GPTCache

Visit Tool

GPTCache is an open-source library designed to create semantic caches for Large Language Model (LLM) queries. It helps reduce LLM API costs and boost query speed by caching responses.

Claim this tool

1View

At a glance

Pricing

open-source

Free tier

Yes

API

—

Skill level

Technical

About

What is GPTCache?

GPTCache is an open-source library that provides a semantic caching mechanism specifically for Large Language Model (LLM) queries. It is built to seamlessly integrate with popular LLM frameworks like LangChain and LlamaIndex. By implementing a semantic cache, GPTCache aims to significantly reduce the operational costs associated with frequent LLM API calls. Additionally, it enhances the performance and speed of applications by serving cached responses for similar or identical queries, rather than re-querying the LLM every time. This makes it a valuable tool for developers and organizations working with LLMs.

Best used for

Optimizing the cost and speed of applications that frequently interact with Large Language Models.

Common actions

Optimize LLM costs

Improve LLM performance

Cache LLM responses

Integrate LLM tools

Develop AI applications

"AI Agents"face swappinggithub copilotdeepfakeopen-sourcelow-code/no-codeautomated workflowcollaborationworkflows

Capabilities

Key features

Semantic cache for LLMs
Reduces API costs
Boosts query speed
Integrates with LangChain
Integrates with LlamaIndex

Target Audience

DevelopersMachine Learning EngineersAI Engineers

Integrations

Not yet documented

Pricing & Plans

open-source

Free

FAQs

Does GPTCache support all LLM providers, or only specific ones?

GPTCache is designed to be highly adaptable. While it integrates seamlessly with popular frameworks like LangChain and LlamaIndex, which support numerous LLMs, its core caching mechanism can be configured to work with virtually any LLM API by defining custom embedding functions and similarity metrics.

How does GPTCache determine if a query is 'semantically similar' enough to return a cached response?

GPTCache uses embedding models to convert queries into vector representations. It then compares the vector of a new query to those in the cache using similarity metrics (e.g., cosine similarity). Users can configure the similarity threshold to control how strict or lenient the matching should be.

What kind of performance improvement can I expect by using GPTCache?

Performance gains vary based on query patterns and cache hit rates. For frequently asked or semantically similar questions, GPTCache can drastically reduce latency by serving responses instantly from the cache, bypassing the need for a full LLM inference cycle, and significantly cutting API costs.

Trending

Subcategories trending in Coding & Development

Open Source & Models DevOps & Infrastructure No-Code / Low-Code Testing & QA Backend & APIs Prompt Engineering

Trending

Explore

Browse AI tools by category

Content & Design Productivity & Business Coding & Development AI Agents & Automation Research & Education Wellness & Lifestyle Career Development Marketing & Growth Data & Analytics Customer Support & CX Finance E-commerce