---
title: "RAG quickstart with Ray, LangChain, and HuggingFace"
url: https://daily.dev/posts/rag-quickstart-with-ray-langchain-and-huggingface-a7i5wn7rw
source_url: https://cloud.google.com/blog/products/ai-machine-learning/rag-quickstart-with-ray-langchain-and-huggingface/
type: article
source: "Google Cloud"
published: 2024-05-02T16:07:28.903Z
updated: 2024-05-09T08:39:06.345Z
tags: ["langchain", "rag", "gke"]
reading_time: 2
upvotes: 3
comments: 0
language: en
---

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# RAG quickstart with Ray, LangChain, and HuggingFace

**[Google Cloud](https://daily.dev/sources/gcp)** · 2 min read · 3 upvotes · 0 comments

## Summary

Learn how to deploy a complete RAG application on Google Kubernetes Engine (GKE) and Cloud SQL for PostgreSQL and pgvector using Ray, LangChain, and Hugging Face. RAG improves the outputs of large language models by retrieving information from an external knowledge base. RAG on GKE and Cloud SQL offers benefits such as fast data loading, deployment, security, cost efficiency, reduced management overhead, and scalability.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://cloud.google.com/blog/products/ai-machine-learning/rag-quickstart-with-ray-langchain-and-huggingface/>

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---

Tags: [#langchain](https://daily.dev/tags/langchain), [#rag](https://daily.dev/tags/rag), [#gke](https://daily.dev/tags/gke)

[View this post on daily.dev](https://daily.dev/posts/rag-quickstart-with-ray-langchain-and-huggingface-a7i5wn7rw)