How to cache LangFlow LLM calls with Crowkis
Add a semantic cache to LangFlow so repeated and reworded questions are served for free, no rewrite, self-hosted.
Your users ask the same things all day, phrased a hundred different ways. If you build with LangFlow, 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 LangFlow'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 LangFlow 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. It's one self-hosted binary, Redis-compatible, free to run.