import asyncio import base64 from playwright.async_api import async_playwright from agent_sandbox import Sandbox async def site_to_markdown(): # Initialize sandbox client c = Sandbox(base_url="http://localhost:8080") home_dir = c.sandbox.get_context().home_dir # Browser: Automation to download HTML async with async_playwright() as p: browser_info = c.browser.get_info().data page = await (await p.chromium.connect_over_cdp(browser_info.cdp_url)).new_page() await page.goto("https://example.com", wait_until="networkidle") html = await page.content() screenshot_b64 = base64.b64encode(await page.screenshot()).decode('utf-8') # Jupyter: Convert HTML to markdown in sandbox c.jupyter.execute_code(code=f""" from markdownify import markdownify html = '''{html}''' screenshot_b64 = "{screenshot_b64}"  md = f"{{markdownify(html)}}\\n\\n![Screenshot](data:image/png;base64,{{screenshot_b64}})" with open('{home_dir}/site.md', 'w') as f:  f.write(md) print("Done!") """) # Shell: List files in sandbox list_result = c.shell.exec_command(command=f"ls -lh {home_dir}") print(f"Files in sandbox: {list_result.data.output}") # File: Read the generated markdown return c.file.read_file(file=f"{home_dir}/site.md").data.content if __name__ == "__main__": result = asyncio.run(site_to_markdown()) print(f"Markdown saved successfully!")

import asyncio from agent_sandbox import Sandbox from browser_use import Agent, Tools from browser_use.browser import BrowserProfile, BrowserSession from browser_use.llm import ChatOpenAI sandbox = Sandbox(base_url="http://localhost:8080") print("sandbox", sandbox.browser) cdp_url = sandbox.browser.get_info().data.cdp_url browser_session = BrowserSession( browser_profile=BrowserProfile(cdp_url=cdp_url, is_local=True) ) tools = Tools() async def main(): agent = Agent( task='Visit https://duckduckgo.com and search for "browser-use founders"', llm=ChatOpenAI(model="gcp-claude4.1-opus"), tools=tools, browser_session=browser_session, ) await agent.run() await browser_session.kill() input("Press Enter to close...") if __name__ == "__main__": asyncio.run(main())

from langchain.tools import BaseTool from agent_sandbox import Sandbox class SandboxTool(BaseTool): name = "sandbox_execute" description = "Execute commands in AIO Sandbox" def _run(self, command: str) -> str: client = Sandbox(base_url="http://localhost:8080") result = client.shell.exec_command(command=command) return result.data.output

from openai import OpenAI from agent_sandbox import Sandbox import json client = OpenAI( api_key="your_api_key", ) sandbox = Sandbox(base_url="http://localhost:8080") # define a tool to run code in the sandbox def run_code(code, lang="python"): if lang == "python": return sandbox.jupyter.execute_code(code=code).data return sandbox.nodejs.execute_nodejs_code(code=code).data # Use OpenAI response = client.chat.completions.create( model="gpt-4", messages=[{"role": "user", "content": "calculate 1+1"}], tools=[ { "type": "function", "function": { "name": "run_code", "parameters": { "type": "object", "properties": { "code": {"type": "string"}, "lang": {"type": "string"}, }, }, }, } ], ) if response.choices[0].message.tool_calls: args = json.loads(response.choices[0].message.tool_calls[0].function.arguments) print("args", args) result = run_code(**args) print(result['outputs'][0]['text'])