fade-out
Automated DJ mix upload pipeline for SoundCloud and YouTube. Monitors audio/video folders, analyzes tracks via AI, generates metadata, creates thumbnails/cover art, uploads to platforms, verifies results, and notifies via Discord.
Ficha actualizada 23 sept 2026, 6:30 · upstream 23 sept 2026, 6:20 · release v2.5.0
Qué es fade-out
Descripción editorial construida a partir del repositorio, su documentación y sus señales de mantenimiento.
fade-out is a fully automated DJ mix upload pipeline designed for SoundCloud and YouTube creators. It takes recorded mixes from local storage (NAS or server), analyzes the audio content using AI-powered tools like Shazamio for track identification and metadata extraction, then generates branded thumbnails, cover art, titles, and descriptions through OpenAI integration. The system uploads verified tracks to both platforms and sends webhook notifications via Discord when uploads succeed or fail.
The architecture is built on Docker Compose with a React-based web dashboard that provides real-time monitoring of the pipeline status, mix management, and brand customization options. It supports batch processing of audio files from directories such as /watch/audio and /watch/video, while also handling cue sheet parsing for DJ software integration.
- Automated upload of recorded DJ sets to SoundCloud and YouTube without manual file handling
- Batch processing multiple mixes with consistent branding across both platforms
- Integration with OBS or Twitch recordings via /watch/video directory
- DJ software cue sheet import using djctl for automatic tracklist generation
- Personalized cover art and thumbnails generated per DJ set based on branding settings
- Discord webhook notifications for upload success/failure tracking
- Fully automated pipeline with zero manual steps after initial setup, reducing human error in metadata entry
- Uses AI-powered tools (Shazamio, fal.ai) to extract track information and generate branded assets from raw audio files
- Supports both SoundCloud and YouTube via dedicated upload endpoints with verification of each submission
- Built on Docker Compose for easy deployment across local NAS or cloud infrastructure
- Includes a React-based web dashboard that provides real-time pipeline status monitoring and brand customization
- No authentication mechanism — credentials must be stored securely; anyone with access to the port can read them, so it should run behind an authenticating reverse proxy or on a private network
- Audio analysis relies on AI models that may struggle with layered/underground DJ mixes lacking clear stems
- YouTube OAuth requires public resolvable URLs for callback handling and may be blocked by YouTube's terms of service if not configured correctly
- Docker image pins Python 3.12 due to a dependency conflict with pydub, limiting use on newer systems without manual patching
- Source file renaming feature is opt-in and requires read-write mounts for /watch/audio and /watch/video directories
Perfil de infraestructura
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Deploy using Docker Compose: clone the repo, configure .env with your API keys (OpenAI, fal.ai, SoundCloud, YouTube OAuth tokens), set WATCH_* paths to your NAS or server folders, then run `docker compose up -d`. For production use, mount /watch directories as read-only and place an authenticating reverse proxy in front of the service. Use a fine-grained personal access token scoped only to repository contents for health checks. Enable source file renaming by setting both the rename option and read-write mounts on audio/video folders.
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