adilsaid64/open-rag-stack

A playground for building and serving Retrieval-Augmented Generation (RAG) systems using best practices in MLOps and LLMOps, with open-source tools.

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Experimental

This project helps machine learning engineers or MLOps practitioners build and manage Retrieval-Augmented Generation (RAG) systems for their applications. It takes your documents and user queries, processes them, and outputs relevant responses, while also providing tools to monitor and evaluate the system's performance. It's designed for professionals who need to ensure their AI systems are reliable and maintainable in production.

No commits in the last 6 months.

Use this if you are an MLOps engineer or AI developer looking for a comprehensive, production-oriented environment to build, deploy, and manage RAG systems with robust monitoring and evaluation capabilities.

Not ideal if you are looking for a simple, plug-and-play RAG solution without needing to understand or manage the underlying infrastructure and MLOps practices.

MLOps LLMOps AI-system-deployment RAG-evaluation data-versioning
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 4 / 25
Maturity 7 / 25
Community 13 / 25

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Stars

7

Forks

2

Language

Python

License

Last pushed

Jun 16, 2025

Commits (30d)

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