GPA-LM is a Python-based framework designed to simplify the creation and orchestration of AI agents powered by large language models. It features a planner that breaks down high-level instructions into sub-tasks, an executor that manages tool calls and interactions, and a memory module that retains context across sessions. The plugin architecture allows developers to add custom tools, APIs, and decision logic. With multi-agent support, GPA-LM can coordinate roles, distribute tasks, and aggregate results. It integrates seamlessly with popular LLMs like OpenAI GPT and supports deployment on various environments. The framework accelerates the development of autonomous agents for research, automation, and application prototyping.

Agentic Website Dev brings automation to website development by coordinating specialized AI agents. One agent analyzes user prompts to draft site architecture, another generates responsive HTML and CSS templates, while a coding agent implements dynamic JavaScript features. Finally, a deployment agent packages and pushes the site to hosting platforms like Vercel or Netlify. This framework abstracts the entire workflow—planning, coding, testing, and deployment—enabling rapid prototyping and iteration. Developers define website requirements in plain English, and the agents collaborate to produce a fully functional, live website. This reduces manual coding, accelerates time-to-market, and democratizes web development for non-technical stakeholders.