- Create detailed README for main repository with architecture overview
- Add package-specific READMEs with usage examples and API documentation
- Create CONTRIBUTING.md with development guidelines and workflow
- Update LLM.md with architectural decisions and patterns
- Document all CLI commands, configuration options, and best practices
- Include installation, testing, and deployment instructions
- Add code examples for all major features
- Document port allocation strategy and integration points
- Ensure 100% test pass rate (197 tests passing)
- Renamed 'cluster' terminology to 'node' throughout codebase for clarity
- Added new 'hanzo router' command for managing LLM proxy server
- Added zsh shell tool with automatic shell detection (prefers zsh over bash)
- Fixed REPL to use cloud mode by default to avoid local server dependency
- Updated chat command to try router (port 4000) before local node (port 8000)
- Added comprehensive Grok documentation to README
- Created NODE_COMPATIBILITY.md documenting integration with desktop app and network
BREAKING CHANGE: 'hanzo cluster' commands now use 'hanzo node' - old commands still work via aliases
Key changes:
- hanzo node start/stop/status - manage local AI nodes
- hanzo router start/stop/status - manage LLM proxy router
- hanzo node worker - manage node workers (formerly cluster nodes)
- Zsh is now default shell when available
- Router runs on port 4000, nodes on port 8000
- Full compatibility with Hanzo desktop app and network layer
- Implement unified CLI tools module for all AI providers
- Add support for claude/cc, codex, gemini, grok, openhands/oh, hanzo-dev, cline, aider
- Enable parallel batch execution of CLI tools
- Add comprehensive test suite with 16 passing tests
- Fix typing issues with mypy strict mode
- Add GitHub Actions CI/CD workflow with optional integration tests
- Support authentication flow for all providers
- Follow DRY principle with single source of truth
- Implement hanzo dev command with System 2 thinking orchestration
- Add support for local models (Llama, Qwen, Mistral) as orchestrators
- Create cost-optimized routing that uses local models for simple tasks
- Add MCP bridge for inter-agent communication
- Enable agent networks where all agents can call each other
- Add comprehensive E2E tests for local AI orchestration
- Fix logger initialization in dev.py
- Add fallback classes for when hanzo-network is not available
- Bump versions: hanzo 0.3.12, hanzo-mcp 0.8.2
- Added Test Status and Hanzo Packages CI badges
- Updated project status to reflect mock-based testing
- Highlighted CI/CD pipeline and no external dependencies
- Add CI status, test coverage, and version badges
- Update with current features and capabilities
- Add comprehensive usage examples
- Include development and testing instructions
- Clean, professional documentation structure
- Reorganized main README to focus on complete AI SDK ecosystem
- Created dedicated hanzoai package README for AI client library
- Clear distinction between ecosystem (hanzo) and client library (hanzoai)
- Updated package descriptions and usage examples
- Bump versions: hanzoai 2.0.2→2.1.0, hanzo 0.2.14→0.3.0, hanzo-mcp 0.7.7→0.8.0
- Highlighted hanzo net command for local AI orchestration
- Added comprehensive installation variants and architecture details
zeekay
stainless-app[bot]