How to measure prompt cache hit ratio in your Hermes Agent
The article discusses how to measure the prompt cache hit ratio in the Hermes Agent. It emphasizes the importance of maintaining a stable cache to avoid increased costs associated with cache-breaking. The author provides a solution using a Python library called cachebench to track cache performance metrics in real time.
- ▪The prompt cache is a significant factor in the billing for Hermes Agent usage.
- ▪Cache metadata can be retrieved from responses from providers like Anthropic, OpenAI, and Bedrock.
- ▪The cachebench library allows users to compute cache hit ratios and track savings compared to an uncached baseline.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3915555) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Mukunda Rao Katta Posted on May 19 How to measure prompt cache hit ratio in your Hermes Agent #hermesagentchallenge #devchallenge #agents Hermes Agent Challenge Submission If you run Hermes Agent for any real workload, the single biggest knob on your bill is the prompt cache. The Hermes developer notes say it plainly: cache-breaking forces dramatically higher costs. The fix is simple. Do not break the cache. The hard part is knowing whether your cache is actually working.
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