#rag

#rag

Developers can now use search and vector search functionality in MongoDB Community Edition and Enterprise Server. These capabilities were previously only available in the Atlas cloud service. During the MongoDB.local NYC conference, MongoDB announced that search and vector search will be available for local installations. The previews are intended for development and testing. Until now, developers and organizations that wanted to use these features had to rely on the fully managed MongoDB Atlas cloud service.

Company CEO Shanea Leven said, unlike other so-called vibecoding platforms that provide a wrapper around a foundational AI model, the Empromptu platform is designed from the ground up to enable application developers to build enterprise applications that are designed to scale using a set of proprietary AI response optimization frameworks and backend services. The Empromptu platform also provides retrieval-augmented generation (RAG) and large language model operations (LLMOps) tooling to provide DevOps teams with a complete

Basic RAG performed well for general topics but struggled with questions involving time, like identifying workshops next month, due to lack of metadata filtering.

While my Gen AI chatbot significantly improves document searching efficiency, I wonder if it can truly compete with the pricing and performance of established solutions like Amazon Q.

Chunking the content involves breaking down materials into smaller, manageable pieces, allowing language models to process and retrieve relevant information efficiently for generating responses.