curl https://api.apipod.ai/v1/images/generations \
  -H "Authorization: Bearer $APIPOD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "gpt-image-2-1k",
  "prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
  "resolution": "1K",
  "aspect_ratio": "auto"
}'

import os
import requests

payload = {
  "model": "gpt-image-2-1k",
  "prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
  "resolution": "1K",
  "aspect_ratio": "auto"
}

response = requests.post(
    "https://api.apipod.ai/v1/images/generations",
    headers={
        "Authorization": f"Bearer {os.environ['APIPOD_API_KEY']}",
        "Content-Type": "application/json",
    },
    json=payload,
    timeout=60,
)
response.raise_for_status()
print(response.json())

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "net/http"
    "os"
)

func main() {
    payload := map[string]any{}
    if err := json.Unmarshal([]byte(`{
  "model": "gpt-image-2-1k",
  "prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
  "resolution": "1K",
  "aspect_ratio": "auto"
}`), &payload); err != nil {
        panic(err)
    }
    body, err := json.Marshal(payload)
    if err != nil {
        panic(err)
    }

    req, err := http.NewRequest(http.MethodPost, "https://api.apipod.ai/v1/images/generations", bytes.NewReader(body))
    if err != nil {
        panic(err)
    }
    req.Header.Set("Authorization", "Bearer "+os.Getenv("APIPOD_API_KEY"))
    req.Header.Set("Content-Type", "application/json")

    resp, err := http.DefaultClient.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()
    fmt.Println(resp.Status)
}

use reqwest::Client;
use serde_json::json;
use std::env;

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let payload = json!({
  "model": "gpt-image-2-1k",
  "prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
  "resolution": "1K",
  "aspect_ratio": "auto"
});
    let response = Client::new()
        .post("https://api.apipod.ai/v1/images/generations")
        .bearer_auth(env::var("APIPOD_API_KEY")?)
        .json(&payload)
        .send()
        .await?
        .error_for_status()?;

    println!("{}", response.text().await?);
    Ok(())
}

const response = await fetch("https://api.apipod.ai/v1/images/generations", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.APIPOD_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify(
  {
    "model": "gpt-image-2-1k",
    "prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
    "resolution": "1K",
    "aspect_ratio": "auto"
  }
  ),
});

if (!response.ok) {
  throw new Error(`APIPod request failed: ${response.status} ${await response.text()}`);
}

console.log(await response.json());

{
  "code": 200,
  "message": "success",
  "data": {
    "task_id": "img_task_01JEXAMPLE"
  }
}