Show HN: AIOpt – local-only guardrail for LLM token/cost regressions (github.com)

AIOpt, a new tool for managing costs associated with large language models (LLMs), has been launched as a local-only guardrail system designed to prevent unexpected cost spikes during development. By analyzing baseline usage logs against proposed changes, AIOpt provides deterministic verdicts on the potential financial impact of alterations before they're deployed. This tool is significant for the AI/ML community as it addresses a common pain point: the hidden cost increases related to model prompts, routing, and system traffic that can lead to budget overruns. Key features include a user-friendly local dashboard that auto-collects usage data, actionable reports, and a continuous integration-friendly gate to block risky changes. AIOpt supports various configurations, such as context multipliers and budget thresholds, to tailor its assessments to specific project needs. By enabling teams to visualize and control AI operational costs, AIOpt mitigates the anxiety of unforeseen expenses, ensuring developers can test modifications safely. This ensures economic sustainability in deploying AI technologies while maintaining efficiency and clarity in cost management.