AutoTuber

automated youtube pipeline · v2.3.1

From script
to upload
overnight.

End-to-end YouTube pipeline: LLM generates script → neural TTS voiceover → FFmpeg video render → YouTube Data API upload → scheduled publish. One Python job runs the whole chain.

287
Videos rendered
1.4M
Total views
98%
Upload success
3.2×
Realtime render
8:24
Python Data Pipelines in 8 Minutes
scheduled · 2025-04-21 · 09:00 AEST
pythonetltutorialbeginner
Active Jobs▲ 2
4
In Queue
12
Avg Duration3:14
5m
API Quota26%
2,640/10k

Current Job · Python Data Pipelines

Running stage: FFmpeg render · 37% · ETA 2m 18s
donerunningwaiting
LLM
Script
847 tokens
TTS
Voiceover
14 chunks · en-AU
FFmpeg
Render
frame 3,552 / 9,600
YT
Upload
awaiting render
Schedule
publish 09:00 AEST

Job Queue

Scheduled + active renders
TitleStageProgressETA
Python Data Pipelines in 8 Minutesrender
2m 18s
What is CVE? Explained in 3 minutesvoiceover
48s
Anatomy of a SQL Injectionscript
3m 10s
I built a neural net over the weekendupload
30s
Top 10 Python one-liners for data engineersdone
published
How Phishing Emails Actually Workfailed
retry ↻

7-Day Throughput

Videos published per day
Rolling avg: 14/day
MonTueWedThuFriSatSun