AutoRAG and rag-pipeline

AutoRAG

Established

rag-pipeline

Experimental

Maintenance 13/25

Adoption 10/25

Maturity 25/25

Community 19/25

Maintenance 10/25

Adoption 1/25

Maturity 11/25

Community 0/25

Stars: 4,609

Forks: 381

Downloads: —

Commits (30d): 4

Language: Python

License: Apache-2.0

Stars: 1

Forks: —

Downloads: —

Commits (30d): 0

Language: Python

License: MIT

No risk flags

No Package No Dependents

About AutoRAG

Marker-Inc-Korea/AutoRAG

AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation

This tool helps AI developers and researchers find the best Retrieval-Augmented Generation (RAG) pipeline for their specific data and use case. You provide your documents and an evaluation dataset (questions and their correct answers), and AutoRAG automatically tests various RAG components and configurations. The output is an optimized RAG pipeline that performs best for your application.

AI development RAG systems LLM application model optimization natural language processing

About rag-pipeline

axiom-llc/rag-pipeline

RAG pipeline: ingest, embed (Gemini gemini-embedding-001), retrieve (ChromaDB cosine), generate (Gemini 2.5 Flash). Context-grounded answers only. CLI + Flask REST API. Python 3.11+.

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