llm-caching
CommunitySlash LLM costs & latency.
AuthorBagelHole
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill significantly reduces LLM API costs and response latency by implementing multi-layered caching strategies for repeated or semantically similar queries.
Core Features & Use Cases
- Multi-Layered Caching: Utilizes exact match (Redis), semantic similarity (GPTCache/Qdrant), and provider-side prompt caching (Anthropic/OpenAI).
- Cost & Latency Reduction: Aims to cut API costs by 30-70% and improve throughput.
- Use Case: Deploying an FAQ bot that receives many similar questions; implementing prompt caching for long system prompts in services like Claude or OpenAI to save on token costs for repeated context.
Quick Start
Use the llm-caching skill to process a user query, leveraging exact match, semantic, and provider-side caching layers to optimize LLM interactions.
Dependency Matrix
Required Modules
redisopenaigptcachesentence-transformersqdrant-clientlitellmanthropic
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: llm-caching Download link: https://github.com/BagelHole/DevOps-Security-Agent-Skills/archive/main.zip#llm-caching Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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