How to cache LangChain LLM calls with Crowkis
Add a semantic cache to LangChain so repeated and reworded questions are served for free, no rewrite, self-hosted.
The cheapest token is the one you never spend twice. If you build with LangChain, 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 LangChain'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 LangChain at the Crowkis gateway base_url = "http://127.0.0.1:6380/v1" # semantic cache in front of your provider
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. Runs self-hosted with zero egress, nothing leaves your machine.