LaVague is an open-source Large Action Model (LAM) framework developed by Mithril Security, specifically designed to facilitate the creation and deployment of AI agents. This framework simplifies the complexities involved in AI development, making it accessible to developers of varying skill levels. LaVague is particularly useful in the domains of web automation and AI-driven information retrieval, offering enhanced performance for tasks such as retrieving current information, automating web interactions, and accessing sensitive data from various Software as a Service (SaaS) tools. LaVague boasts a range of features that enable developers to create efficient AI agents capable of executing complex tasks autonomously. The framework's design emphasizes flexibility, accuracy, and community involvement. Below is an overview of its key features: LaVague can be applied in various scenarios, demonstrating its versatility and effectiveness in automating tasks and enhancing productivity: To begin using LaVague, developers can access the open-source framework through its official repository on GitHub. The repository provides documentation, installation guides, and examples to help users familiarize themselves with the features and capabilities of LaVague. For those interested in exploring the framework further, engaging with the community through forums and collaborative projects is encouraged.Features
Feature
Description
World Model and Action Engine
Translates objectives and web states into executable instructions, allowing for the generation of necessary code to perform tasks autonomously.
Local and Remote LLM Support
Supports both local and remote Large Language Model (LLM) calls, maintaining user privacy and control.
Advanced AI Techniques
Utilizes local embeddings and few-shot learning to generate relevant Selenium code without extensive fine-tuning.
Community Sharing and Collaboration
Encourages developers to share their work and innovations, promoting collaboration within the community.
Web Automation and Private Data Access
Automates interactions such as bill payments and form filling, while accessing private data from SaaS tools.
Transparency and User Alignment
Utilizes open-source projects to ensure transparency and align the AI agent with user interests, promoting ethical AI development.
Use Cases
How to Get Started
The pricing for LaVague AI agents is structured based on various usage factors, including model selection, complexity, and token consumption. However, no specific pricing is available. For more detailed information on costs, please refer to the official LaVague website.LaVague AI Agents Pricing