LaVague

LaVague is an open-source framework designed for building and deploying AI-powered web agents. It enables developers to automate web interactions, from navigating complex sites to extracting specific data, all with just a few lines of code. LaVague leverages state-of-the-art Large Action Models to allow agents to understand objectives, generate the necessary web actions, and learn from them. This framework can be used to automate repetitive tasks, enhance QA processes by converting Gherkin specifications into executable tests, or create tailored data retrieval solutions across SaaS platforms. With flexibility for local or private model deployment and customization, LaVague is an ideal tool for professionals seeking to streamline their workflows and improve their use of web-based tools.

LaVague's strength lies in its ability to perform complex web tasks with a high degree of customization. Developers can tailor the agents' tools, knowledge, and integrations to meet specific needs, and also leverage local models like Llama 3 or on-VPC services such as Azure OpenAI for added privacy and control. The project's open-source nature and active community provide ample opportunity for collaboration, contribution, and support, as well as transparent access to its roadmap and development process. Through its framework, LaVague aims to empower users to harness AI’s potential to efficiently interact with the web.