agents-from-scratch and ai-agents-from-scratch
These two tools are ecosystem siblings, with "ai-agents-from-scratch" being a more comprehensive and updated version of "agents-from-scratch," incorporating advanced concepts like function calling, memory, and ReAct patterns, while both share the educational goal of building AI agents from first principles using local LLMs.
About agents-from-scratch
pguso/agents-from-scratch
Build AI agents from first principles using a local LLM - no frameworks, no cloud APIs, no hidden reasoning.
This project helps software developers understand and build AI agents from foundational principles. It takes you step-by-step through creating a functional agent using a local large language model, starting with basic text interactions and progressing to complex planning, memory, and tool usage. You'll gain a deep, transparent understanding of how agents work by building one from scratch.
About ai-agents-from-scratch
pguso/ai-agents-from-scratch
Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of function calling, memory, and ReAct patterns.
This project helps software developers understand how AI agents work by building them step-by-step using local large language models (LLMs). Developers learn to combine an LLM with tools, memory, and reasoning patterns to create agents that can perform tasks. It takes fundamental concepts and outputs functional, explainable code for various agent architectures.
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