[Add] browser-use and main.py
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browser-use/examples/ui/README.md
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browser-use/examples/ui/README.md
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# **User Interfaces of Browser-Use**
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| **File Name** | **User Interface** | **Description** | **Example Usage** |
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|------------------------|-------------------|-------------------------------------------|-------------------------------------------|
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| `command_line.py` | **Terminal** | Parses arguments for command-line execution. | `python command_line.py` |
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| `gradio_demo.py` | **Gradio** | Provides a Gradio-based interactive UI. | `python gradio_demo.py` |
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| `streamlit_demo.py` | **Streamlit** | Runs a Streamlit-based web interface. | `python -m streamlit run streamlit_demo.py` |
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browser-use/examples/ui/command_line.py
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browser-use/examples/ui/command_line.py
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"""
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To Use It:
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Example 1: Using OpenAI (default), with default task: 'go to reddit and search for posts about browser-use'
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python command_line.py
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Example 2: Using OpenAI with a Custom Query
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python command_line.py --query "go to google and search for browser-use"
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Example 3: Using Anthropic's Claude Model with a Custom Query
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python command_line.py --query "find latest Python tutorials on Medium" --provider anthropic
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"""
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import argparse
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import asyncio
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import os
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import sys
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# Ensure local repository (browser_use) is accessible
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sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
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from dotenv import load_dotenv
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load_dotenv()
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from browser_use import Agent
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from browser_use.browser.browser import Browser, BrowserConfig
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from browser_use.controller.service import Controller
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def get_llm(provider: str):
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if provider == 'anthropic':
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from langchain_anthropic import ChatAnthropic
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api_key = os.getenv('ANTHROPIC_API_KEY')
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if not api_key:
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raise ValueError('Error: ANTHROPIC_API_KEY is not set. Please provide a valid API key.')
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return ChatAnthropic(model_name='claude-3-5-sonnet-20240620', timeout=25, stop=None, temperature=0.0)
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elif provider == 'openai':
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from langchain_openai import ChatOpenAI
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api_key = os.getenv('OPENAI_API_KEY')
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if not api_key:
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raise ValueError('Error: OPENAI_API_KEY is not set. Please provide a valid API key.')
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return ChatOpenAI(model='gpt-4o', temperature=0.0)
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else:
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raise ValueError(f'Unsupported provider: {provider}')
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def parse_arguments():
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"""Parse command-line arguments."""
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parser = argparse.ArgumentParser(description='Automate browser tasks using an LLM agent.')
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parser.add_argument(
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'--query', type=str, help='The query to process', default='go to reddit and search for posts about browser-use'
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)
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parser.add_argument(
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'--provider',
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type=str,
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choices=['openai', 'anthropic'],
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default='openai',
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help='The model provider to use (default: openai)',
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)
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return parser.parse_args()
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def initialize_agent(query: str, provider: str):
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"""Initialize the browser agent with the given query and provider."""
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llm = get_llm(provider)
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controller = Controller()
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browser = Browser(config=BrowserConfig())
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return Agent(
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task=query,
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llm=llm,
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controller=controller,
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browser=browser,
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use_vision=True,
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max_actions_per_step=1,
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), browser
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async def main():
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"""Main async function to run the agent."""
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args = parse_arguments()
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agent, browser = initialize_agent(args.query, args.provider)
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await agent.run(max_steps=25)
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input('Press Enter to close the browser...')
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await browser.close()
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if __name__ == '__main__':
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asyncio.run(main())
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browser-use/examples/ui/gradio_demo.py
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browser-use/examples/ui/gradio_demo.py
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import asyncio
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import os
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import sys
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from dataclasses import dataclass
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sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
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from dotenv import load_dotenv
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load_dotenv()
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# Third-party imports
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import gradio as gr
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from langchain_openai import ChatOpenAI
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from rich.console import Console
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from rich.panel import Panel
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from rich.text import Text
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# Local module imports
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from browser_use import Agent
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@dataclass
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class ActionResult:
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is_done: bool
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extracted_content: str | None
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error: str | None
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include_in_memory: bool
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@dataclass
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class AgentHistoryList:
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all_results: list[ActionResult]
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all_model_outputs: list[dict]
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def parse_agent_history(history_str: str) -> None:
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console = Console()
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# Split the content into sections based on ActionResult entries
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sections = history_str.split('ActionResult(')
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for i, section in enumerate(sections[1:], 1): # Skip first empty section
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# Extract relevant information
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content = ''
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if 'extracted_content=' in section:
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content = section.split('extracted_content=')[1].split(',')[0].strip("'")
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if content:
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header = Text(f'Step {i}', style='bold blue')
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panel = Panel(content, title=header, border_style='blue')
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console.print(panel)
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console.print()
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async def run_browser_task(
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task: str,
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api_key: str,
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model: str = 'gpt-4o',
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headless: bool = True,
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) -> str:
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if not api_key.strip():
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return 'Please provide an API key'
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os.environ['OPENAI_API_KEY'] = api_key
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try:
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agent = Agent(
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task=task,
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llm=ChatOpenAI(model='gpt-4o'),
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)
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result = await agent.run()
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# TODO: The result cloud be parsed better
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return result
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except Exception as e:
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return f'Error: {str(e)}'
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def create_ui():
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with gr.Blocks(title='Browser Use GUI') as interface:
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gr.Markdown('# Browser Use Task Automation')
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with gr.Row():
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with gr.Column():
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api_key = gr.Textbox(label='OpenAI API Key', placeholder='sk-...', type='password')
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task = gr.Textbox(
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label='Task Description',
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placeholder='E.g., Find flights from New York to London for next week',
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lines=3,
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)
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model = gr.Dropdown(choices=['gpt-4', 'gpt-3.5-turbo'], label='Model', value='gpt-4')
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headless = gr.Checkbox(label='Run Headless', value=True)
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submit_btn = gr.Button('Run Task')
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with gr.Column():
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output = gr.Textbox(label='Output', lines=10, interactive=False)
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submit_btn.click(
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fn=lambda *args: asyncio.run(run_browser_task(*args)),
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inputs=[task, api_key, model, headless],
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outputs=output,
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)
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return interface
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if __name__ == '__main__':
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demo = create_ui()
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demo.launch()
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86
browser-use/examples/ui/streamlit_demo.py
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browser-use/examples/ui/streamlit_demo.py
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"""
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To use it, you'll need to install streamlit, and run with:
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python -m streamlit run streamlit_demo.py
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"""
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import asyncio
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import os
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import sys
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sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
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from dotenv import load_dotenv
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load_dotenv()
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import streamlit as st
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from browser_use import Agent
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from browser_use.browser.browser import Browser, BrowserConfig
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from browser_use.controller.service import Controller
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if os.name == 'nt':
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asyncio.set_event_loop_policy(asyncio.WindowsProactorEventLoopPolicy())
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# Function to get the LLM based on provider
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def get_llm(provider: str):
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if provider == 'anthropic':
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from langchain_anthropic import ChatAnthropic
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api_key = os.getenv('ANTHROPIC_API_KEY')
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if not api_key:
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st.error('Error: ANTHROPIC_API_KEY is not set. Please provide a valid API key.')
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st.stop()
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return ChatAnthropic(model_name='claude-3-5-sonnet-20240620', timeout=25, stop=None, temperature=0.0)
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elif provider == 'openai':
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from langchain_openai import ChatOpenAI
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api_key = os.getenv('OPENAI_API_KEY')
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if not api_key:
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st.error('Error: OPENAI_API_KEY is not set. Please provide a valid API key.')
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st.stop()
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return ChatOpenAI(model='gpt-4o', temperature=0.0)
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else:
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st.error(f'Unsupported provider: {provider}')
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st.stop()
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# Function to initialize the agent
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def initialize_agent(query: str, provider: str):
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llm = get_llm(provider)
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controller = Controller()
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browser = Browser(config=BrowserConfig())
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return Agent(
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task=query,
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llm=llm,
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controller=controller,
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browser=browser,
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use_vision=True,
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max_actions_per_step=1,
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), browser
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# Streamlit UI
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st.title('Automated Browser Agent with LLMs 🤖')
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query = st.text_input('Enter your query:', 'go to reddit and search for posts about browser-use')
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provider = st.radio('Select LLM Provider:', ['openai', 'anthropic'], index=0)
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if st.button('Run Agent'):
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st.write('Initializing agent...')
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agent, browser = initialize_agent(query, provider)
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async def run_agent():
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with st.spinner('Running automation...'):
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await agent.run(max_steps=25)
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st.success('Task completed! 🎉')
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asyncio.run(run_agent())
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st.button('Close Browser', on_click=lambda: asyncio.run(browser.close()))
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