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Martin O'Hanlon

GenAI Beyond Chat with RAG, Knowledge Graphs and Python

A Talk by Martin O'Hanlon (Neo4j Graph Database & Analytics, Neo4j)

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About this Talk

GenAI and Large Language Models (LLMs) have the potential to increase productivity and provide access to data, but they need grounding and good context to be truly useful.

In this hands-on GenAI masterclass, you will learn how Knowledge Graphs and Retrieval Augmented Generation (RAG) can support your GenAI projects.

You will:

  • Learn about Large Language Models (LLMs), hallucination and integrating knowledge graphs
  • Explore Retrieval Augmented Generation (RAG) and its role in grounding LLM-generated content
  • Use Vector indexes and embeddings in Neo4j to perform similarity and keyword search
  • Use Python, LangChain and OpenAI to create a Knowledge Graph of unstructured data

After completing this masterclass, you will be able to explain the terms LLM, RAG, grounding, and knowledge graphs. You will also have the knowledge and skills to create simple LLM-based applications using Neo4j and Python.

This masterclass will put you on the path to controlling LLMs and enabling their integration into your projects.

Key Topics

  • Large Language Models (LLMs) and strategies for improving their responses
  • Use Python and LangChain to interact with an LLM
  • Learn how to implement Retrieval Augmented Generation (RAG) strategies, including:
  • Using prompts to provide instructions and context
  • Using Neo4j vectors to query a graph database
  • Use vector indexes to search for similar data
  • Create embeddings and vector indexes
  • Build a graph of unstructured data using Python and LangChain

Target Audience

  • Software developers
  • Data Engineering
  • Managers of the above

Goals

  • Build a knowledge graph of unstructured data
  • Create a Retrieval Augmented Generation (RAG) chat agent using Python, Langchain, and Neo4j

Session outline:

  • Knowledge Graphs, Unstructured Data, and Vectors
  • Semantic search, vectors and embeddings
  • Importing unstructured data
  • Building a graph
  • LLMs, RAG, Python, and LangChain
  • LLMs, hallucination, and grounding
  • Using Python and LangChain
  • Grounding an LLM
  • Agents and Retrievers

Format

This class is very hands-on.

Each section will be introduced by the facilitator, before moving quickly on to hand-on coding exercises.

You will use Python, LangChain, OpenAI, and Neo4j to create a graph of unstructured data and develop a chat agent.

A “starter” repository will be provided, along with a Neo4j instance and OpenAI API key removing the challenges of setup and allowing you to get started quickly.

You can use your own Python development environment or use a prebuilt online environment and VS Code IDE on Gitlab.

All the content will be provided at the start of the class allowing you to either follow along, work at your own pace, or continue after the class has completed. There are multiple open-ended stretch activities where you can practise your skills or develop your own solutions.

The masterclass is split into 2 main activities:

  1. Knowledge Graphs, Unstructured Data, and Vectors - you will import unstructured data, creating embedding and build a graph
  2. LLMs, RAG, Python, and LangChain - you will create a chat agent that will integrate with a graph in Neo4j

Once complete you will have the knowledge and skills to create a graph of your own unstructured data and use an LLM to find and interpret the data.

Level

Beginner - Intermediate

Prerequisite Knowledge

Before taking this masterclass, you should have:

  • A basic understanding of Graph Databases and Neo4j
  • Knowledge of Python and capable of reading simple programs

11 December 2024, 02:00 PM

GenAI & Graph RAG Stage

02:00 PM - 04:00 PM

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About The Speakers

Martin O'Hanlon

Martin O'Hanlon

Neo4j Graph Database & Analytics, Neo4j

Martin is an experienced computer science educator and open source software developer. Martin creates educational content for Neo4j and supports developers in using graph technology. As a child he wanted to be either a Computer Scientist, Astronaut or Snowboard Instructor.

Martin O'Hanlon

Location

Convene 133 Houndsditch

133 Houndsditch, London

Neo4j

Neo4j, the Graph Database & Analytics leader, helps organizations find hidden relationships and patterns across billions of data connections deeply, easily, and quickly.

Platinum Sponsor

Ontotext

Connect the dots of your data! Ontotext helps enterprises to lower data management costs by up to 30%, enable data fabric architectures, create digital twins, utilize Graph RAG benefits, and take information delivery from days to minutes!

Gold Sponsor

Semantic Web Company / PoolParty

The vendor of PoolParty Semantic Suite. Graph-based text mining, recommender systems, and data fabric solutions.

Gold Sponsor

yWorks

yWorks specializes in the development of professional software solutions that enable the clear visualization of diagrams and networks.

Gold Sponsor

Oracle

This global cloud tech company offers infrastructure and software to enhance organizational innovation and efficiency. Its autonomous database delivers top performance, security, and cost savings. Supporting businesses, governments, and research, the company embraces diversity and fosters growth.

Gold Sponsor

Ultipa

Ultipa builds next-gen graph XAI & real-time database empowering smart enterprises w/ smooth digital transformations.

Sliver Sponsor

Oxford Semantic Technologies

Oxford Semantic Technologies (OST) spun out from the University of Oxford and was acquired by Samsung in 2024. OST provides AI software to extract insights from big data, solving issues like medical diagnostics and financial crime. One founder is a BCS Lovelace Medal winner.

Sliver Sponsor

FlureeDB

Web3 data platform built on standards. Fluree powers connected, secure, and agile data ecosystems.

Bronze Sponsor

Senzing

Senzing is the first to deliver real-time, artificial intelligence for entity resolution. Senzing software enables organizations of all sizes to gain highly accurate and valuable insights about who is who and who is related to whom in data.

Bronze Sponsor

Semantic Partners

We partner with you, and your chosen semantic stack, to liberate your data's meaning from isolated silos.

Bronze Sponsor

Epsilla

All-in-one platform to create AI agents powered by your private data and knowledge. Make GenAI prototype to production 10 times faster. We are backed by Y Combinator. Start free today: https://epsilla.com

Bronze Sponsor

Neural Alpha

Since 2016 Neural Alpha have delivered cutting edge, sustainability centric Connected Data solutions for blue-chip corporates, financial institutions, Governments and NGOs. Our bespoke software & data solutions fuse AI, Knowledge Graphs, Taxonomies & other technologies for unprecedented insights.

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