browser-use/web-ui

🖥️ Run AI Agent in your browser.

What it solves

This project provides a user-friendly graphical interface for the browser-use library, allowing users to interact with AI agents that can navigate and use websites. It removes the need for writing code to trigger agentic browser automation tasks.

How it works

Built on Gradio, the WebUI serves as a control panel for the browser agent. It integrates with various Large Language Models (LLMs) such as Google, OpenAI, Azure OpenAI, Anthropic, DeepSeek, and Ollama. Users can configure the agent to use a custom local browser instance to maintain authentication sessions and avoid re-logging into websites.

Who it’s for

Users who want to operate AI browser agents without needing to write Python scripts, as well as developers who want a visual way to monitor and manage their browser-automation agents.

Highlights

  • Broad LLM Support: Compatible with a wide range of providers including DeepSeek, Anthropic, and Ollama.
  • Custom Browser Integration: Ability to use a local browser executable and user data directory to bypass authentication hurdles.
  • Persistent Sessions: Option to keep the browser window open between different AI tasks to maintain state.
  • Detailed Monitoring: Supports high-definition screen recording and VNC viewer access when running via Docker.

Related

  • Project
    browser-use/browser-use

    Browser Use is an open‑source Python/TypeScript library that gives LLM agents full control over a real or cloud‑hosted web browser. It provides 31 browser actions as tools, supports custom functions, works with OpenAI, Anthropic, Google models or its own BU2 model, and offers three usage modes: a fully hosted cloud API, a CLI for existing agents, and a library you embed in your code. Ideal for automating web tasks, building AI assistants that browse, or researching LLM‑driven web navigation.

  • Project
    alibaba/page-agent

    A client-side JavaScript library that embeds an AI agent into web pages for natural language DOM manipulation and automation without requiring headless browsers.

  • Project
    platonai/Browser4

    Browser4 is an AI‑native browser automation engine that lets LLM agents (or humans) drive real browsers via a fast Rust CLI, extract data with zero‑token X‑SQL/CSS selectors, and run large‑scale crawls or ML‑based spreadsheet generation (WebMiner). It combines CDP‑native performance, swarm scaling, and hybrid LLM/ML intelligence, and is distributed as an npm CLI with a Java backend (Maven Central).

  • Project
    open-webui/open-webui

    Open WebUI is an open‑source, self‑hosted web interface for LLMs that works with any OpenAI‑compatible API and with local Ollama models. It provides a rich UI (chat, notes, channels, calendar, voice/video, image generation), extensible plugin system, RBAC, multi‑model support, built‑in RAG (vector DBs, web search), an “Open Terminal” for agents to run code, and enterprise features like LDAP/SSO, SCIM provisioning, and observability. Install via pip, Docker (CPU/GPU, bundled Ollama), or Kubernetes. The ecosystem includes a desktop app, a mobile‑first coding agent, and tools for syncing external knowledge bases.