Add execution_mode enum (local/remote/auto) to config for persistent
control over command execution behavior. Removes --local/--remote flags
from commands to simplify user workflow - no need to check server
connection status manually.
Changes:
- config.zig: Add ExecutionMode enum, execution_mode field, parsing/serialization
- mode.zig: Update detect() to check execution_mode == .local
- init.zig: Add --mode flag (local/remote/auto) for setting during init
- info.zig: Use config execution_mode, removed --local/--remote flags
- run.zig: Use config execution_mode, removed --local/--remote flags
- exec/mod.zig: Use config execution_mode, removed --local/--remote flags
Priority order for determining execution mode:
1. Config setting (execution_mode: local/remote/auto)
2. Auto-detect only if config is 'auto'
Users set mode once during init:
ml init --mode=local # Always use local
ml init --mode=remote # Always use remote
ml init --mode=auto # Auto-detect (default)
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 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.
