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Browser automations are multi-step automations written in code. You launch a cloud browser, get a Playwright page with AI methods layered on top, and write your automation in Python or TypeScript. The code lives in your repo, runs in your CI, and deploys like any other software. This is the code-first path. If you prefer building automations visually with drag-and-drop blocks, see Workflows in the Cloud UI docs.
Workflows vs. Browser Automation: Workflows are built and run in the Cloud UI, no code required. Browser automations are built and run in code using Page, Agent, and Browser. Both can do multi-step work across pages. Choose based on whether your team prefers a visual editor or a code editor.
This guide walks through a real example: logging into a vendor portal, extracting invoice data, and downloading a PDF. Four steps:
  1. Launch a browser and get a page
  2. Navigate and interact with the page using AI actions, selectors, or both
  3. Use the agent for complex goals like login, multi-step tasks, and file downloads
  4. Run the script and check results

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Step 1: Launch a browser and get a page

Every automation starts by launching a cloud browser and getting a page. The browser is a Chromium instance hosted by Skyvern. The page is a Playwright page with AI methods added on top.
Install the SDK first if you haven’t:
pip install skyvern
All code snippets below run inside an async function. See the complete example for the full runnable script.
from skyvern import Skyvern

skyvern = Skyvern(api_key="YOUR_API_KEY")
browser = await skyvern.launch_cloud_browser()
page = await browser.get_working_page()
The browser stays alive until you call browser.close() or the session times out (default: 60 minutes). All pages inside it share cookies, localStorage, and auth state. For browser launch options (timeouts, proxies, connecting to local browsers), see Managing Browsers.

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Step 2: Navigate and interact with the page

Once you have a page, you can interact with it using standard Playwright, AI actions, or both. For the full list of available methods and parameters, see the Actions Reference. 
await page.goto("https://vendor-portal.example.com")

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Use AI actions (no selectors needed)

Four methods let you interact with the page using natural language. Skyvern screenshots the page and determines which elements to target. 
# Perform any action. Returns None.
await page.act("Click the login button")

# Extract structured data. Returns dict (or list if schema root is array).
data = await page.extract(
    "Extract all product names and prices",
    schema={
        "type": "array",
        "items": {
            "type": "object",
            "properties": {
                "name": {"type": "string"},
                "price": {"type": "number"},
            },
        },
    },
)

# Check page state. Returns bool.
is_logged_in = await page.validate("The user is logged in")

# Ask the AI a question. Returns {"llm_response": str}.
result = await page.prompt("What is the total at the bottom of the table?")
answer = result["llm_response"]

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Use selectors with AI fallback

click, fill, and select_option accept both a CSS selector and an AI prompt. The selector runs first. If it fails, the AI takes over. 
# Selector only (fast, deterministic)
await page.click("#submit-button")
await page.fill("#email", value="user@example.com")

# AI only (no selector needed, resilient to layout changes)
await page.click(prompt="Click the 'Submit' button")
await page.fill(prompt="Fill 'user@example.com' in the email field")

# Both - selector first, AI fallback (best for production)
await page.click("#submit-button", prompt="Click the 'Submit' button")
await page.fill("#email", value="user@example.com", prompt="Fill the email field")

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Mix Playwright and AI

Standard Playwright methods work directly. Use selectors where you know the DOM, AI where you don’t. 
await page.goto("https://example.com/login")
await page.fill("#username", value="demo@example.com")    # Playwright - known selector
await page.fill("#password", value="s3cur3-p4ss")         # Playwright - known selector
await page.click(prompt="Click the sign-in button")       # AI - button text varies
await page.wait_for_selector("#dashboard")                # Playwright - wait for page load
data = await page.extract("Extract the account balance")  # AI - table layout varies

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Step 3: Use the agent for complex goals

For multi-step goals (“log in with 2FA”, “navigate to billing and download the invoice”), hand off to the agent. The agent runs a full AI task loop inside your page, preserving all browser state.

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Login with stored credentials

await page.agent.login(
    credential_type="skyvern",
    credential_id="cred_123"
)
The agent handles multi-page login flows, CAPTCHAs, and 2FA automatically. Four credential providers: skyvern (built-in vault), bitwarden, onepassword, azure_vault. Store credentials via the Credentials API.

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Run a multi-step task

result = await page.agent.run_task(
    "Go to the billing page and extract all invoice details",
    data_extraction_schema={
        "type": "object",
        "properties": {
            "invoice_number": {"type": "string"},
            "amount": {"type": "string"},
        },
    },
)
print(result.output)
# {"invoice_number": "INV-2025-042", "amount": "$1,250.00"}
After the agent finishes, you take back control. The page retains all state: 
await page.agent.run_task("Navigate to the settings page")
# Agent is done - use direct page actions
settings = await page.extract("Extract all notification preferences")
await page.click("#save-button")

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Download files

result = await page.agent.download_files(
    "Download the Q4 2025 financial report",
    download_suffix=".pdf",
    download_timeout=30,
)

for file in result.downloaded_files or []:
    print(f"Downloaded: {file.url}")

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Run a workflow on the page

If you have built a workflow, run it on a page you already control: 
await page.agent.login(credential_type="skyvern", credential_id="cred_123")
result = await page.agent.run_workflow(
    "wpid_monthly_report",
    parameters={"month": "2025-03"}
)
agent.run_workflow vs skyvern.run_workflow: The top-level run_workflow opens its own browser. Use agent.run_workflow when you need to log in first or do setup before the workflow runs.

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Complete example

Putting it all together: log into a vendor portal, extract invoices, and download a statement. 
import asyncio
from skyvern import Skyvern

async def main():
    skyvern = Skyvern(api_key="YOUR_API_KEY")
    browser = await skyvern.launch_cloud_browser()
    page = await browser.get_working_page()

    # Navigate
    await page.goto("https://vendor-portal.example.com")

    # Login with stored credentials
    await page.agent.login(credential_type="skyvern", credential_id="cred_abc123")

    # Extract data using a mix of Playwright and AI
    await page.click("#billing-tab")
    invoices = await page.extract(
        "Extract all invoice numbers, dates, and amounts",
        schema={
            "type": "array",
            "items": {
                "type": "object",
                "properties": {
                    "invoice_number": {"type": "string"},
                    "date": {"type": "string"},
                    "amount": {"type": "string"},
                },
            },
        },
    )

    # Download a file
    result = await page.agent.download_files(
        "Download the latest monthly statement",
        download_suffix=".pdf",
    )

    # Check results
    print(f"Found {len(invoices)} invoices")
    for inv in invoices:
        print(f"  {inv['invoice_number']}: {inv['amount']}")

    for file in result.downloaded_files or []:
        print(f"Downloaded: {file.url}")

    await browser.close()

asyncio.run(main())

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Step 4: Run and get results

Run the script: 
python your_automation.py
You’ll see the browser session URL in the console output. Open it in your browser to watch the automation run in real time.

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Example output

Here’s what the Complete Example prints, grouped by the call that produced each block: 
# skyvern.launch_cloud_browser()
[Skyvern] Launched new cloud browser session  url=https://app.skyvern.com/browser-session/pbs_519895987620976102

# page.agent.login(...)
[Skyvern] AI login workflow finished  run_id=wr_519896041203554782  status=completed

# page.extract(...)
[Skyvern] AI extract  prompt=Extract all invoice numbers, dates, and amounts

# page.agent.download_files(...)
[Skyvern] Starting AI file download workflow  navigation_goal=Download the latest monthly statement
[Skyvern] AI file download workflow is running, this may take a while  run_id=wr_519896107880060430
[Skyvern] AI file download workflow finished  run_id=wr_519896107880060430  status=completed

# print(f"Found {len(invoices)} invoices")  +  for inv in invoices: print(...)
Found 3 invoices
  INV-2025-042: $2,340.00
  INV-2025-043: $1,850.00
  INV-2025-044: $3,100.00

# for file in result.downloaded_files: print(f"Downloaded: {file.url}")
Downloaded: https://skyvern-uploads.s3.amazonaws.com/downloads/production/o_510.../wr_519.../statement.pdf?AWS...
The [Skyvern] ... lines come from the SDK’s built-in logger and stream in real time as each call runs. Your own print output appears after the awaited call returns. For the full response shape, see TaskRunResponse and WorkflowRunResponse.

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View results in the Cloud UI

Every run appears in the Runs page. Click any run to see:
  • Recording - video of the browser session
  • Actions - step-by-step timeline with screenshots and AI reasoning
  • Output - extracted data as JSON
  • Artifacts - screenshots, HAR files, generated code

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Artifacts

Every run captures recordings, screenshots, AI reasoning logs, network HAR files, and downloaded files. Access them via the Cloud UI or programmatically: 
artifacts = await skyvern.get_run_artifacts(result.run_id)
for artifact in artifacts:
    print(f"{artifact.artifact_type}: {artifact.uri}")
For the full artifact type reference and debugging workflows, see Using Artifacts.

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Next steps

Actions Reference

Every page action and agent method with parameters and return types

Managing Browsers

Launch options, multiple tabs, proxies, connecting to local browsers

Store Credentials

Set up credentials for automated login with the agent

SDK Reference

Every SDK method, parameter, and type on one page (Python + TypeScript)

API Reference

Full OpenAPI spec for every REST endpoint

llms.txt

Machine-readable index of the entire documentation for AI coding agents