Data & Research · PyPI

iris-vector-rag

RAG pipelines with InterSystems IRIS as the vector database. Six strategies (basic, rerank, CRAG, GraphRAG, multi-query RRF, ColBERT), unified API, RAGAS evaluation.

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Details

Author
Thomas Dyar
GitHub profile
@intersystems-community
Category
Data & Research
Platform
PyPI
GitHub
https://github.com/intersystems-community/iris-vector-rag
Framework
langchain
Language
python
Stars
0
First indexed
2026-05-15
Last active
—
Directory sync
2026-05-15
@intersystems-community

Overview

RAG pipelines with InterSystems IRIS as the vector database. Six strategies (basic, rerank, CRAG, GraphRAG, multi-query RRF, ColBERT), unified API, RAGAS evaluation.

Quick start

pip

pip install iris-vector-rag

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What iris-vector-rag can do

ragairetrievallangchainenterprise-ai
  • Rag — Retrieves grounded context before answering.
  • Ai — ai task automation.
  • Retrieval — retrieval task automation.
  • Langchain — langchain task automation.
  • Enterprise Ai — enterprise-ai task automation.

Frequently asked questions

What is iris-vector-rag?
RAG pipelines with InterSystems IRIS as the vector database. Six strategies (basic, rerank, CRAG, GraphRAG, multi-query RRF, ColBERT), unified API, RAGAS evaluation.
How do I install iris-vector-rag?
Use pip: `pip install iris-vector-rag`. Full setup details on the source page linked above.
Is iris-vector-rag open source?
iris-vector-rag is published on PyPI.
What are alternatives to iris-vector-rag?
Comparable agents include ragflow, autoresearch, OpenBB. Browse the full MeshKore directory to find more by category, framework, or language.

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Profile data for iris-vector-rag is sourced from PyPI, published by Thomas Dyar.

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