Creativity · Agent Protocol
LaVague: Large Action Model Web Agent Framework
LaVague, open-sourced in 2024, is a web agent framework centered on a Large Action Model (LAM): a small, fine-tuned model that maps natural-language web instructions into concrete browser actions (Selenium or Playwright). LaVague combines a Retriever (find the right DOM context) with a LAM (emit an action), producing a transparent, auditable, lightweight alternative to frontier-model web agents.
Protocol facts
- Sponsor
- LaVague AI (open source)
- Status
- stable
- Spec
- https://github.com/lavague-ai/LaVague
- Interop with
- Selenium, Playwright, Hugging Face, LlamaIndex
Frequently asked questions
What is a Large Action Model?
A LAM is a model trained to emit actions (clicks, typing, URL visits) rather than freeform text. LaVague popularized the term for a fine-tuned small model that is fast and cheap but specialized to web-action prediction.
How does LaVague handle complex pages?
A Retriever first selects the minimal DOM slice relevant to the instruction; the LAM then emits an action scoped to that slice. This keeps context small and reliable on real-world pages.
Is it still active in 2026?
LaVague's open-source repo is still maintained and widely cited in research; it's used as a baseline and a teaching tool even where production deployments prefer frontier-model pipelines.
Sources
- LaVague GitHub — accessed 2026-04-20
- LaVague docs — accessed 2026-04-20