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@generacy-ai/smee-backoff

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Generacy

Message routing system connecting Agency instances with Humancy.

Overview

Generacy is a message routing and coordination system that enables communication between Agency AI instances and Humancy (human oversight). It provides the infrastructure for distributed AI agent coordination, message queuing, and human-in-the-loop workflows.

Quick Start

Prerequisites
  • Node.js >= 20.0.0
  • pnpm (recommended) or npm
Installation
pnpm install
Development
# Start development server
pnpm dev

# Build project
pnpm build

# Run tests
pnpm test

# Watch mode for tests
pnpm test:watch

# Lint code
pnpm lint

# Fix linting issues
pnpm lint:fix

Project Structure

generacy/
├── packages/          # Monorepo packages
├── src/              # Core source code
├── tests/            # Test files
├── docs/             # Documentation site (Docusaurus)
├── docker/           # Docker configurations
├── scripts/          # Build and utility scripts
└── specs/            # Feature specifications

Development Stack

For Firebase emulators and backend services, use the development stack:

# Start the stack
/workspaces/tetrad-development/scripts/stack start

# Load environment variables
source /workspaces/tetrad-development/scripts/stack-env.sh

See Development Stack Documentation for details.

Testing

MCP Testing Tools

For browser automation and UI testing with Playwright:

See MCP Testing Tools

Running Tests
# Run all tests
pnpm test

# Watch mode
pnpm test:watch

Publishing

VS Code Extensions

This repository includes VS Code extension development and publishing infrastructure.

Publisher Details:

Documentation:

Documentation

Architecture

Generacy is built as a monorepo with multiple packages:

  • Message Router: Core routing engine for Agency-Humancy communication
  • Redis Integration: Queue management using ioredis
  • Express API: REST endpoints for message submission and retrieval
  • TypeScript: Full type safety across the codebase

Contributing

We welcome contributions! To get started:

  1. Create feature branches from develop
  2. Follow existing code style and linting rules
  3. Write tests for new functionality
  4. Submit PRs for review before merging

Environment Variables

Copy .env.example to .env and configure:

cp .env.example .env

See .env.example for required configuration options.

License

MIT

Contact

  • GitHub Organization: generacy-ai
  • Support: See individual package documentation