Building a RAG Chatbot with LangGraph

​Unleash the power of AI with Retrieval-Augmented Generation (RAG) using LangGraph!

​​Join us for a beginner-friendly, hands-on workshop where we’ll demystify RAG chatbots and guide you through building your first smart, LLM-powered assistant with LangGraph.

​​Whether you’re a developer, data enthusiast, or curious about AI, this workshop will teach you the essentials of RAG systems and how to implement them practically.

​​🔍 What You’ll Learn:
- ​What RAG is and how it enhances LLM performance
- ​How to use LangGraph to build a RAG chatbot
​- How to integrate retrieval tools (e.g., vector stores) with LLMs
​- How to design prompts for effective retrieval and generation
​- How to debug and optimize RAG workflows

​​💻 Hands-On Project:
​You’ll create a RAG chatbot that retrieves relevant data, answers queries, and reasons through tasks step-by-step.

​​💻 Instructor:
​Gokula Krishna
​AI Startups CTO
​10+ years software engineering experience
​Specializes in building robust AI-driven solutions, architecting scalable systems
​Blog: https://www.gokulakrishna.co/

​​🛠️ Tech Stack:
​Python
​LangGraph
​OpenAI (or any preferred LLM)
​LangSmith
​Vector store (e.g., FAISS or Pinecone)

​​📅 Workshop Details:
- ​Date: 29th August 2025
​- Duration: 3 Hours
​- Location: RSVP to SEE
​- Level: Beginner to Intermediate
​- F&B: Complimentary snacks and drinks provided
​- Requirements: Basic programming knowledge required

​​🎁 What You’ll Get:
- ​Sample code and templates to reuse
- ​Access to workshop slides and GitHub repo
​- Free day pass at Working Capitol for attendees
​- Confidence to explore advanced RAG use cases