Redis Semantic Cache

---
name: redis-semantic-cache
description: Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/set via the SDK or REST API, tuning the similarity threshold, separating caches per task type, and filtering with custom attributes. Use when caching LLM completions or RAG answers to cut API cost and latency, building a cache-aside layer in front of OpenAI / Anthropic / etc., tuning hit rate vs precision, or splitting one app's LLM workloads into multiple LangCache caches.
license: MIT
metadata:
  author: Redis, Inc.
  version: "0.1.0"
---

# Redis Semantic Cache

Semantic caching for LLM responses with Redis Cloud's LangCache service. Stores prompts as embeddings; subsequent semantically-similar prompts return the cached response without re-calling the model.

> LangCache is currently in **preview** on Redis Cloud. Features and behavior may change.

## When to apply

- Wrapping an LLM call (OpenAI, Anthropic, etc.) with a cache layer to cut cost and latency.
- Caching RAG answers, classification outputs, or any deterministic LLM workload.
- Tuning the precision/hit-rate trade-off for a semantic cache.
- Splitting one application's LLM workloads across multiple cache instances.

## 1. The cache-aside flow

LangCache fits in front of any LLM call as a standard cache-aside pattern: