What it does
A semantic cache for LLM applications, with integrations for LangChain and LlamaIndex-style workflows.
Why it belongs here
The cheapest token is the one you do not send twice. Semantic caching is the unglamorous cost killer.
Best use case
High-repeat workloads where similar prompts or retrieval requests can reuse prior responses without hurting correctness.
How to use it
Cache normalized prompts or semantic matches, set freshness rules, and track cache hit rate, latency, and avoided model cost.
Limits
Caching can serve stale or inappropriate answers if similarity thresholds, invalidation, and user-specific context are not handled carefully.
Tags
semantic-cachecost-controllatency
