Retrieval-augmented generation is a standard way to ground large language models in enterprise information, but new research ...

You know the ritual. The pipeline hallucinated in front of a customer, so you swapped the embedding model. Then you upgraded ...

In this tutorial, we build a RAG-Anything workflow and use it to explore how multimodal retrieval works across text, tables, equations, and images. We start by preparing the Colab environment, ...

The difficulty in choosing a book on Dify is that books that teach you how to use Dify and books that teach you how to design AI apps for business use often look like they belong on the same shelf.

Step-by-step tutorial perfect for understanding core concepts. Start here if you're new to Agentic RAG or want to experiment quickly. 💡 Optional: If you want to visually inspect or edit your chunks ...

A personal knowledge base continuously maintained with Obsidian + LLM Wiki. Inspired by Karpathy's LLM Wiki pattern. Core idea: Knowledge is not derived from scratch on every query — it is compiled ...

If you've been building AI applications but relying entirely on managed API endpoints, this tutorial is your entry point into running models on raw GPU hardware, your own endpoint, your own model, ...

Do you want your data to stay private and never leave your device? Cloud LLM services often come with ongoing subscription fees based on API calls. Even users in remote areas or those with unreliable ...