Podcast Transcript & Video to Text – X, Facebook, Loom, RSS
Pricing
from $3.00 / 1,000 transcribed minutes
Transcribe audio and video from podcast RSS feeds, Apple Podcasts, X, Facebook, Loom, Twitch or direct media links. Returns transcript text, timestamps, SRT and RAG chunks via Whisper AI. $0.004 per audio minute; music-only and failed items are free. · by TubeText
You can access the Podcast Transcript & Video to Text – X, Facebook, Loom, RSS programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.
1from apify_client import ApifyClient2
3# Initialize the ApifyClient with your Apify API token4# Replace '<YOUR_API_TOKEN>' with your token.5client = ApifyClient("<YOUR_API_TOKEN>")6
7# Prepare the Actor input8run_input = {9 "urls": [10 "https://feeds.npr.org/510318/podcast.xml",11 "https://x.com/TEDTalks/status/2072728824911938015",12 ],13 "maxEpisodesPerPodcast": 1,14}15
16# Run the Actor and wait for it to finish17run = client.actor("tubetext/any-video-podcast-transcript").call(run_input=run_input)18
19# Fetch and print Actor results from the run's dataset (if there are any)20print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")21for item in client.dataset(run.default_dataset_id).iterate_items():22 print(item)23
24# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-startThe Apify API client for Python is the official library that allows you to use Podcast Transcript & Video to Text – X, Facebook, Loom, RSS API in Python, providing convenience functions and automatic retries on errors.
Install the apify-client
$pip install apify-clientOther API clients include: