Retrieval-Augmented Generation (RAG) Workflows

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Documentation for package ‘ragnar’ version 0.3.0

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS
• Package README

Help Pages

chunks_deoverlap	Merge overlapping chunks in retrieved results
embed_azure_openai	Uses Azure AI Foundry to create embeddings
embed_bedrock	Embed text using a Bedrock model
embed_databricks	Embed text using a Databricks model
embed_google_gemini	Embed using Google Vertex API platform
embed_google_vertex	Embed using Google Vertex API platform
embed_lm_studio	Embed Text
embed_ollama	Embed Text
embed_openai	Embed Text
embed_snowflake	Generate embeddings using Snowflake
MarkdownDocument	Markdown documents
MarkdownDocumentChunks	Markdown documents chunks
markdown_chunk	Chunk a Markdown document
mcp_serve_store	Serve a Ragnar store over MCP
ragnar_chunks_view	View chunks with the store inspector
ragnar_find_links	Find links on a page
ragnar_register_tool_retrieve	Register a 'retrieve' tool with ellmer
ragnar_retrieve	Retrieve chunks from a 'RagnarStore'
ragnar_retrieve_bm25	Retrieves chunks using the BM25 score
ragnar_retrieve_vss	Vector Similarity Search Retrieval
ragnar_store_atlas	Visualize a store using Embedding Atlas
ragnar_store_build_index	Build a Ragnar Store index
ragnar_store_connect	Create and connect to a vector store
ragnar_store_create	Create and connect to a vector store
ragnar_store_ingest	Concurrently ingest documents into a Ragnar store
ragnar_store_insert	Inserts or updates chunks in a 'RagnarStore'
ragnar_store_inspect	Launch the Ragnar Store Inspector
ragnar_store_update	Inserts or updates chunks in a 'RagnarStore'
read_as_markdown	Convert files to Markdown