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The RAG Cookbook 2026

Forty self-contained tutorials on production retrieval-augmented generation techniques, from chunking strategies to agentic and graph-based retrieval, runnable on any OpenAI-compatible provider.

Visit website (opens in a new tab)fareedkhan-dev.github.io
The RAG Cookbook 2026

The RAG Cookbook 2026 is a set of forty hands-on recipes covering techniques in retrieval-augmented generation, including late chunking, contextual retrieval, multi-vector late interaction, listwise reranking, agentic workflows over MCP servers, graph indexes and page-as-image vision retrieval. Each recipe includes the underlying theory, an implementation, a discussion of its output and an evaluation harness.

The recipes run end to end on Nebius AI Studio or any OpenAI-compatible provider, and the cookbook can also be read as a browsable documentation site built with MkDocs.

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