chore: import upstream snapshot with attribution

examples/ui/README.md

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+# **User Interfaces of Browser-Use**
+
+| **File Name**          | **User Interface** | **Description**                           | **Example Usage**                         |
+|------------------------|-------------------|-------------------------------------------|-------------------------------------------|
+| `command_line.py`      | **Terminal**      | Parses arguments for command-line execution. | `python command_line.py`                  |
+| `gradio_demo.py`       | **Gradio**        | Provides a Gradio-based interactive UI.  | `python gradio_demo.py`                   |
+| `streamlit_demo.py`    | **Streamlit**     | Runs a Streamlit-based web interface.    | `python -m streamlit run streamlit_demo.py` |

examples/ui/command_line.py

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+"""
+To Use It:
+
+Example 1: Using OpenAI (default), with default task: 'go to reddit and search for posts about browser-use'
+python command_line.py
+
+Example 2: Using OpenAI with a Custom Query
+python command_line.py --query "go to google and search for browser-use"
+
+Example 3: Using Anthropic's Claude Model with a Custom Query
+python command_line.py --query "find latest Python tutorials on Medium" --provider anthropic
+
+"""
+
+import argparse
+import asyncio
+import os
+import sys
+
+# Ensure local repository (browser_use) is accessible
+sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+from browser_use import Agent
+from browser_use.browser import BrowserSession
+from browser_use.tools.service import Tools
+
+
+def get_llm(provider: str):
+	if provider == 'anthropic':
+		from browser_use.llm import ChatAnthropic
+
+		api_key = os.getenv('ANTHROPIC_API_KEY')
+		if not api_key:
+			raise ValueError('Error: ANTHROPIC_API_KEY is not set. Please provide a valid API key.')
+
+		return ChatAnthropic(model='claude-3-5-sonnet-20240620', temperature=0.0)
+	elif provider == 'openai':
+		from browser_use import ChatOpenAI
+
+		api_key = os.getenv('OPENAI_API_KEY')
+		if not api_key:
+			raise ValueError('Error: OPENAI_API_KEY is not set. Please provide a valid API key.')
+
+		return ChatOpenAI(model='gpt-4.1', temperature=0.0)
+
+	else:
+		raise ValueError(f'Unsupported provider: {provider}')
+
+
+def parse_arguments():
+	"""Parse command-line arguments."""
+	parser = argparse.ArgumentParser(description='Automate browser tasks using an LLM agent.')
+	parser.add_argument(
+		'--query', type=str, help='The query to process', default='go to reddit and search for posts about browser-use'
+	)
+	parser.add_argument(
+		'--provider',
+		type=str,
+		choices=['openai', 'anthropic'],
+		default='openai',
+		help='The model provider to use (default: openai)',
+	)
+	return parser.parse_args()
+
+
+def initialize_agent(query: str, provider: str):
+	"""Initialize the browser agent with the given query and provider."""
+	llm = get_llm(provider)
+	tools = Tools()
+	browser_session = BrowserSession()
+
+	return Agent(
+		task=query,
+		llm=llm,
+		tools=tools,
+		browser_session=browser_session,
+		use_vision=True,
+		max_actions_per_step=1,
+	), browser_session
+
+
+async def main():
+	"""Main async function to run the agent."""
+	args = parse_arguments()
+	agent, browser_session = initialize_agent(args.query, args.provider)
+
+	await agent.run(max_steps=25)
+
+	input('Press Enter to close the browser...')
+	await browser_session.kill()
+
+
+if __name__ == '__main__':
+	asyncio.run(main())

examples/ui/gradio_demo.py

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+# pyright: reportMissingImports=false
+import asyncio
+import os
+import sys
+from dataclasses import dataclass
+
+sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+# Third-party imports
+import gradio as gr  # type: ignore
+from rich.console import Console
+from rich.panel import Panel
+from rich.text import Text
+
+# Local module imports
+from browser_use import Agent, ChatOpenAI
+
+
+@dataclass
+class ActionResult:
+	is_done: bool
+	extracted_content: str | None
+	error: str | None
+	include_in_memory: bool
+
+
+@dataclass
+class AgentHistoryList:
+	all_results: list[ActionResult]
+	all_model_outputs: list[dict]
+
+
+def parse_agent_history(history_str: str) -> None:
+	console = Console()
+
+	# Split the content into sections based on ActionResult entries
+	sections = history_str.split('ActionResult(')
+
+	for i, section in enumerate(sections[1:], 1):  # Skip first empty section
+		# Extract relevant information
+		content = ''
+		if 'extracted_content=' in section:
+			content = section.split('extracted_content=')[1].split(',')[0].strip("'")
+
+		if content:
+			header = Text(f'Step {i}', style='bold blue')
+			panel = Panel(content, title=header, border_style='blue')
+			console.print(panel)
+			console.print()
+
+	return None
+
+
+async def run_browser_task(
+	task: str,
+	api_key: str,
+	model: str = 'gpt-4.1',
+	headless: bool = True,
+) -> str:
+	if not api_key.strip():
+		return 'Please provide an API key'
+
+	os.environ['OPENAI_API_KEY'] = api_key
+
+	try:
+		agent = Agent(
+			task=task,
+			llm=ChatOpenAI(model='gpt-4.1-mini'),
+		)
+		result = await agent.run()
+		#  TODO: The result could be parsed better
+		return str(result)
+	except Exception as e:
+		return f'Error: {str(e)}'
+
+
+def create_ui():
+	with gr.Blocks(title='Browser Use GUI') as interface:
+		gr.Markdown('# Browser Use Task Automation')
+
+		with gr.Row():
+			with gr.Column():
+				api_key = gr.Textbox(label='OpenAI API Key', placeholder='sk-...', type='password')
+				task = gr.Textbox(
+					label='Task Description',
+					placeholder='E.g., Find flights from New York to London for next week',
+					lines=3,
+				)
+				model = gr.Dropdown(choices=['gpt-4.1-mini', 'gpt-5', 'o3', 'gpt-5-mini'], label='Model', value='gpt-4.1-mini')
+				headless = gr.Checkbox(label='Run Headless', value=False)
+				submit_btn = gr.Button('Run Task')
+
+			with gr.Column():
+				output = gr.Textbox(label='Output', lines=10, interactive=False)
+
+		submit_btn.click(
+			fn=lambda *args: asyncio.run(run_browser_task(*args)),
+			inputs=[task, api_key, model, headless],
+			outputs=output,
+		)
+
+	return interface
+
+
+if __name__ == '__main__':
+	demo = create_ui()
+	demo.launch()

examples/ui/streamlit_demo.py

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+"""
+To use it, you'll need to install streamlit, and run with:
+
+python -m streamlit run streamlit_demo.py
+
+"""
+
+import asyncio
+import os
+import sys
+
+sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+import streamlit as st  # type: ignore
+
+from browser_use import Agent
+from browser_use.browser import BrowserSession
+from browser_use.tools.service import Tools
+
+if os.name == 'nt':
+	asyncio.set_event_loop_policy(asyncio.WindowsProactorEventLoopPolicy())
+
+
+# Function to get the LLM based on provider
+def get_llm(provider: str):
+	if provider == 'anthropic':
+		from browser_use.llm import ChatAnthropic
+
+		api_key = os.getenv('ANTHROPIC_API_KEY')
+		if not api_key:
+			st.error('Error: ANTHROPIC_API_KEY is not set. Please provide a valid API key.')
+			st.stop()
+
+		return ChatAnthropic(model='claude-3-5-sonnet-20240620', temperature=0.0)
+	elif provider == 'openai':
+		from browser_use import ChatOpenAI
+
+		api_key = os.getenv('OPENAI_API_KEY')
+		if not api_key:
+			st.error('Error: OPENAI_API_KEY is not set. Please provide a valid API key.')
+			st.stop()
+
+		return ChatOpenAI(model='gpt-4.1', temperature=0.0)
+	else:
+		st.error(f'Unsupported provider: {provider}')
+		st.stop()
+		return None  # Never reached, but helps with type checking
+
+
+# Function to initialize the agent
+def initialize_agent(query: str, provider: str):
+	llm = get_llm(provider)
+	tools = Tools()
+	browser_session = BrowserSession()
+
+	return Agent(
+		task=query,
+		llm=llm,  # type: ignore
+		tools=tools,
+		browser_session=browser_session,
+		use_vision=True,
+		max_actions_per_step=1,
+	), browser_session
+
+
+# Streamlit UI
+st.title('Automated Browser Agent with LLMs 🤖')
+
+query = st.text_input('Enter your query:', 'go to reddit and search for posts about browser-use')
+provider = st.radio('Select LLM Provider:', ['openai', 'anthropic'], index=0)
+
+if st.button('Run Agent'):
+	st.write('Initializing agent...')
+	agent, browser_session = initialize_agent(query, provider)
+
+	async def run_agent():
+		with st.spinner('Running automation...'):
+			await agent.run(max_steps=25)
+		st.success('Task completed! 🎉')
+
+	asyncio.run(run_agent())
+
+	st.button('Close Browser', on_click=lambda: asyncio.run(browser_session.kill()))