RAGLight is a lightweight, modular Python library designed to implement Retrieval Augmented Generation (RAG). Its main design goals include:
- Enhancing Contextual Comprehension: Enhancing the context-awareness of Large Language Models (LLMs) by combining document retrieval and natural language generation.
- Streamline the development process: Provides a modular RAG pipeline to support rapid construction of context-aware AI applications.
- Support for multiple models and data sources: Compatible with Ollama and LMStudio's multi-language model and allows importing data from local folders or GitHub repositories.
- Focus on privacy and cost: Supports localized deployments for privacy- and cost-sensitive projects.
This answer comes from the articleRAGLight: Lightweight Retrieval Augmentation Generation Python LibraryThe
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