python

Generate Prerequisite Practice

Demonstrates how to generate prerequisite-based practice questions using the Knowledge Graph REST API, covering:

• API Integration: Using REST API to query standards and learning progressions
• Prerequisite Analysis: Finding standards that build towards a target standard
• Learning Components: Discovering granular learning components that support standards
• Practice Generation: Creating structured practice questions based on prerequisite knowledge using AI

Note: The API is in limited early release and is only available to some private beta users. Because the API is an early release, current users should expect occasional breaking changes.

Prerequisites

• Python 3.8 or higher
• A Learning Commons Platform account
• An API key generated in the Learning Commons Platform
• OpenAI API key

Dependencies

• requests: HTTP library for API calls
• openai: OpenAI API for generating practice questions
• python-dotenv: Environment variable management

Quick Start

1. Clone and Set Up Virtual Environment:

   git clone git@github.com:learning-commons-org/knowledge-graph.git
   cd tutorials/generate_prereq_practice/python
   python -m venv venv
   source venv/bin/activate
   pip install -r requirements.txt

2. Set Environment Variables (create .env file):

   # Knowledge Graph API credentials - get these from the Learning Commons Platform
   API_KEY=your_api_key_here
   BASE_URL=https://api.learningcommons.org/knowledge-graph/v0
   
   # OpenAI API key for generating practice questions
   OPENAI_API_KEY=your_openai_api_key_here

3. Run Tutorial:

   python generate_prereq_practice.py