{"repo":"KruxAI/ragbuilder","free":true,"listed":false,"github":"https://github.com/KruxAI/ragbuilder","clone":"git clone https://github.com/KruxAI/ragbuilder.git","description":"A toolkit to create optimal Production-readyRetrieval Augmented Generation(RAG) setup for your data","language":"Python","stars":1541,"topics":["developer-tools","genai","rag"],"license":"Apache-2.0","category":"ai-agents","readme_excerpt":"RagBuilder is a toolkit that helps you create optimal Production-ready Retrieval-Augmented-Generation (RAG) setup for your data automatically. By performing hyperparameter tuning on various RAG parameters (Eg: chunking strategy: semantic, character etc., chunk size: 1000, 2000 etc.), RagBuilder evaluates these configurations against a test dataset to identify the best-performing setup for your data. Additionally, RagBuilder includes several state-of-the-art, pre-defined RAG templates that have shown strong performance across diverse datasets. So just bring your data, and RagBuilder will generate a production-grade RAG setup in just minutes. Features - Hyperparameter Tuning : Efficiently optimize your RAG configurations using Bayesian optimization - Pre-defined RAG Templates : Use state-of-the-art templates that have demonstrated strong performance Eg: Graph retriever, Contextual chunker etc.) - Evaluation Dataset Options : Generate synthetic test dataset or provide your own - Component Access : Direct access to vectorstore, retriever, and generator components - API Deployment : Easily deploy as an API service - Project Persistence : Save and load optimized RAG pipelines Installation See other installation options here (link) Quick Start Setting Default Models You can specify default LLM and embedding models that will be used throughout the pipeline: Configuration Guide Basic Configuration For most use cases, the default configuration provides good results: Advanced Configurat","default_branch":null,"files":null,"tree":[],"storefront":"/r/KruxAI","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/KruxAI/ragbuilder/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}