AI Agent Example is a hands-on demonstration repository for developers and researchers interested in building intelligent agents powered by large language models. The project includes sample code for agent planning, memory storage, and tool invocation, showcasing how to integrate external APIs or custom functions. It features a simple conversational interface that interprets user intents, formulates action plans, and executes tasks by calling predefined tools. Developers can follow clear patterns to extend the agent with new capabilities, such as scheduling events, web scraping, or automated data processing. By providing a modular architecture, this template accelerates experimentation with AI-driven workflows and personalized digital assistants while offering insights into agent orchestration and state management.

The AWS Sample Model Context Protocol Demos is an open-source repository showcasing standardized patterns for Large Language Model (LLM) context management and tool invocation. It features two complete demos—one in JavaScript/TypeScript and one in Python—that implement the Model Context Protocol, enabling developers to build AI agents that call AWS Lambda functions, preserve conversation history, and stream responses. Sample code demonstrates message formatting, function argument serialization, error handling, and customizable tool integrations, accelerating prototyping of generative AI applications.

SmolAgents Dynamic Tools extends the open-source SmolAgents Python framework to empower LLM-based agents with dynamic tool invocation. Agents can seamlessly call a variety of pre-built tools—such as web search via SerpAPI, mathematical calculators, date and time retrieval, file system operations, and custom HTTP request handlers—based on user intent and chain-of-thought prompts. Developers can register additional tools or customize existing ones, enabling agents to handle data retrieval, content creation, computation, and external API integration within a unified interface. By evaluating tool availability at runtime, SmolAgents Dynamic Tools optimizes agent workflows, reducing hard-coded logic and improving modularity across diverse application scenarios like research assistance, automated reporting, and chatbot augmentation.