{"repo":"Ali-hey-0/ai-runtime-lab","free":true,"listed":false,"github":"https://github.com/Ali-hey-0/ai-runtime-lab","clone":"git clone https://github.com/Ali-hey-0/ai-runtime-lab.git","description":"Engineering deterministic, production-grade systems around non-deterministic LLMs — FSM, durable execution, retries, DAGs, agent runtimes, model routing, edge inference, RAG, memory, multi-agent orchestration, security, and observability. 14 runnable proof-of-concept phases.","language":"Python","stars":38,"topics":["agent-architecture","agent-memory","agentic-ai","ai-agents","ai-security","dag","durable-execution","finite-state-machine","idempotency","llm"],"license":null,"category":"ai-agents","readme_excerpt":"🧠 AI Runtime Lab Engineering Deterministic Systems Around Non-Deterministic Models A hands-on curriculum and reference implementation for building production-grade agentic AI systems — from state machines to multi-agent swarms. Philosophy • Architecture • Phases • Repository Map • Roadmap • فارسی --- 📖 About This Repository This repository is not a framework, and it is not a wrapper around an LLM API. It is a systems-engineering lab built to answer one question properly: How do you build reliable, auditable, production-grade software on top of a component that is fundamentally probabilistic? Every folder here is a self-contained, minimal, runnable proof-of-concept for one architectural concern in agentic AI systems — state control, crash recovery, retries, parallel execution, model routing, edge inference, retrieval, memory, multi-agent orchestration, security, and observability. The code is intentionally small (30–100 lines per concept). The goal is transferable mental models , not framework mastery — you should be able to look at any agent framework (LangGraph, Temporal, AutoGen, CrewAI, Restate...) afterward and immediately recognize which of these primitives it is (re)implementing, and what trade-off it made. This is a personal engineering-education project, structured as a progressive curriculum with runnable reference code at each stop. --- 🎯 Core Philosophy The entire lab is built on a single axiom, referred to throughout as AI Systems Thinking : LLMs are probabilis","default_branch":null,"files":null,"tree":[],"storefront":"/r/Ali-hey-0","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Ali-hey-0/ai-runtime-lab/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}