- Replace std.process.exit(1) with error.InvalidArgs in sync command
- Replace std.process.exit(1) with error.ValidationFailed in validate command
- Update validate.zig to use protocol.ResponsePacket.deinit() for cleanup
- Build verified: zig build --release=fast
Replace inline WebSocket URL construction with Config.getWebSocketUrl()
helper method in all command files. This eliminates code duplication
and ensures consistent URL formatting across the CLI.
Files updated:
- annotate.zig, dataset.zig, experiment.zig, logs.zig
- narrative.zig, prune.zig, queue.zig, requeue.zig
- sync.zig, validate.zig, watch.zig
The helper properly handles ws:// vs wss:// based on port (443).
Extract common UserContext and authentication logic from cancel.zig and
status.zig into new utils/auth.zig module. Add CommonFlags struct to
utils/flags.zig for shared CLI flags. Add getWebSocketUrl() helper to
Config to eliminate URL construction duplication.
Changes:
- Create cli/src/utils/auth.zig with UserContext and authenticateUser()
- Create cli/src/utils/flags.zig with CommonFlags struct
- Update cancel.zig and status.zig to use shared modules
- Add getWebSocketUrl() helper to config.zig
- Export new modules from utils.zig
Reduces code duplication and improves separation of concerns in the
Zig CLI codebase.
- 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
- Add jupyter.zig command with start/stop/status actions
- Update main.zig to include jupyter command in CLI
- CLI now handles all Jupyter setup transparently
- Data scientists only need: ml jupyter start
- Auto-detects container runtime (Podman/Docker)
- Manages container lifecycle automatically
- Provides clear status and error messages
- Fix CLI WebSocket port (9101 vs 9103) in both status and authenticateUser
- Add researcher_user and analyst_user to server config with proper permissions
- Fix API key hashes for all users (complete 64-char SHA256)
- Enable IP whitelist with localhost and private network ranges
- Fix memory leaks in WebSocket handshake (proper key cleanup)
- Fix binary character display in server responses
- All authentication tests now pass: admin, researcher, analyst
Status: Multi-user authentication fully functional
- Add 10ms delay after successful WebSocket handshake
- Use std.posix.nanosleep for proper timing
- This should prevent 'client sent data before handshake complete' error
- CLI WebSocket implementation improved but needs server testing
Status: WebSocket handshake timing improved, ready for testing
- Add Redis configuration to local config
- Fix API key format (api_keys vs apikeys)
- Update CLI to use port 9101
- Disable IP whitelist for testing
- Server now connects to Redis and authenticates
- WebSocket connection reaches server but handshake fails
- CLI needs WebSocket protocol implementation fix
Status: Server running, auth working, WebSocket handshake needs debugging
- 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 modern CLI interface built with Zig for performance
- Include TUI (Terminal User Interface) with bubbletea-like features
- Implement ML experiment commands (run, status, manage)
- Add configuration management and validation
- Include shell completion scripts for bash and zsh
- Add comprehensive CLI testing framework
- Support for multiple ML frameworks and project types
CLI provides fast, efficient interface for ML experiment management
with modern terminal UI and comprehensive feature set.
