Image Editing API Reference

Nano Banana 2 Lite image editing API reference and interactive playground — provide an image + instruction to generate an edited result

POST /v1beta/models/gemini-3.1-flash-lite-image:generateContent

Image editing: edit an existing image per instructions

cURL

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": "Composite the people from these two images into the same 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": "1K"
    }
  }
}
'

import requests

url = "https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent"

payload = {
    "contents": [{ "parts": [{ "text": "Composite the people from these two images into the same 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": "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: 'Composite the people from these two images into the same 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: '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' => 'Composite the people from these two images into the same 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' => '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\": \"Composite the people from these two images into the same 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\": \"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\": \"Composite the people from these two images into the same 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\": \"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\": \"Composite the people from these two images into the same 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\": \"1K\"\n    }\n  }\n}"

response = http.request(request)
puts response.read_body

200

{
  "candidates": [
    {
      "content": {
        "parts": [
          {
            "inlineData": {
              "mimeType": "image/png",
              "data": "<string>"
            }
          }
        ]
      },
      "finishReason": "STOP"
    }
  ],
  "usageMetadata": {
    "promptTokenCount": 10,
    "candidatesTokenCount": 258
  }
}

The interactive Playground on the right supports dropdown selection for parameters. Enter your API Key in the Authorization field (format: Bearer sk-xxx) to send test requests with one click.

Scope: This page is for image editing. You must provide an input image (base64-encoded) along with edit instructions. To generate a new image from text only, use the Text-to-Image endpoint.

🖥️ Browser Playground limitation (important)

This endpoint returns a base64-encoded image (inlineData.data, typically several MB) in the response. Due to browser rendering limits, the Playground on the right may show 请求时发生错误: unable to complete request after the response arrives — the request actually succeeded; the browser just can’t render such a long base64 string.

Recommended workflow (beginner-friendly):

• Copy the Python / Node.js / cURL sample below and run it locally. The code automatically base64.b64decodes the response and writes the image to a file.
• If you must use the in-browser Playground, use a tiny reference image (less than 50KB) to shrink the response.

⚠️ parts array structure (important — read this for multi-image edits)

Each part must be either a text or an inlineData, never both. This matches Google’s official gemini-3.1-flash-lite-image contract.

Correct: one text part (the instruction) + N inlineData parts (one per image):

"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>"}}
  ]
}]

Incorrect (each part contains both text and inlineData — produces undefined behavior):

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

🖼️ About the inlineData.data field

This endpoint uses JSON format (not multipart file upload), so the Playground cannot directly select local files. You need to convert your image to a Base64 string first, then paste it into the data input.

One-line command: convert + copy to clipboard:

# 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

After running, just Cmd+V / Ctrl+V paste into the data field in the Playground. Also remember to set mimeType to the matching image/jpeg or image/png.

Recommendation: Use small images (less than 200KB) for testing to avoid browser lag from long base64 strings. For frequent image editing tests, use the code examples below to run locally instead.

Code Examples

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-3.1-flash-lite-image: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": "1K"}
        }
    },
    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-3.1-flash-lite-image: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: "1K" }
      }
    })
  }
);

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-3.1-flash-lite-image: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": "1K"}
    }
  }'

Multi-Image Editing

When merging or comparing several input images, use a single text part (the instruction) followed by multiple inlineData parts (one per image).

Python (multi-image)

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-3.1-flash-lite-image:generateContent",
    headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
    json={
        "contents": [{"parts": parts}],
        "generationConfig": {
            "responseModalities": ["TEXT", "IMAGE"],
            "imageConfig": {"aspectRatio": "5:4", "imageSize": "1K"}
        }
    },
    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))

Parameter Quick Reference

Parameter	Type	Required	Description
contents[].parts	array	Yes	Composed of 1 text part + N inlineData parts. Each part contains either text or inlineData — never both
contents[].parts[].text	string	Yes	Edit instruction (place it in the first part only)
contents[].parts[].inlineData.mimeType	string	Yes	image/jpeg or image/png
contents[].parts[].inlineData.data	string	Yes	Base64-encoded image (repeat one inlineData part per image for multi-image edits)
generationConfig.responseModalities	array	Yes	Usually ["IMAGE"]
generationConfig.imageConfig.aspectRatio	string	No	14 ratios, default 1:1
generationConfig.imageConfig.imageSize	string	No	1K only (Lite is focused on the 1K canvas)

Multi-turn conversational editing

Nano Banana 2 Lite (gemini-3.1-flash-lite-image) supports conversational multi-turn editing: append each turn’s generated image back into contents as a role: "model" inlineData, then send the next user instruction. The model edits based on the full conversation history and accumulates changes (e.g. first recolor the sofa, then add an accessory — the earlier change is preserved).

import requests, base64

API_KEY = "sk-your-api-key"
URL = "https://api.apiyi.com/v1beta/models/gemini-3.1-flash-lite-image:generateContent"
H = {"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"}
CFG = {"responseModalities": ["IMAGE"], "imageConfig": {"aspectRatio": "1:1", "imageSize": "1K"}}

contents = []  # keep one running conversation history

def turn(instruction, save_to):
    contents.append({"role": "user", "parts": [{"text": instruction}]})
    data = requests.post(URL, headers=H,
                         json={"contents": contents, "generationConfig": CFG}, timeout=300).json()
    part = next(p for p in data["candidates"][0]["content"]["parts"] if "inlineData" in p)
    contents.append({"role": "model", "parts": [part]})   # key: backfill the output image into history
    with open(save_to, "wb") as f:
        f.write(base64.b64decode(part["inlineData"]["data"]))
    return part

turn("Generate an orange cat sitting on a blue sofa, simple line-art style", "step1.png")
turn("Make the sofa red; keep the cat and composition unchanged", "step2.png")   # edits the previous image
turn("Put a small yellow hat on the cat; keep everything else the same", "step3.png")  # accumulates; red sofa kept

Start multi-turn from an existing image: put an inlineData (your own image) plus an instruction in the first user message to edit an existing photo, then keep backfilling the model output into contents each turn.

Authorizations

Authorization · string · header · required

API Key obtained from the APIYI console

Body

application/json

contents · object[] · required

Content array containing the edit instruction and the image(s) to edit

Show child attributes

generationConfig · object · required

Show child attributes

Response

200

application/json

Image generated successfully

candidates · object[]

Array of generation results

Show child attributes

usageMetadata · object

Show child attributes