Podcast RSS Feed to RAG-Ready Transcript Chunks

Created by

Andrew Boiko

Actor

Podcast & Video Transcriber for AI — RAG-ready Text

Turn the latest episodes of a podcast RSS feed into a transcript split into RAG-ready chunks with chapters and a short summary. Ready for vector databases and LLM pipelines. Add your feed URL, set how many episodes to process, and run. Pay per transcribed minute, no API key needed.

Try for free

Podcast & Video Transcriber for AI — RAG-ready Texttiger19935/podcast-video-transcriber-rag

Title

Duration, s

Language

Status

+1 field

Input

Podcast feeds:https://feeds.npr.org/510318/podcast.xml

Episodes per feed:1

RAG pack (chunks, chapters, summary):true

RAG chunk size (tokens):600

Output fields

Title

Duration, s

Language

Status

Source

How it works

Sign up on Apify or log in

The Podcast & Video Transcriber for AI — RAG-ready Text Actor is ready to run with the inputs already set for "Podcast RSS Feed to RAG-Ready Transcript Chunks". Sign up or log in and you'll land in Apify Console with a copy of this exact task.

Start the "Podcast RSS Feed to RAG-Ready Transcript Chunks" task

The Podcast & Video Transcriber for AI — RAG-ready Text Actor will start running based on the input automatically. You can also change all the input fields, like podcast feeds, episodes per feed, and more, to match your specific use case.

Receive the "Podcast RSS Feed to RAG-Ready Transcript Chunks" 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 title, duration, s, language, 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 "Podcast RSS Feed to RAG-Ready Transcript Chunks" task via API.