Building Agent Chains and Self-Improving Loops with LangChain and Ollama

Large Language Models (LLMs) are great at responding to prompts, but what if you could orchestrate multiple LLMs to collaborate, each playing a specific role, like characters in a game or components in a system? That’s exactly what I explored with a tool I developed using LangChain and Ollama , two fantastic libraries that make it easy to run local LLMs and compose them into complex chains. The idea: define a series of agents , each with a role and a prompt, and chain them together so that the output of one