绘图
curl --request POST \
--url https://api.qhaigc.net/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"prompt": "<string>",
"model": "<string>",
"size": "<string>"
}
'import requests
url = "https://api.qhaigc.net/v1/images/generations"
payload = {
"prompt": "<string>",
"model": "<string>",
"size": "<string>"
}
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({prompt: '<string>', model: '<string>', size: '<string>'})
};
fetch('https://api.qhaigc.net/v1/images/generations', 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.qhaigc.net/v1/images/generations",
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([
'prompt' => '<string>',
'model' => '<string>',
'size' => '<string>'
]),
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.qhaigc.net/v1/images/generations"
payload := strings.NewReader("{\n \"prompt\": \"<string>\",\n \"model\": \"<string>\",\n \"size\": \"<string>\"\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.qhaigc.net/v1/images/generations")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"prompt\": \"<string>\",\n \"model\": \"<string>\",\n \"size\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.qhaigc.net/v1/images/generations")
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 \"prompt\": \"<string>\",\n \"model\": \"<string>\",\n \"size\": \"<string>\"\n}"
response = http.request(request)
puts response.read_body{
"created": 123,
"data": [
{
"url": "<string>"
}
]
}绘图模型
香蕉绘图(Image 格式)
使用 Nano Banana 2 生成和参考图驱动图像
POST
/
v1
/
images
/
generations
绘图
curl --request POST \
--url https://api.qhaigc.net/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"prompt": "<string>",
"model": "<string>",
"size": "<string>"
}
'import requests
url = "https://api.qhaigc.net/v1/images/generations"
payload = {
"prompt": "<string>",
"model": "<string>",
"size": "<string>"
}
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({prompt: '<string>', model: '<string>', size: '<string>'})
};
fetch('https://api.qhaigc.net/v1/images/generations', 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.qhaigc.net/v1/images/generations",
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([
'prompt' => '<string>',
'model' => '<string>',
'size' => '<string>'
]),
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.qhaigc.net/v1/images/generations"
payload := strings.NewReader("{\n \"prompt\": \"<string>\",\n \"model\": \"<string>\",\n \"size\": \"<string>\"\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.qhaigc.net/v1/images/generations")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"prompt\": \"<string>\",\n \"model\": \"<string>\",\n \"size\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.qhaigc.net/v1/images/generations")
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 \"prompt\": \"<string>\",\n \"model\": \"<string>\",\n \"size\": \"<string>\"\n}"
response = http.request(request)
puts response.read_body{
"created": 123,
"data": [
{
"url": "<string>"
}
]
}功能说明
使用启航 AI 兼容 OpenAI 的/v1/images/generations 接口调用 nano-banana-2 生成图片。除标准 prompt 和 size 外,还支持通过 extra_fields 传入参考图、原生分辨率和宽高比等高级参数。
支持的模型
Nano Banana 2
模型 ID:
nano-banana-2Google 图像生成模型,支持参考图、多图融合、原生 2K 分辨率和 4K 超分。Nano Banana Pro
模型 ID:
nano-banana-pro适合需要更强角色一致性和复杂图像理解的场景。前置条件
- 渠道需支持图片生成能力
- 如需返回可访问图片 URL,服务端需正确配置图片代理或上传能力
- 模型需支持图片输出,推荐使用
nano-banana-2
基础用法
最简单的调用方式与 OpenAI Images API 保持一致:import openai
client = openai.OpenAI(
api_key="sk-your-api-key-here",
base_url="https://api.qhaigc.net/v1"
)
response = client.images.generate(
model="nano-banana-2",
prompt="一根放在木质餐桌上的新鲜香蕉,写实风格,柔和自然光,高细节",
size="1024x1024"
)
print(response.data[0].url)
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: 'sk-your-api-key-here',
baseURL: 'https://api.qhaigc.net/v1'
});
const response = await client.images.generate({
model: 'nano-banana-2',
prompt: '一根放在木质餐桌上的新鲜香蕉,写实风格,柔和自然光,高细节',
size: '1024x1024'
});
console.log(response.data[0].url);
curl -X POST https://api.qhaigc.net/v1/images/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-your-api-key-here" \
-d '{
"model": "nano-banana-2",
"prompt": "一根放在木质餐桌上的新鲜香蕉,写实风格,柔和自然光,高细节",
"size": "1024x1024"
}'
尺寸与分辨率
除 OpenAI 标准size 外,还支持 Nano Banana 原生分辨率值。
| size | image_size | aspect_ratio | 说明 |
|---|---|---|---|
256x256 | 512 | 1:1 | OpenAI 标准 |
512x512 | 512 | 1:1 | OpenAI 标准 |
1024x1024 | 1K | 1:1 | OpenAI 标准默认值 |
1024x1792 | 1K | 9:16 | OpenAI 标准竖图 |
1792x1024 | 1K | 16:9 | OpenAI 标准横图 |
512 | 512 | - | 原生分辨率 |
1K | 1K | - | 原生分辨率 |
2K | 2K | - | 原生分辨率 |
4K | 4K | - | 原生分辨率 |
如果
size 不在映射表内,例如 800x600,服务端会优雅降级,由模型使用默认分辨率。高级参数
通过extra_fields 传入 Nano Banana 特有能力:
| 参数 | 类型 | 说明 |
|---|---|---|
reference_images | string[] | 参考图片列表,支持图片 URL 和 base64 data URI |
temperature | number | 生成温度,控制随机性,通常范围 0.0 到 2.0 |
image_size | string | 覆盖 size 推导出的分辨率,可选 512、1K、2K、4K |
aspect_ratio | string | 覆盖 size 推导出的宽高比,如 1:1、16:9、9:16、3:4 |
extra_fields.image_size优先于sizeextra_fields.aspect_ratio优先于size
使用示例
指定原生 2K 和宽高比
curl -X POST https://api.qhaigc.net/v1/images/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-your-api-key-here" \
-d '{
"model": "nano-banana-2",
"prompt": "一串挂在树上的香蕉,纪录片摄影风格,细节清晰",
"size": "2K",
"extra_fields": {
"aspect_ratio": "16:9",
"temperature": 0.8
}
}'
使用参考图 URL
curl -X POST https://api.qhaigc.net/v1/images/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-your-api-key-here" \
-d '{
"model": "nano-banana-2",
"prompt": "参考图片的构图和配色,生成一张香蕉产品海报",
"size": "1024x1024",
"extra_fields": {
"reference_images": [
"https://example.com/reference-poster.jpg"
],
"temperature": 0.7
}
}'
使用 base64 参考图并覆盖分辨率
curl -X POST https://api.qhaigc.net/v1/images/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-your-api-key-here" \
-d '{
"model": "nano-banana-2",
"prompt": "将这张香蕉线稿转换为 3D 卡通风格",
"size": "1024x1024",
"extra_fields": {
"reference_images": [
"data:image/png;base64,iVBORw0KGgoAAAANSUhEUg..."
],
"image_size": "4K",
"aspect_ratio": "1:1",
"temperature": 0.5
}
}'
extra_fields.image_size 和 extra_fields.aspect_ratio 会覆盖 size: "1024x1024" 原本映射出的 1K 和 1:1。
多张参考图融合
curl -X POST https://api.qhaigc.net/v1/images/generations \
-H "Content-Type: application/json" \
-H "Authorization: Bearer sk-your-api-key-here" \
-d '{
"model": "nano-banana-2",
"prompt": "融合两张参考图的风格,生成一张极简香蕉品牌 KV",
"size": "2K",
"extra_fields": {
"reference_images": [
"https://example.com/style-1.jpg",
"https://example.com/style-2.jpg"
]
}
}'
返回结果
{
"created": 1742515200,
"data": [
{
"url": "https://proxy.example.com/images/abc123.png"
}
]
}
降级行为
| 场景 | 行为 |
|---|---|
size 不在映射表中 | 不设置分辨率映射,模型使用默认值 |
extra_fields 未传 | 仅使用 prompt 和 size,保持 OpenAI 兼容 |
extra_fields 中字段无效 | 忽略无效字段,继续按默认逻辑生成 |
| 参考图 URL 不可访问 | URL 原样传递给模型,由模型侧返回错误或降级处理 |
常见错误
| 错误 | 说明 |
|---|---|
no base64 image found in response | 模型未返回图片,检查 prompt 或模型是否支持生图 |
failed to upload image | 图片上传到代理服务器失败,检查服务端图片代理配置 |
chat response contains no choices | 模型返回空响应,可能被安全策略过滤 |
相关接口
绘图(Image 格式)
查看通用图片生成接口说明
改图(Image 格式)
基于原图和提示词修改图像
Authorizations
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Body
application/json
⌘I