InterSystems IRIS embedded vector search capabilities lets us search unstructured and semi-structured data. Data is converted to vectors (also called ‘embeddings’) and then stored and indexed in InterSystems IRIS for semantic search, retrieval-augmented generation (RAG), text analysis, recommendation engines, and other use cases.
This is a simple demo of IRIS being used as a vector database and similarity search on IRIS.
Prerequisites:
- Python
- InterSystems IRIS for Health - as it will be used as the vector database
Repository: https://github.com/piyushisc/vectorsearchusingiris
Steps to follow:
- InterSystems IRIS embedded vector search capabilities lets us search unstructured and semi-structured data.
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