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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": "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
  }
}

Documentation Index

Fetch the complete documentation index at: https://docs.apiyi.com/llms.txt

Use this file to discover all available pages before exploring further.

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 (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-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"}
    }
  }'

​
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.aspectRatiostringNo10 ratios, default 1:1
generationConfig.imageConfig.imageSizestringNo1K / 2K / 4K, default 1K
Nano Banana Pro supports multi-image editing: you can input multiple images along with edit instructions for advanced features like multi-image composition and style transfer.

Authorizations

​
Authorization
string
header
required

API Key from APIYI Console

Body

application/json
​
contents
object[]
required

Content array with edit instructions and image to edit

​
generationConfig
object
required

Response

Image edited successfully

​
candidates
object[]

Generated results array

​
usageMetadata
object