ragway

The way to build RAG. ragway is a modular Python library for building Retrieval-Augmented Generation pipelines. Swap any component via a single YAML config file - no Python code changes needed.

What makes ragway different

• One config file - LLM, vectorstore, embeddings, reranker all in rag.yaml
• Fully modular - swap any component with one line
• 6 LLMs - Anthropic, OpenAI, Mistral, Groq, Llama, Local
• 6 vectorstores - FAISS, Chroma, Pinecone, Weaviate, Qdrant, PGVector
• 5 pipelines - naive, hybrid, self-RAG, long context, agentic
• Free tier ready - works with Groq + BGE + FAISS, zero cost

Quick example

from ragway import RAG
import asyncio
 
rag = RAG.from_config("rag.yaml")
asyncio.run(rag.ingest("./docs/"))
answer = asyncio.run(rag.query("What is in my documents?"))
print(answer)