🛠️ Initial YouTube upload and description generation: OAuth, montage flow, thumbnail setup, env config. Work in progress by gramps@llamachile.shop
🎥 LCS Pipeline
Automated livestream highlight rendering and publishing for Fortnite content featuring Gramps.
This project powers the backend of Llama Chile Shop, transforming raw livestream clips into polished, uploaded videos — complete with titles, thumbnails, intros/outros, and social metadata.
⚙️ Features
- ✅ Daily folder scan for new stream sessions (2025‑07‑10) [
v0.1.0] - 📂 Clip classification (
hits/,misses/,montages/,outtakes/,timelapses/) (2025‑08‑07) [v0.1.2] - 🧠 AI‑generated titles and descriptions via OpenAI (2025‑07‑10) [
v0.1.0] - 🎬 Auto‑stitched intro + title card + outro (2025‑07‑23) [
v0.1.0] - 🖼️ Dynamic thumbnail creation with Fortnite styling (2025‑07‑25) [
v0.1.0] - ⬆️ Uploads to YouTube (2025‑07‑29) and PeerTube (2025‑08‑07) [
v0.1.1&v0.1.2] - 📜 Metadata archive and session history (2025‑07‑26) [
v0.1.0] - 🐘 (Planned) Social posts to Mastodon and Bluesky (2025‑07‑20) [
v0.2.0]
🚀 Quick Start
git clone https://llgit.llamachile.tube/gramps/video-pipeline.git
cd video-pipeline
pip install -r requirements.txt
cp .env.example .env # Fill in your API keys and config
python main.py
Requires Python 3.13+ and access to mapped NAS directory (e.g.
Z:\2025.08.05\hits\).
📁 Folder Structure
video-pipeline/
├── main.py
├── config.py
├── .env.example
├── modules/
│ ├── render_engine.py
│ ├── title_utils.py
│ ├── thumbnail_utils.py
│ ├── yt_poster.py
│ └── ...
├── assets/ # Branding assets (intros, fonts, logos)
├── logs/ # Sync logs, wiki publish logs, etc.
└── metadata/
└── history/ # Per-clip metadata archive
📚 Documentation
Full documentation is hosted in the 📖 Gitea Wiki
Recommended pages:
🛠️ Development Mode
DEBUG=Truein.envdisables destructive operations- All modules can be run/tested independently
- Wiki editing is supported via local Markdown and
wiki_publish.log
👤 About
Created by Gramps for Llama Chile Shop — a custom content pipeline for old-school gaming chaos.
Maintainer:
gramps@llamachile.shopContributions welcome in the form of bug reports, pull requests, or Fortnite gifts.
Description
Video Pipeline Automation
The Video Pipeline project automates the process of extracting, processing, and uploading highlights from livestreams, primarily for Fortnite gameplay. This system integrates Eklipse.gg for AI-based highlight detection, DaVinci Resolve for video editing, and custom Python scripts for rendering and metadata management. The pipeline supports seamless uploads to YouTube and PeerTube, automatic social media announcements, and maintains a detailed history of video metadata for each session.
Key Features:
Automated highlight extraction from livestreams
Dynamic title card generation with Fortnite-themed branding
Streamlined YouTube and PeerTube uploads with dynamic descriptions
Metadata tracking and session management
Social media integration for automatic posts to Mastodon and Bluesky
This project is designed to optimize video content creation and management for livestreamers, ensuring efficiency and consistency in processing and sharing content.
Languages
Python
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