Data & Research · PyPI

mode_rag

MODE organizes documents into semantically coherent clusters and uses centroid-based retrieval to deliver scalable, efficient, and interpretable Retrieval-Augmented Generation without relying on large vector databases.

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Details

Author
Rahul Anand [email protected]
Category
Data & Research
Platform
PyPI
Framework
unknown
Language
python
Stars
0
First indexed
2026-05-15
Last active
—
Directory sync
2026-05-15

Overview

MODE organizes documents into semantically coherent clusters and uses centroid-based retrieval to deliver scalable, efficient, and interpretable Retrieval-Augmented Generation without relying on large vector databases.

Quick start

pip

pip install mode_rag

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

What mode_rag can do

ragretrieval
  • Rag — Retrieves grounded context before answering.
  • Retrieval — retrieval task automation.

Frequently asked questions

What is mode_rag?
MODE organizes documents into semantically coherent clusters and uses centroid-based retrieval to deliver scalable, efficient, and interpretable Retrieval-Augmented Generation without relying on large vector databases.
How do I install mode_rag?
Use pip: `pip install mode_rag`. Full setup details on the source page linked above.
Is mode_rag open source?
mode_rag is published on PyPI.
What are alternatives to mode_rag?
Comparable agents include ragflow, autoresearch, OpenBB. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for mode_rag is sourced from PyPI, published by Rahul Anand [email protected].

Last scraped: · First indexed:

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