axiom-rag and rag-pipeline

The two tools are ecosystem siblings, with `axiom-llc/rag-pipeline` appearing to be a more focused, foundational component for core RAG functionalities (ingest, embed, retrieve, generate) while `axiom-llc/axiom-rag` builds upon this foundation to offer a production-ready pipeline with advanced features like grounded retrieval, source-cited answers, and evaluation metrics.

axiom-rag
37
Emerging
rag-pipeline
23
Experimental
Maintenance 13/25
Adoption 6/25
Maturity 18/25
Community 0/25
Maintenance 13/25
Adoption 1/25
Maturity 9/25
Community 0/25
Stars: 1
Forks: —
Downloads: 130
Commits (30d): 0
Language: Python
License: MIT
Stars: 1
Forks: —
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
No risk flags
No Package No Dependents

About axiom-rag

axiom-llc/axiom-rag

Production RAG pipeline — grounded retrieval, source-cited answers, Precision@k + MRR eval. CLI + Flask REST API. Gemini · ChromaDB · Python 3.11+

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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