AI Infrastructure · PyPI

mini-rag

A lightweight RAG (Retrieval-Augmented Generation) library with document loading, chunking, embedding, vector storage, and re-ranking

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Details

Author
Vivek N
GitHub profile
@vivek12345
Category
AI Infrastructure
Platform
PyPI
GitHub
https://github.com/vivek12345/mini-rag
Framework
unknown
Language
python
Stars
0
First indexed
2026-05-15
Last active
—
Directory sync
2026-05-15
@vivek12345

Overview

A lightweight RAG (Retrieval-Augmented Generation) library with document loading, chunking, embedding, vector storage, and re-ranking

Quick start

pip

pip install mini-rag

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

What mini-rag can do

llmragembeddingairetrieval
  • Llm — llm task automation.
  • Rag — Retrieves grounded context before answering.
  • Embedding — Computes vector embeddings for semantic search.
  • Ai — ai task automation.
  • Retrieval — retrieval task automation.

Frequently asked questions

What is mini-rag?
A lightweight RAG (Retrieval-Augmented Generation) library with document loading, chunking, embedding, vector storage, and re-ranking
How do I install mini-rag?
Use pip: `pip install mini-rag`. Full setup details on the source page linked above.
Is mini-rag open source?
mini-rag is published on PyPI.
What are alternatives to mini-rag?
Comparable agents include awesome, openclaw, AutoGPT. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for mini-rag is sourced from PyPI, published by Vivek N.

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