patchy631/ai-engineering-hub
AI Engineering Hub offers in-depth tutorials and practical resources on Large Language Models, Retrieval-Augmented Generation, and real-world AI agent applications for all skill levels.
Awesome MCP › MCP Resources & Educational Materials
strands-agents/samples
Strands Agents Samples is a repository designed to provide example projects that demonstrate how to build AI agents using the Strands Agents SDK. The approach is model-driven, focusing on simplicity and educational value, allowing users to create AI agents with just a few lines of code. The repository serves as a learning and demonstration tool rather than a production-ready solution, emphasizing the importance of security and testing before deployment in real environments. The repository includes a variety of sample projects and tutorials that guide users through the process of setting up the environment, installing necessary packages, configuring model providers, and building their first AI agent. It features practical examples such as creating tools for counting letters in words, performing calculations, and checking the current time, showcasing the integration of different functionalities within an AI agent. The samples are organized into directories for tutorials and real-world use cases, providing a structured learning path from fundamental concepts to more advanced applications. The project encourages community contributions and provides detailed documentation, including a contributing guide, security information, and licensing under the Apache License 2.0. Strands Agents Samples is part of a broader ecosystem that includes the Strands Agents SDK, tools, an agent builder, and an MCP server, all aimed at facilitating the development of AI agents. The repository is actively maintained with visible commit activity and issue tracking, reflecting ongoing development and community engagement. Overall, this project is a valuable resource for developers and researchers interested in exploring AI agent development through a model-driven methodology, offering practical examples and a supportive framework to accelerate learning and experimentation.
https://github.com/strands-agents/samples
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