Скачать с ютуб Step-by-Step Guide to Create AI RAG Agent using LangGraph | Python Tutorial в хорошем качестве

Step-by-Step Guide to Create AI RAG Agent using LangGraph | Python Tutorial

Hi, My name is Sunny Solanki, and in this video, I provide a step-by-step guide to implementing the RAG AGENT using the Python library "LANGGRAPH". The agent uses chunks from Apple 10k report to answer questions about apple's financials. I have used open-source LLM Llama-3.3 (70B) freely available through Groq API for building the agent. The tutorial is good starting point for someone new to LangGraph. ============================================ CODE - https://github.com/sunny2309/langchai... ============================================== ======================================================= WEBSITE - https://coderzcolumn.com ======================================================= Important Chapters: 0:00 - Build RAG Agent using LangGraph Intro 2:20 - Load LLM 3:55 - Define Retriever Tools | Functions 13:02 - Bind Tools with LLM 15:45 - Define RAG Agent 28:16 - Query Agent #python #datascience #datasciencetutorial #python #pythonprogramming #pythoncode #pythontutorial #llama3 #langchain #langchain-function-calling #langchain-llama3 #groqapi #langchain-open-source-llms #how-to-use-langchain #langgraph #langgraph-agent #rag-agent