Chat completion using G4F Endpoint

Sends a request for chat completions using the g4f library

POST v1/gpt4free

Chat completion using G4F Endpoint

cURL

curl --request POST \
  --url http://localhost:9000/api/v1/gpt4free \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "messages": [
    {
      "role": "<string>",
      "content": "<string>"
    }
  ],
  "model": "<string>",
  "stream": true,
  "timeout": 123,
  "shuffle": true,
  "image_url": "<string>"
}
'

import requests

url = "http://localhost:9000/api/v1/gpt4free"

payload = {
    "messages": [
        {
            "role": "<string>",
            "content": "<string>"
        }
    ],
    "model": "<string>",
    "stream": True,
    "timeout": 123,
    "shuffle": True,
    "image_url": "<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({
    messages: [{role: '<string>', content: '<string>'}],
    model: '<string>',
    stream: true,
    timeout: 123,
    shuffle: true,
    image_url: '<string>'
  })
};

fetch('http://localhost:9000/api/v1/gpt4free', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_PORT => "9000",
  CURLOPT_URL => "http://localhost:9000/api/v1/gpt4free",
  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([
    'messages' => [
        [
                'role' => '<string>',
                'content' => '<string>'
        ]
    ],
    'model' => '<string>',
    'stream' => true,
    'timeout' => 123,
    'shuffle' => true,
    'image_url' => '<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 := "http://localhost:9000/api/v1/gpt4free"

	payload := strings.NewReader("{\n  \"messages\": [\n    {\n      \"role\": \"<string>\",\n      \"content\": \"<string>\"\n    }\n  ],\n  \"model\": \"<string>\",\n  \"stream\": true,\n  \"timeout\": 123,\n  \"shuffle\": true,\n  \"image_url\": \"<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("http://localhost:9000/api/v1/gpt4free")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"messages\": [\n    {\n      \"role\": \"<string>\",\n      \"content\": \"<string>\"\n    }\n  ],\n  \"model\": \"<string>\",\n  \"stream\": true,\n  \"timeout\": 123,\n  \"shuffle\": true,\n  \"image_url\": \"<string>\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("http://localhost:9000/api/v1/gpt4free")

http = Net::HTTP.new(url.host, url.port)

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"messages\": [\n    {\n      \"role\": \"<string>\",\n      \"content\": \"<string>\"\n    }\n  ],\n  \"model\": \"<string>\",\n  \"stream\": true,\n  \"timeout\": 123,\n  \"shuffle\": true,\n  \"image_url\": \"<string>\"\n}"

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

200

{
  "response": "Large language models like me are advanced artificial intelligence systems designed to understand and generate human language. These models are trained on vast amounts of text data to learn patterns and relationships within language, enabling them to perform various tasks such as text generation, translation, summarization, and more. They are characterized by their ability to handle complex language tasks and generate coherent responses based on the input they receive."
}

{
  "error": "error message"
}

Request Body

messages · array · required

Array of messages to send to the chat model.

Show properties

role · string · required

The role of the message sender (e.g., ‘user’ or ‘assistant’ or ‘system’).

content · string · required

The content of the message.

model · string · default: "gpt-4o"

The model could be gpt-40, gpt-3.5-turbo or gpt-4

stream · boolean

Whether to stream the response or not.

timeout · int

timeout for the response to be sent.

shuffle · boolean · default: "false"

Shuffle the providers used for the chat completions. More details here

image_url · string

Include image for vision processing using the google gemini-pro model.

200 - Successful chat completion response

response · string

Response Text.

400 - Error message

error · string

The error message explaining what went wrong.

200

{
  "response": "Large language models like me are advanced artificial intelligence systems designed to understand and generate human language. These models are trained on vast amounts of text data to learn patterns and relationships within language, enabling them to perform various tasks such as text generation, translation, summarization, and more. They are characterized by their ability to handle complex language tasks and generate coherent responses based on the input they receive."
}

{
  "error": "error message"
}