AIエージェント
go-micro
A framework for building agents and services
★ 23.1k スターApache-2.0
ガイドを見る →LaVagueは、lavague-aiが公開しているオープンソースのAIエージェントプロジェクトです（GitHub: lavague-ai/LaVague）。GitHubスターは6,395、フォークは575で、Apache-2.0ライセンスの下で公開されています。GitHubでの最終更新は2025年1月21日です。
A Large Action Model framework for building AI web agents that browse and act for you.
Define the objective your agent should accomplish on a website, in one clear sentence.
Install LaVague from PyPI and pick a driver — Selenium, Playwright or the Chrome extension.
Connect the multimodal LLM the World Model will use to read pages and plan actions.
Launch the Gradio demo or write a short script, give the agent an objective, and watch it act on the page.
A World Model takes your objective plus the current web page state and outputs the set of instructions needed to progress.
Instructions are compiled into action code — Selenium or Playwright — and executed against the live page.
Supports a Selenium webdriver, a Playwright webdriver and a Chrome extension driver.
LaVague QA provides tooling aimed at QA engineers for automated web testing.
A ready-made Gradio agent demo lets you try web agents interactively without writing integration code first.
Data collection is documented in the README, including how to turn telemetry off entirely.
Clone LaVague to explore the framework and examples.
git clone https://github.com/lavague-ai/LaVague.git
cd LaVagueInstall LaVague from PyPI.
pip install lavagueStart the Gradio agent demo and give the agent a web objective (see the README's Getting Started for the exact demo command).
# Launch Gradio Agent Demo — see README for the exact commandLaVague is maintained by lavague-ai, with documentation at docs.lavague.ai.
The framework is Apache-2.0 licensed and free to use; you pay for the LLM calls your agents make.
Yes, in practice: the World Model uses an LLM (the README's examples use GPT-4-class multimodal models), so you need a key for your chosen provider.
Plain Selenium requires hand-written scripts; LaVague adds an LLM World Model that plans actions from a natural-language objective, then compiles them to Selenium or Playwright.
pip install lavague, configure your LLM, and run the Gradio demo with a simple objective.
A framework for building agents and services
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