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how IRIS Vector Search within langchain-iris facilitates storage, retrieval, and semantic search of data, enabling precise and up-to-date responses to user queries. Through seamless

into vectors we store the vectors in an IRIS database. we call an LLM (Large Language Model) that accesses these vectors as context to generate responses in human language

The introduction of InterSystems' "Vector Search" marks a paradigm shift in data processing. This cutting-edge technology employs an embedding model to transform unstructured data

as generative AI and their foundation is the vectorization of huge amounts of texts. Through this vectorization we will obtain a vector space (excuse the redundancy) in which related

platforms. Central to this architecture is the use of InterSystems IRIS, particularly its vector store and vector search capabilities, which play a pivotal role in the Retrieval-Augmented

ideas marked for implementation by Community members ✓ New ideas related to topics like Vector Search, GenAI and ML More than 50 new ideas have been posted since the last news

$vector datatype. $vector is an internal-only (for now) datatype that leverages adaptive encoding schemes to allow efficient storage of both sparse and dense data. The encoding

small example project, how we can find the most appropriate context for the question we want to send to our LLM model and for this we will make use of the vector search

Discover the capabilities of InterSystems IRIS Vector Search, including integrating dense vector storage and search with InterSystems IRIS SQL for advanced semantic search and other GenAI

Hi Community,Traditional keyword-based search struggles with nuanced, domain-specific queries. Vector search, however, leverages semantic understanding, enabling AI agents

Coach is built around the following key components: 1. **Scoring Agent** 2. **Vector Search in RAG Pipeline** --------- ### Scoring Agent The Scoring Agent evaluates

#InterSystems Demo Games entry ⏯️ FHIR-Powered AI Healthcare Assistant Leverage InterSystems's FHIR SQL Builder to project FHIR data to a dataset for vector

, I chat with @Elijah.Cotterrell as he walks through a demo of his chatbot application. He shows what a RAG application can do, including: Embed text data as vectors. Perform

: set $somefunction(param1,param2, ...) = value The reason to raise that subject is that with IRIS 2024.1 there is after may years a "new kid on this block" $VECTOR() Assigns

With the introduction of vector data types and the Vector Search functionality in IRIS, a whole world of possibilities opens up for the development of applications and an example