AI Horde is a free, community-driven distributed computing platform for AI art and text generation. It allows volunteers to contribute their GPU power to a shared cluster, enabling users without powerful hardware to access advanced AI models. The system uses a "kudos" point system to manage resource allocation and reward contributors, ensuring equitable access without commercialization.

How It Works

The AI Horde operates as a distributed inference cluster, connecting users (clients) with volunteer compute resources (workers). When a request is made, the system routes it to available workers capable of processing the task. Workers earn kudos for their contributions, which can be used to gain priority for their own requests or simply to support the network. This crowdsourced model allows for high scalability and flexibility, supporting both image and text generation models.

Quick Start & Requirements

• Public Instance: Access via REST API or through various client applications. Registration with OAuth2 is recommended for priority and kudos tracking. Anonymous usage is possible with API key '0000000000' but has lowest priority.
• Worker Contribution: Requires Python 3.9+, PostgreSQL, and Redis. Docker is supported for containerization. Specific worker software like horde-worker-reGen for image generation or various options for text generation (e.g., AI-Horde-Worker, KoboldAI) are available.
• Documentation: AI Horde Documentation

Highlighted Details

• Crowdsourced distributed inference cluster for enterprise-level ML-Ops.
• Supports both image (e.g., Stable Diffusion) and text (e.g., LLMs) generation.
• Scalable architecture with seamless drop-in/drop-out of compute resources.
• Kudos system for fair resource allocation and priority, cannot be bought or sold.

Maintenance & Community

• Active community on Discord.
• Details on contributing and integrating are available.

Licensing & Compatibility

• The repository itself does not explicitly state a license in the provided README. However, the project's ethos emphasizes free and community-driven access.

Limitations & Caveats

• The README does not specify a license for the core middleware, which could impact commercial use or closed-source integration. Anonymous usage may be restricted during high load periods.