curl --request GET \
  --url https://api.firecrawl.dev/v2/search/research/papers \
  --header 'Authorization: Bearer <token>'

import requests

url = "https://api.firecrawl.dev/v2/search/research/papers"

headers = {"Authorization": "Bearer <token>"}

response = requests.get(url, headers=headers)

print(response.text)

const options = {method: 'GET', headers: {Authorization: 'Bearer <token>'}};

fetch('https://api.firecrawl.dev/v2/search/research/papers', 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.firecrawl.dev/v2/search/research/papers",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "GET",
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"net/http"
	"io"
)

func main() {

	url := "https://api.firecrawl.dev/v2/search/research/papers"

	req, _ := http.NewRequest("GET", url, nil)

	req.Header.Add("Authorization", "Bearer <token>")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.get("https://api.firecrawl.dev/v2/search/research/papers")
  .header("Authorization", "Bearer <token>")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.firecrawl.dev/v2/search/research/papers")

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

request = Net::HTTP::Get.new(url)
request["Authorization"] = 'Bearer <token>'

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

{
  "results": [
    {
      "abstract": "We show that diffusion models can achieve image sample quality superior to the current state-of-the-art generative models...",
      "ids": {
        "arxiv": [
          "2105.05233"
        ]
      },
      "paperId": "2014215642691656232",
      "primaryId": "arxiv:2105.05233",
      "score": 0.0163934,
      "title": "Diffusion Models Beat GANs on Image Synthesis"
    }
  ],
  "success": true
}