LiteWebAgent: The Open-Source Suite for VLM-Based Web-Agent Applications
원문 초록
We introduce LiteWebAgent, an open-source suite for VLM-based web agent applications. Our framework addresses a critical gap in the web agent ecosystem with a production-ready solution that combines minimal serverless backend configuration, intuitive user and browser interfaces, and extensible research capabilities in agent planning, memory, and tree search. For the core LiteWebAgent agent framework, we implemented a simple yet effective baseline using recursive function calling, providing with decoupled action generation and action grounding. In addition, we integrate advanced research components such as agent planning, agent workflow memory, and tree search in a modular and extensible manner. We then integrate the LiteWebAgent agent framework with frontend and backend as deployed systems in two formats: (1) a production Vercel-based web application, which provides users with an agent-controlled remote browser, (2) a Chrome extension leveraging LiteWebAgent's API to control an existing Chrome browser via CDP (Chrome DevTools Protocol). The LiteWebAgent framework is available at https://github.com/PathOnAI/LiteWebAgent, with deployed frontend at https://lite-web-agent.vercel.app/.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Parallels Between VLA Model Post-Training and Human Motor Learning: Progress, Challenges, and Trends
WorldVLA: Towards Autoregressive Action World Model
AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning
Time to Talk: LLM Agents for Asynchronous Group Communication in Mafia Games
STAR: Learning Diverse Robot Skill Abstractions through Rotation-Augmented Vector Quantization
OWMM-Agent: Open World Mobile Manipulation With Multi-modal Agentic Data Synthesis
토론
이 논문과 연결된 포럼 글이 아직 없습니다.