liebherr-aerospace/rago
RAGO (Retrieval Augmented Generation Optimizer) is a toolkit that automatically discovers the best configuration for your RAG system through smart experimentation
This tool helps AI engineers and machine learning practitioners fine-tune their Retrieval Augmented Generation (RAG) systems. It takes your documents and a set of RAG configuration options, automatically tests various combinations, and identifies the best setup for optimal answer quality. The output is a highly effective RAG system tailored to your specific needs.
Use this if you are building or maintaining a RAG system and need to systematically find the best combination of retrieval, embedding, and LLM parameters to achieve top performance on your specific data.
Not ideal if you are not working with RAG systems or prefer manual, ad-hoc experimentation for system configuration.
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9
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2
Language
Python
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Category
Last pushed
Feb 13, 2026
Commits (30d)
0
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