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.

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Installation

install.packages("RAGFlowChainR")

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Development version

install.packages("remotes")
# remotes::install_github("knowusuboaky/RAGFlowChainR")
install.packages("RAGFlowChainR", repos = c('https://knowusuboaky.r-universe.dev', 'https://cloud.r-project.org'))

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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

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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.

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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")

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License

MIT (c) Kwadwo Daddy Nyame Owusu Boakye