KruxAI/ragbuilder
A toolkit that automatically optimizes Retrieval-Augmented Generation configurations using Bayesian hyperparameter tuning and pre-defined RAG templates.
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RagBuilder is a Python toolkit for creating production-ready RAG pipelines. It performs automated hyperparameter optimization on chunking strategies, chunk sizes, and other RAG parameters using Bayesian optimization, evaluating configurations against test datasets to identify the best setup. The toolkit includes state-of-the-art RAG templates such as graph retrievers and contextual chunkers, and supports direct access to vectorstore, retriever, and generator components with API deployment capabilities.
Frequently asked
- What is KruxAI/ragbuilder?
- A toolkit that automatically optimizes Retrieval-Augmented Generation configurations using Bayesian hyperparameter tuning and pre-defined RAG templates.
- Is ragbuilder open source?
- Yes — KruxAI/ragbuilder is open source, released under the Apache-2.0 license.
- What language is ragbuilder written in?
- KruxAI/ragbuilder is primarily written in Python.
- How popular is ragbuilder?
- KruxAI/ragbuilder has 1.5k stars on GitHub.
- Where can I find ragbuilder?
- KruxAI/ragbuilder is on GitHub at https://github.com/KruxAI/ragbuilder.