Transform images (img2img)

Transform reference images with a prompt (img2img)

curl --request POST \
  --url https://api.samsa.ai/public/v1/images/img2img \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "images": [
    {
      "image_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
      "url": "https://cdn.example.com/photo.png",
      "base64": "<string>",
      "mime_type": "image/png"
    }
  ],
  "prompt": "<string>",
  "engine": "nano_banana_pro",
  "aspect_ratio": "1:1",
  "resolution": "1K",
  "num_outputs": 1,
  "output_format": "png",
  "webhook_url": "https://example.com/webhooks/samsa"
}
'

import requests

url = "https://api.samsa.ai/public/v1/images/img2img"

payload = {
    "images": [
        {
            "image_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
            "url": "https://cdn.example.com/photo.png",
            "base64": "<string>",
            "mime_type": "image/png"
        }
    ],
    "prompt": "<string>",
    "engine": "nano_banana_pro",
    "aspect_ratio": "1:1",
    "resolution": "1K",
    "num_outputs": 1,
    "output_format": "png",
    "webhook_url": "https://example.com/webhooks/samsa"
}
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({
    images: [
      {
        image_id: '3c90c3cc-0d44-4b50-8888-8dd25736052a',
        url: 'https://cdn.example.com/photo.png',
        base64: '<string>',
        mime_type: 'image/png'
      }
    ],
    prompt: '<string>',
    engine: 'nano_banana_pro',
    aspect_ratio: '1:1',
    resolution: '1K',
    num_outputs: 1,
    output_format: 'png',
    webhook_url: 'https://example.com/webhooks/samsa'
  })
};

fetch('https://api.samsa.ai/public/v1/images/img2img', 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.samsa.ai/public/v1/images/img2img",
  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([
    'images' => [
        [
                'image_id' => '3c90c3cc-0d44-4b50-8888-8dd25736052a',
                'url' => 'https://cdn.example.com/photo.png',
                'base64' => '<string>',
                'mime_type' => 'image/png'
        ]
    ],
    'prompt' => '<string>',
    'engine' => 'nano_banana_pro',
    'aspect_ratio' => '1:1',
    'resolution' => '1K',
    'num_outputs' => 1,
    'output_format' => 'png',
    'webhook_url' => 'https://example.com/webhooks/samsa'
  ]),
  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.samsa.ai/public/v1/images/img2img"

	payload := strings.NewReader("{\n  \"images\": [\n    {\n      \"image_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n      \"url\": \"https://cdn.example.com/photo.png\",\n      \"base64\": \"<string>\",\n      \"mime_type\": \"image/png\"\n    }\n  ],\n  \"prompt\": \"<string>\",\n  \"engine\": \"nano_banana_pro\",\n  \"aspect_ratio\": \"1:1\",\n  \"resolution\": \"1K\",\n  \"num_outputs\": 1,\n  \"output_format\": \"png\",\n  \"webhook_url\": \"https://example.com/webhooks/samsa\"\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.samsa.ai/public/v1/images/img2img")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"images\": [\n    {\n      \"image_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n      \"url\": \"https://cdn.example.com/photo.png\",\n      \"base64\": \"<string>\",\n      \"mime_type\": \"image/png\"\n    }\n  ],\n  \"prompt\": \"<string>\",\n  \"engine\": \"nano_banana_pro\",\n  \"aspect_ratio\": \"1:1\",\n  \"resolution\": \"1K\",\n  \"num_outputs\": 1,\n  \"output_format\": \"png\",\n  \"webhook_url\": \"https://example.com/webhooks/samsa\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.samsa.ai/public/v1/images/img2img")

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  \"images\": [\n    {\n      \"image_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n      \"url\": \"https://cdn.example.com/photo.png\",\n      \"base64\": \"<string>\",\n      \"mime_type\": \"image/png\"\n    }\n  ],\n  \"prompt\": \"<string>\",\n  \"engine\": \"nano_banana_pro\",\n  \"aspect_ratio\": \"1:1\",\n  \"resolution\": \"1K\",\n  \"num_outputs\": 1,\n  \"output_format\": \"png\",\n  \"webhook_url\": \"https://example.com/webhooks/samsa\"\n}"

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

{
  "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "estimated_credits": 123
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

POST

images

img2img

Transform reference images with a prompt (img2img)

curl --request POST \
  --url https://api.samsa.ai/public/v1/images/img2img \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "images": [
    {
      "image_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
      "url": "https://cdn.example.com/photo.png",
      "base64": "<string>",
      "mime_type": "image/png"
    }
  ],
  "prompt": "<string>",
  "engine": "nano_banana_pro",
  "aspect_ratio": "1:1",
  "resolution": "1K",
  "num_outputs": 1,
  "output_format": "png",
  "webhook_url": "https://example.com/webhooks/samsa"
}
'

import requests

url = "https://api.samsa.ai/public/v1/images/img2img"

payload = {
    "images": [
        {
            "image_id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
            "url": "https://cdn.example.com/photo.png",
            "base64": "<string>",
            "mime_type": "image/png"
        }
    ],
    "prompt": "<string>",
    "engine": "nano_banana_pro",
    "aspect_ratio": "1:1",
    "resolution": "1K",
    "num_outputs": 1,
    "output_format": "png",
    "webhook_url": "https://example.com/webhooks/samsa"
}
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({
    images: [
      {
        image_id: '3c90c3cc-0d44-4b50-8888-8dd25736052a',
        url: 'https://cdn.example.com/photo.png',
        base64: '<string>',
        mime_type: 'image/png'
      }
    ],
    prompt: '<string>',
    engine: 'nano_banana_pro',
    aspect_ratio: '1:1',
    resolution: '1K',
    num_outputs: 1,
    output_format: 'png',
    webhook_url: 'https://example.com/webhooks/samsa'
  })
};

fetch('https://api.samsa.ai/public/v1/images/img2img', 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.samsa.ai/public/v1/images/img2img",
  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([
    'images' => [
        [
                'image_id' => '3c90c3cc-0d44-4b50-8888-8dd25736052a',
                'url' => 'https://cdn.example.com/photo.png',
                'base64' => '<string>',
                'mime_type' => 'image/png'
        ]
    ],
    'prompt' => '<string>',
    'engine' => 'nano_banana_pro',
    'aspect_ratio' => '1:1',
    'resolution' => '1K',
    'num_outputs' => 1,
    'output_format' => 'png',
    'webhook_url' => 'https://example.com/webhooks/samsa'
  ]),
  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.samsa.ai/public/v1/images/img2img"

	payload := strings.NewReader("{\n  \"images\": [\n    {\n      \"image_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n      \"url\": \"https://cdn.example.com/photo.png\",\n      \"base64\": \"<string>\",\n      \"mime_type\": \"image/png\"\n    }\n  ],\n  \"prompt\": \"<string>\",\n  \"engine\": \"nano_banana_pro\",\n  \"aspect_ratio\": \"1:1\",\n  \"resolution\": \"1K\",\n  \"num_outputs\": 1,\n  \"output_format\": \"png\",\n  \"webhook_url\": \"https://example.com/webhooks/samsa\"\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.samsa.ai/public/v1/images/img2img")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"images\": [\n    {\n      \"image_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n      \"url\": \"https://cdn.example.com/photo.png\",\n      \"base64\": \"<string>\",\n      \"mime_type\": \"image/png\"\n    }\n  ],\n  \"prompt\": \"<string>\",\n  \"engine\": \"nano_banana_pro\",\n  \"aspect_ratio\": \"1:1\",\n  \"resolution\": \"1K\",\n  \"num_outputs\": 1,\n  \"output_format\": \"png\",\n  \"webhook_url\": \"https://example.com/webhooks/samsa\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.samsa.ai/public/v1/images/img2img")

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  \"images\": [\n    {\n      \"image_id\": \"3c90c3cc-0d44-4b50-8888-8dd25736052a\",\n      \"url\": \"https://cdn.example.com/photo.png\",\n      \"base64\": \"<string>\",\n      \"mime_type\": \"image/png\"\n    }\n  ],\n  \"prompt\": \"<string>\",\n  \"engine\": \"nano_banana_pro\",\n  \"aspect_ratio\": \"1:1\",\n  \"resolution\": \"1K\",\n  \"num_outputs\": 1,\n  \"output_format\": \"png\",\n  \"webhook_url\": \"https://example.com/webhooks/samsa\"\n}"

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

{
  "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
  "estimated_credits": 123
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

{
  "error": {
    "type": "<string>",
    "code": "<string>",
    "message": "<string>",
    "request_id": "<string>",
    "param": "aspect_ratio"
  }
}

Transform 1–14 source images with a prompt. The call returns 202 Accepted with a job id; poll GET /images/img2img/{id} for the result. Each entry in images is a source object taking exactly one of image_id, url, or base64 + mime_type; order is preserved. Requires the images.edit scope.

Example: one source per mode

curl -X POST https://api.samsa.ai/public/v1/images/img2img \
  -H "Authorization: Bearer $SAMSA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "images": [{ "image_id": "123e4567-e89b-12d3-a456-426614174000" }],
    "prompt": "Place the product on a marble kitchen counter"
  }'

curl -X POST https://api.samsa.ai/public/v1/images/img2img \
  -H "Authorization: Bearer $SAMSA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "images": [{ "url": "https://cdn.example.com/photo.png" }],
    "prompt": "Turn this sketch into a photorealistic render",
    "resolution": "2K"
  }'

curl -X POST https://api.samsa.ai/public/v1/images/img2img \
  -H "Authorization: Bearer $SAMSA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "images": [{ "base64": "iVBORw0KGgoAAAANSUhEUg...", "mime_type": "image/png" }],
    "prompt": "Apply a warm sunset color grade",
    "num_outputs": 2
  }'

Example: blend multiple sources

Pass several sources — mixing modes is allowed — and tune the engine, aspect ratio, and resolution:

Body

{
  "images": [
    { "image_id": "123e4567-e89b-12d3-a456-426614174000" },
    { "url": "https://cdn.example.com/reference.jpg" },
    { "base64": "iVBORw0KGgoAAAANSUhEUg...", "mime_type": "image/webp" }
  ],
  "prompt": "Blend the subject into the reference scene",
  "engine": "nano_banana_2",
  "aspect_ratio": "16:9",
  "resolution": "4K",
  "webhook_url": "https://example.com/webhooks/samsa"
}

The 202 response is the async job handle:

202 Accepted

{
  "id": "b3f1c2d4-5e6f-4a7b-8c9d-0e1f2a3b4c5d",
  "status": "pending",
  "estimated_credits": 20
}

images holds 1–14 sources; each is exactly one of image_id, an https url, or base64 + mime_type. prompt is required. engine is nano_banana_pro (default) or nano_banana_2; an unknown engine returns 422. aspect_ratio is validated against the engine’s supported list (1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9; nano_banana_2 also 4:1, 1:4, 8:1, 1:8); omitted preserves the source shape. resolution is 1K (default), 2K, or 4K. num_outputs (1–4) defaults to 1 and each output is billed. output_format is png only in v1.

Credits

Each output costs 5 credits at 1K, scaling with resolution (1K ×1, 2K ×2, 4K ×4) and multiplied by num_outputs. See Pricing.

Errors

Status	Code	When
`402`	`insufficient_credits` / `insufficient_team_credits` / `insufficient_unallocated_credits`	The balance this credential can spend is below the job cost. Organizations with at least one active team get the team-aware codes instead of `insufficient_credits` (budget-exempt system organizations excepted). An operational failure inside the deduction can still surface as the generic `insufficient_credits`, whatever the regime.
`402`	`subscription_inactive`	The organization has no usable subscription.
`403`	`missing_scope`	Key lacks the `images.edit` scope.
`404`	`not_found`	A source `image_id` is unknown, or not owned by the API key’s creator — an image another member of your organization created is a `404` too.
`422`	`validation_error`	Zero/multiple source modes, bad prompt, unknown engine, or unsupported aspect ratio.
`429`	`rate_limited` / `too_many_active_jobs`	Per-key rate window or per-org concurrency cap exceeded.

Authorizations

Authorization

string

header

required

Organization API key as a bearer token: Authorization: Bearer samsa_sk_....

Body

application/json

POST /images/img2img body (SAM-815 / S8.3 — ADR §8, §10).

Transform 1-14 source images with a prompt (the app's Edit-tab img2img flow). Each source is exactly one of image_id (an image in your organization's context), an https url, or base64+mime_type. engine is a public-safe alias of the internal edit model (nano_banana_pro default, nano_banana_2); num_outputs defaults to 1 (the app default is 4). Each output is billed at 5 x resolution_multiplier credits (1K:1x, 2K:2x, 4K:4x).

images

PublicImageEditSource · object[]

required

1-14 source images; each exactly one of image_id, an https url, or base64+mime_type. Order is preserved.

Required array length: 1 - 14 elements

Show child attributes

prompt

string

required

Text prompt describing the transformation. Runs the same validation as the app (rejects empty / malformed / policy-violating prompts with a 422).

Minimum string length: 1

Example:

"Combine the products into one cohesive lifestyle scene"

engine

string | null

Img2img engine — one of nano_banana_pro (default) or nano_banana_2. Omit to use the default. Unknown engines return 422.

Example:

"nano_banana_pro"

aspect_ratio

string | null

Optional aspect ratio for the generated image(s), validated against the engine's supported list (1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, 21:9; nano_banana_2 additionally 4:1, 1:4, 8:1, 1:8). Omitted = the engine preserves the source shape.

Example:

"1:1"

resolution

string

default:1K

Output resolution — 1K (default), 2K, or 4K. Credits scale 1K:1x, 2K:2x, 4K:4x per output.

Example:

"1K"

num_outputs

integer

default:1

Number of images to generate (1-4). Defaults to 1 (the app default is 4); each output is billed.

Required range: 1 <= x <= 4

Example:

1

output_format

enum<string>

default:png

Encoding of the returned images. v1 supports png only.

Available options:

png

Example:

"png"

webhook_url

string | null

Optional https webhook notified once on terminal status (signed per the webhook signature scheme; see the webhooks docs).

Example:

"https://example.com/webhooks/samsa"

Response

Successful Response

Shared 202 body for the transform-op submits (SAM-813 / S8 wave).

Every POST /images/<op> returns the async job handle {id, status, estimated_credits}. The initial status is pending (the job is queued), with ONE exception: background-removals and vectorizations answer an owned-image_id cache hit (a ready result already exists for that image) with status: "completed" and estimated_credits: 0 — no new job is queued, the completed webhook event is emitted immediately for a supplied webhook_url, and the result is already available from the op's GET .../{id} endpoint. The other transform ops (img2img, variations, resizes, upscales) always start pending.

string<uuid>

required

The job id — poll the op's GET .../{id} endpoint.

status

enum<string>

required

Initial status: pending (job queued — enter the polling flow), or completed with estimated_credits: 0 when background-removals / vectorizations serve an owned-image cache hit (the result is immediately available).

Available options:

pending,

processing,

completed,

failed,

cancelled

Example:

"pending"

estimated_credits

integer

required

Credits this job is expected to cost — 0 on a cache-hit completed response.

Example:

5

Overview

Endpoints

Transform images (img2img)

Example: one source per mode

Example: blend multiple sources

Credits

Errors

Authorizations

Body

Response

​Example: one source per mode

​Example: blend multiple sources

​Credits

​Errors

Authorizations

Body

Response

Example: one source per mode

Example: blend multiple sources

Credits

Errors