tools-only The "Glass Box" Philosophy
The primary challenge in production-grade AI is a lack of traceability. When a multi-step agent fails, it's often impossible to determine why.
The "Black Box" (Chatbots)
Traditional agent frameworks build "Chatbots." A chatbot is probabilistic, messy, and hard to reproduce.
- Scientific Flaw: If you run a chatbot twice with the same input, you might get different answers.
- Regulatory Nightmare: You cannot audit a probability cloud. You cannot submit a chat log to an auditor.
The "Glass Box" (Scientific Workflows)
Lár is built for Science, not Chat. We believe that reliability comes from deterministic reproducibility.
1. The Reproducibility Standard
Lár is Deterministic out of the box.
- Immutable Audit Trails: Every state change is a cryptographic entry in a flight log.
- 21 CFR Part 11: We don't just "log" text; we log the entire causal chain of the agent's reasoning.
2. Audit-Ready Hooks
Real research happens in SCIFs and secure labs.
- Other Frameworks: Require cloud tracing (LangSmith) or constant API calls.
- Lár: The engine is fully decoupled from the internet. It provides hooks for air-gapped environments.
- Air-Gap: Lár can run entirely offline for maximum security.
The "Glass Box" (The Lár Way)
Lár is built on the opposite philosophy. We believe that reliability comes from simplicity and transparency.
Our "engine" (GraphExecutor) is simple, "dumb," and predictable. It only knows how to do one thing:
Run one node at a time.
Log the exact change to the agent's memory (
state_diff).Move to the next node.
This "glass box" approach is not an "add-on"; it is the core, default, open-source output of the engine.
This means you get:
Instant Debugging: You can see the exact node that failed, the exact data it received, and the exact error it produced.
Total Auditability: Your "history log" is a complete, immutable "flight data recorder" for every agent run. This is essential for compliance and security.
Deterministic Control: You are not in a "chaotic chat room." You are building a deterministic "assembly line," where you have 100% control over the agent's path.
Lár is the framework for developers who are tired of "magic" and are ready to build production-grade agents they can actually trust.