fetch_ml/internal/worker/worker.go

// Package worker provides the ML task worker implementation
package worker

import (
	"context"
	"net/http"
	"time"

	"github.com/jfraeys/fetch_ml/internal/jupyter"
	"github.com/jfraeys/fetch_ml/internal/logging"
	"github.com/jfraeys/fetch_ml/internal/metrics"
	"github.com/jfraeys/fetch_ml/internal/worker/executor"
	"github.com/jfraeys/fetch_ml/internal/worker/lifecycle"
)

// MLServer wraps network.SSHClient for backward compatibility.
type MLServer struct {
	SSHClient interface{}
}

// JupyterManager interface for jupyter service management
type JupyterManager interface {
	StartService(ctx context.Context, req *jupyter.StartRequest) (*jupyter.JupyterService, error)
	StopService(ctx context.Context, serviceID string) error
	RemoveService(ctx context.Context, serviceID string, purge bool) error
	RestoreWorkspace(ctx context.Context, name string) (string, error)
	ListServices() []*jupyter.JupyterService
	ListInstalledPackages(ctx context.Context, serviceName string) ([]jupyter.InstalledPackage, error)
}

// isValidName validates that input strings contain only safe characters.
func isValidName(input string) bool {
	return len(input) > 0 && len(input) < 256
}

// NewMLServer creates a new ML server connection.
func NewMLServer(cfg *Config) (*MLServer, error) {
	return &MLServer{}, nil
}

// Worker represents an ML task worker with composed dependencies.
type Worker struct {
	id     string
	config *Config
	logger *logging.Logger

	// Composed dependencies from previous phases
	runLoop    *lifecycle.RunLoop
	runner     *executor.JobRunner
	metrics    *metrics.Metrics
	metricsSrv *http.Server
	health     *lifecycle.HealthMonitor

	// Legacy fields for backward compatibility during migration
	jupyter JupyterManager
}

// Start begins the worker's main processing loop.
func (w *Worker) Start() {
	w.logger.Info("worker starting",
		"worker_id", w.id,
		"max_concurrent", w.config.MaxWorkers)

	w.health.RecordHeartbeat()
	w.runLoop.Start()
}

// Stop gracefully shuts down the worker immediately.
func (w *Worker) Stop() {
	w.logger.Info("worker stopping", "worker_id", w.id)
	w.runLoop.Stop()

	if w.metricsSrv != nil {
		ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
		defer cancel()
		if err := w.metricsSrv.Shutdown(ctx); err != nil {
			w.logger.Warn("metrics server shutdown error", "error", err)
		}
	}

	w.logger.Info("worker stopped", "worker_id", w.id)
}

// Shutdown performs a graceful shutdown with timeout.
func (w *Worker) Shutdown() error {
	w.logger.Info("starting graceful shutdown", "worker_id", w.id)

	w.runLoop.Stop()

	if w.metricsSrv != nil {
		ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
		defer cancel()
		if err := w.metricsSrv.Shutdown(ctx); err != nil {
			w.logger.Warn("metrics server shutdown error", "error", err)
		}
	}

	w.logger.Info("worker shut down gracefully", "worker_id", w.id)
	return nil
}

// IsHealthy returns true if the worker is healthy.
func (w *Worker) IsHealthy() bool {
	return w.health.IsHealthy(5 * time.Minute)
}

// GetMetrics returns current worker metrics.
func (w *Worker) GetMetrics() map[string]any {
	stats := w.metrics.GetStats()
	stats["worker_id"] = w.id
	stats["max_workers"] = w.config.MaxWorkers
	stats["healthy"] = w.IsHealthy()
	return stats
}

// GetID returns the worker ID.
func (w *Worker) GetID() string {
	return w.id
}

// runningCount returns the number of currently running tasks
func (w *Worker) runningCount() int {
	return 0 // Placeholder - will be implemented with runLoop integration
}

func (w *Worker) getGPUDetector() GPUDetector {
	factory := &GPUDetectorFactory{}
	return factory.CreateDetector(w.config)
}