curl https://api.apipod.ai/v1/images/generations \
-H "Authorization: Bearer $APIPOD_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-image-2.6-flare-lite",
"prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
"quality": "auto",
"aspect_ratio": "auto",
"resolution": "1K"
}'import os
import requests
payload = {
"model": "gpt-image-2.6-flare-lite",
"prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
"quality": "auto",
"aspect_ratio": "auto",
"resolution": "1K"
}
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-2.6-flare-lite",
"prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
"quality": "auto",
"aspect_ratio": "auto",
"resolution": "1K"
}`), &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-2.6-flare-lite",
"prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
"quality": "auto",
"aspect_ratio": "auto",
"resolution": "1K"
});
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-2.6-flare-lite",
"prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
"quality": "auto",
"aspect_ratio": "auto",
"resolution": "1K"
}
),
});
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"
}
}GPT Image 2.6 Flare Lite
GPT Image 2.6 Flare Lite 是 APIPod 基于 Azure、Adobe 等低成本渠道提供的 GPT Image 2.6 Flare 路由版本,并非独立的 OpenAI 模型,不支持 SVG 输出。
curl https://api.apipod.ai/v1/images/generations \
-H "Authorization: Bearer $APIPOD_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-image-2.6-flare-lite",
"prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
"quality": "auto",
"aspect_ratio": "auto",
"resolution": "1K"
}'import os
import requests
payload = {
"model": "gpt-image-2.6-flare-lite",
"prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
"quality": "auto",
"aspect_ratio": "auto",
"resolution": "1K"
}
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-2.6-flare-lite",
"prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
"quality": "auto",
"aspect_ratio": "auto",
"resolution": "1K"
}`), &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-2.6-flare-lite",
"prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
"quality": "auto",
"aspect_ratio": "auto",
"resolution": "1K"
});
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-2.6-flare-lite",
"prompt": "A premium product photograph on a dark studio set, precise typography, soft rim lighting, highly detailed.",
"quality": "auto",
"aspect_ratio": "auto",
"resolution": "1K"
}
),
});
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"
}
}授权
在 Authorization 请求头中使用 Bearer APIPod_API_KEY。
请求体
APIPod 公开模型 ID。
"gpt-image-2.6-flare-lite"生成或编辑指令。输出 GIF 时需写明主体、运动方式与循环目标。
32000可公开访问的源图或参考图 URL。与 gif 输出不能同时使用。
16局部重绘遮罩图,支持公网 URL 或 base64 数据 URI。透明像素标记允许编辑的区域,其余区域保持不变;须伴随 image_urls 使用,且不能与 markup_url 同时使用。
编辑标注图,支持公网 URL 或 base64 数据 URI(GPT Image 2.5/2.6 新增)。透明 PNG 叠加在第一张参考图上,不透明笔迹引导模型编辑对应区域;尺寸须与第一张参考图一致。须伴随 image_urls 使用,且不能与 mask_url 同时使用。
输出格式。gif 仅文生图可用,且不支持 output_compression 与透明背景;GPT Image 2.6 Lite 不支持 svg。
png, jpeg, webp, gif 渲染前的规划复杂度。low 适合改背景这类聚焦型编辑,high 适合密集文字与复杂版式;缺省为 high,不额外收费。
low, medium, high 保真档位。background 为 transparent 时不得低于 medium。
auto, low, medium, high, xhigh, max 背景模式。transparent 返回带 alpha 通道的图片,并要求 quality 不低于 medium。
auto, opaque, transparent 生成图片的宽高比。
auto, 61, 123, 182, 184, 243, 245, 304, 556, 969, 1269 生成图片的分辨率档位。
1K, 2K, 4K 可选的精确像素通道,格式为 宽x高(例如 1024x1536)。宽高必须是 16 的倍数且不超过 3840;与 resolution、aspect_ratio 同时出现时以 size 为准。1K/2K/4K 档位配合 15 种宽高比已覆盖常见尺寸,GIF 单帧也可直接使用,因此只有像素级对齐或非标准比例时才需要 size。
GIF 总帧数,取值 2-64。仅当 output_format 为 gif 时生效,缺省为 9。
2 <= x <= 64GIF 每帧时长(毫秒),取值 20-2000。仅当 output_format 为 gif 时生效,缺省为 200。
20 <= x <= 2000jpeg 与 webp 的输出压缩率,取值 0-100。gif 不支持该参数。
0 <= x <= 100内容审核严格度。APIPod 对 GPT Image 2.6 默认下发 low 以减少误拦;传 auto 可恢复 OpenAI 默认的严格过滤。
low, auto 此页面对您有帮助吗?