> ## Documentation Index
> Fetch the complete documentation index at: https://helix-digitalocean.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Task Overview

> This guide will walk you through the process of building a Graph-Vector RAG in Python to recommend professors based on their research areas.

## Introduction

We want to create a Python script that uses HelixDB to help students find professors based on their research areas and bio. For example a user could ask

* "What professors does High-Energy Physics research?"
* "What professors are working in the X University?"
* "What professors are working in the Computer Science department?"
* "What professors are working in the X University and are working in the Computer Science department?"
* "I like doing research in Large Language Models, can you recommend me some professors doing this in X University?"

***

## The dataset

In this example, we have a dataset on Professors with fields like:

* Name
* Department
* University
* Short biography
* Key Research Areas

We will be ingesting this data from a JSON file, an example is shown below:

```json theme={null}
{
  "name": "James",
  "department": "Computer Science",
  "university": "Uni X",
  "bio": "James is an Assistant Professor focusing on basketball analytics, computer vision, and machine learning. Projects include ShotNet and DunkGPT.",
  "key_research_areas": [
    {"area": "Computer Vision for Basketball"},
    {"area": "Predictive Modelling & Simulation"},
    {"area": "Sports Analytics with Large Language Models"},
    {"area": "Wearable Sensor Data Mining"},
    {"area": "Fairness & Ethics in Sports AI"}
  ]
}
```

## Building a Graph

Based on this data, we can create a Vector Graph RAG with the following nodes and edges:

**Nodes:**

* Professor Node with properties `name`, `bio`
* Research Area Node with properties `research_area`
* Department Node with the property `name`
* University Node with the property `name`

**Vector Nodes for Embeddings:**

We will have an embedding of the professor's research area

* Vector Node with the property `research_area`

**Edges:**

* Professor to Research Area Edge
* Professor to Department Edge
* Professor to University Edge
* Professor to Vector Node Edge