agentic-rag-for-dummies and Building-Natural-Language-and-LLM-Pipelines
These are complementary educational resources that teach overlapping agentic RAG concepts using the same core frameworks (LangGraph, Haystack), so a learner might use the simpler introductory project (A) first, then progress to the more comprehensive Packt book (B) for production-grade implementation patterns.
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.
About Building-Natural-Language-and-LLM-Pipelines
PacktPublishing/Building-Natural-Language-and-LLM-Pipelines
Building RAG and Agentic Applications with Haystack 2.0, RAGAS and LangGraph 1.0 published by Packt
This repository provides code examples for building reliable AI applications that use large language models (LLMs). It guides you through creating robust systems that can retrieve specific information from your own documents and automate complex tasks using AI agents. This is ideal for AI/ML engineers and data scientists looking to implement advanced natural language processing solutions.
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