iframe-proxy | Sunbelt Computer Software

Browser automations are built in code using three layers: Page (AI-enhanced Playwright), Agent (multi-step AI goals), and Browser (cloud Chromium instance). This page lists every operation available on a Page or through an Agent. For the full SDK documentation with all parameter options, see the SDK Reference. If you’re building automations visually instead, see blocks reference for the equivalent operations in the Cloud UI agent editor.

Quick reference

Page actions

Action	Purpose	Returns
`act`	Perform any action from a natural-language prompt	`None`
`extract`	Pull structured data from the page	`dict`, `list`, `str`, or `None`
`validate`	Assert a condition about the page	`bool`
`prompt`	Ask the LLM a question about the page	`dict`, `list`, `str`, or `None`
`click`	Click an element (selector, AI, or both)	`str \| None`
`fill`	Fill an input field (selector, AI, or both)	`str`
`select_option`	Select a dropdown option (selector, AI, or both)	`str \| None`
`type`	Enter text into an input; same as `fill` (Python only)	`str`
`hover`	Move mouse over an element (Python only)	`str`
`scroll`	Scroll the page by pixel offset (Python only)	`None`
`upload_file`	Upload files to a file input (Python only)	`str`
`locator`	Locate an element with AI, returns a chainable Locator (Python only)	`Locator`

Agent methods

Method	Purpose	Returns
`agent.login`	Authenticate with stored credentials	`WorkflowRunResponse`
`agent.run_task`	Run a multi-step AI task on the current page	`TaskRunResponse`
`agent.download_files`	Navigate and download files	`WorkflowRunResponse`
`agent.run_workflow`	Run a Cloud UI workflow on the current page	`WorkflowRunResponse`

Form automation (Python only)

Method	Purpose	Returns
`fill_form`	AI-powered single-page form fill	`None`
`fill_multipage_form`	Form fill across multiple pages	`int` (pages filled)
`fill_from_mapping`	Fill fields by index-to-value mapping	`None`
`extract_form_fields`	Extract all form field metadata	`list[dict]`
`validate_mapping`	Check if a field mapping is valid	`bool`
`fill_autocomplete`	Fill input with typeahead handling	`str`

iframe management (Python only)

Method	Purpose	Returns
`frame_switch`	Switch context to an iframe	`dict`
`frame_main`	Switch back to the main frame	`dict`
`frame_list`	List all frames on the page	`list[dict]`

Page actions

act

Perform any action described in natural language.

await page.act("Click the login button")
await page.act("Scroll down to the pricing section")

await page.act("Click the login button")
await page.act("Scroll down to the pricing section")

Parameter	Type	Required	Description
`prompt`	`str`	Yes	What action to perform
`skip_refresh`	`bool`	No	Skip page refresh before acting
`use_economy_tree`	`bool`	No	Use a smaller DOM tree for faster processing

Returns: None SDK reference: act

extract

Pull structured data from the visible page.

data = await page.extract(
    "Extract all product names and prices",
    schema={
        "type": "array",
        "items": {
            "type": "object",
            "properties": {
                "name": {"type": "string"},
                "price": {"type": "number"},
            },
        },
    },
)

const data = await page.extract({
    prompt: "Extract all product names and prices",
    schema: {
        type: "array",
        items: {
            type: "object",
            properties: {
                name: { type: "string" },
                price: { type: "number" },
            },
        },
    },
})

Parameter	Type	Required	Description
`prompt`	`str`	Yes	What to extract
`schema`	`dict \| list \| str`	No	JSON Schema for typed output
`error_code_mapping`	`dict`	No	Map custom error codes

Returns: dict, list, str, or None SDK reference: extract

validate

Assert a condition about the current page state.

is_logged_in = await page.validate("The user is logged in")

const isLoggedIn = await page.validate("The user is logged in")

Parameter	Type	Required	Description
`prompt`	`str`	Yes	Condition to check
`model`	`dict`	No	Override LLM model config

Returns: bool SDK reference: validate

prompt

Ask the LLM a question about the current page.

result = await page.prompt(
    "How many items are in the navigation menu?",
    schema={"type": "object", "properties": {"count": {"type": "integer"}}}
)

const result = await page.prompt(
    "How many items are in the navigation menu?",
    { schema: { type: "object", properties: { count: { type: "integer" } } } }
)

Parameter	Type	Required	Description
`prompt`	`str`	Yes	Question to ask
`schema`	`dict`	No	JSON Schema for structured response
`model`	`dict`	No	Override LLM model config

Returns: dict, list, str, or None. Without a schema, returns a dict of the form {"llm_response": "..."} (TypeScript: { llmResponse: "..." }). With a schema, returns data shaped to your schema. SDK reference: prompt

click

Click an element using a selector, AI prompt, or both.

await page.click("#submit-button")                                       # selector
await page.click(prompt="Click the 'Submit' button")                     # AI
await page.click("#submit-button", prompt="Click the 'Submit' button")   # both

await page.click("#submit-button")                                       // selector
await page.click({ prompt: "Click the 'Submit' button" })                // AI
await page.click("#submit-button", { prompt: "Click the 'Submit' button" })  // both

Parameter	Type	Required	Description
`selector`	`str`	No	CSS selector
`prompt`	`str`	No	AI prompt (fallback or primary)
`ai`	`str`	No	AI mode: `"fallback"` (default) or `None`

Returns: str | None (resolved selector) SDK reference: click

fill

Fill an input field using a selector, AI prompt, or both.

await page.fill("#email", value="user@example.com")                         # selector
await page.fill(prompt="Fill 'user@example.com' in the email field")         # AI
await page.fill("#email", value="user@example.com", prompt="Fill email")     # both

await page.fill("#email", "user@example.com")                               // selector
await page.fill({ prompt: "Fill 'user@example.com' in the email field" })    // AI
await page.fill("#email", "user@example.com", { prompt: "Fill email" })      // both

Parameter	Type	Required	Description
`selector`	`str`	No	CSS selector
`value`	`str`	No	Value to fill
`prompt`	`str`	No	AI prompt (fallback or primary)
`ai`	`str`	No	AI mode: `"fallback"` (default) or `None`
`totp_identifier`	`str`	No	TOTP identifier for 2FA fields
`totp_url`	`str`	No	TOTP URL

Returns: str (resolved selector) SDK reference: fill

select_option

Select a dropdown option using a selector, AI prompt, or both.

await page.select_option("#country", value="us")                                       # selector
await page.select_option(prompt="Select 'United States' from the country dropdown")    # AI
await page.select_option("#country", value="us", prompt="Select United States")         # both

await page.selectOption("#country", { value: "us" })                                       // selector
await page.selectOption({ prompt: "Select 'United States' from the country dropdown" })    // AI
await page.selectOption("#country", { value: "us", prompt: "Select United States" })        // both

Parameter	Type	Required	Description
`selector`	`str`	No	CSS selector
`value`	`str \| list[str]`	No	Option value(s) to select
`prompt`	`str`	No	AI prompt (fallback or primary)
`ai`	`str`	No	AI mode: `"fallback"` (default) or `None`

Returns: str | None (resolved selector) SDK reference: select_option

type

Enter text into an input. type behaves the same as fill: with a selector, the value is set in one step rather than typed key by key. For fields that react to individual key presses (search autocomplete, OTP inputs), use fill_autocomplete or press_sequentially on a Playwright locator. Python only.

# Input via selector
await page.type("#search", value="wireless headphones")

# AI-powered type
await page.type(prompt="Type 'hello' into the search box")

# Selector with AI fallback
await page.type("#search", value="query text", prompt="Type into the search field")

# TOTP input from a stored secret
await page.type("#otp", totp_identifier="my-app")

# TOTP generated on the fly from an otpauth URI
await page.type("#otp", totp_url="otpauth://totp/Example:alice?secret=JBSWY3DPEHPK3PXP")

Parameter	Type	Required	Description
`selector`	`str`	No	CSS or XPath selector for the input field
`value`	`str`	No	Text to enter
`prompt`	`str`	No	Natural-language description of the target field
`ai`	`str`	No	AI mode: `"fallback"` (default) tries the selector first, then AI
`totp_identifier`	`str`	No	Identifier for a stored TOTP secret
`totp_url`	`str`	No	`otpauth://` URI to generate a one-time password on the fly

Returns: str (resolved selector) SDK reference: type

hover

Move the mouse over an element. Python only.

# Simple hover
await page.hover("#menu-item")

# Hover with a hold duration (useful for tooltip reveals)
await page.hover("#tooltip-trigger", hold_seconds=1.5)

# Hover with intention logging for debugging
await page.hover("#menu-item", intention="Reveal the main menu dropdown")

Parameter	Type	Required	Description
`selector`	`str`	Yes	CSS or XPath selector for the target element
`timeout`	`float`	No	Max wait time in milliseconds for the element. Defaults to `BROWSER_ACTION_TIMEOUT_MS`
`hold_seconds`	`float`	No	How long to hold the hover, in seconds. Default `0.0`
`intention`	`str`	No	Description of the hover intent, used for logging

Returns: str (resolved selector) SDK reference: hover

scroll

Scroll the page by a pixel offset along the x and y axes. Python only.

await page.scroll(0, 500)   # Scroll down 500px
await page.scroll(0, -300)  # Scroll up 300px
await page.scroll(200, 0)   # Scroll right 200px

Parameter	Type	Required	Description
`scroll_x`	`int`	Yes	Horizontal scroll offset in pixels. Positive values scroll right
`scroll_y`	`int`	Yes	Vertical scroll offset in pixels. Positive values scroll down

Returns: None SDK reference: scroll

upload_file

Upload a file to a file input. Pass a selector for direct Playwright behavior, a prompt for AI-powered file input detection, or both. Python only.

# Direct selector
await page.upload_file("#file-input", files="/path/to/file.pdf")

# AI-powered file input detection (no selector needed)
await page.upload_file(prompt="Upload the resume to the file input")

# Selector with AI fallback: try the selector first, use AI if it fails
await page.upload_file(
    "#file-input",
    files="/path/to/file.pdf",
    prompt="Upload the resume to the file input",
)

Parameter	Type	Required	Description
`selector`	`str`	No	CSS or XPath selector for the file input
`files`	`str \| list[str]`	No	File path or list of file paths to upload
`prompt`	`str`	No	Natural-language description of the file input to target
`ai`	`str`	No	AI mode: `"fallback"` (default) tries the selector first, then AI

Returns: str (resolved selector) SDK reference: upload_file

locator

Locate an element using a CSS/XPath selector, an AI prompt, or both. When called with a prompt, returns an AILocator, a lazy Playwright Locator that resolves the element via AI on first use. Python only.

# AI-powered: pass a natural-language prompt
locator = page.locator(prompt="the submit button")
await locator.click()

# Full Playwright chaining works
text = await page.locator(prompt="the error message").text_content()

# Standard Playwright selector (no AI, identical to vanilla Playwright)
locator = page.locator("#submit-btn")
await locator.click()

# Selector with AI fallback: try the selector first, use AI if it fails
locator = page.locator("#submit-btn", prompt="the submit button")
await locator.click()

When called with only a selector (no prompt), page.locator(selector) behaves exactly like the standard Playwright page.locator(selector). No AI is involved.

Parameter	Type	Required	Description
`selector`	`str`	No	CSS or XPath selector passed to Playwright’s built-in `locator()`
`prompt`	`str`	No	Natural-language description of the element. When provided, returns an `AILocator` that resolves via AI
`ai`	`str`	No	AI mode: `"fallback"` (default) tries the selector first, then AI
`**kwargs`		No	Additional keyword arguments forwarded to Playwright’s `locator()`

Returns: Locator (standard Playwright Locator when only a selector is given, or AILocator when a prompt is provided)

AILocator methods

When prompt is provided, the returned AILocator supports all standard Playwright Locator methods:

Actions: click(), fill(), type(), select_option(), check(), uncheck(), clear(), hover(), focus(), press()
Queries: text_content(), inner_text(), inner_html(), get_attribute(), input_value(), count()
State: is_visible(), is_hidden(), is_enabled(), is_disabled(), is_editable(), is_checked()
Chaining: first(), last(), nth(), filter(), locator(), get_by_text(), get_by_role(), get_by_label(), get_by_placeholder()
Utilities: wait_for(), screenshot(), playwright_locator (access raw Locator)

SDK reference: locator

Agent methods

All agent methods return either a TaskRunResponse (for agent.run_task) or a WorkflowRunResponse (for agent.login, agent.download_files, agent.run_workflow). Follow the links for the full field list. Authenticate with stored credentials. Handles multi-page login flows, CAPTCHAs, and 2FA.

await page.agent.login(
    credential_type="skyvern",
    credential_id="cred_123"
)

await page.agent.login("skyvern", {
    credentialId: "cred_123"
})

Parameter	Type	Required	Description
`credential_type`	`CredentialType`	No	`skyvern` (default), `bitwarden`, `1password`, or `azure_vault`
`credential_id`	`str`	No	Credential ID (required for `skyvern` type)
`bitwarden_collection_id`, `bitwarden_item_id`	`str`	No	Bitwarden item to use (for `bitwarden` type)
`onepassword_vault_id`, `onepassword_item_id`	`str`	No	1Password item to use (for `1password` type)
`azure_vault_name`, `azure_vault_username_key`, `azure_vault_password_key`, `azure_vault_totp_secret_key`	`str`	No	Azure Key Vault secrets to use (for `azure_vault` type)
`url`	`str`	No	Login page URL
`prompt`	`str`	No	Additional login instructions
`timeout`	`float`	No	Max wait time in seconds (default: 1800)

Returns: WorkflowRunResponse SDK reference: agent.login

agent.run_task

Run a multi-step AI task on the current page.

result = await page.agent.run_task(
    "Go to the billing page and download the latest invoice",
    data_extraction_schema={
        "type": "object",
        "properties": {
            "invoice_number": {"type": "string"},
            "amount": {"type": "string"},
        },
    },
)
print(result.output)

const result = await page.agent.runTask(
    "Go to the billing page and download the latest invoice",
    {
        dataExtractionSchema: {
            type: "object",
            properties: {
                invoice_number: { type: "string" },
                amount: { type: "string" },
            },
        },
    },
)
console.log(result.output)

Parameter	Type	Required	Description
`prompt`	`str`	Yes	Multi-step goal description
`data_extraction_schema`	`dict \| str`	No	JSON Schema for structured output. See Extract Structured Data.
`max_steps`	`int`	No	Cap AI steps. The run ends with status `failed` (“Reached the maximum steps”) if hit. Controls cost; each step is one AI decision + action cycle.
`engine`	`RunEngine`	No	AI engine. Defaults to `skyvern-1.0`. On Skyvern Cloud, blocks with no engine set run on Skyvern 3.0 in agents created since October 1, 2026, and the engine selector labels `skyvern-3.0` Recommended. `skyvern-2.0` remains available for existing Skyvern 2.0 agents and explicitly requested Skyvern 2.0 task runs. Other options: `skyvern-3.0`, `openai-cua`, `anthropic-cua`, `ui-tars`, `yutori-navigator`.
`model`	`dict` / `Record<string, unknown>`	No	Override LLM model configuration
`url`	`str` / `string`	No	URL to navigate to (defaults to current page URL)
`webhook_url`	`str` / `string`	No	Callback URL. Skyvern POSTs the full run result on completion or failure. See Webhooks.
`totp_identifier`	`str` / `string`	No	Identifier for push-based TOTP. See Two-factor authentication.
`totp_url`	`str` / `string`	No	Endpoint Skyvern calls to pull TOTP codes. See Two-factor authentication.
`title`	`str` / `string`	No	Display name for this run
`error_code_mapping`	`dict` / `Record<string, string>`	No	Map custom error codes to conditions. Keys are your error codes, values describe when to trigger them. If matched, the run’s `errors` list contains an entry with `error_code` set to your code.
`user_agent`	`str` / `string`	No	Custom User-Agent header for the browser
`timeout`	`float`	No	Max wait in seconds (default: 1800)

Returns: TaskRunResponse SDK reference: agent.run_task

agent.download_files

Navigate and download files from the current page.

result = await page.agent.download_files(
    "Download the latest invoice PDF",
    download_suffix="invoice",
    download_timeout=30,
)

const result = await page.agent.downloadFiles(
    "Download the latest invoice PDF",
    {
        downloadSuffix: "invoice",
        downloadTimeout: 30,
    },
)

Parameter	Type	Required	Description
`prompt`	`str`	Yes	What to download
`download_suffix`	`str`	No	Filename for the saved file. A name without an extension (e.g., `"invoice"`) gets the downloaded file’s extension (`invoice.pdf`); a full name like `"invoice.pdf"` is used as is. Don’t pass only an extension such as `".pdf"`: it becomes the whole name (`.pdf.pdf`). `{{ original_filename }}` inserts the site’s own file name (`"archive_{{ original_filename }}"` → `archive_Q4 Report.pdf`).
`download_timeout`	`float`	No	Soft hint (seconds) for how long to wait for a download. The overall `timeout` is what actually fails the run.
`max_steps_per_run`	`int`	No	Cap AI steps
`timeout`	`float`	No	Max wait in seconds (default: 1800)

Returns: WorkflowRunResponse SDK reference: agent.download_files

agent.run_workflow

Run a Cloud UI workflow on the current page.

result = await page.agent.run_workflow(
    "wpid_monthly_report",
    parameters={"month": "2025-03"}
)

const result = await page.agent.runWorkflow(
    "wpid_monthly_report",
    { parameters: { month: "2025-03" } }
)

Parameter	Type	Required	Description
`workflow_id`	`str`	Yes	Workflow permanent ID
`parameters`	`dict`	No	Workflow input parameters
`template`	`bool`	No	Run a template workflow
`title`	`str` / `string`	No	Display name for this run
`webhook_url`	`str` / `string`	No	Callback URL for run completion. See Webhooks.
`totp_url`	`str` / `string`	No	Endpoint for pulling TOTP codes
`totp_identifier`	`str` / `string`	No	Identifier for push-based TOTP
`max_elapsed_time_minutes`	`int`	No	Time out the workflow run after this many minutes
`run_metadata`	`dict[str, str]`	No	String key/value metadata to attach to the run
`timeout`	`float`	No	Max wait in seconds (default: 1800)

Returns: WorkflowRunResponse SDK reference: agent.run_workflow

Form automation (Python only)

fill_form

Fill a single-page form using AI. Pass a data dict describing the values to fill.

# Simple form fill
await page.fill_form(
    data={"name": "John Doe", "email": "john@example.com", "role": "Engineer"},
)

# With a custom prompt to guide the AI
await page.fill_form(
    data={"name": "John Doe", "email": "john@example.com"},
    prompt="Fill out the registration form with the provided user details",
)

Parameter	Type	Required	Description
`data`	`dict[str, Any]`	Yes	Key-value pairs of form data to fill
`prompt`	`str`	No	Instruction for the AI. Defaults to `"Fill out the form"`

Returns: None SDK reference: fill_form

fill_multipage_form

Fill a form that spans multiple pages, handling page transitions automatically.

pages_filled = await page.fill_multipage_form(
    data={"name": "John Doe", "email": "john@example.com", "address": "123 Main St"},
    max_pages=5,
)
print(f"Filled {pages_filled} pages")

Parameter	Type	Required	Description
`data`	`dict[str, Any]`	Yes	Key-value pairs of form data to fill across all pages
`prompt`	`str`	No	Instruction for the AI. Defaults to `"Fill out the form"`
`next_button`	`str`	No	Selector or description of the button to advance to the next page
`max_pages`	`int`	No	Maximum number of pages to fill. Defaults to `10`
`timeout_seconds`	`float`	No	Timeout in seconds for the entire operation. Defaults to `300`

Returns: int (the number of pages filled) SDK reference: fill_multipage_form

fill_from_mapping

Fill form fields using an explicit index-based mapping produced by extract_form_fields. Use this when you need precise control over which field gets which value.

fields = await page.extract_form_fields()
await page.fill_from_mapping(
    form_fields=fields,
    mapping={0: "John", 1: "Doe", 2: "john@example.com"},  # keys are field indices
    data={"name": "John Doe"},  # optional context
)

Parameter	Type	Required	Description
`form_fields`	`list[dict[str, Any]]`	Yes	Field metadata returned by `extract_form_fields`
`mapping`	`dict[int, str \| list \| bool \| None]`	Yes	Map of field index to the value to fill
`data`	`dict[str, Any] \| None`	No	Optional source data for context. Defaults to `None`

Returns: None SDK reference: fill_from_mapping

extract_form_fields

Extract all form fields with metadata from the current page. Use the output to drive fill_from_mapping or validate_mapping.

fields = await page.extract_form_fields()
# Returns a list of dicts with field name, type, options, and other metadata:
# [{"name": "First Name", "type": "text", "index": 0, ...}, ...]

Returns: list[dict[str, Any]] where each dict contains field name, type, options, and other metadata. SDK reference: extract_form_fields

validate_mapping

Check if a field mapping is correct for the current form.

fields = await page.extract_form_fields()
is_valid = await page.validate_mapping(
    form_fields=fields,
    mapping={0: "John", 1: "Doe"},
    prompt="Validate the name fields are filled correctly",
)

Parameter	Type	Required	Description
`form_fields`	`list[dict[str, Any]]`	Yes	Field metadata returned by `extract_form_fields`
`mapping`	`dict[int, str \| list \| bool \| None]`	Yes	Map of field index to the value to validate
`prompt`	`str`	Yes	Instruction describing what to validate

Returns: bool (True if the mapping is valid, False otherwise) SDK reference: validate_mapping

fill_autocomplete

Fill an input that has autocomplete/typeahead behavior. Types the value, waits for suggestions, then clicks the matching option.

# Direct selector
await page.fill_autocomplete(
    selector="#city",
    value="San Francisco",
    option_selector=".autocomplete-option",
    wait_seconds=1.5,
)

# AI-powered
await page.fill_autocomplete(prompt="Fill 'San Francisco' in the city autocomplete")

Parameter	Type	Required	Description
`selector`	`str`	No	CSS selector for the input field
`value`	`str`	No	The text value to type into the field
`prompt`	`str`	No	Natural-language description of the field and value
`ai`	`str`	No	AI mode: `"fallback"` (default) tries the selector first, then AI
`option_selector`	`str`	No	CSS selector for the autocomplete dropdown options
`wait_seconds`	`float`	No	Seconds to wait for the dropdown to appear. Default `1.5`
`**kwargs`		No	Standard Playwright fill options (e.g., `timeout`, `force`)

Returns: str (resolved selector) SDK reference: fill_autocomplete

iframe management (Python only)

frame_switch

Switch the working context to an iframe. Exactly one of selector, name, or index must be provided.

# By CSS selector
await page.frame_switch(selector="#payment-iframe")

# By frame name
await page.frame_switch(name="checkout")

# By index into page.frames (0 is the main frame, so the first iframe is usually 1)
await page.frame_switch(index=1)

Parameter	Type	Required	Description
`selector`	`str`	No	CSS selector for the iframe element
`name`	`str`	No	The `name` attribute of the iframe
`index`	`int`	No	Index into `page.frames`. `0` is the main frame.

Exactly one of selector, name, or index must be provided.

Returns: dict[str, Any] (frame metadata for the switched-to iframe) SDK reference: frame_switch

frame_main

Switch back to the main page frame after working inside an iframe.

page.frame_main()

Returns: dict[str, str] SDK reference: frame_main

frame_list

List all frames on the current page with metadata.

frames = await page.frame_list()
# [{"name": "checkout", "url": "...", "index": 0}, ...]

Returns: list[dict[str, Any]] (metadata for each frame on the page) SDK reference: frame_list

Sunbelt Computer Software

PL/B Language Development and Support

​Quick reference

​Page actions

​Agent methods

​Form automation (Python only)

​iframe management (Python only)

​Page actions

​act

​extract

​validate

​prompt

​click

​fill

​select_option

​type

​hover

​scroll

​upload_file

​locator

​AILocator methods

​Agent methods

​agent.login

​agent.run_task

​agent.download_files

​agent.run_workflow

​Form automation (Python only)

​fill_form

​fill_multipage_form

​fill_from_mapping

​extract_form_fields

​validate_mapping

​fill_autocomplete

​iframe management (Python only)

​frame_switch

​frame_main

​frame_list

Quick reference

Page actions

Agent methods

Form automation (Python only)

iframe management (Python only)

Page actions

act

extract

validate

prompt

click

fill

select_option

type

hover

scroll

upload_file

locator

AILocator methods

Agent methods

agent.login

agent.run_task

agent.download_files

agent.run_workflow

Form automation (Python only)

fill_form

fill_multipage_form

fill_from_mapping

extract_form_fields

validate_mapping

fill_autocomplete

iframe management (Python only)

frame_switch

frame_main

frame_list