AI Infrastructure · PyPI

ragpipe-lite

ragpipe-lite: unified RAG ingestion pipeline (loaders, chunking, embeddings, vector store export).

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Details

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

Overview

ragpipe-lite: unified RAG ingestion pipeline (loaders, chunking, embeddings, vector store export).

Quick start

pip

pip install ragpipe-lite

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

What ragpipe-lite can do

llmragembeddingaifaiss
  • Llm — llm task automation.
  • Rag — Retrieves grounded context before answering.
  • Embedding — Computes vector embeddings for semantic search.
  • Ai — ai task automation.
  • Faiss — faiss task automation.

Frequently asked questions

What is ragpipe-lite?
ragpipe-lite: unified RAG ingestion pipeline (loaders, chunking, embeddings, vector store export).
How do I install ragpipe-lite?
Use pip: `pip install ragpipe-lite`. Full setup details on the source page linked above.
Is ragpipe-lite open source?
ragpipe-lite is published on PyPI.
What are alternatives to ragpipe-lite?
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 ragpipe-lite is sourced from PyPI, published by Kubenew.

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