https://github.com/ry-ops/commit-relay
Autonomous multi-agent AI platform for GitHub repository lifecycle management. MoE routing, self-healing workers, LLM mesh gateway, RAG-enhanced context, enterprise governance. [Archived]
https://github.com/ry-ops/commit-relay
ai-agents anthropic-claude autonomous-agents devops-automation enterprise-governance github-automation llm mcp-server mixture-of-experts multi-agent-system nodejs observability opentelemetry python pytorch rag self-healing typescript vector-database
Last synced: 10 days ago
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Autonomous multi-agent AI platform for GitHub repository lifecycle management. MoE routing, self-healing workers, LLM mesh gateway, RAG-enhanced context, enterprise governance. [Archived]
- Host: GitHub
- URL: https://github.com/ry-ops/commit-relay
- Owner: ry-ops
- License: other
- Created: 2026-03-08T09:09:50.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2026-04-27T10:45:03.000Z (about 1 month ago)
- Last Synced: 2026-05-05T08:41:38.629Z (23 days ago)
- Topics: ai-agents, anthropic-claude, autonomous-agents, devops-automation, enterprise-governance, github-automation, llm, mcp-server, mixture-of-experts, multi-agent-system, nodejs, observability, opentelemetry, python, pytorch, rag, self-healing, typescript, vector-database
- Language: Shell
- Size: 5.68 MB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 20
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Security: SECURITY.md
- Governance: GOVERNANCE-ARCHITECTURE.md
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README
# Commit-Relay
**Multi-agent AI system for autonomous GitHub repository management.**
[](https://github.com/ry-ops/commit-relay)
[](./docs/master-worker-architecture.md)
[](./LICENSE)
> **Note:** This project is archived and no longer in active development or production use. The codebase is preserved as-is for reference.
---
## What is Commit-Relay?
Commit-Relay was an autonomous multi-agent platform that managed the entire GitHub repository lifecycle — from task routing to code implementation, security scanning, testing, and deployment — with zero manual intervention.
Agents communicated through structured coordination files rather than direct API calls, creating a fully auditable, transparent orchestration system. A central Coordinator routed incoming tasks to specialized master agents using a Mixture of Experts (MoE) router, which then spawned lightweight workers to execute in parallel.
---
## Architecture
### Core Components
| Component | Description |
|-----------|-------------|
| **5 Master Agents** | Coordinator, Development, Security, Inventory, CI/CD |
| **7 Worker Types** | Implementation, Fix, Test, Scan, Security Fix, Documentation, Analysis |
| **8+ Autonomous Daemons** | Coordinator, Worker Manager, Process Monitor, Heartbeat, Zombie Cleanup, Worker Restart, Failure Detection, Auto-Fix |
| **LLM Mesh Gateway** | Multi-provider support (Anthropic, OpenAI, Ollama) with circuit breakers, cost tracking, and automatic failover |
| **MoE Router v4.0** | 350+ activation keywords, learned weights, semantic routing, 100% routing confidence |
| **RAG System** | FAISS vector store with 5 collections (code, docs, decisions, patterns, tasks) using sentence-transformers |
| **API Server** | 128 REST endpoints, WebSocket streaming, rate limiting, authentication |
| **MCP Server** | Model Context Protocol interface exposing system capabilities as tools |
| **Python SDK** | Full client library with task orchestration, analytics, health monitoring, and reporting |
| **Observability** | Elastic APM, LangSmith tracing, 27 event types, distributed tracing, anomaly detection |
---
## Key Capabilities
### Intelligent Task Routing
- Mixture of Experts router with 350+ keywords and continuous learning
- PyTorch neural routing with training pipeline
- Semantic routing via embeddings (94.5% coverage)
- Margin-based confidence with automatic fallback
### Self-Healing System
- 12+ automated remediation strategies
- Heartbeat monitoring with 2-minute intervals
- Zombie worker detection and cleanup
- Exponential backoff restart logic
- ML-based failure pattern recognition
### LLM Mesh (Multi-Provider Gateway)
- Anthropic Claude (primary), OpenAI, and Ollama support
- Cost-aware model selection (simple tasks -> haiku, complex -> opus)
- Circuit breaker middleware with provider health monitoring
- Automatic failover chains with retries
- Token usage and cost analytics
### Enterprise Governance
- PII scanning (emails, phone numbers, SSNs, API keys)
- RBAC with permission inheritance across 7 namespaces
- SOC2, GDPR, HIPAA compliance policy checking
- Data quality monitoring with schema validation
- Complete audit trail via file-based coordination
### Observability Stack
- Elastic Cloud APM with custom spans and business metrics
- LangSmith for LLM performance tracking
- 27 event types with real-time streaming
- Distributed tracing with waterfall visualization
- 50+ system metrics with aggregation
### RAG-Enhanced Context
- Pluggable vector store (Weaviate, Qdrant, file-based)
- Connectors for GitHub, Confluence, Slack
- Hybrid search (BM25 + semantic with Reciprocal Rank Fusion)
- 5 specialized collections with metadata schemas
---
## Project Structure
```
commit-relay/
├── agents/ # Agent configs, prompts, logs, worker outputs
├── api-server/ # Express.js API server (128 endpoints)
├── config/ # System configuration
├── coordination/ # File-based coordination (task queue, worker pool, handoffs)
│ ├── masters/ # Master agent configurations and libraries
│ ├── governance/ # Governance policies and audit logs
│ ├── catalog/ # Data and AI catalog
│ └── observability/ # Event streams and metrics
├── docs/ # 40+ documentation files
├── examples/ # Usage examples
├── lib/ # Shared libraries
│ ├── cache/ # Adaptive LRU cache
│ ├── governance/ # PII scanner, access control, compliance
│ ├── orchestration/ # Workflow engine, SLA monitor, rate limiter
│ └── rag/ # Vector store, embeddings, connectors
├── llm-mesh/ # Multi-provider LLM gateway
├── mcp-server/ # Model Context Protocol server
├── python-sdk/ # Python client library
├── scripts/ # 117+ operational scripts
├── security/ # Security scanning and CVE tracking
└── testing/ # Test suites and test utilities
```
---
## Tech Stack
| Category | Technologies |
|----------|-------------|
| **Runtime** | Node.js 18+, Python 3.8+, Bash |
| **AI/ML** | Anthropic Claude, OpenAI, Ollama, PyTorch, sentence-transformers, FAISS |
| **API** | Express.js 5, WebSocket, JSON-RPC 2.0 (MCP) |
| **Observability** | Elastic APM, LangSmith, OpenTelemetry |
| **Security** | Helmet, express-rate-limit, JWT, PII scanning |
| **Data** | FAISS, Weaviate, Qdrant, MiniSearch |
| **Deployment** | Docker, systemd/launchd |
---
## License
[MIT](./LICENSE)