Show HN: LáR – An open-source, deterministic "Glass Box" agent framework (github.com)

Lár, an open-source "Glass Box" agent framework, has been introduced as a game-changer for developing deterministic, auditable AI agents. Unlike existing frameworks that often act as black boxes with chaotic behaviors and difficult debugging processes, Lár provides a "define-by-run" environment that meticulously logs every action an agent takes. This audit trail not only enables instant debugging—allowing developers to pinpoint the exact cause of failures—but also ensures full control over agent execution, eliminating uncertainty in multi-agent collaborations. The significance of Lár for the AI/ML community lies in its architectural design that favors reliability and efficiency. Built-without dependencies and optimized for a "Code-as-Graph" execution approach, Lár addresses the pitfalls of traditional frameworks that rely heavily on large language models for every operation, incurring high costs and latency. By utilizing components like GraphState, BaseNode, and GraphExecutor, developers can create agents that operate deterministically, making it feasible to build complex workflows that save both time and operational costs. This marks a shift from merely prototyping chatbots to developing high-performance software agents, thus empowering developers to build more trustworthy AI solutions.