Step-by-Step Guide to Build RAG App using LangChain | Ollama | Llama-2 | Python

Hi, My name is Sunny Solanki, and in this video, I provide a step-by-step guide to creating a RAG LLM App using the Python framework "langchain". To build our LLM app, we have used open-source LLM "llama-2" with 7B parameters. To access LLMs, we use a tool named "Ollama". The tutorial is a good starting point for someone new to LangChain and wants to learn how to create LLM Apps. It's a good introduction to the RAG concept.

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CODE - https://github.com/sunny2309/langchai...
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Learn Ollama -    • Ollama: Run LLMs on your Local Machine for...  
Learn Ollama Python Library -    • Ollama Python Library: Use LLMs on your Lo...  
What is RAG -    • RAG (Retrieval Augmented Generation) Expla...  
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Important Chapters:

0:00 - Build RAG LLM App using LangChain
0:58 - RAG App Workflow
2:11 - Download Ollama & "llama-2 (TB)" Model
4:25 - Code Explanation
5:12 - Simple LLM App
8:20 - Simple RAG App
11:20 - Create Vector Store Index (FAISS)
13:57 - Langchain Retrieval Chain

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