curl --request POST \
  --url https://app.uselamina.ai/v1/intelligence/predict \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: <api-key>' \
  --data '
{
  "concept": "A lifestyle photo of our new sneakers in an urban setting with warm golden-hour lighting",
  "platform": "instagram",
  "modality": "image",
  "brandProfileId": null,
  "campaignId": null
}
'

import requests

url = "https://app.uselamina.ai/v1/intelligence/predict"

payload = {
    "concept": "A lifestyle photo of our new sneakers in an urban setting with warm golden-hour lighting",
    "platform": "instagram",
    "modality": "image",
    "brandProfileId": None,
    "campaignId": None
}
headers = {
    "x-api-key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'x-api-key': '<api-key>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    concept: 'A lifestyle photo of our new sneakers in an urban setting with warm golden-hour lighting',
    platform: 'instagram',
    modality: 'image',
    brandProfileId: null,
    campaignId: null
  })
};

fetch('https://app.uselamina.ai/v1/intelligence/predict', 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://app.uselamina.ai/v1/intelligence/predict",
  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([
    'concept' => 'A lifestyle photo of our new sneakers in an urban setting with warm golden-hour lighting',
    'platform' => 'instagram',
    'modality' => 'image',
    'brandProfileId' => null,
    'campaignId' => null
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json",
    "x-api-key: <api-key>"
  ],
]);

$response = curl_exec($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://app.uselamina.ai/v1/intelligence/predict"

	payload := strings.NewReader("{\n  \"concept\": \"A lifestyle photo of our new sneakers in an urban setting with warm golden-hour lighting\",\n  \"platform\": \"instagram\",\n  \"modality\": \"image\",\n  \"brandProfileId\": null,\n  \"campaignId\": null\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("x-api-key", "<api-key>")
	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://app.uselamina.ai/v1/intelligence/predict")
  .header("x-api-key", "<api-key>")
  .header("Content-Type", "application/json")
  .body("{\n  \"concept\": \"A lifestyle photo of our new sneakers in an urban setting with warm golden-hour lighting\",\n  \"platform\": \"instagram\",\n  \"modality\": \"image\",\n  \"brandProfileId\": null,\n  \"campaignId\": null\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://app.uselamina.ai/v1/intelligence/predict")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["x-api-key"] = '<api-key>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"concept\": \"A lifestyle photo of our new sneakers in an urban setting with warm golden-hour lighting\",\n  \"platform\": \"instagram\",\n  \"modality\": \"image\",\n  \"brandProfileId\": null,\n  \"campaignId\": null\n}"

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

{
  "data": {
    "predictedScore": 78.5,
    "confidence": "medium",
    "strengths": [
      "Strong alignment with brand visual identity",
      "Lifestyle format historically performs well"
    ],
    "risks": [
      "Golden-hour lighting may not differentiate from competitors",
      "Urban setting is overused in category"
    ],
    "suggestions": [
      "Add a human subject for +15% predicted engagement",
      "Consider a close-up crop variant"
    ]
  }
}

{
  "error": "concept, platform, and modality are required"
}

{
  "error": "Invalid API key"
}

"Too many requests from this IP, please try again in a minute"