---
title: "How to Implement RAG With Amazon Bedrock and LangChain"
url: https://daily.dev/posts/how-to-implement-rag-with-amazon-bedrock-and-langchain-pjer5vxqx
source_url: https://www.timescale.com/blog/how-to-implement-rag-with-amazon-bedrock-and-langchain/
type: article
source: "TigerData (Creators of TimescaleDB)"
published: 2024-05-10T11:04:42.853Z
updated: 2024-05-10T11:04:42.093Z
tags: ["ai", "nlp", "langchain", "rag", "amazon-bedrock"]
reading_time: 11
upvotes: 9
comments: 0
language: en
---

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# How to Implement RAG With Amazon Bedrock and LangChain

**[TigerData \(Creators of TimescaleDB\)](https://daily.dev/sources/tigerdata)** · 11 min read · 9 upvotes · 0 comments

## Summary

Learn how to implement RAG (retrieval-augmented generation) with Amazon Bedrock and LangChain. Set up Amazon Bedrock, interact with language models, understand pricing, load and split datasets with LangChain, store embeddings, and use a retriever. Discover how to construct a chatbot using Chains and prompts.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.timescale.com/blog/how-to-implement-rag-with-amazon-bedrock-and-langchain/>

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---

Tags: [#ai](https://daily.dev/tags/ai), [#nlp](https://daily.dev/tags/nlp), [#langchain](https://daily.dev/tags/langchain), [#rag](https://daily.dev/tags/rag), [#amazon-bedrock](https://daily.dev/tags/amazon-bedrock)

[View this post on daily.dev](https://daily.dev/posts/how-to-implement-rag-with-amazon-bedrock-and-langchain-pjer5vxqx)