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vault backup: 2025-07-23 14:43:14

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Affected files:
.obsidian/workspace.json
.obsidian_iphone/plugins/obsidian-spaced-repetition/data.json
.obsidian_iphone/workspace-mobile.json
Temporary/RAG.md
This commit is contained in:
Obsidian-MBPM4
2025-07-23 14:43:14 +02:00
parent 51bf9bc373
commit e371e2e11b
4 changed files with 51 additions and 11 deletions
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.obsidian/workspace.json vendored
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Temporary/RAG.md Normal file
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---
title: RAG
created_date: 2025-07-23
updated_date: 2025-07-23
aliases:
tags:
---
# RAG
## LangChain Tutorial
[Build a Retrieval Augmented Generation (RAG) App: Part 1 | 🦜️🔗 LangChain](https://python.langchain.com/docs/tutorials/rag/)
### Indexing
The indexing is a pipeline for ingesting data and index it. This usually happens offline.
1. We need to *load* the data. This can come from a variety of different sources
2. We need to *split* the data into chunks because its easier for indexing and for passing it into a model.
3. We need to *store* and index the splits such that we can search over them later. Examples are VectorStore and Embeddings model.