This project is an automation framework that connects large language models to web browsers via the Chrome DevTools Protocol for autonomous task execution. It functions as a bridge between intelligent agents and browser engines, allowing for the direct control of browser sessions and profiles.
Die Hauptfunktionen von browser-use/browser-harness sind: Agentic Browser Controllers, LLM-Driven Automation, Dynamic Helper Generation, Browser Automation Agents, Self-Improving Automation Code, DOM State Inspection, Dynamic Automation Helper Generation, Element Interaction.
Open-Source-Alternativen zu browser-use/browser-harness sind unter anderem: vercel-labs/agent-browser — This project is an agentic framework designed to enable autonomous web navigation and browser automation. It functions… lavague-ai/lavague — LaVague is an LLM web agent framework and large action model designed to translate natural language instructions into… browser-use/workflow-use — This project is an LLM browser automation framework and AI agent browser interface. It serves as a control layer that… chromedp/chromedp — chromedp is a browser automation framework and driver that controls web browsers via the Chrome DevTools Protocol. It… autoscrape-labs/pydoll — pydoll is a Chrome DevTools Protocol automation library and headless browser controller used for web data extraction… ultrafunkamsterdam/nodriver — nodriver is an asynchronous Chromium browser automation framework that provides headless control and web scraping…
This project is an agentic framework designed to enable autonomous web navigation and browser automation. It functions as a controller that translates natural language instructions into deterministic browser actions, allowing agents to interact with websites, perform data extraction, and manage complex authentication flows. By leveraging accessibility trees and semantic element resolution, the framework mimics human-like navigation, moving beyond brittle DOM selectors to interact reliably with modern web interfaces. The framework distinguishes itself through its focus on secure, scalable exec
LaVague is an LLM web agent framework and large action model designed to translate natural language instructions into executable browser automation scripts. It functions as a multi-modal orchestrator that reasons over web page states and HTML content to automate multi-step tasks via a Selenium-based automation engine. The framework features a modular model provider layer, allowing users to swap between different language and vision models from providers such as Anthropic, Gemini, and Azure OpenAI. It employs a multi-modal world model to process screenshots and HTML structures, utilizing retri
This project is an LLM browser automation framework and AI agent browser interface. It serves as a control layer that translates natural language instructions into browser interactions using large language models, enabling AI agents to navigate and interact with web pages through standardized browser-control functions. The system functions as an RPA workflow orchestrator and headless browser management tool, capable of recording and replaying deterministic browser sequences to automate repetitive tasks. It distinguishes itself through stealth configurations, including residential proxies and
chromedp is a browser automation framework and driver that controls web browsers via the Chrome DevTools Protocol. It functions as a headless browser automation tool and web browser controller, enabling the programmatic management of browser sessions, targets, and network responses through a remote debugging interface. The project provides specialized capabilities for Chrome DevTools Protocol automation, including headless browser testing, web scraping and data extraction, and mobile device emulation. It also supports browser-based visual regression by capturing precise screenshots of web pag