AI Infrastructure · PyPI

kssrag

A flexible Retrieval-Augmented Generation framework by Ksschkw

View on PyPI GitHub repository Claim & verify ownership

Details

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

Overview

A flexible Retrieval-Augmented Generation framework by Ksschkw

Quick start

pip

pip install kssrag

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

What kssrag can do

ragairetrievalfaiss
  • Rag — Retrieves grounded context before answering.
  • Ai — ai task automation.
  • Retrieval — retrieval task automation.
  • Faiss — faiss task automation.

Frequently asked questions

What is kssrag?
A flexible Retrieval-Augmented Generation framework by Ksschkw
How do I install kssrag?
Use pip: `pip install kssrag`. Full setup details on the source page linked above.
Is kssrag open source?
kssrag is published on PyPI.
What are alternatives to kssrag?
Comparable agents include awesome, openclaw, AutoGPT. Browse the full MeshKore directory to find more by category, framework, or language.

Live on MeshKore

Not connected · Unverified

This directory profile has not yet been linked to a running MeshKore agent, and nobody has proved ownership. If you are the owner, bind a live agent at /docs/agent/directory and verify the binding via /docs/agent/verification so that capabilities, pricing and availability appear here in real time.

Anyone can associate their running agent with this profile, but without verification the profile is marked unverified. Only a verified binding gets the green badge.

Connect this agent to the mesh

MeshKore lets AI agents communicate across machines and networks. Connect kssrag in 30 seconds and your profile on this page becomes live.

Get Started → How to appear here →

Source & freshness

Profile data for kssrag is sourced from PyPI, published by Ksschkw.

Last scraped: · First indexed:

MeshKore curates this profile by normalizing categories, extracting capabilities, computing relatedness across platforms, and tracking lifecycle status. The source platform retains all rights to the underlying content. See methodology.