Step-by-Step Guide to Build AI 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 ReAct/Tool Calling agent using the Python library LangGraph. The agent has access to a list of finance tools that can be used to retrieve the latest details about any stock ticker. The agent uses the necessary tools to answer the user's query about stocks. I have used open-source LLM Llama-3.1 (70B) freely available through Groq API for building the agent. The tutorial is good starting point for someone new to LangGraph.
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CODE - https://github.com/sunny2309/langchai...
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Important Chapters:
0:00 - Build ReAct Agent using LangGraph Intro
2:11 - Code Start
4:20 - Load LLM
6:15 - Define Finance Tools | Functions
10:16 - Bind Tools with LLM
13:38 - Define ReAct | Tool Calling Agent
30:33 - 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