Тёмный

GraphRAG - The Most Advanced Futuristic RAG | Introduction, Setup, Working, Testing 

Neural Hacks with Vasanth
Подписаться 6 тыс.
Просмотров 3 тыс.
50% 1

🎥 Welcome to our channel! Today, we dive into the revolutionary Graph RAG from Microsoft, an advanced retrieval-augmented generation system that enhances AI responses by providing relevant context.
GraphRAG - The Most Advanced Futuristic RAG | Introduction, Setup, Working, Testing
📌 In this video, you will learn:
What is RAG (Retrieval-Augmented Generation)?
Differences between Basic RAG and Graph RAG
How to implement Graph RAG in your local system
Step-by-step guide on setting up Graph RAG
Advantages of using Graph RAG over traditional methods
Working of GraphRAG
🔍 Key Features:
Entity Extraction
Hierarchy Extraction
Graph Embedding
Community Summarization
Topic Detection
🔧 Setup Steps:
Install the Graph RAG package
Configure API keys and settings
Initialize your project
Upload and process data
Run queries to extract high-quality answers
Join this channel to get access to perks:
/ @neuralhackswithvasanth
Important Links:
Github Repo: github.com/Vasanthengineer494...
For further discussions please join the following telegram group
Telegram Group Link: t.me/nhv4949
You can also connect with me in the following socials
Gmail: vasanth51430@gmail.com
LinkedIn: / vasanthengineer4949
Other Playlist Links:
AI Realtime Projects using LLMs - • AI Realtime Projects u...
NLP Advanced Roadmap - • NLP Advanced Roadmap
LLMs Related - • LLMs Related
NLP Research Papers - • NLP Research Papers
Mistral Research to Real World Applications - • Mistral Research To Re...
NLP Projects - • NLP Projects
Langchain Projects - • Langchain Projects
ML Bootcamp - • ML Bootcamp

Наука

Опубликовано:

 

25 июл 2024

Поделиться:

Ссылка:

Скачать:

Готовим ссылку...

Добавить в:

Мой плейлист
Посмотреть позже
Комментарии : 11   
@vaitesh
@vaitesh 9 дней назад
This is very detailed explanation. I already tried setting up the graphrag and followed the instructions, but none gave the proper explanation about the indexing that is created by graphrag. Thanks for sharing this , hope to see more content here
@muhammedaslama9908
@muhammedaslama9908 20 дней назад
Amazing .Expecting more vedios like this from you.
@NeuralHackswithVasanth
@NeuralHackswithVasanth 19 дней назад
Sure 😊
@mikew2883
@mikew2883 22 дня назад
Great video! I did not see this sample code in your repository. Can you confirm it should be there?
@HemangJoshi
@HemangJoshi 5 дней назад
How to use this with ollama? Instead of openAI API?
@henkhbit5748
@henkhbit5748 21 день назад
Has langchain not a text importer for neo4j?. Thanks for the video.
@rockypunk91
@rockypunk91 9 дней назад
I want to understand, how can we use it in a actual application. I reality users will upload their documents anytime they want, If I run indexer for different documents seperately it creates a seperate timestamp based folders in output, now how will the graph rag work when we have multiple artifacts? Our do I have to run indexer on entire documents even if one new document is added? and how do we trigger it programitically
@MayankKumar-ch8pq
@MayankKumar-ch8pq 4 дня назад
The gpt llms already know everything about the Christmas carol, so it's very easy for the llm to answer the questions you can ask about that story, it was most definitely part of the training data itself, wouldn't it be more realistic to add brand new data that the LLM has not seen before? Production environments mostly suffer because LLMs struggle to make sense of retrieved data cause you often can't pack the entire story of your data in the context length of the model.
@NeuralHackswithVasanth
@NeuralHackswithVasanth 20 дней назад
Commands: pip install graphrag - Installation mkdir -p ./ragtest/input - Input folder curl www.gutenberg.org/cache/epub/24022/pg24022.txt > ./ragtest/input/book.txt - Input download python -m graphrag.index --init --root ./ragtest - Initialization of GraphRAG project python -m graphrag.index --root ./ragtest - Indexing Docs python -m graphrag.query --root ./ragtest --method global "What are the top themes in this story?" - Global Search python -m graphrag.query --root ./ragtest --method local "Who is Scrooge, and what are his main relationships?" - Local Search
@user-nc1ky9no3k
@user-nc1ky9no3k 22 дня назад
😢open ai api
@artur50
@artur50 18 дней назад
OpenAI sucks . Go4 ollama
Далее
GraphRAG Free: Use Without Open AI API Key
10:56
Просмотров 1,6 тыс.
GraphRAG: LLM-Derived Knowledge Graphs for RAG
15:40
Просмотров 96 тыс.
ПОДВОДНЫЙ ГЕЙМИНГ #shorts
00:22
Просмотров 847 тыс.
Graph RAG: Improving RAG with Knowledge Graphs
15:58
Просмотров 37 тыс.
Python RAG Tutorial (with Local LLMs): AI For Your PDFs
21:33
I can't believe this is real
11:54
Просмотров 162 тыс.
Reliable Graph RAG with Neo4j and Diffbot
8:02
Просмотров 13 тыс.
Every AI Developer Should Know This
25:17
Просмотров 2,7 тыс.
Multi-modal RAG: Chat with Docs containing Images
17:40
Future Proof Your Tech Career In the Age of AI
10:21
Просмотров 31 тыс.
5 Design Patterns That Are ACTUALLY Used By Developers
9:27
100+ Linux Things you Need to Know
12:23
Просмотров 862 тыс.
НЕ БЕРУ APPLE VISION PRO!
0:37
Просмотров 218 тыс.
Красиво, но телефон жаль
0:32
Просмотров 1,5 млн