LUT Agent

Technical Explanation

The LUT Agent wraps the standard client libraries for OpenAI, Anthropic, and Gemini. When a developer replaces their client instantiation with the Lutflow wrapper, every inference call passes through the enforcement layer. The agent checks the call against active budget policies (caps, model restrictions, rate limits) and, on breach, applies the configured strategy in-process: raise an error, warn and continue, invoke a callback, or SIGKILL the current process. The entire enforcement check happens locally, with no round-trip to a remote server. The LUT Agent is installed via pip install lutflow and requires three lines of code change in the application: import, initialization with budget policy, and client replacement.

Business Explanation

For development teams, the LUT Agent is the fastest path to budget enforcement. No infrastructure changes, no DevOps involvement — just pip install and three lines of code. For engineering managers, it provides per-developer and per-project cost control. For CTOs, it means budget enforcement can be added to any existing application without architectural changes.

Lookup → Flow → Value

The LUT Agent is the application-level enforcement layer. It sits above the application code and intercepts inference calls, applying financial policy before each API request is sent. Sentinel, by contrast, is monitoring-only and metadata-only: it reports infrastructure-level telemetry but does not itself enforce budget policy.

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Frequently Asked Questions