Building LLM Applications with Kernel Memory and Redis
Blog post from Redis
Microsoft's developer toolkit, Semantic Kernel, now integrates with Redis to allow developers to build high-performance AI applications. The integration enables the use of unstructured multimodal data and common LLM design patterns such as retrieval-augmented generation (RAG). By using Redis as the back end for Kernel Memory, developers can achieve high performance and reliability in their apps. Semantic Kernel is designed to be platform-neutral, allowing it to work with any language that can make HTTP requests. The integration of Kernel Memory with Redis makes managing the memory layer of the semantic computer more intuitive and flexible.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 7 | 2,643 | 305 | 124 | -22% |
| RAG | 5 | 773 | 144 | 59 | -57% |
| Vector Search | 4 | 1,187 | 169 | 73 | -55% |
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