How do I build a retrieval-augmented generation (RAG) pipeline on Databricks — what are the best pra

Suheb — Thu, 27 Nov 2025 07:10:28 GMT

How can I build an AI system (using Databricks) where the AI model doesn’t just rely on its built-in knowledge, but also retrieves real information from a database or documents before answering?

Re: How do I build a retrieval-augmented generation (RAG) pipeline on Databricks — what are the best

KaushalVachhani — Thu, 27 Nov 2025 07:18:45 GMT

@Suheb , We have a bunch of resources around Databricks RAG. Did you have a chance to look at the available documentation? Adding a few of them below.

Databricks docs for RAG: https://docs.databricks.com/aws/en/generative-ai/retrieval-augmented-generation

Databricks docs on Agents with tool calling: https://docs.databricks.com/aws/en/generative-ai/agent-framework/author-agent?language=LangGraph

Dbdemos: https://notebooks.databricks.com/demos/ai-agent/index.html

We also have MCPs and Agent bricks, which might be helpful. Feel free to search them as needed.

topic How do I build a retrieval-augmented generation (RAG) pipeline on Databricks — what are the best pra in Generative AI

How do I build a retrieval-augmented generation (RAG) pipeline on Databricks — what are the best pra

Re: How do I build a retrieval-augmented generation (RAG) pipeline on Databricks — what are the best