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POST
/
v1beta
/
models
/
{model}
:generateContent
Gemini Image(Nano Banana)
curl --request POST \
  --url https://api.ai.cc/v1beta/models/{model}:generateContent \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "contents": [
    {
      "role": "user",
      "parts": [
        {
          "text": "draw a cat"
        }
      ]
    }
  ],
  "generationConfig": {
    "responseModalities": [
      "TEXT",
      "IMAGE"
    ],
    "imageConfig": {
      "aspectRatio": "16:9",
      "imageSize": "1K"
    }
  }
}
'
import requests

url = "https://api.ai.cc/v1beta/models/{model}:generateContent"

payload = {
"contents": [
{
"role": "user",
"parts": [{ "text": "draw a cat" }]
}
],
"generationConfig": {
"responseModalities": ["TEXT", "IMAGE"],
"imageConfig": {
"aspectRatio": "16:9",
"imageSize": "1K"
}
}
}
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({
contents: [{role: 'user', parts: [{text: 'draw a cat'}]}],
generationConfig: {
responseModalities: ['TEXT', 'IMAGE'],
imageConfig: {aspectRatio: '16:9', imageSize: '1K'}
}
})
};

fetch('https://api.ai.cc/v1beta/models/{model}:generateContent', 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.ai.cc/v1beta/models/{model}:generateContent",
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([
'contents' => [
[
'role' => 'user',
'parts' => [
[
'text' => 'draw a cat'
]
]
]
],
'generationConfig' => [
'responseModalities' => [
'TEXT',
'IMAGE'
],
'imageConfig' => [
'aspectRatio' => '16:9',
'imageSize' => '1K'
]
]
]),
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.ai.cc/v1beta/models/{model}:generateContent"

payload := strings.NewReader("{\n \"contents\": [\n {\n \"role\": \"user\",\n \"parts\": [\n {\n \"text\": \"draw a cat\"\n }\n ]\n }\n ],\n \"generationConfig\": {\n \"responseModalities\": [\n \"TEXT\",\n \"IMAGE\"\n ],\n \"imageConfig\": {\n \"aspectRatio\": \"16:9\",\n \"imageSize\": \"1K\"\n }\n }\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.ai.cc/v1beta/models/{model}:generateContent")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"contents\": [\n {\n \"role\": \"user\",\n \"parts\": [\n {\n \"text\": \"draw a cat\"\n }\n ]\n }\n ],\n \"generationConfig\": {\n \"responseModalities\": [\n \"TEXT\",\n \"IMAGE\"\n ],\n \"imageConfig\": {\n \"aspectRatio\": \"16:9\",\n \"imageSize\": \"1K\"\n }\n }\n}")
.asString();
require 'uri'
require 'net/http'

url = URI("https://api.ai.cc/v1beta/models/{model}:generateContent")

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 \"contents\": [\n {\n \"role\": \"user\",\n \"parts\": [\n {\n \"text\": \"draw a cat\"\n }\n ]\n }\n ],\n \"generationConfig\": {\n \"responseModalities\": [\n \"TEXT\",\n \"IMAGE\"\n ],\n \"imageConfig\": {\n \"aspectRatio\": \"16:9\",\n \"imageSize\": \"1K\"\n }\n }\n}"

response = http.request(request)
puts response.read_body
{
  "candidates": [
    {
      "content": {
        "role": "<string>",
        "parts": [
          {
            "inlineData": {
              "mimeType": "<string>",
              "data": "<string>"
            }
          }
        ]
      },
      "finishReason": "<string>",
      "safetyRatings": [
        {}
      ]
    }
  ],
  "usageMetadata": {
    "promptTokenCount": 123,
    "candidatesTokenCount": 123,
    "totalTokenCount": 123
  }
}
This endpoint integrates a third-party model. For detailed parameter information, please refer to the official documentation at Gemini Docs.

Authorizations

Authorization
string
header
required

Authentication is done using Bearer Token. Format: Authorization: Bearer sk-xxxxxx

Path Parameters

model
string
required

model name

Body

application/json
contents
object[]
required
generationConfig
object
required

Response

200 - application/json

Successfully

candidates
object[]
usageMetadata
object