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POST
/
v1beta
/
models
/
gemini-3.1-flash-image-preview:generateContent
Image Editing: Edit an existing image with text instructions
curl --request POST \
  --url https://api.apiyi.com/v1beta/models/gemini-3.1-flash-image-preview:generateContent \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "contents": [
    {
      "parts": [
        {
          "text": "Please blur the background to highlight the person in the foreground"
        },
        {
          "inlineData": {
            "mimeType": "image/jpeg",
            "data": "BASE64_ENCODED_IMAGE_DATA"
          }
        }
      ]
    }
  ],
  "generationConfig": {
    "responseModalities": [
      "IMAGE"
    ],
    "imageConfig": {
      "aspectRatio": "16:9",
      "imageSize": "2K"
    }
  }
}
'
{
  "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.
🖼️ About the inlineData.data fieldThis 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 (< 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-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-3.1-flash-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"));

​
Parameter Quick Reference

ParameterTypeRequiredDescription
contents[].parts[].textstringYesEdit instruction
contents[].parts[].inlineData.mimeTypestringYesimage/jpeg or image/png
contents[].parts[].inlineData.datastringYesBase64-encoded image
generationConfig.responseModalitiesarrayYesUsually ["IMAGE"]
generationConfig.imageConfig.aspectRatiostringNo14 ratios, default 1:1
generationConfig.imageConfig.imageSizestringNo512 / 1K / 2K / 4K, default 1K
Nano Banana 2 supports multi-turn conversational editing: feed the previous output image as the next inlineData input along with a new edit instruction to iteratively refine the result.

Authorizations

​
Authorization
string
header
required

API Key obtained from APIYI Console

Body

application/json
​
contents
object[]
required

Content array containing edit instructions and the image to edit

​
generationConfig
object
required

Response

Successfully edited image

​
candidates
object[]

Generation results array

​
usageMetadata
object