LLM-Agent provides a structured architecture for building intelligent agents using LLMs. It includes a toolkit for defining custom tools, memory modules for context preservation, and executors that orchestrate complex chains of actions. Agents can call APIs, run local processes, query databases, and manage conversational state. Prompt templates and plugin hooks allow fine-tuning of agent behavior. Designed for extensibility, LLM-Agent supports adding new tool interfaces, custom evaluators, and dynamic routing of tasks, enabling automated research, data analysis, code generation, and more.

Agno AI Agent is designed to help developers quickly build autonomous agents powered by large language models. It provides a modular tool registry, memory management, planning and execution loops, and seamless integration with external APIs (such as web search, file systems, and databases). Users can define custom tool interfaces, configure agent personalities, and orchestrate complex, multi-step workflows. Agents can plan tasks, call tools dynamically, and learn from previous interactions to improve performance over time.