Minimalist Agent provides a bare-bones framework for building AI agents in Python. It leverages LangChain’s agent classes and OpenAI’s API to perform multi-step reasoning, dynamically select tools, and execute functions. You can clone the repository, configure your OpenAI API key, define custom tools or endpoints, and run the CLI script to interact with the agent. The design emphasizes clarity and extensibility, making it easy to study, modify, and extend core agent behaviors for experimentation or teaching.

GRASP provides a structured pipeline for building AI agents in TypeScript or JavaScript environments. At its core, developers define agents by registering a set of tools—functions or external API connectors—and specifying prompt templates that guide agent behavior. Built-in memory modules allow agents to store and retrieve contextual information, enabling multi-turn conversations with persistent state. The planning component orchestrates tool selection and execution based on user input, while the execution layer handles API calls and result processing. GRASP’s plugin system supports custom extensions, enabling capabilities such as retrieval-augmented generation (RAG), scheduling tasks, and logging. Its modular design means teams can choose only the components they need, facilitating integration with existing systems and services for chatbots, virtual assistants, and automated workflows.