{ "_id": "6a12a29eacfb0bcc41d121b2", "Package": "ragnar", "Title": "Retrieval-Augmented Generation (RAG) Workflows", "Version": "0.3.0.9000", "Authors@R": "c(\nperson(\"Tomasz\", \"Kalinowski\", , \"tomasz@posit.co\", role = c(\"aut\", \"cre\")),\nperson(\"Daniel\", \"Falbel\", , \"daniel@posit.co\", role = \"aut\"),\nperson(\"Posit Software, PBC\", role = c(\"cph\", \"fnd\"),\ncomment = c(ROR = \"03wc8by49\"))\n)", "Description": "Provides tools for implementing Retrieval-Augmented\nGeneration (RAG) workflows with Large Language Models (LLM).\nIncludes functions for document processing, text chunking,\nembedding generation, storage management, and content\nretrieval. Supports various document types and embedding\nproviders ('Ollama', 'OpenAI'), with 'DuckDB' as the default\nstorage backend. Integrates with the 'ellmer' package to equip\nchat objects with retrieval capabilities. 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