RAG with Langchain, Ollama Llama3, and HuggingFace Embedding | Complete Guide

In this video, I'll show you how to create a powerful Retrieval-Augmented Generation (RAG) system using LangChain, Llama 3, and HuggingFace Embeddings. You'll learn how to make a Large Language Model (LLM) understand and answer questions about a complex PDF document.

➡️Chapters:
0:00 Introduction
2:25 Setting up the Environment
5:25 Setting Up LangChain
7:20 Chunking Large Documents
11:40 vector stores
12:30 HuggingFace Embedding
14:32 Retrieval QA
17:10 Run the chain
18:58 Conclusion


🔗 Repo Link: https://github.com/bitfumes/Langchain...

If you’ve found my content helpful and want to show your appreciation, consider buying me a coffee! → https://ko-fi.com/sarthaksavvy

🔔 Subscribe for more tutorials and hit the notification bell to stay updated with the latest content!

🔗 Links
Buy me a coffee → https://ko-fi.com/sarthaksavvy
Hindi Channel →    / @code-jugaad  
LinkedIn →   / sarthaksavvy  
Instagram →   / sarthaksavvy  
X → https://x.com/sarthaksavvy
Telegram → https://t.me/+BwLR8bKD6iw5MWU1
Github → https://github.com/sarthaksavvy
Newsletter → https://bitfumes.com/newsletters

#langchain #ollama #llama3 #RetrievalAugmentedGeneration #huggingface