- Move ci-test.sh and setup.sh to scripts/
- Trim docs/src/zig-cli.md to current structure
- Replace hardcoded secrets with placeholders in configs
- Update .gitignore to block .env*, secrets/, keys, build artifacts
- Slim README.md to reflect current CLI/TUI split
- Add cleanup trap to ci-test.sh
- Ensure no secrets are committed
- Move docker-compose.prod.yml and docker-compose.homelab-secure.yml to deployments/
- Create deployments/README.md with usage instructions
- Update test scripts to use new deployment paths
- Fix performance regression detection to output to tests/bin/
- All test outputs now properly organized in tests/bin/
- 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 production setup scripts for automated deployment
- Include monitoring setup and configuration validation
- Add legacy setup scripts for various Linux distributions
- Implement Bitwarden integration for secure credential management
- Add development and production environment setup
- Include comprehensive management tools and utilities
- Add shell script library with common functions
Provides complete automation for setup, deployment, and management
of FetchML platform in development and production environments.
