Prompt caching in generative response engines
Topics: Chunk Relevance, LLM Readability, LLMO / GEO, OpenAI / ChatGPT, Retrieval Augmented Generation (RAG)
This patent, assigned to OpenAI OpCo, LLC, describes a system and method for caching prompts used with generative response engines (such as large language models) within a cloud computing environment. The core idea is that when a user sends a prompt to a generative AI service via an API, the system can hash a portion of that prompt and use it to route the request to the same server that previously processed a similar prompt. By reusing previously activated tokens (intermediate computational results) from cached prompts, the system avoids redundant computations, reduces latency, lowers power consumption, and enables cost savings for the user through discounted input token pricing. The patent also covers caching of multimodal inputs such as images and audio, and describes an automatic billing mechanism that credits users for reused cached tokens.
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