How to Build an Automated YouTube Quiz Generator with Apify and Bilship

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How to Build an Automated YouTube Quiz Generator with Apify and Bilship

Web scraping and data extraction can be significantly simplified using Apify, a versatile platform for building, deploying, and publishing web scrapers – or ‘actors’ as they’re called in Apify terminology. These actors can extract data from popular platforms such as TikTok, Google Maps, LinkedIn, and YouTube. When combined with Bilship, you can create powerful automation workflows.

Building a YouTube Quiz Generator

A practical application of this combination is creating an automated quiz generator from YouTube videos. This workflow accepts a YouTube video URL, extracts the captions using Apify, and then uses AI to generate engaging quiz questions with multiple-choice answers in a structured JSON format.

Step-by-Step Implementation Guide

  1. Create an Apify account and access the console
  2. Create a new Bilship workflow named “YouTube Quiz Generator”
  3. Add a string input named “video URL”
  4. Add the Apify integration – specifically the “Get YouTube Captions” node
  5. Configure the Apify node with your API key and connect it to the video URL input
  6. Add an extract and join utility node to combine the caption text from different timestamps
  7. Configure the node to use the “text” field from the Apify results
  8. Add an Anthropic Claude AI node to generate quiz questions
  9. Configure Claude with instructions to create multiple-choice questions based on the video content
  10. Add a JSON generator node to structure the quiz output
  11. Define the schema with fields for questions, choices, and answers

Benefits of the Structured Output

The resulting structured JSON output contains an array of quiz questions, each with the question text, multiple-choice options, and the correct answer. This format makes it easy to integrate with any frontend system or AI builder like Bolt or Tempo Labs, allowing you to create engaging quizzes to share with your audience after publishing videos.

Debugging and Testing

During implementation, you may encounter validation errors that require minor adjustments, such as:

  • Ensuring proper data type specifications (array vs. object)
  • Using compatible AI model versions
  • Adding field names to your JSON structure

Once these issues are resolved, the workflow can successfully generate quizzes from any YouTube video automatically, creating engaging supplemental content with minimal effort.

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