From Ancient Epic to Modern Marvel: Demystifying the Mahabharata Chatbot with GraphRAG

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Description:

Embark on a captivating adventure where the ancient Mahabharata meets modern technology! This session unveils a Python-built chatbot powered by GraphRAG, a groundbreaking approach that merges knowledge graphs with Large Language Models (LLMs). We'll explore how GraphRAG empowers the chatbot to navigate the Mahabharata's intricate web of characters, events, and relationships.

Unveiling the Magic:

  • Graphing the Epic: Discover how Python scripts and Neo4j wrangle the vast Mahabharata into a comprehensive character and relationship graph, unlocking powerful connections.
  • Gradio for Conversational Exploration: We'll delve into Gradio, a user-friendly Python framework, for building a chatbot interface. This interface allows you to interact with the Neo4j graph using natural language, fostering an intuitive way to explore the Mahabharata.
  • Vertex AI: Bridging Language and Data: Witness the innovative integration of Google's Vertex AI. This powerful AI service acts as a bridge, translating your natural language queries into efficient Cypher queries, the language of Neo4j. This empowers you to explore the graph with ease.

Unveiling the Benefits:

  • Practical Graph Mastery: Learn practical techniques for graph database modeling with Python and Neo4j.
  • Craft Your Own Chatbot: Gain hands-on experience building a chatbot using Gradio.
  • Unlocking Gen-AI Potential: Discover the transformative power of Generative AI for interactive storytelling and data exploration with Vertex AI.
  • A Fresh Perspective on the Mahabharata: Deepen your understanding of this timeless epic through a novel, interactive lens.

Join this exciting exploration and witness the power of Python, graph databases, and Gen-AI unveil the hidden depths of the Mahabharata!

Prerequisites:

Basic understanding of Python and data structures.

Content URLs:

  • Github Repo: https://github.com/sidagarwal04/mahabharata-genai
    • Part-1 Blog: https://sidagarwal04.medium.com/unveiling-the-mahabharatas-web-a-graph-journey-using-neo4j-from-epic-relationships-to-7be4a7a29b6d
    • Part-2 Blog: https://medium.com/@sidagarwal04/bringing-the-mahabharata-epic-to-life-a-neo4j-powered-chatbot-using-google-gemini-part-2-6eef8676e757
    • Part-3 Blog: https://sidagarwal04.medium.com/from-ancient-epic-to-modern-marvel-demystifying-the-mahabharata-chatbot-with-graphrag-part-3-5942260a9560

Speaker Info:

Hello, I'm Sid Agarwal, currently leading Developer Communities for APAC at Neo4j. Formerly, I pioneered India's first fintech community as the 'Developer Relations Lead' at Open Financial Technologies. Prior to that, I spearheaded community efforts as a Program Manager with Google's Developer Relations team in India, overseeing programs like Developer Student Clubs, TensorFlow User Groups, Google Developer Groups, and Google Developer Experts. In 2019, I collaborated with the Ministry of Electronics & Information Technology, Government of India, to launch 'Build for Digital India,' engaging 7,000+ students in solving India's challenges. I'm passionate about design thinking and enjoy mentoring startups to enhance their UX and designs. Recognized as one of ACM's Distinguished Speakers, my career of roughly a decade is dedicated to building, scaling, and growing communities in India, launching ed-tech initiatives, fostering design innovation, and contributing to the startup ecosystem. In 2021, I was nominated as a finalist for the CMX Community Industry Awards for my role in community building. As an avid public speaker, I've shared insights at over 1,000 national and international forums, reaching 300K+ individuals.

Speaker Links:

  • Github: https://github.com/sidagarwal04
    • YouTube recordings: https://www.youtube.com/playlist?list=PLSw4ttUqWj85SA4XfXP7jNPvOryy5PPPl
    • Medium: https://sidagarwal04.medium.com/
    • Linkedin: https://www.linkedin.com/in/sidagarwal04/
    • Twitter: https://twitter.com/sidagarwal04

Section: Artificial Intelligence and Machine Learning
Type: Talk
Target Audience: Intermediate
Last Updated: