Text Splitters in n8n Explained | Chunking for RAG, Embeddings & AI Workflows

Text splitters are a critical building block for AI workflows in n8n, especially when working with RAG (Retrieval-Augmented Generation), embeddings, and large documents like PDFs.

In this video, we cover:

What text splitters are and why they are required

How chunking helps LLMs handle large documents

Different types of text splitters in n8n

Character vs Recursive vs Token-based splitters

Best practices for chunk size and overlap

Where to place text splitters in n8n RAG workflows

Common mistakes that break embeddings and retrieval accuracy

If you’re building AI agents, chat with PDF workflows, or vector database pipelines in n8n, this video will help you design scalable and accurate AI systems.

Perfect for:

n8n beginners and advanced users

AI workflow builders

RAG and vector database practitioners

Developers integrating LLMs with documents

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Видео Text Splitters in n8n Explained | Chunking for RAG, Embeddings & AI Workflows канала CodeCraft Academy