Elastic has just released a new tool called Playground that will enable users to experiment with retrieval-augmented generation (RAG) more easily. RAG is a practice in which local data is added to an LLM, such as private company data or data that is more up-to-date than the LLMs training set. This allows it to give more accurate responses and reduces the occurrence of hallucinations. Playground offers a low-code interface for adding data to an LLM for RAG implementations. They can use any data stored in an Elasticsearch index for this. It also allows developers to A/B test LLMs from different model providers to see what suits their needs best. The platform can utilize transformer models in Elasticsearch and also makes use of the Elasticsearch Open Inference API that integrates with inference providers, such as Cohere and Azure AI Studio. “While prototyping conversational search, the ability to experiment with and rapidly iterate on key components of a RAG workflow is essenti
This website is about programming knowledge. You can call this blog best programming master.