All notable changes to the LLM Swarm project will be documented in this file.
- Swarm API Key Authentication: Implemented shared-secret
X-Swarm-Keyheader validation on all tracker and node endpoints. WhenSWARM_API_KEYis set, unauthorized requests are rejected with401. Backward-compatible: unset key allows open access. - All outgoing node-to-tracker and node-to-node HTTP calls now include the
X-Swarm-Keyheader automatically. - Updated
docker-compose.ymlto propagateSWARM_API_KEYto all services.
- Initial Prototype: Core P2P Pooled Compute architecture implemented in Python.
- Pipeline Parallelism: Logic for forwarding hidden state tensors between nodes.
- Dynamic Peer Discovery: Centralized Tracker Node (
tracker.py) for automatic node registration and health monitoring. - Docker Support: Added
Dockerfileanddocker-compose.ymlfor multi-platform deployment (M1 Mac, Linux, Windows). - Test Suite: Automated local mesh simulation script
test_mesh.py. - Project Documentation: Comprehensive README with architecture overview and installation guides.
- Model Slicing Utility: Added
slice_model.pyto allow nodes to host specific layer ranges of large GGUF models (e.g., Qwen-27B). - Agent Integration: Implemented OpenAI-compatible
/v1/chat/completionsendpoint for seamless use with Hermes Agent, AutoGPT, and other AI frameworks. - Public Swarm Instructions: Added detailed guides for users to join live swarms via public tracker URLs (e.g., ngrok).
- Moved from hardcoded peer lists to dynamic tracker-based discovery.
- Standardized tracker port to
12345to avoid common system conflicts.
- Implemented MIT License for open-source distribution.
- Added basic heartbeat mechanism to prevent stale peer routing.