create_rag_chain: create_rag_chain.R Overview

In RAGFlowChainR: Retrieval-Augmented Generation (RAG) Workflows in R with Local and Web Search

create_rag_chain.R Overview

Description

A refined implementation of a LangChain-style Retrieval-Augmented Generation (RAG) pipeline. Includes vector search using DuckDB, optional web search using the Tavily API, and a built-in chat message history.

This function powers 'create_rag_chain()', the exported entry point for constructing a full RAG pipeline.

## Features: - Context-aware reformulation of user queries - Semantic chunk retrieval using DuckDB - Optional real-time web search (Tavily) - Compatible with any LLM function (OpenAI, Claude, etc.)

## Required Packages install.packages(c("DBI", "duckdb", "httr", "jsonlite", "stringi", "dplyr"))

Arguments

llm	A function that takes a prompt and returns a response (e.g. a call to OpenAI or Claude).
vector_database_directory	Path to the DuckDB database file.
method	Retrieval method backend. Currently only '"DuckDB"' is supported.
embedding_function	A function to embed text. Defaults to embed_openai().
system_prompt	Optional prompt with placeholders {chat_history}, {input}, {context}.
chat_history_prompt	Prompt used to rephrase follow-up questions using prior conversation history.
tavily_search	Tavily API key (set to NULL to disable web search).
embedding_dim	Integer; embedding vector dimension. Defaults to 1536.
use_web_search	Logical; whether to include web results from Tavily. Defaults to TRUE.

Details

Create a Retrieval-Augmented Generation (RAG) Chain

Creates a LangChain-style RAG chain using DuckDB for vector store operations, optional Tavily API for web search, and in-memory message history for conversational context.

Value

A list of utility functions:

• invoke(text) — Performs full context retrieval and LLM response

• custom_invoke(text) — Retrieves context only (no LLM call)

• get_session_history() — Returns complete conversation history

• clear_history() — Clears in-memory chat history

• disconnect() — Closes the underlying DuckDB connection

Note

Only create_rag_chain() is exported. Helper functions are internal.

Examples

## Not run: 
rag_chain <- create_rag_chain(
  llm = call_llm,
  vector_database_directory = "tests/testthat/test-data/my_vectors.duckdb",
  method = "DuckDB",
  embedding_function = embed_openai(),
  use_web_search = FALSE
)

response <- rag_chain$invoke("Tell me about R")

## End(Not run)

RAGFlowChainR documentation built on June 8, 2025, 11:06 a.m.