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browser-usevsrod

MIT 226 30 87,251
8.9 million (month) Nov 01 2024 0.12.6(2026-04-02 07:55:13 ago)
6,853 3 202 MIT
Sep 23 2022 v0.116.2(2024-07-12 11:52:28 ago)

Browser-use is a Python library that enables AI agents to control web browsers using natural language instructions. It connects large language models (LLMs) to browser automation, allowing you to describe what you want done in plain English instead of writing explicit selectors and interaction code.

Key features include:

  • Natural language browser control Describe tasks like "go to Amazon and find the cheapest laptop under $500" and the AI agent will navigate, interact with elements, and extract the requested information.
  • Multi-step task execution Can handle complex workflows that require multiple pages, form filling, clicking, scrolling, and waiting for dynamic content.
  • Vision support Uses screenshot analysis (multimodal LLMs) to understand page layout and find elements visually, not just through DOM inspection.
  • Multiple LLM providers Works with OpenAI, Anthropic Claude, Google Gemini, and other LLM providers.
  • Playwright backend Uses Playwright under the hood for reliable browser automation across Chrome, Firefox, and Safari.
  • Structured output Can return extracted data in structured formats defined by Pydantic models.

Browser-use represents a new paradigm in web scraping where instead of writing brittle selectors, you describe the extraction task and let the AI figure out how to navigate and extract the data. This is especially useful for scraping diverse sites with varying layouts.

Rod is a high-level Go library for browser automation built on the Chrome DevTools Protocol (CDP). It provides a simpler and more intuitive API compared to chromedp, making it easier to write browser automation and web scraping scripts in Go.

Key features include:

  • Simple API Rod's API is designed to be intuitive and requires less boilerplate than chromedp. Common operations like clicking, typing, and waiting are straightforward single-line calls.
  • Auto-wait Automatically waits for elements to be ready before interacting with them, reducing the need for explicit wait statements and making scripts more reliable.
  • Page pool Built-in page pool for managing multiple browser pages efficiently, useful for concurrent scraping tasks.
  • Stealth mode Includes a stealth plugin (rod/lib/launcher/flags) that can disable common automation detection vectors.
  • Element screenshots Can take screenshots of specific elements, not just full pages.
  • Network interception Supports hijacking network requests and responses for modification or monitoring.
  • Input emulation Realistic mouse and keyboard input emulation for interacting with complex web applications.

Rod is the recommended choice for new Go browser automation projects due to its simpler API and active maintenance. It is comparable to Playwright in terms of developer experience but native to the Go ecosystem.

Highlights


ai-powerednatural-languageasync
cdpfast

Example Use


```python from browser_use import Agent from langchain_openai import ChatOpenAI import asyncio async def main(): # Create an AI agent with a language model agent = Agent( task="Go to reddit.com/r/webscraping, find the top 5 posts " "from today, and extract their titles and scores", llm=ChatOpenAI(model="gpt-4o"), ) # Run the agent - it navigates and extracts automatically result = await agent.run() print(result) # More complex multi-step task agent = Agent( task="Go to example.com/login, log in with user@test.com " "and password 'test123', then navigate to the dashboard " "and extract all notification messages", llm=ChatOpenAI(model="gpt-4o"), ) result = await agent.run() print(result) asyncio.run(main()) ```
```go package main import ( "fmt" "github.com/go-rod/rod" "github.com/go-rod/rod/lib/launcher" ) func main() { // Launch browser url := launcher.New().Headless(true).MustLaunch() browser := rod.New().ControlURL(url).MustConnect() defer browser.MustClose() // Navigate and auto-wait for the page to load page := browser.MustPage("https://example.com") page.MustWaitStable() // Find elements and extract text - auto-waits for element title := page.MustElement("h1").MustText() fmt.Println("Title:", title) // Fill in a form page.MustElement("input[name='search']").MustInput("web scraping") page.MustElement("button[type='submit']").MustClick() // Wait for results and extract page.MustWaitStable() results := page.MustElements(".result-item") for _, el := range results { text := el.MustText() href := el.MustElement("a").MustProperty("href").String() fmt.Printf("Result: %s (%s)\n", text, href) } // Take screenshot of specific element page.MustElement(".results").MustScreenshot("results.png") } ```

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