How I Built a Free, Self-Hosted Pipeline That Auto-Generates Faceless YouTube Shorts

The article describes FreeFaceless, an open-source, self-hosted pipeline that automatically generates faceless YouTube Shorts using free tools and local models, avoiding the typical $75-100/month subscription costs. The pipeline handles script generation via Groq's free tier, voiceover with edge-tts, captioning through local Whisper, b-roll from Pexels, and video assembly with ffmpeg, all controlled by a single config file. The author also shares a common Windows bug fix involving TLS certificate verification and provides the repository link for setup.

Every "AI YouTube" tutorial ends the same way: sign up for ChatGPT Plus, then ElevenLabs, then Pictory, then n8n Cloud. Add it up and you're paying $75–100/month before you've made a single video — let alone a single dollar. I didn't want a subscription stack. I wanted something that ran on my own machine, used free tiers and local models, and that I actually owned. So I built it, and I just open-sourced it under MIT. It's called FreeFaceless , and it takes one command to go from nothing to an uploaded Short: script → voiceover → captions → b-roll → assembled video → YouTube upload Repo: https://github.com/nils44344/FreeFaceless https://github.com/nils44344/FreeFaceless Here's how each stage works — and the one bug that cost me an evening. The orchestration The whole thing is a linear pipeline. Here's the heart of it trimmed : python def run once publish at=None, upload to youtube=True : data = script.generate 1. Groq writes the script voice mp3 = voice.synth data "full text" , ... 2. edge-tts voiceover words = captions.transcribe words voice mp3 3. local Whisper timing scenes = visuals.fetch for scenes data "scenes" 4. Pexels b-roll ass = captions.write ass words, ... 5. caption file final = assemble.build scenes, voice mp3, ass, … 6. ffmpeg if upload to youtube: upload.upload video final, data "title" , … 7. YouTube Data API Every stage is its own module, and everything is driven by a single config.yaml — so changing the niche, voice, or caption style is an edit, not a code change. 1. Script generation — Groq free tier Groq's free tier serves Llama 3.3 70B fast, and it's OpenAI-compatible, so the official openai SDK works by just pointing the base URL at Groq: python from openai import OpenAI client = OpenAI api key=GROQ API KEY, base url="https://api.groq.com/openai/v1" resp = client.chat.completions.create model="llama-3.3-70b-versatile", response format={"type": "json object"}, forces clean JSON messages= {"role": "system", "content": SYSTEM PROMPT}, ... , The prompt asks for a hook + 4–6 facts + a CTA, returned as JSON with per-scene visual query strings I can feed straight to stock search. JSON mode means no fragile regex parsing. 2. Voiceover — edge-tts free, no key edge-tts exposes Microsoft's neural voices for free, no API key: python import edge tts communicate = edge tts.Communicate text, "en-US-ChristopherNeural", rate="-12%" await communicate.save "voice.mp3" The quality is genuinely good enough for faceless content, and there are dozens of voices/accents to match the niche. 3. Word-level captions — faster-whisper local This is the part most paid tools charge per-minute for. faster-whisper runs locally on CPU and gives word-level timestamps , which I turn into karaoke-style captions: python from faster whisper import WhisperModel model = WhisperModel "base", device="cpu", compute type="int8" segments, = model.transcribe "voice.mp3", word timestamps=True Then I write an ASS subtitle file, 3 words at a time, in a big bold style — the look every Shorts channel uses. FreeFaceless ships the open-licensed Anton font so it works out of the box. 4. B-roll — Pexels free API Each scene's visual query becomes a Pexels Videos search, pulling vertical clips. Free API, generous limits. 5. Assembly — ffmpeg ffmpeg crops every clip to 1080×1920, concatenates them to match the voiceover length, overlays the audio, and burns in the captions: "-vf", f"subtitles='{ass path}':fontsdir='{fonts dir}'" 6. Upload — YouTube Data API OAuth desktop flow, token cached after the first browser login, then every future run refreshes silently. Supports immediate or scheduled publishing. The bug that cost me an evening: SSL on Windows On my machine, every HTTPS call died with CERTIFICATE VERIFY FAILED . The culprit: antivirus doing TLS interception with a custom root cert that Python's bundled certifi doesn't know about. The fix is one import, before any network client is built: python import truststore truststore.inject into ssl use the OS cert store instead of certifi If you build anything network-heavy on Windows, keep this in your back pocket. Honest limitations - Free tiers are rate-limited. This is built for one channel on a normal schedule, not bulk farms. Push it hard and you'll hit limits. - Windows-first. The Python core runs anywhere; the helper scripts are PowerShell. Cross-platform PRs very welcome. - It's a production tool, not a money machine. It automates making videos. Views and revenue depend on your content and the algorithm — no tool changes that. Try it / contribute The repo has a full setup guide including the Google OAuth walkthrough, which is the only fiddly part : https://github.com/nils44344/FreeFaceless https://github.com/nils44344/FreeFaceless If it's useful, a star helps other people find it — and I'd genuinely love feedback, especially on making the setup smoother for non-developers and getting it running on macOS/Linux.