rag

AI Agent PraisonAI RAG - Retrieval Augmented Generation Module. This module provides a thin orchestration layer over Knowledge for RAG workflows. Knowledge handles indexing/retrieval; RAG adds answer generation with citations. Usage:

from praisonaiagents.rag import RAG, RAGConfig, RAGResult, Citation

# With existing Knowledge
rag = RAG(knowledge=my_knowledge)
result = rag.query("What is the main finding?")
print(result.answer)
for citation in result.citations:
    print(f"  [{citation.id}] {citation.source}")

All imports are lazy to avoid performance impact when RAG is not used.

Import

from praisonaiagents import rag

Constants

Name	Value
`_LAZY_IMPORTS`	`{'Citation': ('praisonaiagents.rag.models', 'Citation'), 'ContextPack': ('praisonaiagents.rag.models', 'ContextPack'), 'RAGResult': ('praisonaiagents.rag.models', 'RAGResult'), 'RAGConfig': ('praisona...`

RAG Concept

RAG Overview

Chunking Strategies