GTS-Federator is a high-efficiency content discovery tool designed for GoToSocial instances. It solves the "empty timeline" problem of small or personal instances by automatically discovering and federating content from RSS feeds across the Fediverse.

By leveraging RSS feeds from larger instances or specific hashtags, GTS-Federator acts as a lightweight alternative to traditional relays, giving you full control over what kind of content populates your federated timeline.

🏛 Evolution & Credits

GTS-Federator is a refined and modernized fork built upon the innovative concepts of the original Fediverse discovery tools. This project stands on the shoulders of:

@aliceif – The original creator of HolMirDas, who pioneered the concept of RSS-based federation.
Matthias – Whose fork introduced essential GoToSocial adaptations and performance improvements.

This version takes these foundations and optimizes them for modern production environments, focusing on native Docker integration, long-term stability, and GoToSocial's unique architectural requirements.

🛠 What this service is for

GTS-Federator is not a relay in the traditional sense. It is a targeted discovery engine. Instead of receiving everything from a relay, you "pull" exactly what interests you.

It is a perfect fit if you:

run a personal or small GoToSocial instance (especially on low-power hardware like a Synology NAS or Raspberry Pi)
want to populate your federated timeline with specific topics (via Hashtag-RSS)
prefer a pull-based discovery over the "firehose" of public relays
need a "set and forget" solution that runs silently in the background

🚀 Core Features

Smart Content Discovery

The bot monitors a configurable list of RSS feeds. For every new entry found, it triggers your GoToSocial instance to fetch and federate the post. This makes the content available for your local users and populates your instance's database with new remote profiles and statuses.

Efficient Resource Management

Unlike many other fetchers, GTS-Federator is designed with a "Single User" philosophy. It uses a persistent HTTP session and a local JSON-based memory to ensure that your instance isn't hammered with redundant requests.

Real-Time Analytics

After every run, the bot provides a clean summary of its activity:

Runtime: How long the discovery took.
New Posts: Number of successfully federated statuses.
Instance Growth: Tracking how many new Fediverse domains your instance has discovered through the process.

Adaptive Pausing & Timezone Support

The bot calculates its next run based on your local time. With built-in timezone support, the logs will always show you exactly when the next discovery cycle starts, matching your local wall clock.

Production-Ready Dockerization

The entire application is container-native. It runs as a non-root user for enhanced security and can be deployed in seconds using Docker Compose.

🚀 Key Upgrades in this Fork

While the original project pioneered the core discovery concept, this fork has been fundamentally restructured for modern, containerized production environments:

From "Script" to "Service": Replaced external dependency on system cron jobs with an internal interval-based engine, allowing for a native "always-on" Docker experience.
Controlled Request Sequencing: Introduced staggered execution and request delays. By throttling API calls, we prevent the "thundering herd" effect, effectively load-balancing discovery traffic to keep your instance responsive.
Resilient State Persistence: Upgraded from simple URL tracking to a structured JSON database that persists across container restarts, including tracking for domain growth metrics.
Professional Logging & Observability: Implemented a standardized logging framework that supports custom log levels (DEBUG/INFO) and provides real-time feedback on runtime, processed posts, and instance growth.
Environment-Native Design: Complete decoupling of configuration from code. Every aspect—from API timeouts to timing intervals—is now managed via standardized environment variables (.env).
Security-First Containerization: Provided a hardened Dockerfile that ensures the bot runs as a non-root user with minimized permissions, suitable for high-security home lab setups.

🧠 Design Philosophy

GTS-Federator follows a few key principles:

Keep it lightweight – Written in clean Python, utilizing minimal RAM and CPU.
Zero-Maintenance – Once configured, it handles rate limits, connection timeouts, and state persistence automatically.
Privacy First – No external tracking. The bot only communicates with your instance and the RSS sources you define.
Transparency – Clear, human-readable logs that tell you exactly what is happening.

⚙️ Configuration (Environment Variables)

The bot is configured via environment variables. Create a .env file in your project directory using the following parameters:

Variable	Description	Default / Example
Basics
`GTS_SERVER_URL`	The full URL of your GoToSocial instance.	`https://social.domain.tld`
`GTS_ACCESS_TOKEN`	Your application's Access Token (needs read/search scopes).	`YOUR_SECRET_TOKEN`
Performance
`FETCH_INTERVAL`	Time the bot sleeps between discovery runs (e.g., `30m`, `1h`).	`30m`
`MAX_POSTS_PER_RUN`	Maximum number of new posts to process per RSS feed per run.	`25`
`DELAY_BETWEEN_REQUESTS`	Delay in seconds between API calls to prevent rate limiting.	`1`
`REQUEST_TIMEOUT`	Seconds to wait for responses from external servers.	`30`
Identity & Logs
`LOG_LEVEL`	Level of logging detail (`DEBUG`, `INFO`, `WARNING`, `ERROR`).	`INFO`
`USER_AGENT`	Custom User-Agent to identify your bot to remote instances.	`GTS-Federator/1.0...`
Paths
`RSS_URLS_FILE`	Internal path to the feed list (change only if necessary).	`/app/rss_feeds.txt`
`DATABASE_PATH`	Internal path to the JSON state file (change only if necessary).	`/app/data/processed_urls.json`

📦 Installation

Preparation

Before deploying, you need to set up the directory structure. This ensures the bot can save its "memory" and find your configuration.

Create the Project Folder: Create a main directory (e.g., gts-federation).
Create the Data Subfolder: Inside that folder, create a subfolder named data. This is where the bot stores its database (processed_urls.json).
Place your Files: Put your compose.yaml, .env, and rss_feeds.txt into the main directory.

Folder Structure:

Your final structure should look like this:


gts-federation/
├── data/               <-- Subfolder for the database (Required)
├── .env                <-- Your credentials & settings
├── compose.yaml        <-- Docker configuration
└── rss_feeds.txt       <-- Your list of RSS feeds

Note on Permissions:

Ensure the data folder is writable. If you are using a specific UID (e.g., on a Synology NAS), assign ownership to that user: chown -R 1026:100 ./data

Compose.yaml

version: "3"

services:
  gts-federation:
    image: domoel/gts-federator:latest
    container_name: gts-federator
    #user: 1026:100 # If you run into permission issues with the 'data' folder, make sure to set the correct UID/GID for your system.
    volumes:
      - ./data:/app/data
      - ./rss_feeds.txt:/app/rss_feeds.txt:ro
    environment:
      - TZ=Europe/Berlin # Change to your local timezone.
    env_file:
      - .env
    restart: always

You can download the docker image on Docker Hub

📜 License & Credits

This project is released under the MIT License. This ensures that the code remains open and accessible to the community.

README.md Unescape Escape

GTS Federator

A powerful RSS-based discovery engine to populate GoToSocial instances.

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✨ Introduction