Build a YouTube transcript corpus for RAG

Created by

Khadin Akbar

Actor

YouTube Transcript and Subtitle Data Scraper

Collect transcript text and LLM-ready context from public YouTube videos to support retrieval, indexing, or grounded analysis.

Try for free

YouTube Transcript and Subtitle Data Scraperkhadinakbar/youtube-transcript-extractor

Video title

Full transcript (plain text)

Word count

Estimated token count

+2 fields

Input

Search Query:customer support best practices

Max videos:5

Transcript language:en

Transcript format:all

Include video metadata:false

Apify proxy:{2 fields}

Output fields

Video title

Full transcript (plain text)

Word count

Estimated token count

Language used

Auto-generated captions

How it works

Sign up on Apify or log in

The YouTube Transcript and Subtitle Data Scraper Actor is ready to run with the inputs already set for "Build a YouTube transcript corpus for RAG". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Build a YouTube transcript corpus for RAG" task

The YouTube Transcript and Subtitle Data Scraper Actor will start running based on the input automatically. You can also change all the input fields, like search query, max videos, and more, to match your specific use case.

Receive the "Build a YouTube transcript corpus for RAG" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as video title, full transcript (plain text), word count, and more.

Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Build a YouTube transcript corpus for RAG" task via API.