RAG Agents: Build Apps & GPTs with APIs/MCP, LangChain & n8n

AI Agents & LLMs with RAG: n8n, LangChain, LangGraph, Flowise, MCP & more – with ChatGPT, Gemini, Claude, DeepSeek & Co.

One of the most important concepts in the AI world is "RAG" – Retrieval-Augmented Generation!

You need to give LLMs knowledge!

But how do you build powerful RAG chatbots and intelligent AI agents to optimize your business processes and personal projects?

In this course, you’ll learn exactly that—comprehensively and clearly explained—using ChatGPT, Claude, Google Gemini, open‑source LLMs, Flowise, n8n, and more!

Fundamentals: LLMs, RAG & Vector Databases
Build a solid foundation for your AI projects:

• Deepen your knowledge of LLMs: ChatGPT, Claude, Gemini, Deepseek, Llama, Mistral, and many more.

• Understand how Function Calling and API communication work in LLMs.

• Learn why vector databases and embedding models are the heart of RAG.

• Master the ChatGPT interface, GPT models, settings, and the OpenAI Playground.

• Explore key concepts like Test‑Time Compute (e.g. OpenAI o1, o3; Deepseek R1).

• Discover how Google’s NotebookLM works and leverage it effectively for RAG projects.

Simple RAG Implementations with ChatGPT & Custom GPTs
Get your first AI applications up and running quickly and easily:

• Create your very first RAG bot from PDFs using Custom GPTs.

• Turn HTML web pages and YouTube videos into interactive RAG chatbots.

• Train ChatGPT on your personal writing style via RAG.

• Use CSV data to build smart chatbots and explore the full potential of Custom GPTs.

RAG with Open‑Source LLMs: AnythingLLM & Ollama
Dive into the world of local AI:

• Install and use Ollama: learn about models, commands, and hardware requirements.

• Integrate AnythingLLM effectively with Ollama—optimize chunking and embeddings.

• Build local RAG chatbots and precisely control language and behavior with system prompts and temperature settings.

• Leverage agent capabilities like web search, scraping, and more.

Flowise: RAG with LangChain & LangGraph Made Easy
Harness the power of the OpenAI API for professional applications:

• Master the OpenAI API, pricing models, GDPR compliance, and project setup.

• Build efficient RAG applications via the OpenAI Playground and response APIs.

• Install Flowise, manage updates, and become proficient with its interface—including the Marketplace and OpenAI Assistant.

• Create comprehensive RAG chatflows with web scraping, embeddings, HTML splitters, and vector databases.

• Develop your own chatbot UI and handle Flowise’s technical details.

• Implement local AI security with Ollama & LangChain and use Flowise’s tool‑agent nodes (e.g. email, calendar, Airtable).

• Combine Pinecone vector databases with Supabase and Postgres.

• Master prompt engineering and sequential agents with human‑in‑the‑loop workflows.

n8n: Building AI Automations & RAG Agents
Use n8n as a powerful automation platform for your AI projects:

• Learn local installation, updates, and n8n basics.

• Automate Pinecone database updates via Google Drive.

• Develop RAG chatbots with AI‑agent nodes, vector databases, and supplementary tools.

• Create automated chatbots from websites using HTML requests and scraping.

Hosting, Selling & Monetizing Your RAG Agents
Take your AI projects to market professionally:

• Host Flowise and n8n apps on platforms like Render and embed them in websites (HTML, WordPress).

• Design branded, professional chatbots and offer them as services or standalone products.

• Develop effective marketing and sales strategies for your AI agents.

Advanced Workflows & Specialized RAG Techniques
Adopt professional, cutting‑edge technologies:

• Learn advanced techniques like webhooks, MCPs with Claude, GPT Actions, and n8n integration.

• Understand the Model Context Protocol (MCP) and build both MCP servers and clients in n8n and Claude Desktop.

• Explore innovative RAG strategies such as Cache‑Augmented Generation (CAG), GraphRAG (Microsoft), LightRAG, and Anthropic’s Contextual Retrieval.

• Optimize chunking, embedding, and Top‑K retrieval for your RAG apps.

• Choose the right strategy for your projects and maximize your RAG outcomes.

Security, Privacy & Legal Foundations
Protect your AI projects effectively:

• Recognize security risks (Telegram exploits, jailbreaks, prompt injections, data poisoning).

• Secure your AI against attacks and respect copyrights in generated content.

• Deepen your understanding of GDPR and the upcoming EU AI Act to ensure legal compliance.

Become an expert in AI automations, AI agents & RAG!
By the end of this course, you will be fully equipped to build, optimize, and successfully market RAG chatbots, AI agents, and automations.