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guidesMay 11, 2026· 4 min read

Cache the OpenAI Python SDK in your AI search with Crowkis

Building AI search on the OpenAI Python SDK? Add a semantic cache so popular queries hit again and again stop costing full price.

AI search built on the OpenAI Python SDK share one problem: popular queries hit again and again. Each repeat is a full-price the OpenAI Python SDK call for an answer you already have.

Put a semantic cache in front. Point the OpenAI Python SDK'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 AI search logic.

the OpenAI Python SDK + Crowkis
base_url = "http://127.0.0.1:6380/v1"   # Crowkis gateway, semantic cache in front
In plain words: The AI search 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.