GraphAcademy

Introduction to Vector Indexes and Unstructured Data

Introduction

Vector indexes

Importing unstructured data

Setup your development environment

In this module, you will use Python to create a graph from unstructured data. You must set up a development environment to run the code examples and exercises.

Get started

The repository, neo4j-graphacademy/llm-vectors-unstructured, has been created for this course. It contains any starter code and resources you need.

You can use a GitHub codespace as an online IDE and workspace for this course. It will automatically clone the course repository and set up your environment.

GitHub Codespaces

You will need to login with a GitHub account. The GitHub Codespaces free monthly usage will cover the duration of this course.

Open in GitHub Codespace

Develop on your local machine

You will need Python installed and the ability to install packages using pip.

You may want to set up a virtual environment using venv or virtualenv to keep your dependencies separate from other projects.

Clone the github.com/neo4j-graphacademy/llm-vectors-unstructured repository:

bash
git clone https://github.com/neo4j-graphacademy/llm-vectors-unstructured

Install the required packages using pip and download the required data:

bash
cd llm-vectors-unstructured
pip install -r requirements.txt
python -m textblob.download_corpora

You do not need to create a Neo4j database as you will use the provided sandbox instance. The sandbox includes Neo4j’s GenAI functions which you can learn more about in the Neo4j GenAI integration documentation.

Setup the environment

Create a copy of the .env.example file and name it .env. Fill in the required values.

Create a .env file
OPENAI_API_KEY="sk-..."
NEO4J_URI="bolt://"
NEO4J_USERNAME="neo4j"
NEO4J_PASSWORD="password"

Add your Open AI API key (OPENAI_API_KEY), which you can get from platform.openai.com.

Update the Neo4j sandbox connection details:

NEO4J_URI

bolt://{sandbox-ip}:{sandbox-boltPort}

NEO4J_USERNAME

{sandbox-username}

NEO4J_PASSWORD

{sandbox-password}

Test your setup

You can test your setup by running llm-vectors-unstructured\test_environment.py - this will attempt to connect to the Neo4j sandbox and the OpenAI API.

You will see an OK message if you have set up your environment correctly. If any tests fail, check the contents of the .env file.

Continue

When you are ready, you can move on to the next task.

Summary

You have setup your environment and are ready to start this module.

In the next lesson, you will explore a strategy for storing unstructured data in a graph.