didiergarcia/tiny-rag
TinyRAG is a minimalist Python library that enables developers to rapidly build RAG-powered applications. It supports a flexible range of LLM endpoints and provides a clean API for combining retrieval with generation.
This project helps developers quickly build systems that can answer specific questions using your own documents, even on topics a language model doesn't know about. You input a PDF document and a question, and it gives you a precise answer, drawing information directly from your document. This is for developers prototyping or creating applications that need to provide up-to-date, document-specific answers.
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Use this if you need to quickly prototype a system that can answer questions about content in your own PDF documents, especially when working with limited computing resources or needing to update information beyond a language model's training data.
Not ideal if you need a production-ready system with advanced error handling, security, and scalability for a large user base or very complex document sets.
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Jun 19, 2025
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