GPTCache
Accelerates and reduces the cost of large language model (LLM) API calls through semantic caching.
Acerca de
GPTCache is a Python library designed to implement a semantic cache for Large Language Model (LLM) queries. It addresses the challenges of high LLM API costs and slow response times by storing and retrieving similar or related query results. By converting queries into embeddings and utilizing a vector store for similarity search, GPTCache significantly increases cache hit rates, reducing the number of requests and tokens sent to LLM services. This leads to substantial cost savings and performance improvements, often slashing costs by 10x and boosting speed by 100x. Its modular design allows for customization of caching mechanisms, and it offers full integration with popular LLM frameworks like LangChain and Llama_index, making it an essential tool for scalable and cost-efficient LLM application development.
Características Principales
- Enhanced LLM response performance
- Improved scalability and availability by mitigating rate limits
- Adaptable development and testing environment for LLM apps
- Decreased LLM API expenses
- Customizable semantic caching with modular design
- 7,580 GitHub stars
Casos de Uso
- Optimizing LangChain applications for cost and speed
- Improving Llama_index performance for data retrieval and QA
- Accelerating OpenAI API calls for chat completion, image generation, and speech-to-text
