Developers integrating multiple LLM APIs often receive only raw billing data in JSON format, lacking a web dashboard for monitoring usage and costs. This post addresses that gap by outlining a method to build a custom visualization dashboard. The approach leverages common tools to parse billing JSON, extract key metrics like token consumption and cost per API, and display them in an intuitive interface. This is particularly valuable for teams managing budgets across multiple LLM providers or for indie developers tracking personal usage. The solution is practical, open-source friendly, and can be adapted to various billing formats. It highlights a growing need for transparency in AI service costs and empowers developers to take control of their spending.
Many developers using aggregated LLM APIs face the challenge of opaque billing data buried in JSON responses. This post presents a practical approach to building a custom usage dashboard that visualizes token consumption, cost breakdowns, and trends. It's a timely solution for cost-conscious teams and indie developers.