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FareedKhan-dev/all-agentic-architectures

⭐ 4494 Jupyter Notebook added to this list on 2025-12-15 repository created 2025-09-24

The project "All Agentic Architectures" is a comprehensive repository that implements over 17 state-of-the-art AI agentic architectures designed for practical use across various stages of AI system development. It serves as a hands-on masterclass in modern AI agent design, bridging the gap between theoretical concepts and practical, production-ready code. The repository is built using LangChain and LangGraph frameworks and is structured as a living textbook with runnable Jupyter notebooks that progressively build knowledge from foundational patterns to advanced multi-agent and self-aware systems. The project emphasizes a structured learning path, starting with foundational single-agent enhancements such as Reflection, Tool Use, ReAct, and Planning, which improve output quality, enable real-world interaction, combine reasoning and action, and add foresight to agent behavior. It then advances to multi-agent collaboration architectures like Multi-Agent Systems, Blackboard Systems, and Meta-Controller, which enable teams of specialized agents to collaborate, share knowledge, and route tasks efficiently. Further architectures include robust self-correcting loops (PEV), dual-memory systems combining episodic and semantic memory, tree of thoughts for exploring multiple reasoning paths, mental loop simulators for risk assessment, graph-based world-model memory for complex reasoning, ensemble methods for unbiased decision-making, dry-run harnesses for safety-critical deployment, reinforcement learning with human feedback for self-improvement, cellular automata for emergent behavior, and reflexive metacognitive agents that reason about their own capabilities. Each notebook features practical real-world scenarios such as financial analysis, coding, social media management, medical triage, robotics, and high-stakes advisory roles, making the concepts immediately relevant. The repository also incorporates evaluation mechanisms using an LLM-as-a-Judge pattern to provide quantitative feedback on agent performance, which is critical for production AI. Overall, this project is an invaluable resource for developers, researchers, and AI enthusiasts aiming to master the art of building intelligent, adaptive, and collaborative AI systems.

https://github.com/FareedKhan-dev/all-agentic-architectures

agentic-architecturesai-agentsai-evaluationai-system-developmentblackboard-systemscellular-automatadry-run-harnesseducational-aiensemble-methodsepisodic-memorygraph-memoryjupyter-notebookslangchainlanggraphllm-as-a-judgemental-loopmeta-controllermulti-agent-collaborationmulti-agent-systemspevplanningpractical-aireactreflectionreflexive-metacognitive-agentsrlhfself-aware-systemssemantic-memorytool-usetree-of-thoughts