ragflow and agentic-rag-for-dummies

RAGFlow is a comprehensive production-ready RAG engine, while Agentic RAG for Dummies is an educational framework for learning agentic RAG patterns—they are complements where one serves as a reference implementation and the other as a learning resource, though they could also function as alternatives depending on whether production deployment or learning is the priority.

ragflow
69
Established
agentic-rag-for-dummies
64
Established
Maintenance 22/25
Adoption 10/25
Maturity 16/25
Community 21/25
Maintenance 17/25
Adoption 10/25
Maturity 15/25
Community 22/25
Stars: 74,911
Forks: 8,368
Downloads:
Commits (30d): 201
Language: Python
License: Apache-2.0
Stars: 2,743
Forks: 383
Downloads:
Commits (30d): 11
Language: Jupyter Notebook
License: MIT
No Package No Dependents
No Package No Dependents

About ragflow

infiniflow/ragflow

RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs

This tool helps create advanced AI assistants that can accurately answer questions using your specific business documents and data. You input various documents like PDFs, Word files, web pages, and even structured data, and it outputs a system that provides precise, traceable answers. It's designed for business leaders, knowledge managers, or AI product developers who need to build reliable question-answering systems for internal teams or customers.

knowledge-management enterprise-search customer-support-automation business-intelligence document-intelligence

About agentic-rag-for-dummies

GiovanniPasq/agentic-rag-for-dummies

A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.

This project helps developers build advanced AI assistants that can intelligently answer questions using custom data. It takes your documents (like PDFs or Markdown files) and processes them into a searchable format, then uses an AI to interpret user questions, find relevant information, and generate clear, coherent answers. It's designed for AI developers or data scientists who want to create sophisticated conversational agents.

AI-development conversational-AI information-retrieval large-language-models agent-systems

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