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RAGFlowChainR

Overview

RAGFlowChainR is an R package for Retrieval-Augmented Generation (RAG) workflows with local retrieval backends (DuckDB and VectrixDB) plus optional web search.

The README is intentionally short. Full backend workflows are documented in vignettes.

Installation

install.packages("RAGFlowChainR")

Development version

install.packages("remotes")
remotes::install_github("knowusuboaky/RAGFlowChainR")

Backend Guides

• DuckDB backend article: https://knowusuboaky.github.io/RAGFlowChainR/articles/duckdb-backend.html
• VectrixDB backend article: https://knowusuboaky.github.io/RAGFlowChainR/articles/vectrixdb-backend.html
• Function reference: https://knowusuboaky.github.io/RAGFlowChainR/reference/

Quick Start

library(RAGFlowChainR)

rag <- create_rag_chain(
  llm = function(prompt) "mock answer",
  vector_database_directory = "my_vectors.duckdb",
  method = "DuckDB",
  use_web_search = FALSE
)

rag$invoke("What is RAG?")
rag$disconnect()

For complete ingestion, indexing, and backend-specific setup, use the two backend vignettes above.

Environment Setup

Sys.setenv(TAVILY_API_KEY    = "your-tavily-api-key")
Sys.setenv(OPENAI_API_KEY    = "your-openai-api-key")
Sys.setenv(GROQ_API_KEY      = "your-groq-api-key")
Sys.setenv(ANTHROPIC_API_KEY = "your-anthropic-api-key")

License

MIT (c) Kwadwo Daddy Nyame Owusu Boakye

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.