Semantic caching & routing: two powerful patterns for vector classification

Redis' vector datatype facilitates rapid unsupervised classification, supporting the semantic caching and routing patterns to optimize system performance. Semantic caching uses vector math to determine if an input is close enough to a cached result, minimizing the need to recompute expensive processes, while semantic routing classifies inputs into multiple labels swiftly, directing them to appropriate paths based on predefined criteria. These techniques offer a cost-effective and efficient alternative to relying solely on large language models (LLMs) for processing, reducing latency and resource consumption. Implementable across various stages of an application, they enhance performance by avoiding redundant computations and enabling quick classification of diverse data types such as text, images, or audio. By employing RedisVL, developers can utilize these patterns easily, ensuring optimal system responses with minimal resource use.

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