curl --request POST \
--url https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello, please introduce yourself"
}
]
}
]
}'
import requests
url = "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent"
payload = {
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello, please introduce yourself"
}
]
}
]
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
const url = "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent";
const payload = {
contents: [
{
role: "user",
parts: [
{
text: "Hello, please introduce yourself"
}
]
}
]
};
const headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
};
fetch(url, {
method: "POST",
headers: headers,
body: JSON.stringify(payload)
})
.then(response => response.json())
.then(data => console.log(data))
.catch(error => console.error('Error:', error));
package main
import (
"bytes"
"encoding/json"
"fmt"
"io/ioutil"
"net/http"
)
func main() {
url := "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent"
payload := map[string]interface{}{
"contents": []map[string]interface{}{
{
"role": "user",
"parts": []map[string]interface{}{
{
"text": "Hello, please introduce yourself",
},
},
},
},
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Authorization", "Bearer <token>")
req.Header.Set("Content-Type", "application/json")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := ioutil.ReadAll(resp.Body)
fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
String url = "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent";
String payload = """
{
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello, please introduce yourself"
}
]
}
]
}
""";
HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create(url))
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.POST(HttpRequest.BodyPublishers.ofString(payload))
.build();
HttpResponse<String> response = client.send(request,
HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
<?php
$url = "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent";
$payload = [
"contents" => [
[
"role" => "user",
"parts" => [
[
"text" => "Hello, please introduce yourself"
]
]
]
]
];
$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
"Authorization: Bearer <token>",
"Content-Type: application/json"
]);
$response = curl_exec($ch);
curl_close($ch);
echo $response;
?>
require 'net/http'
require 'json'
require 'uri'
url = URI("https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent")
payload = {
contents: [
{
role: "user",
parts: [
{
text: "Hello, please introduce yourself"
}
]
}
]
}
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 = payload.to_json
response = http.request(request)
puts response.body
{
"code": 200,
"data": {
"candidates": [
{
"content": {
"role": "model",
"parts": [
{
"text": "Hello! I'm pleased to introduce myself.\n\nI am a large language model, trained and developed by Google..."
}
]
},
"finishReason": "STOP",
"index": 0,
"safetyRatings": [
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"probability": "NEGLIGIBLE"
}
]
}
],
"promptFeedback": {
"safetyRatings": [
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"probability": "NEGLIGIBLE"
}
]
]
},
"usageMetadata": {
"promptTokenCount": 4,
"candidatesTokenCount": 611,
"totalTokenCount": 2422,
"thoughtsTokenCount": 1807,
"promptTokensDetails": [
{
"modality": "TEXT",
"tokenCount": 4
}
]
}
}
{
"error": {
"code": 400,
"message": "Invalid request parameters",
"status": "INVALID_ARGUMENT"
}
}
{
"error": {
"code": 401,
"message": "Authentication failed, please check your API Key",
"status": "UNAUTHENTICATED"
}
}
{
"error": {
"code": 402,
"message": "Insufficient balance, please recharge",
"status": "PAYMENT_REQUIRED"
}
}
{
"error": {
"code": 403,
"message": "Access denied",
"status": "PERMISSION_DENIED"
}
}
{
"error": {
"code": 404,
"message": "Model not found",
"status": "NOT_FOUND"
}
}
{
"error": {
"code": 429,
"message": "Rate limit exceeded, please try again later",
"status": "RESOURCE_EXHAUSTED"
}
}
{
"error": {
"code": 500,
"message": "Internal server error",
"status": "INTERNAL"
}
}
{
"error": {
"code": 502,
"message": "Bad gateway, service temporarily unavailable",
"status": "BAD_GATEWAY"
}
}
{
"error": {
"code": 503,
"message": "Service temporarily unavailable",
"status": "UNAVAILABLE"
}
}
Text Series
Gemini Native Format
- Call Gemini models using Google Native API format
- Synchronous processing mode with real-time response
- Minimal parameters for quick start
POST
/
v1beta
/
models
/
{model}
:
{method}
curl --request POST \
--url https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello, please introduce yourself"
}
]
}
]
}'
import requests
url = "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent"
payload = {
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello, please introduce yourself"
}
]
}
]
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
const url = "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent";
const payload = {
contents: [
{
role: "user",
parts: [
{
text: "Hello, please introduce yourself"
}
]
}
]
};
const headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
};
fetch(url, {
method: "POST",
headers: headers,
body: JSON.stringify(payload)
})
.then(response => response.json())
.then(data => console.log(data))
.catch(error => console.error('Error:', error));
package main
import (
"bytes"
"encoding/json"
"fmt"
"io/ioutil"
"net/http"
)
func main() {
url := "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent"
payload := map[string]interface{}{
"contents": []map[string]interface{}{
{
"role": "user",
"parts": []map[string]interface{}{
{
"text": "Hello, please introduce yourself",
},
},
},
},
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Authorization", "Bearer <token>")
req.Header.Set("Content-Type", "application/json")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := ioutil.ReadAll(resp.Body)
fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
String url = "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent";
String payload = """
{
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello, please introduce yourself"
}
]
}
]
}
""";
HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create(url))
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.POST(HttpRequest.BodyPublishers.ofString(payload))
.build();
HttpResponse<String> response = client.send(request,
HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
<?php
$url = "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent";
$payload = [
"contents" => [
[
"role" => "user",
"parts" => [
[
"text" => "Hello, please introduce yourself"
]
]
]
]
];
$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
"Authorization: Bearer <token>",
"Content-Type: application/json"
]);
$response = curl_exec($ch);
curl_close($ch);
echo $response;
?>
require 'net/http'
require 'json'
require 'uri'
url = URI("https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent")
payload = {
contents: [
{
role: "user",
parts: [
{
text: "Hello, please introduce yourself"
}
]
}
]
}
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 = payload.to_json
response = http.request(request)
puts response.body
{
"code": 200,
"data": {
"candidates": [
{
"content": {
"role": "model",
"parts": [
{
"text": "Hello! I'm pleased to introduce myself.\n\nI am a large language model, trained and developed by Google..."
}
]
},
"finishReason": "STOP",
"index": 0,
"safetyRatings": [
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"probability": "NEGLIGIBLE"
}
]
}
],
"promptFeedback": {
"safetyRatings": [
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"probability": "NEGLIGIBLE"
}
]
]
},
"usageMetadata": {
"promptTokenCount": 4,
"candidatesTokenCount": 611,
"totalTokenCount": 2422,
"thoughtsTokenCount": 1807,
"promptTokensDetails": [
{
"modality": "TEXT",
"tokenCount": 4
}
]
}
}
{
"error": {
"code": 400,
"message": "Invalid request parameters",
"status": "INVALID_ARGUMENT"
}
}
{
"error": {
"code": 401,
"message": "Authentication failed, please check your API Key",
"status": "UNAUTHENTICATED"
}
}
{
"error": {
"code": 402,
"message": "Insufficient balance, please recharge",
"status": "PAYMENT_REQUIRED"
}
}
{
"error": {
"code": 403,
"message": "Access denied",
"status": "PERMISSION_DENIED"
}
}
{
"error": {
"code": 404,
"message": "Model not found",
"status": "NOT_FOUND"
}
}
{
"error": {
"code": 429,
"message": "Rate limit exceeded, please try again later",
"status": "RESOURCE_EXHAUSTED"
}
}
{
"error": {
"code": 500,
"message": "Internal server error",
"status": "INTERNAL"
}
}
{
"error": {
"code": 502,
"message": "Bad gateway, service temporarily unavailable",
"status": "BAD_GATEWAY"
}
}
{
"error": {
"code": 503,
"message": "Service temporarily unavailable",
"status": "UNAVAILABLE"
}
}
curl --request POST \
--url https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello, please introduce yourself"
}
]
}
]
}'
import requests
url = "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent"
payload = {
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello, please introduce yourself"
}
]
}
]
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
const url = "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent";
const payload = {
contents: [
{
role: "user",
parts: [
{
text: "Hello, please introduce yourself"
}
]
}
]
};
const headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
};
fetch(url, {
method: "POST",
headers: headers,
body: JSON.stringify(payload)
})
.then(response => response.json())
.then(data => console.log(data))
.catch(error => console.error('Error:', error));
package main
import (
"bytes"
"encoding/json"
"fmt"
"io/ioutil"
"net/http"
)
func main() {
url := "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent"
payload := map[string]interface{}{
"contents": []map[string]interface{}{
{
"role": "user",
"parts": []map[string]interface{}{
{
"text": "Hello, please introduce yourself",
},
},
},
},
}
jsonData, _ := json.Marshal(payload)
req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
req.Header.Set("Authorization", "Bearer <token>")
req.Header.Set("Content-Type", "application/json")
client := &http.Client{}
resp, err := client.Do(req)
if err != nil {
panic(err)
}
defer resp.Body.Close()
body, _ := ioutil.ReadAll(resp.Body)
fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;
public class Main {
public static void main(String[] args) throws Exception {
String url = "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent";
String payload = """
{
"contents": [
{
"role": "user",
"parts": [
{
"text": "Hello, please introduce yourself"
}
]
}
]
}
""";
HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create(url))
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.POST(HttpRequest.BodyPublishers.ofString(payload))
.build();
HttpResponse<String> response = client.send(request,
HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
}
}
<?php
$url = "https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent";
$payload = [
"contents" => [
[
"role" => "user",
"parts" => [
[
"text" => "Hello, please introduce yourself"
]
]
]
]
];
$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
"Authorization: Bearer <token>",
"Content-Type: application/json"
]);
$response = curl_exec($ch);
curl_close($ch);
echo $response;
?>
require 'net/http'
require 'json'
require 'uri'
url = URI("https://api.apimart.ai/v1beta/models/gemini-2.5-pro:generateContent")
payload = {
contents: [
{
role: "user",
parts: [
{
text: "Hello, please introduce yourself"
}
]
}
]
}
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 = payload.to_json
response = http.request(request)
puts response.body
{
"code": 200,
"data": {
"candidates": [
{
"content": {
"role": "model",
"parts": [
{
"text": "Hello! I'm pleased to introduce myself.\n\nI am a large language model, trained and developed by Google..."
}
]
},
"finishReason": "STOP",
"index": 0,
"safetyRatings": [
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"probability": "NEGLIGIBLE"
}
]
}
],
"promptFeedback": {
"safetyRatings": [
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"probability": "NEGLIGIBLE"
}
]
]
},
"usageMetadata": {
"promptTokenCount": 4,
"candidatesTokenCount": 611,
"totalTokenCount": 2422,
"thoughtsTokenCount": 1807,
"promptTokensDetails": [
{
"modality": "TEXT",
"tokenCount": 4
}
]
}
}
{
"error": {
"code": 400,
"message": "Invalid request parameters",
"status": "INVALID_ARGUMENT"
}
}
{
"error": {
"code": 401,
"message": "Authentication failed, please check your API Key",
"status": "UNAUTHENTICATED"
}
}
{
"error": {
"code": 402,
"message": "Insufficient balance, please recharge",
"status": "PAYMENT_REQUIRED"
}
}
{
"error": {
"code": 403,
"message": "Access denied",
"status": "PERMISSION_DENIED"
}
}
{
"error": {
"code": 404,
"message": "Model not found",
"status": "NOT_FOUND"
}
}
{
"error": {
"code": 429,
"message": "Rate limit exceeded, please try again later",
"status": "RESOURCE_EXHAUSTED"
}
}
{
"error": {
"code": 500,
"message": "Internal server error",
"status": "INTERNAL"
}
}
{
"error": {
"code": 502,
"message": "Bad gateway, service temporarily unavailable",
"status": "BAD_GATEWAY"
}
}
{
"error": {
"code": 503,
"message": "Service temporarily unavailable",
"status": "UNAVAILABLE"
}
}
Authorizations
string
required
All API endpoints require Bearer Token authenticationGet your API Key:Visit the API Key Management Page to get your API KeyAdd it to the request header:
Authorization: Bearer YOUR_API_KEY
Path Parameters
string
required
Model nameThe examples use
gemini-2.5-pro, which you can replace with other supported Gemini models:gemini-3.5-flash- Gemini 3.5 Flashgemini-3.1-pro-preview- Gemini 3.1 Pro Previewgemini-3-pro-preview- Gemini 3 Pro Previewgemini-2.5-pro- Gemini 2.5 Pro
enum<string>
required
Generation method (recommended:
generateContent for quick start):generateContent: Wait for complete response and return at oncestreamGenerateContent: Stream response, return content in chunks
generateContent, streamGenerateContentBody
array
required
List of conversation contentsMinimum 1 message required
Example:
Show contents object structure
Show contents object structure
string
required
Role type:
user: User messagemodel: Model response (used in conversation history)
[
{
"role": "user",
"parts": [{ "text": "Hello, please introduce yourself" }]
}
]
object
Generation configuration (optional)
Show generationConfig properties
Show generationConfig properties
number
Controls output randomness, range 0.0-2.0
- Lower values make output more deterministic
- Higher values make output more random
integer
Maximum number of tokens to generateDifferent models have different maximum limits
number
Nucleus sampling parameter, range 0.0-1.0Controls the probability mass considered during sampling
integer
Top-K sampling parameterSample only from the K most probable tokens at each step
array
List of stop sequencesStop generation when these sequences are encountered
array
Safety settings (optional)
Show safetySettings object structure
Show safetySettings object structure
string
Safety category:
HARM_CATEGORY_HATE_SPEECH: Hate speechHARM_CATEGORY_DANGEROUS_CONTENT: Dangerous contentHARM_CATEGORY_HARASSMENT: HarassmentHARM_CATEGORY_SEXUALLY_EXPLICIT: Sexually explicit content
string
Threshold level:
BLOCK_NONE: Don’t blockBLOCK_ONLY_HIGH: Block only high riskBLOCK_MEDIUM_AND_ABOVE: Block medium and above riskBLOCK_LOW_AND_ABOVE: Block low and above risk
Response
array
List of candidate responses
Show candidates object structure
Show candidates object structure
object
string
Finish reason:
STOP: Normal completionMAX_TOKENS: Maximum token limit reachedSAFETY: Stopped for safety reasonsRECITATION: Stopped due to recitationOTHER: Other reasons
integer
Index of the candidate response
object
object
Usage statistics
Show usageMetadata properties
Show usageMetadata properties
integer
Number of tokens in the prompt
integer
Number of tokens in candidate responses
integer
Total number of tokens consumed
integer
Number of tokens used for thinking (if applicable)
⌘I