GiovanniPasq/agentic-rag-for-dummies resource

Health v2 · maintenance only

Adoption not part of the score

3969 stars · 514 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A tutorial-style repository and modular reference implementation for building Agentic RAG systems with LangGraph. It combines learning materials (notebooks, Colab) with an extensible architecture featuring hierarchical indexing, conversation memory, query clarification, and multi-agent map-reduce.

Use cases

• learn how to build an agentic RAG system
• build a RAG chatbot with conversation memory
• implement parent-document retrieval with Qdrant
• run RAG locally with Ollama
• add human-in-the-loop query clarification to a RAG pipeline
• decompose complex queries into parallel sub-queries with LangGraph
• understand hybrid BM25 and vector retrieval

When to choose

• you want a hands-on, well-documented introduction to agentic RAG with LangGraph
• you need a modular, extensible RAG architecture to adapt for your own project
• you prefer running LLMs locally with Ollama or swapping providers (OpenAI, Anthropic, Google)
• you want runnable notebooks plus a production-style pipeline in one repo

When to avoid

• you need a battle-tested production RAG service rather than a learning-oriented reference
• you want a framework-agnostic solution without LangChain/LangGraph dependencies
• you need a no-code or hosted RAG product
• your stack is not Python 3.11+

Facets

learning-resource · maturity active

rag agent-framework llm-inference search-engine chatbot large-language-models machine-learning tutorials python cross-platform self-hosted langgraph langchain qdrant ollama gradio bm25 agentic-rag jupyter-notebook parent-document-retrieval conversation-memory human-in-the-loop map-reduce self-correction retrieval-augmented-generation ai-agents docker

Member repositories

For agents

markdown · JSON · MCP: product_card(name="GiovanniPasq/agentic-rag-for-dummies")