AI & Developer

Weights & Biases Scraper

Extract ML experiment reports, model benchmarks, public project data, and research artifacts from Weights & Biases. Powered by spider-browser .

Get Started Documentation

wandb.ai target

99.5% success rate

~4ms latency

Quick Start

Extract data in minutes

wandb-scraper.ts

import { SpiderBrowser } from "spider-browser";

const spider = new SpiderBrowser({
  apiKey: process.env.SPIDER_API_KEY!,
});

await spider.connect();
const page = spider.page!;
await page.goto("https://wandb.ai/fully-connected");
await page.content(10000);

const data = await page.evaluate(`(() => {
  const reports = [];
  document.querySelectorAll("[class*='ReportCard'], [class*='report-card'], article").forEach(el => {
    const title = el.querySelector("h2, h3, [class*='title']")?.textContent?.trim();
    const author = el.querySelector("[class*='author']")?.textContent?.trim();
    const desc = el.querySelector("p, [class*='description']")?.textContent?.trim();
    const views = el.querySelector("[class*='views']")?.textContent?.trim();
    const link = el.querySelector("a")?.getAttribute("href");
    if (title) reports.push({ title, author, desc, views, link });
  });
  return JSON.stringify({ total: reports.length, reports: reports.slice(0, 15) });
})()`);

console.log(JSON.parse(data));
await spider.close();

✓ ready to run | spider-browser | TypeScript

Fetch API

Structured data endpoint

Extract structured JSON from wandb.ai with a single POST request. AI-configured selectors, cached for fast repeat calls.

POST /fetch/wandb.ai/

Report titleAuthorViewsTagsDescriptionFramework

Try it Fetch API Docs

curl

curl -X POST https://api.spider.cloud/fetch/wandb.ai/ \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"return_format": "json"}'

Python

import requests

resp = requests.post(
    "https://api.spider.cloud/fetch/wandb.ai/",
    headers={
        "Authorization": "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
    },
    json={"return_format": "json"},
)
print(resp.json())

Node.js

const resp = await fetch("https://api.spider.cloud/fetch/wandb.ai/", {
  method: "POST",
  headers: {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({ return_format: "json" }),
});
const data = await resp.json();
console.log(data);

Extraction