                                                                                                'mimeType' => 'image/png',
                                                                                                                                'data' => '<BASE64_DATA_IMG_1>'
                                                                ]
                                ],
                                [
                                                                'inlineData' => [
                                                                                                                                'mimeType' => 'image/png',
                                                                                                                                'data' => '<BASE64_DATA_IMG_2>'
                                                                ]
                                ]
                ]
        ]
    ],
    'generationConfig' => [
        'responseModalities' => [
                'IMAGE'
        ],
        'imageConfig' => [
                'aspectRatio' => '16:9',
                'imageSize' => '2K'
        ]
    ]
  ]),
  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-pro-image-preview:generateContent"

	payload := strings.NewReader("{\n  \"contents\": [\n    {\n      \"parts\": [\n        {\n          \"text\": \"Combine the people from these two images into one office scene, making funny faces\"\n        },\n        {\n          \"inlineData\": {\n            \"mimeType\": \"image/png\",\n            \"data\": \"<BASE64_DATA_IMG_1>\"\n          }\n        },\n        {\n          \"inlineData\": {\n            \"mimeType\": \"image/png\",\n            \"data\": \"<BASE64_DATA_IMG_2>\"\n          }\n        }\n      ]\n    }\n  ],\n  \"generationConfig\": {\n    \"responseModalities\": [\n      \"IMAGE\"\n    ],\n    \"imageConfig\": {\n      \"aspectRatio\": \"16:9\",\n      \"imageSize\": \"2K\"\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-pro-image-preview:generateContent")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"contents\": [\n    {\n      \"parts\": [\n        {\n          \"text\": \"Combine the people from these two images into one office scene, making funny faces\"\n        },\n        {\n          \"inlineData\": {\n            \"mimeType\": \"image/png\",\n            \"data\": \"<BASE64_DATA_IMG_1>\"\n          }\n        },\n        {\n          \"inlineData\": {\n            \"mimeType\": \"image/png\",\n            \"data\": \"<BASE64_DATA_IMG_2>\"\n          }\n        }\n      ]\n    }\n  ],\n  \"generationConfig\": {\n    \"responseModalities\": [\n      \"IMAGE\"\n    ],\n    \"imageConfig\": {\n      \"aspectRatio\": \"16:9\",\n      \"imageSize\": \"2K\"\n    }\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview: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\": \"Combine the people from these two images into one office scene, making funny faces\"\n        },\n        {\n          \"inlineData\": {\n            \"mimeType\": \"image/png\",\n            \"data\": \"<BASE64_DATA_IMG_1>\"\n          }\n        },\n        {\n          \"inlineData\": {\n            \"mimeType\": \"image/png\",\n            \"data\": \"<BASE64_DATA_IMG_2>\"\n          }\n        }\n      ]\n    }\n  ],\n  \"generationConfig\": {\n    \"responseModalities\": [\n      \"IMAGE\"\n    ],\n    \"imageConfig\": {\n      \"aspectRatio\": \"16:9\",\n      \"imageSize\": \"2K\"\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、パラメータをドロップダウンで選択できます。API Key を Authorization フィールド（形式: Bearer sk-xxx）に入力すると、ワンクリックでテストリクエストを送信できます。

範囲: このページは 画像編集 用です。編集指示に加えて、入力画像（base64エンコードされたもの）を提供する必要があります。テキストのみから新しい画像を生成するには、Text-to-Image エンドポイントを使用してください。

🖥️ ブラウザ Playground の制限（重要）このエンドポイントは、レスポンスで 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 が表示される場合があります — リクエスト自体は正常に成功しています。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。コードが自動で base64.b64decodes し、画像をファイルに書き出します。
どうしてもブラウザ内の Playground を使う必要がある場合は、小さな参照画像（< 50KB）を使用し、imageSize を最小の階層（例: 1K）に設定してください。

⚠️ parts 配列の構造（重要 — 複数画像編集ではここを読んでください）各 part は、text か inlineData のどちらか一方のみでなければなりません。両方を含めてはいけません。これは Google の公式な gemini-3-pro-image-preview 契約と一致します。正しい例: 1 つの text part（指示） + N 個の inlineData part（画像 1 枚につき 1 つ）:

"contents": [{
  "parts": [
    {"text": "Combine the people from these two images into one office scene"},
    {"inlineData": {"mimeType": "image/png", "data": "<BASE64_DATA_IMG_1>"}},
    {"inlineData": {"mimeType": "image/png", "data": "<BASE64_DATA_IMG_2>"}}
  ]
}]

誤った例（各 part に text と inlineData の両方が含まれている — 未定義動作を引き起こします）:

"contents": [{
  "parts": [
    {"inlineData": {...}, "text": "is this the prompt 1"},
    {"inlineData": {...}, "text": "is this the prompt 2"}
  ]
}]

inlineData.data フィールドについてこのエンドポイントは JSON 形式（multipart のファイルアップロードではありません）を使用するため、Playground からローカルファイルを直接選択することはできません。まず画像を Base64 文字列 に変換し、それを data 入力に貼り付ける必要があります。1 行コマンド: 変換 + クリップボードにコピー:

# macOS
base64 -i your-image.jpg | tr -d '\n' | pbcopy

# Linux
base64 -w0 your-image.jpg | xclip -selection clipboard

# Windows PowerShell
[Convert]::ToBase64String([IO.File]::ReadAllBytes("your-image.jpg")) | Set-Clipboard

実行後は、そのまま Cmd+V / Ctrl+V して Playground の data フィールドに貼り付けてください。また、mimeType を対応する image/jpeg または image/png に設定することも忘れないでください。推奨: ブラウザの遅延を避けるため、テストには小さな画像（200KB 未満）を使用してください。画像編集のテストを頻繁に行う場合は、代わりに下のコード例を使ってローカルで実行してください。

コード例

Python

import requests
import base64

API_KEY = "sk-your-api-key"

# Read the image to edit
with open("input.jpg", "rb") as f:
    image_b64 = base64.b64encode(f.read()).decode()

response = requests.post(
    "https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview:generateContent",
    headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
    json={
        "contents": [{
            "parts": [
                {"text": "Please blur the background to highlight the person in the foreground"},
                {"inlineData": {"mimeType": "image/jpeg", "data": image_b64}}
            ]
        }],
        "generationConfig": {
            "responseModalities": ["IMAGE"],
            "imageConfig": {"aspectRatio": "16:9", "imageSize": "2K"}
        }
    },
    timeout=300
).json()

img_data = response["candidates"][0]["content"]["parts"][0]["inlineData"]["data"]
with open("edited.png", 'wb') as f:
    f.write(base64.b64decode(img_data))
print("Edited image saved to edited.png")

Node.js

import fs from "fs";

const API_KEY = "sk-your-api-key";
const imageB64 = fs.readFileSync("input.jpg").toString("base64");

const response = await fetch(
  "https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview:generateContent",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${API_KEY}`,
      "Content-Type": "application/json"
    },
    body: JSON.stringify({
      contents: [{
        parts: [
          { text: "Please blur the background to highlight the person in the foreground" },
          { inlineData: { mimeType: "image/jpeg", data: imageB64 } }
        ]
      }],
      generationConfig: {
        responseModalities: ["IMAGE"],
        imageConfig: { aspectRatio: "16:9", imageSize: "2K" }
      }
    })
  }
);

const data = await response.json();
const imgBase64 = data.candidates[0].content.parts[0].inlineData.data;
fs.writeFileSync("edited.png", Buffer.from(imgBase64, "base64"));

cURL

# Note: convert image to base64 first
# IMAGE_B64=$(base64 -i input.jpg | tr -d '\n')

curl -X POST "https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview:generateContent" \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [
        {"text": "Please blur the background to highlight the person in the foreground"},
        {"inlineData": {"mimeType": "image/jpeg", "data": "'"$IMAGE_B64"'"}}
      ]
    }],
    "generationConfig": {
      "responseModalities": ["IMAGE"],
      "imageConfig": {"aspectRatio": "16:9", "imageSize": "2K"}
    }
  }'

複数画像編集

複数の入力画像を結合または比較する場合は、単一の text パート（指示）を使用し、その後に複数の inlineData パート（画像ごとに 1 つ）を続けます。

Python（複数画像）

import requests
import base64

API_KEY = "sk-your-api-key"

def to_b64(path):
    with open(path, "rb") as f:
        return base64.b64encode(f.read()).decode()

# Prepare multiple images (2 here as an example)
images = ["person1.png", "person2.png"]
parts = [{"text": "Combine the people from these images into one office scene, making funny faces"}]
for path in images:
    parts.append({"inlineData": {"mimeType": "image/png", "data": to_b64(path)}})

response = requests.post(
    "https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview:generateContent",
    headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
    json={
        "contents": [{"parts": parts}],
        "generationConfig": {
            "responseModalities": ["TEXT", "IMAGE"],
            "imageConfig": {"aspectRatio": "5:4", "imageSize": "2K"}
        }
    },
    timeout=300
).json()

img_data = response["candidates"][0]["content"]["parts"][0]["inlineData"]["data"]
with open("merged.png", "wb") as f:
    f.write(base64.b64decode(img_data))

cURL（複数画像、Google の公式形式に準拠）

curl -X POST "https://api.apiyi.com/v1beta/models/gemini-3-pro-image-preview:generateContent" \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [
        {"text": "An office group photo of these people, they are making funny faces."},
        {"inlineData": {"mimeType": "image/png", "data": "<BASE64_DATA_IMG_1>"}},
        {"inlineData": {"mimeType": "image/png", "data": "<BASE64_DATA_IMG_2>"}},
        {"inlineData": {"mimeType": "image/png", "data": "<BASE64_DATA_IMG_3>"}}
      ]
    }],
    "generationConfig": {
      "responseModalities": ["TEXT", "IMAGE"],
      "imageConfig": {"aspectRatio": "5:4", "imageSize": "2K"}
    }
  }'

パラメータ早見表

パラメータ	型	必須	説明
`contents[].parts`	array	はい	1つのテキスト部分 + N個の inlineData 部分で構成されます。各部分には `text` または `inlineData` のどちらか一方のみが含まれます — 両方は含まれません
`contents[].parts[].text`	string	はい	編集指示（最初の部分のみに入れてください）
`contents[].parts[].inlineData.mimeType`	string	はい	`image/jpeg` または `image/png`
`contents[].parts[].inlineData.data`	string	はい	Base64 エンコードされた画像（複数画像編集では、画像ごとに inlineData 部分を 1 つずつ繰り返します）
`generationConfig.responseModalities`	array	はい	通常は `["IMAGE"]`
`generationConfig.imageConfig.aspectRatio`	string	いいえ	10 個の比率、デフォルトは `1:1`
`generationConfig.imageConfig.imageSize`	string	いいえ	`1K` / `2K` / `4K`、デフォルトは `1K`

Nano Banana Pro はマルチ画像編集をサポートします。複数の画像を編集指示とともに入力でき、マルチ画像合成やスタイル転送のような高度な機能に対応しています。

承認

Authorization

string

header

必須

API Key from APIYI Console

ボディ

application/json

contents

object[]

必須

Content array with edit instructions and image to edit

Show child attributes

generationConfig

object

必須

Show child attributes

レスポンス

Image edited successfully

candidates

object[]

Generated results array

Show child attributes

usageMetadata

object

Show child attributes

テキストから画像への API リファレンス Nano Banana Pro エージェントスキル

基本

基本API

画像API（公式）

動画API（公式）

マルチモーダル理解API

テキストAPI

Image Editing API リファレンス

コード例

Python

Node.js

cURL

複数画像編集

Python（複数画像）

cURL（複数画像、Google の公式形式に準拠）

パラメータ早見表

承認

ボディ

レスポンス

​コード例

​Python

​Node.js

​cURL

​複数画像編集

​Python（複数画像）

​cURL（複数画像、Google の公式形式に準拠）

​パラメータ早見表

承認

ボディ

レスポンス

コード例

Python

Node.js

cURL

複数画像編集

Python（複数画像）

cURL（複数画像、Google の公式形式に準拠）

パラメータ早見表