📚 Wouldn't it be great to run ReAct, RAG, and Tree of Thoughts behind one API and compare them, instead of wrangling scattered per-paper implementations? This repo delivers exactly that, with all 35 patterns in one place. Title: FareedKhan-dev/all-agentic-architectures URL: 📦 Overview This is a Python library and a "living textbook" implementing 35 production-grade agentic AI patterns. Every architecture exposes the same .run(task) method and returns an identical result shape, so you can swap patterns without touching downstream code. ❓ Challenges Solved Agentic design patterns have been scattered across papers, each with its own implementation and conventions. The real value here is unifying them under a single interface so you can try them side by side. 💡 Core Idea & Approach The central idea is the "deterministic-picker discipline." ・Instead of handing scoring entirely to the LLM, it first has the LLM commit to categorical features like booleans and enums ・The final decision is then composed in Python logic This mitigates the flat-band pathology of LLM-as-Scorer, and it appears in 13 of the 35 architectures. 🎯 Coverage & Use Cases It spans eight families: reasoning and reflection (Reflection, Self-Discover), search (Tree of Thoughts, LATS), RAG (Corrective/Self/Adaptive/GraphRAG), memory (MemGPT, Voyager), tools and actions (ReAct, SWE-Agent), and multi-agent (Debate, STORM). Each pattern ships with an executed Jupyter notebook, giving reproducible references grounded in real LLM output. 📊 Highlights ・Built on LangGraph, with support for Nebius, OpenAI, Anthropic, Ollama and more, switchable via a single env var ・283 passing pytest tests ・On a 17-task benchmark it recently scored 33/42 correct (78%), with Reflection and Self-Consistency among the strongest #AIAgents# #LangGraph#