Lár the Pytorch for Agents is the open-source "glass box" engine for building, debugging, and running auditable, self-correcting AI agents.

Lár: The PyTorch for Agents

Lár (Irish for "core" or "center") is the open source standard for Deterministic, Auditable, and Air-Gap Capable AI agents.

It is a "define-by-run" framework that acts as a Flight Recorder for your agent, creating a complete audit trail for every single step.

[!NOTE] Lár is NOT a wrapper. It is a standalone, ground-up engine designed for reliability. It does not wrap LangChain, OpenAI Swarm, or any other library. It is pure, dependency-lite Python code optimized for "Code-as-Graph" execution.

The "Black Box" Problem

You are a developer launching a mission-critical AI agent. It works on your machine, but in production, it fails. You don't know why, where, or how much it cost. You just get a 100-line stack trace from a "magic" framework.

The "Glass Box" Solution

Lár removes the magic.

It is a simple engine that runs one node at a time, logging every single step to a forensic Flight Recorder.

This means you get:

1. Instant Debugging: See the exact node and error that caused the crash.
2. Free Auditing: A complete history of every decision and token cost, built-in by default.
3. Total Control: Build deterministic "assembly