How to cache the Gemini SDK LLM calls with Crowkis
Add a semantic cache to the Gemini SDK so repeated and reworded questions are served for free, no rewrite, self-hosted.
Production LLM traffic is deeply repetitive, and repetition is exactly what a bill is made of. If you build with the Gemini SDK, most of that repetition is invisible in your code but very visible on your bill. A semantic cache in front of your model calls fixes it.
The lowest-friction path is the OpenAI-compatible gateway: point the Gemini SDK's base URL at Crowkis and every model call flows through a semantic cache. Repeated and reworded prompts are served from cache with no upstream call; new ones pass through and get cached.
# point the Gemini SDK at the Crowkis gateway
base_url = "http://127.0.0.1:6380/v1" # semantic cache in front of your providerIn plain words. You don't restructure your the Gemini SDK app. You change where the calls go, and repeats stop costing money.
On repetitive workloads this cuts LLM costs up to 60-70% on repetitive workloads, and every hit comes back with a confidence score so reuse stays safe. Drop it in over RESP, gRPC, REST, or MCP, no rewrite required.