LangGraph Beginner Project 🚀 Q&A Agent with Memory in Python
github:-https://github.com/dearnidhi/LangGrap...
In this hands-on tutorial, we build a Simple Q&A AI Agent with Memory using LangGraph and Groq API.
This project demonstrates how AI agents can store context, make decisions, and generate responses using graph-based workflows instead of traditional linear code.
You will learn how to:
Build nodes for processing and response generation
Manage shared state (memory) in LangGraph
Use Groq LLM for intelligent responses
Implement conditional routing and decision logic
Create a simple AI workflow using graphs
🚀 Project Highlights:
AI Q&A Agent with memory
Context-aware responses
Conditional decision making
Graph-based execution flow
Beginner-friendly LangGraph example
🛠 Tech Stack:
Python, LangGraph, LangChain, Groq API
By the end of this project, you’ll understand the core building blocks of AI agent systems and how real-world agent workflows are designed.
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