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
Agents Towards Production provides a comprehensive collection of tutorials and resources aimed at guiding developers through the process of building and deploying production-ready Generative AI agents. The project focuses on practical, code-first approaches, covering a wide range of topics essential for enterprise-level agent deployment. Key areas include implementing stateful workflows, integrating vector memory systems, utilizing real-time web search APIs, and containerizing agents using Docker for deployment. It also addresses crucial aspects such as developing FastAPI endpoints, implementing security guardrails, handling GPU scaling for performance, enabling browser automation, and fine-tuning models. Furthermore, the tutorials delve into complex multi-agent coordination, observability for monitoring agent performance, robust evaluation methodologies, and UI development for agent interactions. The project emphasizes the transition from experimental prototypes to robust, scalable enterprise solutions, supported by integrations with frameworks like LangGraph and tools for RAG (Retrieval Augmented Generation), making it a valuable resource for developers and organizations looking to operationalize AI agents.
https://github.com/NirDiamant/agents-towards-production
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.
This repository offers a comprehensive collection of over 50 tutorials and implementations for Generative AI Agent techniques, ranging from basic conversational bots to complex multi-agent systems,...
An open-source curriculum designed to teach the concepts and fundamentals of the Model Context Protocol (MCP) with practical coding examples in multiple programming languages.
A comprehensive collection of practical examples, tutorials, and tools for building powerful LLM-powered AI applications, including chatbots, agents, and workflows, with a focus on the Model Context Protocol (MCP).
The Model Context Protocol project provides a standardized specification and schema for managing model context to enable interoperability in model-driven systems.
A curated repository of modular skills, tools, and tutorials for enhancing AI coding agents like Claude, Codex, Copilot, and VS Code through dynamic instruction files.
A comprehensive curated collection of free resources to learn AI, Machine Learning, Large Language Models, AI Agents, and the Model Context Protocol from scratch.
A comprehensive and detailed guide for Claude Code CLI tool, covering all commands, installation, configuration, and Model Context Protocol (MCP) integration for optimized use.