Agent_In_Action and all-agentic-architectures
Project A, a practical development handbook for agentic AI, would likely use the implementations from Project B, an extensive collection of agentic architectures, making them complements.
About Agent_In_Action
FlyAIBox/Agent_In_Action
Agentic AI 智能体开发实战
Implements a complete agentic AI system using LangGraph and MCP protocols, covering architecture (GAME framework with Goals/Actions/Memory/Environment), tool integration patterns, and production deployment via FastAPI + Streamlit with Docker. Includes six end-to-end projects spanning multi-agent orchestration, monitoring via Langfuse, and domain-specific model fine-tuning with LlamaFactory and vLLM inference optimization.
About all-agentic-architectures
FareedKhan-dev/all-agentic-architectures
Implementation of 17+ agentic architectures designed for practical use across different stages of AI system development.
Implements 17+ architectures using LangGraph for stateful agent orchestration, with each pattern (Reflection, ReAct, Planning, Multi-Agent, Tree of Thoughts, etc.) demonstrated end-to-end in executable Jupyter notebooks. Features integrated evaluation via LLM-as-a-Judge for quantitative performance measurement and real-world scenarios spanning financial analysis, coding, and medical triage. Designed as a structured learning path progressing from single-agent enhancements through advanced multi-agent collaboration, memory systems, and self-aware agents with built-in safety mechanisms.
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