Używanie Web Unlocker z agentami AI

import requests
import anthropic

html = requests.get(
    "https://parsing.webunlocker.gologin.com/v1/scrape",
    params={"url": "https://news.ycombinator.com"},
    headers={"apikey": "YOUR_API_KEY"}
).text

client = anthropic.Anthropic()
message = client.messages.create(
    model="claude-sonnet-4-5-20250514",
    max_tokens=1024,
    messages=[
        {
            "role": "user",
            "content": f"Extract the top 5 story titles and URLs from this HTML:\n\n{html[:8000]}"
        }
    ]
)

print(message.content[0].text)

import Anthropic from "@anthropic-ai/sdk";

const html = await fetch(
  "https://parsing.webunlocker.gologin.com/v1/scrape?url=" +
    encodeURIComponent("https://news.ycombinator.com"),
  { headers: { apikey: "YOUR_API_KEY" } }
).then((r) => r.text());

const client = new Anthropic();
const message = await client.messages.create({
  model: "claude-sonnet-4-5-20250514",
  max_tokens: 1024,
  messages: [
    {
      role: "user",
      content: `Extract the top 5 story titles and URLs from this HTML:\n\n${html.slice(0, 8000)}`,
    },
  ],
});

console.log(message.content[0].text);

import requests
import anthropic

def scrape(url: str) -> str:
    """Fetch a URL and return its rendered HTML."""
    return requests.get(
        "https://parsing.webunlocker.gologin.com/v1/scrape",
        params={"url": url},
        headers={"apikey": "YOUR_API_KEY"}
    ).text

tools = [
    {
        "name": "scrape",
        "description": "Fetch the rendered HTML of any URL, including JavaScript-heavy and protected sites.",
        "input_schema": {
            "type": "object",
            "properties": {
                "url": {"type": "string", "description": "The URL to scrape"}
            },
            "required": ["url"]
        }
    }
]

client = anthropic.Anthropic()
messages = [
    {"role": "user", "content": "What is the current price of the iPhone 16 Pro on apple.com?"}
]

while True:
    response = client.messages.create(
        model="claude-sonnet-4-5-20250514",
        max_tokens=1024,
        tools=tools,
        messages=messages
    )

    if response.stop_reason == "end_turn":
        print(response.content[0].text)
        break

    tool_results = []
    for block in response.content:
        if block.type == "tool_use" and block.name == "scrape":
            html = scrape(block.input["url"])
            tool_results.append({
                "type": "tool_result",
                "tool_use_id": block.id,
                "content": html[:10000]
            })

    messages.append({"role": "assistant", "content": response.content})
    messages.append({"role": "user", "content": tool_results})

import { WebUnlocker } from "gologin-webunlocker";

const client = new WebUnlocker({
  apiKey: process.env.GOLOGIN_WEBUNLOCKER_API_KEY!
});

// get structured metadata instead of raw HTML
const { data } = await client.scrapeJSON("https://example.com");
console.log(data.title, data.description, data.headings);

// get clean text for LLM context
const { text } = await client.scrapeText("https://example.com");

// batch scrape with concurrency control
const results = await client.batchScrape(
  ["https://example.com/1", "https://example.com/2", "https://example.com/3"],
  { concurrency: 3 }
);

# plain text — good for LLM context
gologin-web-access scrape-text https://example.com

# structured JSON — title, description, headings, links
gologin-web-access scrape-json https://example.com

# batch scrape — many pages at once
gologin-web-access batch-scrape url1 url2 url3 --format text --summary

# search the web
gologin-web-access search "best antidetect browser 2026" --limit 10

# extract structured data with a schema
gologin-web-access extract https://example.com --schema ./schema.json