mirror of
https://github.com/browser-use/browser-use
synced 2026-05-06 17:52:15 +02:00
Replaces pixel-based scrolling with page unit determination, allowing for more intuitive scroll actions by specifying the number of pages. Adjusts related documentation, examples, and tests to reflect this change for improved code consistency and user experience.
1041 lines
40 KiB
Python
1041 lines
40 KiB
Python
import asyncio
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import enum
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import json
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import logging
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import os
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from collections.abc import Awaitable, Callable
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from typing import Any, Generic, TypeVar, cast
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from pydantic import BaseModel
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from browser_use.agent.views import ActionModel, ActionResult
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from browser_use.browser import BrowserSession
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from browser_use.browser.types import Page
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from browser_use.controller.registry.service import Registry
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from browser_use.controller.views import (
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ClickElementAction,
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CloseTabAction,
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DoneAction,
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GoToUrlAction,
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InputTextAction,
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NoParamsAction,
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ScrollAction,
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SearchGoogleAction,
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SendKeysAction,
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StructuredOutputAction,
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SwitchTabAction,
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UploadFileAction,
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)
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from browser_use.filesystem.file_system import FileSystem
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from browser_use.llm.base import BaseChatModel
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from browser_use.llm.messages import UserMessage
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from browser_use.utils import time_execution_sync
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logger = logging.getLogger(__name__)
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async def retry_async_function(
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func: Callable[[], Awaitable[Any]], error_message: str, n_retries: int = 3, sleep_seconds: float = 1
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) -> tuple[Any | None, ActionResult | None]:
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"""
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Retry an async function n times before giving up and returning an ActionResult with an error.
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Args:
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func: Async function to retry
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error_message: Error message to use in ActionResult if all retries fail
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n_retries: Number of retries (default 3)
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sleep_seconds: Seconds to sleep between retries (default 1)
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Returns:
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Tuple of (result, None) on success or (None, ActionResult) on failure
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"""
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for attempt in range(n_retries):
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try:
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result = await func()
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return result, None
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except Exception as e:
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await asyncio.sleep(sleep_seconds)
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logger.debug(f'Error (attempt {attempt + 1}/{n_retries}): {e}')
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if attempt == n_retries - 1: # Last attempt failed
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return None, ActionResult(error=error_message + str(e))
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# Should never reach here but make type checker happy
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return None, ActionResult(error=error_message)
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Context = TypeVar('Context')
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T = TypeVar('T', bound=BaseModel)
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class Controller(Generic[Context]):
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def __init__(
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self,
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exclude_actions: list[str] = [],
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output_model: type[T] | None = None,
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display_files_in_done_text: bool = True,
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):
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self.registry = Registry[Context](exclude_actions)
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self.display_files_in_done_text = display_files_in_done_text
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"""Register all default browser actions"""
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self._register_done_action(output_model)
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# Basic Navigation Actions
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@self.registry.action(
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'Search the query in Google, the query should be a search query like humans search in Google, concrete and not vague or super long.',
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param_model=SearchGoogleAction,
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)
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async def search_google(params: SearchGoogleAction, browser_session: BrowserSession):
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search_url = f'https://www.google.com/search?q={params.query}&udm=14'
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page = await browser_session.get_current_page()
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if page.url.strip('/') == 'https://www.google.com':
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# SECURITY FIX: Use browser_session.navigate_to() instead of direct page.goto()
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# This ensures URL validation against allowed_domains is performed
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await browser_session.navigate_to(search_url)
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else:
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# create_new_tab already includes proper URL validation
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page = await browser_session.create_new_tab(search_url)
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msg = f'🔍 Searched for "{params.query}" in Google'
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logger.info(msg)
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return ActionResult(
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extracted_content=msg, include_in_memory=True, long_term_memory=f"Searched Google for '{params.query}'"
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)
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@self.registry.action(
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'Navigate to URL, set new_tab=True to open in new tab, False to navigate in current tab', param_model=GoToUrlAction
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)
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async def go_to_url(params: GoToUrlAction, browser_session: BrowserSession):
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try:
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if params.new_tab:
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# Open in new tab (logic from open_tab function)
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page = await browser_session.create_new_tab(params.url)
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tab_idx = browser_session.tabs.index(page)
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memory = f'Opened new tab with URL {params.url}'
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msg = f'🔗 Opened new tab #{tab_idx} with url {params.url}'
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logger.info(msg)
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return ActionResult(extracted_content=msg, include_in_memory=True, long_term_memory=memory)
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else:
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# Navigate in current tab (original logic)
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# SECURITY FIX: Use browser_session.navigate_to() instead of direct page.goto()
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# This ensures URL validation against allowed_domains is performed
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await browser_session.navigate_to(params.url)
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memory = f'Navigated to {params.url}'
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msg = f'🔗 {memory}'
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logger.info(msg)
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return ActionResult(extracted_content=msg, include_in_memory=True, long_term_memory=memory)
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except Exception as e:
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error_msg = str(e)
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# Check for network-related errors
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if any(
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err in error_msg
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for err in [
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'ERR_NAME_NOT_RESOLVED',
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'ERR_INTERNET_DISCONNECTED',
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'ERR_CONNECTION_REFUSED',
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'ERR_TIMED_OUT',
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'net::',
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]
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):
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site_unavailable_msg = f'Site unavailable: {params.url} - {error_msg}'
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logger.warning(site_unavailable_msg)
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return ActionResult(
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success=False, error=site_unavailable_msg, include_in_memory=True, long_term_memory=site_unavailable_msg
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)
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else:
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# Re-raise non-network errors (including URLNotAllowedError for unauthorized domains)
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raise
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@self.registry.action('Go back', param_model=NoParamsAction)
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async def go_back(_: NoParamsAction, browser_session: BrowserSession):
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await browser_session.go_back()
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msg = '🔙 Navigated back'
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logger.info(msg)
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return ActionResult(extracted_content=msg, include_in_memory=True, long_term_memory='Navigated back')
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# wait for x seconds
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@self.registry.action('Wait for x seconds default 3')
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async def wait(seconds: int = 3):
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msg = f'🕒 Waiting for {seconds} seconds'
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logger.info(msg)
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await asyncio.sleep(seconds)
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return ActionResult(extracted_content=msg, include_in_memory=True, long_term_memory=f'Waited for {seconds} seconds')
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# Element Interaction Actions
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@self.registry.action('Click element by index', param_model=ClickElementAction)
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async def click_element_by_index(params: ClickElementAction, browser_session: BrowserSession):
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# Browser is now a BrowserSession itself
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# Check if element exists in current selector map
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selector_map = await browser_session.get_selector_map()
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if params.index not in selector_map:
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# Force a state refresh in case the cache is stale
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logger.info(f'Element with index {params.index} not found in selector map, refreshing state...')
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await browser_session.get_state_summary(
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cache_clickable_elements_hashes=True
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) # This will refresh the cached state
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selector_map = await browser_session.get_selector_map()
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if params.index not in selector_map:
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# Return informative message with the new state instead of error
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max_index = max(selector_map.keys()) if selector_map else -1
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msg = f'Element with index {params.index} does not exist. Page has {len(selector_map)} interactive elements (indices 0-{max_index}). State has been refreshed - please use the updated element indices or scroll to see more elements'
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return ActionResult(extracted_content=msg, include_in_memory=True, success=False, long_term_memory=msg)
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element_node = await browser_session.get_dom_element_by_index(params.index)
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initial_pages = len(browser_session.tabs)
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# if element has file uploader then dont click
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# Check if element is actually a file input (not just contains file-related keywords)
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if element_node is not None and browser_session.is_file_input(element_node):
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msg = f'Index {params.index} - has an element which opens file upload dialog. To upload files please use a specific function to upload files '
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logger.info(msg)
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return ActionResult(extracted_content=msg, include_in_memory=True, success=False, long_term_memory=msg)
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msg = None
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try:
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assert element_node is not None, f'Element with index {params.index} does not exist'
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download_path = await browser_session._click_element_node(element_node)
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if download_path:
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emoji = '💾'
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msg = f'Downloaded file to {download_path}'
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else:
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emoji = '🖱️'
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msg = f'Clicked button with index {params.index}: {element_node.get_all_text_till_next_clickable_element(max_depth=2)}'
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logger.info(f'{emoji} {msg}')
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logger.debug(f'Element xpath: {element_node.xpath}')
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if len(browser_session.tabs) > initial_pages:
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new_tab_msg = 'New tab opened - switching to it'
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msg += f' - {new_tab_msg}'
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emoji = '🔗'
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logger.info(f'{emoji} {new_tab_msg}')
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await browser_session.switch_to_tab(-1)
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return ActionResult(extracted_content=msg, include_in_memory=True, long_term_memory=msg)
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except Exception as e:
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error_msg = str(e)
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if 'Execution context was destroyed' in error_msg or 'Cannot find context with specified id' in error_msg:
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# Page navigated during click - refresh state and return it
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logger.info('Page context changed during click, refreshing state...')
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await browser_session.get_state_summary(cache_clickable_elements_hashes=True)
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return ActionResult(
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error='Page navigated during click. Refreshed state provided.', include_in_memory=True, success=False
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)
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else:
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logger.warning(f'Element not clickable with index {params.index} - most likely the page changed')
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return ActionResult(error=error_msg, success=False)
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@self.registry.action(
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'Click and input text into a input interactive element',
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param_model=InputTextAction,
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)
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async def input_text(params: InputTextAction, browser_session: BrowserSession, has_sensitive_data: bool = False):
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if params.index not in await browser_session.get_selector_map():
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raise Exception(f'Element index {params.index} does not exist - retry or use alternative actions')
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element_node = await browser_session.get_dom_element_by_index(params.index)
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assert element_node is not None, f'Element with index {params.index} does not exist'
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try:
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await browser_session._input_text_element_node(element_node, params.text)
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except Exception:
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msg = f'Failed to input text into element {params.index}.'
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return ActionResult(error=msg)
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if not has_sensitive_data:
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msg = f'⌨️ Input {params.text} into index {params.index}'
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else:
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msg = f'⌨️ Input sensitive data into index {params.index}'
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logger.info(msg)
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logger.debug(f'Element xpath: {element_node.xpath}')
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return ActionResult(
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extracted_content=msg,
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include_in_memory=True,
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long_term_memory=f"Input '{params.text}' into element {params.index}.",
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)
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@self.registry.action('Upload file to interactive element with file path', param_model=UploadFileAction)
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async def upload_file(params: UploadFileAction, browser_session: BrowserSession, available_file_paths: list[str]):
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if params.path not in available_file_paths:
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return ActionResult(error=f'File path {params.path} is not available')
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if not os.path.exists(params.path):
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return ActionResult(error=f'File {params.path} does not exist')
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file_upload_dom_el = await browser_session.find_file_upload_element_by_index(
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params.index, max_height=3, max_descendant_depth=3
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)
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if file_upload_dom_el is None:
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msg = f'No file upload element found at index {params.index}'
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logger.info(msg)
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return ActionResult(error=msg)
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file_upload_el = await browser_session.get_locate_element(file_upload_dom_el)
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if file_upload_el is None:
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msg = f'No file upload element found at index {params.index}'
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logger.info(msg)
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return ActionResult(error=msg)
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try:
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await file_upload_el.set_input_files(params.path)
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msg = f'📁 Successfully uploaded file to index {params.index}'
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logger.info(msg)
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return ActionResult(
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extracted_content=msg,
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include_in_memory=True,
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long_term_memory=f'Uploaded file {params.path} to element {params.index}',
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)
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except Exception as e:
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msg = f'Failed to upload file to index {params.index}: {str(e)}'
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logger.info(msg)
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return ActionResult(error=msg)
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# Tab Management Actions
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@self.registry.action('Switch tab', param_model=SwitchTabAction)
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async def switch_tab(params: SwitchTabAction, browser_session: BrowserSession):
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await browser_session.switch_to_tab(params.page_id)
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page = await browser_session.get_current_page()
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try:
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await page.wait_for_load_state(state='domcontentloaded', timeout=5_000)
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# page was already loaded when we first navigated, this is additional to wait for onfocus/onblur animations/ajax to settle
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except Exception as e:
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pass
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msg = f'🔄 Switched to tab #{params.page_id} with url {page.url}'
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logger.info(msg)
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return ActionResult(
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extracted_content=msg, include_in_memory=True, long_term_memory=f'Switched to tab {params.page_id}'
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)
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@self.registry.action('Close an existing tab', param_model=CloseTabAction)
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async def close_tab(params: CloseTabAction, browser_session: BrowserSession):
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await browser_session.switch_to_tab(params.page_id)
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page = await browser_session.get_current_page()
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url = page.url
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await page.close()
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new_page = await browser_session.get_current_page()
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new_page_idx = browser_session.tabs.index(new_page)
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msg = f'❌ Closed tab #{params.page_id} with {url}, now focused on tab #{new_page_idx} with url {new_page.url}'
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logger.info(msg)
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return ActionResult(
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extracted_content=msg,
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include_in_memory=True,
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long_term_memory=f'Closed tab {params.page_id} with url {url}, now focused on tab {new_page_idx} with url {new_page.url}.',
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)
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# Content Actions
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@self.registry.action(
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"""Extract structured, semantic data (e.g. product description, price, all information about XYZ) from the current webpage based on a textual query.
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This tool takes the entire markdown of the page and extracts the query from it.
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Set extract_links=True ONLY if your query requires extracting links/URLs from the page.
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Only use this for specific queries for information retrieval from the page. Don't use this to get interactive elements - the tool does not see HTML elements, only the markdown.
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""",
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)
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async def extract_structured_data(
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query: str,
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extract_links: bool,
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page: Page,
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page_extraction_llm: BaseChatModel,
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file_system: FileSystem,
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):
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from functools import partial
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import markdownify
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strip = []
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if not extract_links:
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strip = ['a', 'img']
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# Run markdownify in a thread pool to avoid blocking the event loop
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loop = asyncio.get_event_loop()
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# Try getting page content with retries
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page_html_result, action_result = await retry_async_function(
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lambda: page.content(), "Couldn't extract page content due to an error."
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)
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if action_result:
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return action_result
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page_html = page_html_result
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markdownify_func = partial(markdownify.markdownify, strip=strip)
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content = await loop.run_in_executor(None, markdownify_func, page_html)
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# manually append iframe text into the content so it's readable by the LLM (includes cross-origin iframes)
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for iframe in page.frames:
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try:
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await iframe.wait_for_load_state(timeout=5000) # extra on top of already loaded page
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except Exception as e:
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pass
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if iframe.url != page.url and not iframe.url.startswith('data:'):
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content += f'\n\nIFRAME {iframe.url}:\n'
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# Run markdownify in a thread pool for iframe content as well
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try:
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iframe_html = await iframe.content()
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iframe_markdown = await loop.run_in_executor(None, markdownify_func, iframe_html)
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except Exception as e:
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logger.debug(f'Error extracting iframe content from within page {page.url}: {type(e).__name__}: {e}')
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iframe_markdown = ''
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content += iframe_markdown
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# limit to 40000 characters - remove text in the middle this is approx 20000 tokens
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max_chars = 40000
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if len(content) > max_chars:
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content = (
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content[: max_chars // 2]
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+ '\n... left out the middle because it was too long ...\n'
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+ content[-max_chars // 2 :]
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)
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prompt = """You convert websites into structured information. Extract information from this webpage based on the query. Focus only on content relevant to the query. If
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1. The query is vague
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2. Does not make sense for the page
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3. Some/all of the information is not available
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Explain the content of the page and that the requested information is not available in the page. Respond in JSON format.\nQuery: {query}\n Website:\n{page}"""
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try:
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formatted_prompt = prompt.format(query=query, page=content)
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response = await page_extraction_llm.ainvoke([UserMessage(content=formatted_prompt)])
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extracted_content = f'Page Link: {page.url}\nQuery: {query}\nExtracted Content:\n{response.completion}'
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# if content is small include it to memory
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MAX_MEMORY_SIZE = 600
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if len(extracted_content) < MAX_MEMORY_SIZE:
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memory = extracted_content
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include_extracted_content_only_once = False
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else:
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# find lines until MAX_MEMORY_SIZE
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lines = extracted_content.splitlines()
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display = ''
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display_lines_count = 0
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for line in lines:
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if len(display) + len(line) < MAX_MEMORY_SIZE:
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display += line + '\n'
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display_lines_count += 1
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else:
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break
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save_result = await file_system.save_extracted_content(extracted_content)
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memory = f'Extracted content from {page.url}\n<query>{query}\n</query>\n<extracted_content>\n{display}{len(lines) - display_lines_count} more lines...\n</extracted_content>\n<file_system>{save_result}</file_system>'
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include_extracted_content_only_once = True
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logger.info(f'📄 {memory}')
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return ActionResult(
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extracted_content=extracted_content,
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include_extracted_content_only_once=include_extracted_content_only_once,
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long_term_memory=memory,
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)
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except Exception as e:
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logger.debug(f'Error extracting content: {e}')
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msg = f'📄 Extracted from page\n: {content}\n'
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logger.info(msg)
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return ActionResult(error=str(e))
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|
|
# @self.registry.action(
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# 'Get the accessibility tree of the page in the format "role name" with the number_of_elements to return',
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# )
|
|
# async def get_ax_tree(number_of_elements: int, page: Page):
|
|
# node = await page.accessibility.snapshot(interesting_only=True)
|
|
|
|
# def flatten_ax_tree(node, lines):
|
|
# if not node:
|
|
# return
|
|
# role = node.get('role', '')
|
|
# name = node.get('name', '')
|
|
# lines.append(f'{role} {name}')
|
|
# for child in node.get('children', []):
|
|
# flatten_ax_tree(child, lines)
|
|
|
|
# lines = []
|
|
# flatten_ax_tree(node, lines)
|
|
# msg = '\n'.join(lines)
|
|
# logger.info(msg)
|
|
# return ActionResult(
|
|
# extracted_content=msg,
|
|
# include_in_memory=False,
|
|
# long_term_memory='Retrieved accessibility tree',
|
|
# include_extracted_content_only_once=True,
|
|
# )
|
|
|
|
@self.registry.action(
|
|
'Scroll the page by specified number of pages (set down=True to scroll down, down=False to scroll up, num_pages=number of pages to scroll like 0.5 for half page, 1.0 for one page, etc. or None for one page)',
|
|
param_model=ScrollAction,
|
|
)
|
|
async def scroll(params: ScrollAction, browser_session: BrowserSession):
|
|
"""
|
|
(a) Use browser._scroll_container for container-aware scrolling.
|
|
(b) If that JavaScript throws, fall back to window.scrollBy().
|
|
"""
|
|
page = await browser_session.get_current_page()
|
|
|
|
# Get window height with retries
|
|
dy_result, action_result = await retry_async_function(
|
|
lambda: page.evaluate('() => window.innerHeight'), 'Scroll failed due to an error.'
|
|
)
|
|
if action_result:
|
|
return action_result
|
|
window_height = dy_result or 0
|
|
|
|
# Determine scroll amount based on num_pages
|
|
if params.num_pages is not None:
|
|
scroll_amount = int(window_height * params.num_pages)
|
|
pages_scrolled = params.num_pages
|
|
else:
|
|
# Default to one page
|
|
scroll_amount = window_height
|
|
pages_scrolled = 1.0
|
|
|
|
# Set direction based on down parameter
|
|
dy = scroll_amount if params.down else -scroll_amount
|
|
|
|
try:
|
|
await browser_session._scroll_container(cast(int, dy))
|
|
except Exception as e:
|
|
# Hard fallback: always works on root scroller
|
|
await page.evaluate('(y) => window.scrollBy(0, y)', dy)
|
|
logger.debug('Smart scroll failed; used window.scrollBy fallback', exc_info=e)
|
|
|
|
direction = 'down' if params.down else 'up'
|
|
if params.num_pages is not None:
|
|
if pages_scrolled == 1.0:
|
|
msg = f'🔍 Scrolled {direction} the page by one page'
|
|
long_term_memory = f'Scrolled {direction} the page by one page'
|
|
else:
|
|
msg = f'🔍 Scrolled {direction} the page by {pages_scrolled} pages'
|
|
long_term_memory = f'Scrolled {direction} the page by {pages_scrolled} pages'
|
|
else:
|
|
msg = f'🔍 Scrolled {direction} the page by one page'
|
|
long_term_memory = f'Scrolled {direction} the page by one page'
|
|
|
|
logger.info(msg)
|
|
return ActionResult(extracted_content=msg, include_in_memory=True, long_term_memory=long_term_memory)
|
|
|
|
# send keys
|
|
@self.registry.action(
|
|
'Send strings of special keys to use Playwright page.keyboard.press - examples include Escape, Backspace, Insert, PageDown, Delete, Enter, or Shortcuts such as `Control+o`, `Control+Shift+T`',
|
|
param_model=SendKeysAction,
|
|
)
|
|
async def send_keys(params: SendKeysAction, page: Page):
|
|
try:
|
|
await page.keyboard.press(params.keys)
|
|
except Exception as e:
|
|
if 'Unknown key' in str(e):
|
|
# loop over the keys and try to send each one
|
|
for key in params.keys:
|
|
try:
|
|
await page.keyboard.press(key)
|
|
except Exception as e:
|
|
logger.debug(f'Error sending key {key}: {str(e)}')
|
|
raise e
|
|
else:
|
|
raise e
|
|
msg = f'⌨️ Sent keys: {params.keys}'
|
|
logger.info(msg)
|
|
return ActionResult(extracted_content=msg, include_in_memory=True, long_term_memory=f'Sent keys: {params.keys}')
|
|
|
|
@self.registry.action(
|
|
description='Scroll to a text in the current page',
|
|
)
|
|
async def scroll_to_text(text: str, page: Page): # type: ignore
|
|
try:
|
|
# Try different locator strategies
|
|
locators = [
|
|
page.get_by_text(text, exact=False),
|
|
page.locator(f'text={text}'),
|
|
page.locator(f"//*[contains(text(), '{text}')]"),
|
|
]
|
|
|
|
for locator in locators:
|
|
try:
|
|
if await locator.count() == 0:
|
|
continue
|
|
|
|
element = locator.first
|
|
is_visible = await element.is_visible()
|
|
bbox = await element.bounding_box()
|
|
|
|
if is_visible and bbox is not None and bbox['width'] > 0 and bbox['height'] > 0:
|
|
await element.scroll_into_view_if_needed()
|
|
await asyncio.sleep(0.5) # Wait for scroll to complete
|
|
msg = f'🔍 Scrolled to text: {text}'
|
|
logger.info(msg)
|
|
return ActionResult(
|
|
extracted_content=msg, include_in_memory=True, long_term_memory=f'Scrolled to text: {text}'
|
|
)
|
|
|
|
except Exception as e:
|
|
logger.debug(f'Locator attempt failed: {str(e)}')
|
|
continue
|
|
|
|
msg = f"Text '{text}' not found or not visible on page"
|
|
logger.info(msg)
|
|
return ActionResult(
|
|
extracted_content=msg,
|
|
include_in_memory=True,
|
|
long_term_memory=f"Tried scrolling to text '{text}' but it was not found",
|
|
)
|
|
|
|
except Exception as e:
|
|
msg = f"Failed to scroll to text '{text}': {str(e)}"
|
|
logger.error(msg)
|
|
return ActionResult(error=msg, include_in_memory=True)
|
|
|
|
# File System Actions
|
|
@self.registry.action('Write content to file_name in file system. Allowed extensions are .md, .txt, .json, .csv.')
|
|
async def write_file(file_name: str, content: str, file_system: FileSystem):
|
|
result = await file_system.write_file(file_name, content)
|
|
logger.info(f'💾 {result}')
|
|
return ActionResult(extracted_content=result, include_in_memory=True, long_term_memory=result)
|
|
|
|
@self.registry.action('Append content to file_name in file system')
|
|
async def append_file(file_name: str, content: str, file_system: FileSystem):
|
|
result = await file_system.append_file(file_name, content)
|
|
logger.info(f'💾 {result}')
|
|
return ActionResult(extracted_content=result, include_in_memory=True, long_term_memory=result)
|
|
|
|
@self.registry.action('Read file_name from file system')
|
|
async def read_file(file_name: str, available_file_paths: list[str], file_system: FileSystem):
|
|
if available_file_paths and file_name in available_file_paths:
|
|
result = await file_system.read_file(file_name, external_file=True)
|
|
else:
|
|
result = await file_system.read_file(file_name)
|
|
|
|
MAX_MEMORY_SIZE = 1000
|
|
if len(result) > MAX_MEMORY_SIZE:
|
|
lines = result.splitlines()
|
|
display = ''
|
|
lines_count = 0
|
|
for line in lines:
|
|
if len(display) + len(line) < MAX_MEMORY_SIZE:
|
|
display += line + '\n'
|
|
lines_count += 1
|
|
else:
|
|
break
|
|
remaining_lines = len(lines) - lines_count
|
|
memory = f'{display}{remaining_lines} more lines...' if remaining_lines > 0 else display
|
|
else:
|
|
memory = result
|
|
logger.info(f'💾 {memory}')
|
|
return ActionResult(
|
|
extracted_content=result,
|
|
include_in_memory=True,
|
|
long_term_memory=memory,
|
|
include_extracted_content_only_once=True,
|
|
)
|
|
|
|
@self.registry.action(
|
|
description='Get all options from a native dropdown',
|
|
)
|
|
async def get_dropdown_options(index: int, browser_session: BrowserSession) -> ActionResult:
|
|
"""Get all options from a native dropdown"""
|
|
page = await browser_session.get_current_page()
|
|
selector_map = await browser_session.get_selector_map()
|
|
dom_element = selector_map[index]
|
|
|
|
try:
|
|
# Frame-aware approach since we know it works
|
|
all_options = []
|
|
frame_index = 0
|
|
|
|
for frame in page.frames:
|
|
try:
|
|
options = await frame.evaluate(
|
|
"""
|
|
(xpath) => {
|
|
const select = document.evaluate(xpath, document, null,
|
|
XPathResult.FIRST_ORDERED_NODE_TYPE, null).singleNodeValue;
|
|
if (!select) return null;
|
|
|
|
return {
|
|
options: Array.from(select.options).map(opt => ({
|
|
text: opt.text, //do not trim, because we are doing exact match in select_dropdown_option
|
|
value: opt.value,
|
|
index: opt.index
|
|
})),
|
|
id: select.id,
|
|
name: select.name
|
|
};
|
|
}
|
|
""",
|
|
dom_element.xpath,
|
|
)
|
|
|
|
if options:
|
|
logger.debug(f'Found dropdown in frame {frame_index}')
|
|
logger.debug(f'Dropdown ID: {options["id"]}, Name: {options["name"]}')
|
|
|
|
formatted_options = []
|
|
for opt in options['options']:
|
|
# encoding ensures AI uses the exact string in select_dropdown_option
|
|
encoded_text = json.dumps(opt['text'])
|
|
formatted_options.append(f'{opt["index"]}: text={encoded_text}')
|
|
|
|
all_options.extend(formatted_options)
|
|
|
|
except Exception as frame_e:
|
|
logger.debug(f'Frame {frame_index} evaluation failed: {str(frame_e)}')
|
|
|
|
frame_index += 1
|
|
|
|
if all_options:
|
|
msg = '\n'.join(all_options)
|
|
msg += '\nUse the exact text string in select_dropdown_option'
|
|
logger.info(msg)
|
|
return ActionResult(
|
|
extracted_content=msg,
|
|
include_in_memory=True,
|
|
long_term_memory=f'Found dropdown options for index {index}.',
|
|
include_extracted_content_only_once=True,
|
|
)
|
|
else:
|
|
msg = 'No options found in any frame for dropdown'
|
|
logger.info(msg)
|
|
return ActionResult(
|
|
extracted_content=msg, include_in_memory=True, long_term_memory='No dropdown options found'
|
|
)
|
|
|
|
except Exception as e:
|
|
logger.error(f'Failed to get dropdown options: {str(e)}')
|
|
msg = f'Error getting options: {str(e)}'
|
|
logger.info(msg)
|
|
return ActionResult(extracted_content=msg, include_in_memory=True)
|
|
|
|
@self.registry.action(
|
|
description='Select dropdown option for interactive element index by the text of the option you want to select',
|
|
)
|
|
async def select_dropdown_option(
|
|
index: int,
|
|
text: str,
|
|
browser_session: BrowserSession,
|
|
) -> ActionResult:
|
|
"""Select dropdown option by the text of the option you want to select"""
|
|
page = await browser_session.get_current_page()
|
|
selector_map = await browser_session.get_selector_map()
|
|
dom_element = selector_map[index]
|
|
|
|
# Validate that we're working with a select element
|
|
if dom_element.tag_name != 'select':
|
|
logger.error(f'Element is not a select! Tag: {dom_element.tag_name}, Attributes: {dom_element.attributes}')
|
|
msg = f'Cannot select option: Element with index {index} is a {dom_element.tag_name}, not a select'
|
|
return ActionResult(extracted_content=msg, include_in_memory=True, long_term_memory=msg)
|
|
|
|
logger.debug(f"Attempting to select '{text}' using xpath: {dom_element.xpath}")
|
|
logger.debug(f'Element attributes: {dom_element.attributes}')
|
|
logger.debug(f'Element tag: {dom_element.tag_name}')
|
|
|
|
xpath = '//' + dom_element.xpath
|
|
|
|
try:
|
|
frame_index = 0
|
|
for frame in page.frames:
|
|
try:
|
|
logger.debug(f'Trying frame {frame_index} URL: {frame.url}')
|
|
|
|
# First verify we can find the dropdown in this frame
|
|
find_dropdown_js = """
|
|
(xpath) => {
|
|
try {
|
|
const select = document.evaluate(xpath, document, null,
|
|
XPathResult.FIRST_ORDERED_NODE_TYPE, null).singleNodeValue;
|
|
if (!select) return null;
|
|
if (select.tagName.toLowerCase() !== 'select') {
|
|
return {
|
|
error: `Found element but it's a ${select.tagName}, not a SELECT`,
|
|
found: false
|
|
};
|
|
}
|
|
return {
|
|
id: select.id,
|
|
name: select.name,
|
|
found: true,
|
|
tagName: select.tagName,
|
|
optionCount: select.options.length,
|
|
currentValue: select.value,
|
|
availableOptions: Array.from(select.options).map(o => o.text.trim())
|
|
};
|
|
} catch (e) {
|
|
return {error: e.toString(), found: false};
|
|
}
|
|
}
|
|
"""
|
|
|
|
dropdown_info = await frame.evaluate(find_dropdown_js, dom_element.xpath)
|
|
|
|
if dropdown_info:
|
|
if not dropdown_info.get('found'):
|
|
logger.error(f'Frame {frame_index} error: {dropdown_info.get("error")}')
|
|
continue
|
|
|
|
logger.debug(f'Found dropdown in frame {frame_index}: {dropdown_info}')
|
|
|
|
# "label" because we are selecting by text
|
|
# nth(0) to disable error thrown by strict mode
|
|
# timeout=1000 because we are already waiting for all network events, therefore ideally we don't need to wait a lot here (default 30s)
|
|
selected_option_values = (
|
|
await frame.locator('//' + dom_element.xpath).nth(0).select_option(label=text, timeout=1000)
|
|
)
|
|
|
|
msg = f'selected option {text} with value {selected_option_values}'
|
|
logger.info(msg + f' in frame {frame_index}')
|
|
|
|
return ActionResult(
|
|
extracted_content=msg, include_in_memory=True, long_term_memory=f"Selected option '{text}'"
|
|
)
|
|
|
|
except Exception as frame_e:
|
|
logger.error(f'Frame {frame_index} attempt failed: {str(frame_e)}')
|
|
logger.error(f'Frame type: {type(frame)}')
|
|
logger.error(f'Frame URL: {frame.url}')
|
|
|
|
frame_index += 1
|
|
|
|
msg = f"Could not select option '{text}' in any frame"
|
|
logger.info(msg)
|
|
return ActionResult(extracted_content=msg, include_in_memory=True, long_term_memory=msg)
|
|
|
|
except Exception as e:
|
|
msg = f'Selection failed: {str(e)}'
|
|
logger.error(msg)
|
|
return ActionResult(error=msg, include_in_memory=True)
|
|
|
|
@self.registry.action('Google Sheets: Get the contents of the entire sheet', domains=['https://docs.google.com'])
|
|
async def read_sheet_contents(page: Page):
|
|
# select all cells
|
|
await page.keyboard.press('Enter')
|
|
await page.keyboard.press('Escape')
|
|
await page.keyboard.press('ControlOrMeta+A')
|
|
await page.keyboard.press('ControlOrMeta+C')
|
|
|
|
extracted_tsv = await page.evaluate('() => navigator.clipboard.readText()')
|
|
return ActionResult(
|
|
extracted_content=extracted_tsv,
|
|
include_in_memory=True,
|
|
long_term_memory='Retrieved sheet contents',
|
|
include_extracted_content_only_once=True,
|
|
)
|
|
|
|
@self.registry.action('Google Sheets: Get the contents of a cell or range of cells', domains=['https://docs.google.com'])
|
|
async def read_cell_contents(cell_or_range: str, browser_session: BrowserSession):
|
|
page = await browser_session.get_current_page()
|
|
|
|
await select_cell_or_range(cell_or_range=cell_or_range, page=page)
|
|
|
|
await page.keyboard.press('ControlOrMeta+C')
|
|
await asyncio.sleep(0.1)
|
|
extracted_tsv = await page.evaluate('() => navigator.clipboard.readText()')
|
|
return ActionResult(
|
|
extracted_content=extracted_tsv,
|
|
include_in_memory=True,
|
|
long_term_memory=f'Retrieved contents from {cell_or_range}',
|
|
include_extracted_content_only_once=True,
|
|
)
|
|
|
|
@self.registry.action(
|
|
'Google Sheets: Update the content of a cell or range of cells', domains=['https://docs.google.com']
|
|
)
|
|
async def update_cell_contents(cell_or_range: str, new_contents_tsv: str, browser_session: BrowserSession):
|
|
page = await browser_session.get_current_page()
|
|
|
|
await select_cell_or_range(cell_or_range=cell_or_range, page=page)
|
|
|
|
# simulate paste event from clipboard with TSV content
|
|
await page.evaluate(f"""
|
|
const clipboardData = new DataTransfer();
|
|
clipboardData.setData('text/plain', `{new_contents_tsv}`);
|
|
document.activeElement.dispatchEvent(new ClipboardEvent('paste', {{clipboardData}}));
|
|
""")
|
|
|
|
return ActionResult(
|
|
extracted_content=f'Updated cells: {cell_or_range} = {new_contents_tsv}',
|
|
include_in_memory=False,
|
|
long_term_memory=f'Updated cells {cell_or_range} with {new_contents_tsv}',
|
|
)
|
|
|
|
@self.registry.action('Google Sheets: Clear whatever cells are currently selected', domains=['https://docs.google.com'])
|
|
async def clear_cell_contents(cell_or_range: str, browser_session: BrowserSession):
|
|
page = await browser_session.get_current_page()
|
|
|
|
await select_cell_or_range(cell_or_range=cell_or_range, page=page)
|
|
|
|
await page.keyboard.press('Backspace')
|
|
return ActionResult(
|
|
extracted_content=f'Cleared cells: {cell_or_range}',
|
|
include_in_memory=False,
|
|
long_term_memory=f'Cleared cells {cell_or_range}',
|
|
)
|
|
|
|
@self.registry.action('Google Sheets: Select a specific cell or range of cells', domains=['https://docs.google.com'])
|
|
async def select_cell_or_range(cell_or_range: str, page: Page):
|
|
await page.keyboard.press('Enter') # make sure we dont delete current cell contents if we were last editing
|
|
await page.keyboard.press('Escape') # to clear current focus (otherwise select range popup is additive)
|
|
await asyncio.sleep(0.1)
|
|
await page.keyboard.press('Home') # move cursor to the top left of the sheet first
|
|
await page.keyboard.press('ArrowUp')
|
|
await asyncio.sleep(0.1)
|
|
await page.keyboard.press('Control+G') # open the goto range popup
|
|
await asyncio.sleep(0.2)
|
|
await page.keyboard.type(cell_or_range, delay=0.05)
|
|
await asyncio.sleep(0.2)
|
|
await page.keyboard.press('Enter')
|
|
await asyncio.sleep(0.2)
|
|
await page.keyboard.press('Escape') # to make sure the popup still closes in the case where the jump failed
|
|
return ActionResult(
|
|
extracted_content=f'Selected cells: {cell_or_range}',
|
|
include_in_memory=False,
|
|
long_term_memory=f'Selected cells {cell_or_range}',
|
|
)
|
|
|
|
@self.registry.action(
|
|
'Google Sheets: Fallback method to type text into (only one) currently selected cell',
|
|
domains=['https://docs.google.com'],
|
|
)
|
|
async def fallback_input_into_single_selected_cell(text: str, page: Page):
|
|
await page.keyboard.type(text, delay=0.1)
|
|
await page.keyboard.press('Enter') # make sure to commit the input so it doesn't get overwritten by the next action
|
|
await page.keyboard.press('ArrowUp')
|
|
return ActionResult(
|
|
extracted_content=f'Inputted text {text}',
|
|
include_in_memory=False,
|
|
long_term_memory=f"Inputted text '{text}' into cell",
|
|
)
|
|
|
|
# Custom done action for structured output
|
|
def _register_done_action(self, output_model: type[T] | None, display_files_in_done_text: bool = True):
|
|
if output_model is not None:
|
|
self.display_files_in_done_text = display_files_in_done_text
|
|
|
|
@self.registry.action(
|
|
'Complete task - with return text and if the task is finished (success=True) or not yet completely finished (success=False), because last step is reached',
|
|
param_model=StructuredOutputAction[output_model],
|
|
)
|
|
async def done(params: StructuredOutputAction):
|
|
# Exclude success from the output JSON since it's an internal parameter
|
|
output_dict = params.data.model_dump()
|
|
|
|
# Enums are not serializable, convert to string
|
|
for key, value in output_dict.items():
|
|
if isinstance(value, enum.Enum):
|
|
output_dict[key] = value.value
|
|
|
|
return ActionResult(
|
|
is_done=True,
|
|
success=params.success,
|
|
extracted_content=json.dumps(output_dict),
|
|
long_term_memory=f'Task completed. Success Status: {params.success}',
|
|
)
|
|
|
|
else:
|
|
|
|
@self.registry.action(
|
|
'Complete task - provide a summary of results for the user. Set success=True if task completed successfully, false otherwise. Text should be your response to the user summarizing results. Include files you would like to display to the user in files_to_display.',
|
|
param_model=DoneAction,
|
|
)
|
|
async def done(params: DoneAction, file_system: FileSystem):
|
|
user_message = params.text
|
|
|
|
len_text = len(params.text)
|
|
len_max_memory = 100
|
|
memory = f'Task completed: {params.success} - {params.text[:len_max_memory]}'
|
|
if len_text > len_max_memory:
|
|
memory += f' - {len_text - len_max_memory} more characters'
|
|
|
|
attachments = []
|
|
if params.files_to_display:
|
|
if self.display_files_in_done_text:
|
|
file_msg = ''
|
|
for file_name in params.files_to_display:
|
|
if file_name == 'todo.md':
|
|
continue
|
|
file_content = file_system.display_file(file_name)
|
|
if file_content:
|
|
file_msg += f'\n\n{file_name}:\n{file_content}'
|
|
attachments.append(file_name)
|
|
if file_msg:
|
|
user_message += '\n\nAttachments:'
|
|
user_message += file_msg
|
|
else:
|
|
logger.warning('Agent wanted to display files but none were found')
|
|
else:
|
|
for file_name in params.files_to_display:
|
|
if file_name == 'todo.md':
|
|
continue
|
|
file_content = file_system.display_file(file_name)
|
|
if file_content:
|
|
attachments.append(file_name)
|
|
|
|
attachments = [str(file_system.get_dir() / file_name) for file_name in attachments]
|
|
|
|
return ActionResult(
|
|
is_done=True,
|
|
success=params.success,
|
|
extracted_content=user_message,
|
|
long_term_memory=memory,
|
|
attachments=attachments,
|
|
)
|
|
|
|
def use_structured_output_action(self, output_model: type[T]):
|
|
self._register_done_action(output_model)
|
|
|
|
# Register ---------------------------------------------------------------
|
|
|
|
def action(self, description: str, **kwargs):
|
|
"""Decorator for registering custom actions
|
|
|
|
@param description: Describe the LLM what the function does (better description == better function calling)
|
|
"""
|
|
return self.registry.action(description, **kwargs)
|
|
|
|
# Act --------------------------------------------------------------------
|
|
|
|
@time_execution_sync('--act')
|
|
async def act(
|
|
self,
|
|
action: ActionModel,
|
|
browser_session: BrowserSession,
|
|
#
|
|
page_extraction_llm: BaseChatModel | None = None,
|
|
sensitive_data: dict[str, str | dict[str, str]] | None = None,
|
|
available_file_paths: list[str] | None = None,
|
|
file_system: FileSystem | None = None,
|
|
#
|
|
context: Context | None = None,
|
|
) -> ActionResult:
|
|
"""Execute an action"""
|
|
|
|
for action_name, params in action.model_dump(exclude_unset=True).items():
|
|
if params is not None:
|
|
# with Laminar.start_as_current_span(
|
|
# name=action_name,
|
|
# input={
|
|
# 'action': action_name,
|
|
# 'params': params,
|
|
# },
|
|
# span_type='TOOL',
|
|
# ):
|
|
result = await self.registry.execute_action(
|
|
action_name=action_name,
|
|
params=params,
|
|
browser_session=browser_session,
|
|
page_extraction_llm=page_extraction_llm,
|
|
file_system=file_system,
|
|
sensitive_data=sensitive_data,
|
|
available_file_paths=available_file_paths,
|
|
context=context,
|
|
)
|
|
|
|
# Laminar.set_span_output(result)
|
|
|
|
if isinstance(result, str):
|
|
return ActionResult(extracted_content=result)
|
|
elif isinstance(result, ActionResult):
|
|
return result
|
|
elif result is None:
|
|
return ActionResult()
|
|
else:
|
|
raise ValueError(f'Invalid action result type: {type(result)} of {result}')
|
|
return ActionResult()
|