Cache LlamaIndex in your voice assistant with Crowkis
Building voice assistants on LlamaIndex? Add a semantic cache so latency-sensitive, repetitive spoken queries stop costing full price.
Voice assistants built on LlamaIndex share one problem: latency-sensitive, repetitive spoken queries. 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 voice assistants logic.
base_url = "http://127.0.0.1:6380/v1" # Crowkis gateway, semantic cache in frontIn plain words. The voice assistants keep working exactly as before; the repeats just stop hitting the model.
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.