2c596038b5
- Update Makefile with build-sqlite target matching rsync pattern - Fix build.zig to handle SQLite assets and dataset_hash linking - Add SQLite asset detection mirroring rsync binary detection - Update CLI README with local mode documentation - Restructure rsync assets into rsync/ subdirectory - Remove obsolete files (fix_arraylist.sh, old rsync_placeholder.bin) - Add build_rsync.sh script to fetch/build rsync from source
105 lines
2.5 KiB
Markdown
105 lines
2.5 KiB
Markdown
# ML CLI
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Fast CLI tool for managing ML experiments. Supports both **local mode** (SQLite) and **server mode** (WebSocket).
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## Quick Start
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```bash
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# 1. Build
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zig build
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# 2. Initialize local tracking (creates fetch_ml.db)
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./zig-out/bin/ml init
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# 3. Create experiment and run locally
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./zig-out/bin/ml experiment create --name "baseline"
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./zig-out/bin/ml run start --experiment <id> --name "run-1"
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./zig-out/bin/ml experiment log --run <id> --name loss --value 0.5
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./zig-out/bin/ml run finish --run <id>
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```
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## Commands
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### Local Mode Commands (SQLite)
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- `ml init` - Initialize local experiment tracking database
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- `ml experiment create --name <name>` - Create experiment locally
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- `ml experiment list` - List experiments from SQLite
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- `ml experiment log --run <id> --name <key> --value <val>` - Log metrics
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- `ml run start --experiment <id> [--name <name>]` - Start a run
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- `ml run finish --run <id>` - Mark run as finished
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- `ml run fail --run <id>` - Mark run as failed
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- `ml run list` - List all runs
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### Server Mode Commands (WebSocket)
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- `ml sync <path>` - Sync project to server
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- `ml queue <job1> [job2 ...] [--commit <id>] [--priority N] [--note <text>]` - Queue jobs
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- `ml status` - Check system/queue status
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- `ml validate <commit_id> [--json] [--task <task_id>]` - Validate provenance
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- `ml cancel <job>` - Cancel a running/queued job
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### Shared Commands (Auto-detect Mode)
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- `ml experiment log|show|list|delete` - Works in both local and server mode
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- `ml monitor` - Launch TUI (local SQLite or remote SSH)
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Notes:
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- Commands auto-detect mode from config (`sqlite://` vs `wss://`)
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- `--json` mode is designed to be pipe-friendly
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## Configuration
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### Local Mode (SQLite)
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```toml
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# .fetchml/config.toml or ~/.ml/config.toml
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tracking_uri = "sqlite://./fetch_ml.db"
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artifact_path = "./experiments/"
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sync_uri = "" # Optional: server to sync with
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```
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### Server Mode (WebSocket)
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```toml
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# ~/.ml/config.toml
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worker_host = "worker.local"
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worker_user = "mluser"
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worker_base = "/data/ml-experiments"
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worker_port = 22
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api_key = "your-api-key"
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```
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## Building
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### Development
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```bash
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cd cli
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zig build
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```
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### Production (requires SQLite in assets/)
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```bash
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cd cli
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make build-sqlite # Fetch SQLite amalgamation
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zig build prod # Build with embedded SQLite
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```
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## Install
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```bash
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# Install to system
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make install
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# Or copy binary manually
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cp zig-out/bin/ml /usr/local/bin/
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```
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## Need Help?
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- `ml --help` - Show command help
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- `ml <command> --help` - Show command-specific help
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