OperAgents is a developer-oriented toolkit for building and orchestrating autonomous agents using large language models like GPT. It supports defining custom agent classes, integrating external tools (APIs, databases, code execution), and managing agent memory for context retention. Through configurable pipelines, agents can perform multi-step tasks—such as research, summarization, and decision support—while dynamically invoking tools and maintaining state. The framework includes modules for monitoring agent performance, handling errors automatically, and scaling agent executions. By abstracting LLM interactions and tool management, OperAgents accelerates the development of AI-driven workflows in domains like automated customer support, data analysis, and content generation.

OSU NLP Middleware is a lightweight framework built in Python that simplifies the development of AI agent systems. It provides a core agent loop that orchestrates interactions between natural language models and external tool functions defined as plugins. The framework supports popular LLM providers (OpenAI, Hugging Face, etc.), and enables developers to register custom tools for tasks like database queries, document retrieval, web search, mathematical computation, and RESTful API calls. Middleware manages conversation history, handles rate limits, and logs all interactions. It also offers configurable caching and retry policies for improved reliability, making it easy to build intelligent assistants, chatbots, and autonomous workflows with minimal boilerplate code.