Search

{
  "count": 1,
  "coverage": {
    "complete": true,
    "missing": [],
    "retry": false
  },
  "items": [
    {
      "authors": [
        "Ashish Vaswani",
        "Noam Shazeer",
        "Niki Parmar"
      ],
      "citationCount": 181057,
      "citationsPerYear": 18105.7,
      "detail_url": "https://papers.use.x402atlas.com/paper?id=10.48550/arxiv.1706.03762",
      "doi": "10.48550/arxiv.1706.03762",
      "id": "10.48550/arxiv.1706.03762",
      "is_retracted": false,
      "oa_status": "green",
      "pdfUrl": "https://arxiv.org/pdf/1706.03762",
      "snippet": "The dominant sequence transduction models are based on complex recurrent or convolutional neural networks that include an encoder and a decoder. The best performing models also connect the encoder and decoder through an attention mechanism…",
      "title": "Attention Is All You Need",
      "type": "preprint",
      "url": "https://doi.org/10.48550/arxiv.1706.03762",
      "venue": "Advances in Neural Information Processing Systems",
      "year": 2017
    }
  ],
  "query": "transformer attention mechanism year:2017-2026 sort:impact"
}

# bash or zsh: see the payment challenge. Nothing is charged.
curl -sS -g -i 'https://papers.use.x402atlas.com/search?limit=10&open_access=false&query=transformer+attention+mechanism&sort=impact&source=all&year_from=2017&year_to=2026'

# x402 v2 sends the challenge base64-encoded in the PAYMENT-REQUIRED header (v1 sends it in the body).
# To read the header:
curl -sS -g -o /dev/null -D - 'https://papers.use.x402atlas.com/search?limit=10&open_access=false&query=transformer+attention+mechanism&sort=impact&source=all&year_from=2017&year_to=2026' \
  | grep -i '^payment-required:' | cut -d' ' -f2 | tr -d '\r' | base64 --decode

// npm i @x402/fetch @x402/evm viem
import { wrapFetchWithPayment, x402Client } from "@x402/fetch";
import { registerExactEvmScheme } from "@x402/evm/exact/client";
import { privateKeyToAccount } from "viem/accounts";

// Pays at most $0.01 per call.
const client = new x402Client().setSpendControls({ maxAmountPerPayment: "$0.01" });
registerExactEvmScheme(client, { signer: privateKeyToAccount(process.env.EVM_PRIVATE_KEY) });
const pay = wrapFetchWithPayment(fetch, client);

// Not sure it's safe to pay? ToolVet checks it first for $0.005. Pay for that from a separate
// client: this one is capped at $0.01 per payment. GET https://toolvet.app/api/v1/check?url=https%3A%2F%2Fpapers.use.x402atlas.com%2Fsearch
const res = await pay("https://papers.use.x402atlas.com/search?limit=10&open_access=false&query=transformer+attention+mechanism&sort=impact&source=all&year_from=2017&year_to=2026");
console.log(res.status, await res.text());

# pip install "x402[requests,evm]"
import os
from eth_account import Account
from x402 import x402ClientSync
from x402.http.clients import x402_requests
from x402.mechanisms.evm import EthAccountSigner
from x402.mechanisms.evm.exact.register import register_exact_evm_client

# Pays at most $0.01 per call.
client = x402ClientSync().set_spend_controls({"max_amount_per_payment": "$0.01"})
register_exact_evm_client(client, EthAccountSigner(Account.from_key(os.environ["EVM_PRIVATE_KEY"])))

with x402_requests(client) as session:
    res = session.get("https://papers.use.x402atlas.com/search?limit=10&open_access=false&query=transformer+attention+mechanism&sort=impact&source=all&year_from=2017&year_to=2026")
    print(res.status_code, res.text)