monitor

type Config struct {
	// Window is how often drift is judged; MinRows how many predicted rows a
	// window needs before it is.
	Window  time.Duration
	MinRows int
	// Queue bounds the observations waiting for the monitor's goroutine.
	Queue int
	// Batch and Flush bound how many logged rows wait to be written, and for
	// how long.
	Batch int
	Flush time.Duration
}

type Deps struct {
	// Logs returns the current log store; one that is not a
	// storage.MLPredictionLogStore drops logged rows, counted.
	Logs   func() any
	Stats  StatsFunc
	Notify NotifyFunc
	Logger hermod.Logger
}

type FeatureDrift struct {
	Feature string `json:"feature"`
	Kind    string `json:"kind"`
	// PSI is the population stability index of the live values against the
	// training split, over the training bins plus one bin for missing values.
	PSI    float64 `json:"psi"`
	Status string  `json:"status"`
	// NullFraction and TrainingNullFraction are the share of missing values
	// live and in training, the commonest drift there is.
	NullFraction         float64 `json:"null_fraction"`
	TrainingNullFraction float64 `json:"training_null_fraction"`
}

type Monitor struct {
	// contains filtered or unexported fields
}

type NotifyFunc func(ctx context.Context, r Report)

type Observation struct {
	// Model is the model as it was called: its live version, features and
	// monitoring settings.
	Model      storage.MLModel
	CallerKind string
	CallerID   string
	// Inputs and Outputs are the rows sent and the predictions returned, in
	// the same order.
	Inputs  []map[string]any
	Outputs []map[string]any
	Latency time.Duration
	At      time.Time
	// Recommendation is set for a call of a recommendation model, which is
	// watched by coverage and popular share rather than drift
	// (recommendations.go).
	Recommendation *RecommendationCall
}

type RecommendationCall struct {
	// Items are the ids it answered.
	Items []string
	// Fallback reports that the person or item was unknown, so the answer is
	// the popular items.
	Fallback bool
	// Catalog is how many items the model can recommend.
	Catalog int
}

type RecommendationReport struct {
	VHost       string    `json:"vhost"`
	Model       string    `json:"model"`
	Version     string    `json:"version"`
	WindowStart time.Time `json:"window_start"`
	WindowEnd   time.Time `json:"window_end"`
	// Calls is how many calls the window holds; Fallbacks how many were
	// answered with popular items.
	Calls     int64 `json:"calls"`
	Fallbacks int64 `json:"fallbacks"`
	// PopularShare is Fallbacks / Calls.
	PopularShare float64 `json:"popular_share"`
	// Recommended is how many distinct items were recommended, of Catalog;
	// Coverage is the share.
	Recommended int     `json:"recommended"`
	Catalog     int     `json:"catalog"`
	Coverage    float64 `json:"coverage"`
}

type Report struct {
	VHost       string    `json:"vhost"`
	Model       string    `json:"model"`
	Version     string    `json:"version"`
	WindowStart time.Time `json:"window_start"`
	WindowEnd   time.Time `json:"window_end"`
	// Rows is how many predicted rows the window holds.
	Rows  int64   `json:"rows"`
	Warn  float64 `json:"warn"`
	Alert float64 `json:"alert"`
	// Status is the worst of the features'.
	Status string `json:"status"`
	// Features are ordered most drifted first.
	Features []FeatureDrift `json:"features"`
}

type StatsFunc func(ctx context.Context, vhost, model, version string) (map[string]worker.FeatureStats, error)