- Add cleanup.sh script with dry-run, force, and all options
- Add auto-cleanup service setup for macOS (launchd) and Linux (systemd)
- Add cleanup-status.sh for monitoring Docker resources
- Add Makefile targets: self-cleanup, auto-cleanup
- Features colored output, confirmation prompts, and detailed logging
- Auto-cleanup runs daily to keep system clean
- Status monitoring shows resources and service state
- Fix YAML tags in auth config struct (json -> yaml)
- Update CLI configs to use pre-hashed API keys
- Remove double hashing in WebSocket client
- Fix port mapping (9102 -> 9103) in CLI commands
- Update permission keys to use jobs:read, jobs:create, etc.
- Clean up all debug logging from CLI and server
- All user roles now authenticate correctly:
* Admin: Can queue jobs and see all jobs
* Researcher: Can queue jobs and see own jobs
* Analyst: Can see status (read-only access)
Multi-user authentication is now fully functional.
- Add comprehensive README with architecture overview and quick start guide
- Set up Go module with production-ready dependencies
- Configure build system with Makefile for development and production builds
- Add Docker Compose for local development environment
- Include project configuration files (linting, Python, etc.)
This establishes the foundation for a production-ready ML experiment platform
with task queuing, monitoring, and modern CLI/API interface.
