Move configuration types to queue/mod.zig:
- TrackingConfig with MLflow, TensorBoard, Wandb sub-configs
- QueueOptions with all queue-related options
queue.zig now re-exports from queue/mod.zig for backward compatibility.
Build passes successfully.
Update command structure with improved implementations:
- exec.zig: consolidated command execution
- queue.zig: improved job queuing with narrative support
- run.zig: enhanced local run execution
- dataset.zig, dataset_hash.zig: improved dataset management
Part of CLI hardening for better UX and reliability.
Replace space-padding with consistent tab (\t) alignment in all printUsage() functions.
Add ligature-friendly ASCII symbols:
- => for results/outcomes (renders as ⇒ with ligatures)
- ~> for modifications/changes (renders as ~> with ligatures)
- -> for state transitions (renders as → with ligatures)
- [OK] / [FAIL] for status indicators
All symbols use ASCII 32-126 for xargs-safe, copy-pasteable output.
- queue.zig: Add --rerun <run_id> flag to re-queue completed local runs
- Requires server connection, rejects in offline mode with clear error
- HandleRerun function sends rerun request via WebSocket
- sync.zig: Rewrite for WebSocket experiment sync protocol
- Queries unsynced runs from SQLite ml_runs table
- Builds sync JSON with metrics and params
- Sends sync_run message, waits for sync_ack response
- MarkRunSynced updates synced flag in database
- watch.zig: Add --sync flag for continuous experiment sync
- Auto-sync runs to server every 30 seconds when online
- Mode detection with offline error handling
Add comprehensive research context tracking to jobs:
- Narrative fields: hypothesis, context, intent, expected_outcome
- Experiment groups and tags for organization
- Run comparison (compare command) for diff analysis
- Run search (find command) with criteria filtering
- Run export (export command) for data portability
- Outcome setting (outcome command) for experiment validation
Update queue and requeue commands to support narrative fields.
Add narrative validation to manifest validator.
Add WebSocket handlers for compare, find, export, and outcome operations.
Includes E2E tests for phase 2 features.
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).
- 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.
