Gemini Native Format

curl --request POST \
  --url https://api.gregapi.com/v1beta/models/{model}:generateContent \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "contents": [
    {
      "parts": [
        {
          "text": "Hello"
        }
      ]
    }
  ]
}
'

import requests

url = "https://api.gregapi.com/v1beta/models/{model}:generateContent"

payload = { "contents": [{ "parts": [{ "text": "Hello" }] }] }
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: [{parts: [{text: 'Hello'}]}]})
};

fetch('https://api.gregapi.com/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.gregapi.com/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' => [
        [
                'parts' => [
                                [
                                                                'text' => 'Hello'
                                ]
                ]
        ]
    ]
  ]),
  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.gregapi.com/v1beta/models/{model}:generateContent"

	payload := strings.NewReader("{\n  \"contents\": [\n    {\n      \"parts\": [\n        {\n          \"text\": \"Hello\"\n        }\n      ]\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.gregapi.com/v1beta/models/{model}:generateContent")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"contents\": [\n    {\n      \"parts\": [\n        {\n          \"text\": \"Hello\"\n        }\n      ]\n    }\n  ]\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.gregapi.com/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      \"parts\": [\n        {\n          \"text\": \"Hello\"\n        }\n      ]\n    }\n  ]\n}"

response = http.request(request)
puts response.read_body

POST

v1beta

models

{model}

:generateContent

Gemini Native Format

curl --request POST \
  --url https://api.gregapi.com/v1beta/models/{model}:generateContent \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "contents": [
    {
      "parts": [
        {
          "text": "Hello"
        }
      ]
    }
  ]
}
'

import requests

url = "https://api.gregapi.com/v1beta/models/{model}:generateContent"

payload = { "contents": [{ "parts": [{ "text": "Hello" }] }] }
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: [{parts: [{text: 'Hello'}]}]})
};

fetch('https://api.gregapi.com/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.gregapi.com/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' => [
        [
                'parts' => [
                                [
                                                                'text' => 'Hello'
                                ]
                ]
        ]
    ]
  ]),
  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.gregapi.com/v1beta/models/{model}:generateContent"

	payload := strings.NewReader("{\n  \"contents\": [\n    {\n      \"parts\": [\n        {\n          \"text\": \"Hello\"\n        }\n      ]\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.gregapi.com/v1beta/models/{model}:generateContent")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"contents\": [\n    {\n      \"parts\": [\n        {\n          \"text\": \"Hello\"\n        }\n      ]\n    }\n  ]\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.gregapi.com/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      \"parts\": [\n        {\n          \"text\": \"Hello\"\n        }\n      ]\n    }\n  ]\n}"

response = http.request(request)
puts response.read_body

Endpoints

Purpose	Path
Text / multimodal generation	`POST /v1beta/models/{model}:generateContent`
Streaming output	`POST /v1beta/models/{model}:streamGenerateContent?alt=sse`

The native interface supports Authorization: Bearer <TOKEN>, and also x-goog-api-key: <TOKEN>.

Quick start

curl -X POST "https://api.gregapi.com/v1beta/models/gemini-2.5-flash:generateContent" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{"parts": [{"text": "Hello"}]}]
  }'

Streaming output

curl -N "https://api.gregapi.com/v1beta/models/gemini-2.5-flash:streamGenerateContent?alt=sse" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{"parts": [{"text": "Write a poem"}]}]
  }'

Multimodal input

The native interface carries multimodal content through contents[].parts[]: text uses text, and media uses inline_data (mime_type + Base64 data).

Audio understanding

curl -X POST "https://api.gregapi.com/v1beta/models/gemini-2.5-flash:generateContent" \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{
      "parts": [
        {"text": "Transcribe this audio"},
        {"inline_data": {"mime_type": "audio/mp3", "data": "<BASE64>"}}
      ]
    }]
  }'

Images similarly use inline_data with a mime_type of image/png, image/jpeg, and so on. The gemini-3-pro-preview-file model can analyze video files directly via URL; see the video analysis documentation for details.

Reasoning

The Gemini 2.5 and 3 series support reasoning, configured through generationConfig.thinkingConfig. The Gemini 3 series uses thinkingLevel:

{
  "generationConfig": {
    "thinkingConfig": {"thinkingLevel": "high"}
  }
}

The Gemini 2.5 series uses thinkingBudget:

{
  "generationConfig": {
    "thinkingConfig": {"thinkingBudget": 8192}
  }
}

Generation parameters

Parameter	Description	Default
`temperature`	Randomness, 0-2	1.0
`max_tokens`	Maximum output tokens	Model default
`top_p`	Nucleus sampling probability	0.95
`stop`	Stop sequences	-

Gemini 3 recommends keeping temperature at 1.0; too low a value may degrade reasoning.

SDK example (Python · Google SDK)

from google import genai

client = genai.Client(
    api_key="your-token",
    http_options={"base_url": "https://api.gregapi.com"},
)

response = client.models.generate_content(
    model="gemini-2.5-flash",
    contents="Hello",
)
print(response.text)

Authorizations

Authorization

string

header

required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Path Parameters

model

string

required

Model name

Example:

"gemini-2.5-flash"

Body

application/json

contents

object[]

required

Conversation content

Show child attributes

generationConfig

object

Generation configuration, e.g. temperature, thinkingConfig

Response

200

Successful generation response

Large Language Models (LLM)

Image Models

Video Models

Speech Models

Gemini Native Format

Endpoints

Quick start

Streaming output

Multimodal input

Audio understanding

Reasoning

Generation parameters

SDK example (Python · Google SDK)

Authorizations

Path Parameters

Body

Response

​Endpoints

​Quick start

​Streaming output

​Multimodal input

​Audio understanding

​Reasoning

​Generation parameters

​SDK example (Python · Google SDK)

Authorizations

Path Parameters

Body

Response

Endpoints

Quick start

Streaming output

Multimodal input

Audio understanding

Reasoning

Generation parameters

SDK example (Python · Google SDK)