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4.2 KiB
4.2 KiB
Actor API (Legacy Direct Browser Control)
Low-level Playwright-like browser automation built on CDP. Use for precise, deterministic operations alongside the AI agent.
Table of Contents
Architecture
Browser (BrowserSession) → Page → Element
→ Mouse
→ AI Features (extract, find by prompt)
NOT Playwright — built on CDP with a subset of the Playwright API. Key differences:
get_elements_by_css_selector()returns immediately (no visibility wait)- Manual timing required after navigation
evaluate()requires arrow function format:() => {}
Browser Methods
browser = Browser()
await browser.start()
page = await browser.new_page("https://example.com") # Open new tab
pages = await browser.get_pages() # List all pages
current = await browser.get_current_page() # Active page
await browser.close_page(page) # Close tab
await browser.stop() # Cleanup
Page Methods
Navigation
goto(url: str)— Navigate to URLgo_back()— Back in historygo_forward()— Forward in historyreload()— Reload page
Element Finding
get_elements_by_css_selector(selector: str) -> list[Element]— Immediate returnget_element(backend_node_id: int) -> Element— By CDP node IDget_element_by_prompt(prompt: str, llm) -> Element | None— LLM-poweredmust_get_element_by_prompt(prompt: str, llm) -> Element— Raises if not found
JavaScript & Controls
evaluate(page_function: str, *args) -> str— Execute JS (arrow function format)press(key: str)— Keyboard inputset_viewport_size(width: int, height: int)screenshot(format='jpeg', quality=None) -> str— Base64 screenshot
Information
get_url() -> strget_title() -> strmouse -> Mouse— Mouse instance
AI Features
extract_content(prompt: str, structured_output: type[T], llm) -> T— LLM-powered extraction
Element Methods
Interactions
click(button='left', click_count=1, modifiers=None)fill(text: str, clear=True)— Clear field and typehover()focus()check()— Toggle checkbox/radioselect_option(values: str | list[str])— Select dropdowndrag_to(target: Element | Position)
Properties
get_attribute(name: str) -> str | Noneget_bounding_box() -> BoundingBox | Noneget_basic_info() -> ElementInfoscreenshot(format='jpeg') -> str
Mouse Methods
mouse = page.mouse
await mouse.click(x=100, y=200, button='left', click_count=1)
await mouse.move(x=500, y=600, steps=1)
await mouse.down(button='left')
await mouse.up(button='left')
await mouse.scroll(x=0, y=100, delta_x=None, delta_y=-500)
Examples
Mixed Agent + Actor
async def main():
llm = ChatOpenAI(api_key="your-key")
browser = Browser()
await browser.start()
# Actor: precise navigation
page = await browser.new_page("https://github.com/login")
email = await page.must_get_element_by_prompt("username field", llm=llm)
await email.fill("your-username")
# Agent: AI-driven completion
agent = Agent(browser=browser, llm=llm)
await agent.run("Complete login and navigate to repositories")
await browser.stop()
JavaScript Execution
title = await page.evaluate('() => document.title')
result = await page.evaluate('(x, y) => x + y', 10, 20)
stats = await page.evaluate('''() => ({
url: location.href,
links: document.querySelectorAll('a').length
})''')
LLM-Powered Extraction
from pydantic import BaseModel
class ProductInfo(BaseModel):
name: str
price: float
product = await page.extract_content("Extract product name and price", ProductInfo, llm=llm)
Best Practices
- Use
asyncio.sleep()after navigation-triggering actions - Check URL/title changes to verify state transitions
- Implement retry logic for flaky elements
- Always call
browser.stop()for cleanup