Cache LlamaIndex in your meeting-notes summarizer with Crowkis
Building meeting-notes summarizers on LlamaIndex? Add a semantic cache so similar summaries requested repeatedly stop costing full price.
Meeting-notes summarizers built on LlamaIndex share one problem: similar summaries requested repeatedly. Each repeat is a full-price LlamaIndex call for an answer you already have.
Put a semantic cache in front. Point LlamaIndex's base URL at the Crowkis OpenAI-compatible gateway, or wrap the call in get-or-compute, and reworded repeats are served from cache, no rewrite of your meeting-notes summarizers logic.
base_url = "http://127.0.0.1:6380/v1" # Crowkis gateway, semantic cache in front
On repetitive traffic this cuts costs up to 60-70% on repetitive workloads, and every hit carries a confidence score so reuse stays safe. Runs self-hosted with zero egress, nothing leaves your machine.