apps/google/gemini-3-1-flash-image

gemini-3-1-flash-image

Gemini 3.1 Flash Image (NanoBanana 2) via Vertex AI - Advanced image generation model powered by Google Cloud

run in browser run via API

run with your agent

# install belt

$curl -fsSL https://cli.inference.sh | sh

# view schema & details

$belt app get google/gemini-3-1-flash-image

# run

$belt app run google/gemini-3-1-flash-image

api reference

about

gemini 3.1 flash image (nanobanana 2) via vertex ai - advanced image generation model powered by google cloud

1. calling the api

install the client

the client provides a convenient way to interact with the api.

bash

1pip install inferencesh

setup your api key

set INFERENCE_API_KEY as an environment variable. get your key from settings → api keys.

bash

1export INFERENCE_API_KEY="inf_your_key"

run and get result

submit a request and wait for the final result. best for batch processing or when you don't need progress updates.

python

1from inferencesh import inference23client = inference()456result = client.run({7        "app": "google/gemini-3-1-flash-image",8        "input": {}9    })1011print(result["output"])

stream live updates

get real-time progress updates as the task runs. ideal for showing progress bars, partial results, or long-running tasks.

python

1from inferencesh import inference23client = inference()456# stream=True yields updates as they arrive7for update in client.run({8        "app": "google/gemini-3-1-flash-image",9        "input": {}10    }, stream=True):11    if update.get("progress"):12        print(f"progress: {update['progress']}%")13    if update.get("output"):14        print(f"output: {update['output']}")

2. authentication

the api uses api keys for authentication. see the authentication docs for detailed setup instructions.

3. files

file inputs are automatically handled by the sdk. you can pass local paths, urls, or base64 data.

automatic upload

the python sdk automatically detects local file paths and uploads them. urls are passed through as-is.

python

1# local file paths are automatically uploaded2result = client.run({3    "app": "google/gemini-3-1-flash-image",4    "input": {5        "image": "/path/to/local/image.png",  # detected & uploaded6        "audio": "https://example.com/audio.mp3",  # url passed through7    }8})

manual upload

you can also upload files manually and use the returned url.

python

1# upload and get a hosted URL2file = client.files.upload("/path/to/file.png")3print(file.uri)  # https://cloud.inference.sh/...

4. webhooks

get notified when a task completes by providing a webhook url. when the task reaches a terminal state (completed, failed, or cancelled), a POST request is sent to your url with the task result.

python

1result = client.run({2    "app": "google/gemini-3-1-flash-image",3    "input": {},4    "webhook": "https://your-server.com/webhook"5}, wait=False)

webhook payload

your endpoint receives a JSON POST with the task result:

json

1{2  "id": "task_abc123",3  "status": 9,4  "output": { ... },5  "error": "",6  "session_id": null,7  "created_at": "2024-01-15T10:30:00Z",8  "updated_at": "2024-01-15T10:30:05Z"9}

idstring— task id

statusnumber— terminal status (9=completed, 10=failed, 11=cancelled)

outputobject— task output (when completed)

errorstring— error message (when failed)

session_idstring— session id (if using sessions)

created_atstring— iso timestamp

updated_atstring— iso timestamp

5. schema

input

promptstring*

the prompt for image generation or editing. describe what you want to create or change.

imagesarray

optional list of input images for editing (up to 14 images). when provided, the model will edit these images based on the prompt. when not provided, the model will generate new images from the text prompt. supported formats: jpeg, png, webp

num_imagesinteger

number of images to generate.

default: 1min:1max:4

aspect_ratiostring

aspect ratio for the output image. supports extreme ratios like 1:4, 4:1, 1:8, 8:1. use 'auto' to automatically match the first input image's aspect ratio. default: 1:1

default: "1:1"

options:"auto""21:9""16:9""8:1""4:1""3:2""4:3""5:4""1:1""4:5""3:4""2:3""1:4""1:8""9:16"

resolutionstring

output resolution. options: 1k, 2k, 4k. default: 1k

default: "1K"

options:"512""1K""2K""4K"

output_formatstring

output format for the generated images.

default: "png"

options:"png""jpeg""webp"

enable_google_searchboolean

enable google search grounding for real-time information (weather, news, etc.)

default: false

safety_tolerancestring

safety filter threshold. options: block_none, block_low_and_above, block_medium_and_above, block_only_high

default: "BLOCK_NONE"

options:"BLOCK_NONE""BLOCK_LOW_AND_ABOVE""BLOCK_MEDIUM_AND_ABOVE""BLOCK_ONLY_HIGH"

retry_countinteger

number of automatic retries on 429 rate limit errors using exponential backoff with jitter. set to 0 to disable retries. example: retry_count=2 means up to 3 total attempts (1 initial + 2 retries).

default: 2min:0max:5

output

descriptionstring

text description or response from the model

imagesarray*

the generated or edited images

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