Show HN: Flatagents: State machine orchestration with stateless LLM agents (github.com)

A new tool named Flatagents has been introduced, enabling the orchestration of stateless large language model (LLM) agents through YAML definitions. This innovative system allows users to create and manage LLM agents and state machines, facilitating both simple and complex workflows. Flatagents emphasizes composition over inheritance, enabling users to define agents and machines in a compact, language-agnostic manner while ensuring inputs and outputs can be easily managed and inspected. This development is significant for the AI/ML community as it simplifies the integration and orchestration of LLMs in various applications, from code reviews to complex multi-agent workflows. Flatagents supports functionalities such as dynamic agent creation, error recovery, and conditional execution, thereby enhancing the capabilities of LLM implementations. The architecture, inspired by Kubernetes manifests, offers common TypeScript and Python interfaces, positioning Flatagents as a versatile tool in the growing landscape of LLM orchestration. With potential applications ranging from document analysis to creative writing, Flatagents represents a substantial step forward in managing LLM-based tasks in an efficient and accessible manner.