LEANN and llama-index-RAG

LEANN
70
Verified
llama-index-RAG
27
Experimental
Maintenance 17/25
Adoption 10/25
Maturity 24/25
Community 19/25
Maintenance 0/25
Adoption 6/25
Maturity 16/25
Community 5/25
Stars: 10,303
Forks: 894
Downloads:
Commits (30d): 9
Language: Python
License: MIT
Stars: 15
Forks: 1
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
No risk flags
Stale 6m No Package No Dependents

About LEANN

yichuan-w/LEANN

[MLsys2026]: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.

This tool helps you turn your computer into a private AI assistant for searching through all your digital information. It takes your personal documents, emails, browser history, chat logs, and even live social media feeds, allowing you to ask questions and get answers from them. Anyone who needs to quickly find information across a vast and varied personal data collection without relying on cloud services would use this.

personal-knowledge-management document-retrieval digital-archiving information-search data-privacy

About llama-index-RAG

romilandc/llama-index-RAG

A RAG implementation on Llama Index using Qdrant vector stores as storage. Take some pdfs, store them in the db, use LLM to inference.

This helps researchers, analysts, or anyone working with large collections of PDF documents quickly find specific information and generate summaries or answers. You feed it a set of PDF files, and it allows you to ask questions in plain language, extracting relevant details or creating new content based on your documents. It's for professionals who need to synthesize information from many PDFs efficiently without manually sifting through each one.

document-analysis information-retrieval research-automation knowledge-management content-synthesis

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