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import path from 'path'
/**
* Shared training data deletion utilities.
*
* All training data deletion should go through these functions to ensure
* deletions are recorded in tombstone files (preventing re-sync from production).
*/
// Base paths for training data
const VISION_TRAINING_DIR = path.join(process.cwd(), 'data/vision-training')
const COLUMN_CLASSIFIER_DIR = path.join(VISION_TRAINING_DIR, 'collected')
const BOUNDARY_DETECTOR_DIR = path.join(VISION_TRAINING_DIR, 'boundary-frames')
// Tombstone file paths
const COLUMN_CLASSIFIER_TOMBSTONE = path.join(COLUMN_CLASSIFIER_DIR, '.deleted')
const BOUNDARY_DETECTOR_TOMBSTONE = path.join(BOUNDARY_DETECTOR_DIR, '.deleted')
export interface DeletionResult {
success: boolean
/** True if file was deleted (false if it didn't exist) */
deleted: boolean
/** True if deletion was recorded to tombstone */
tombstoneRecorded: boolean
/** Error message if something went wrong */
error?: string
}
/**
* Record a deletion to a tombstone file.
*
* The tombstone file is a simple newline-delimited list of relative paths.
* These paths are excluded during rsync from production.
*
* @param tombstonePath - Path to the tombstone file
* @param relativePath - Relative path of the deleted file (e.g., "3/filename.png")
* @returns True if recorded successfully, false otherwise
*/
async function recordToTombstone(tombstonePath: string, relativePath: string): Promise<boolean> {
try {
// Ensure parent directory exists
await fs.mkdir(path.dirname(tombstonePath), { recursive: true })
// Append to tombstone file
await fs.appendFile(tombstonePath, `${relativePath}\n`)
return true
} catch (error) {
console.error('[trainingDataDeletion] Failed to record to tombstone:', error)
return false
}
}
/**
* Delete a column classifier training sample.
*
* Deletes the PNG file and records the deletion to the tombstone file
* to prevent re-syncing from production.
*
* @param digit - The digit label (0-9)
* @param filename - The filename (e.g., "1234567890_player_session_col0_uuid.png")
*/
export async function deleteColumnClassifierSample(
digit: number,
filename: string
): Promise<DeletionResult> {
// Validate inputs
if (!Number.isInteger(digit) || digit < 0 || digit > 9) {
return {
success: false,
deleted: false,
tombstoneRecorded: false,
error: 'Invalid digit',
}
}
if (!filename || filename.includes('..') || filename.includes('/') || filename.includes('\\')) {
return {
success: false,
deleted: false,
tombstoneRecorded: false,
error: 'Invalid filename',
}
}
if (!filename.endsWith('.png')) {
return {
success: false,
deleted: false,
tombstoneRecorded: false,
error: 'Filename must end with .png',
}
}
const filePath = path.join(COLUMN_CLASSIFIER_DIR, String(digit), filename)
const relativePath = `${digit}/${filename}`
let deleted = false
let tombstoneRecorded = false
// Try to delete the file
try {
await fs.unlink(filePath)
deleted = true
} catch (error) {
if ((error as NodeJS.ErrnoException).code === 'ENOENT') {
// File doesn't exist - that's fine, still record to tombstone
// (in case it exists on production)
} else {
return {
success: false,
deleted: false,
tombstoneRecorded: false,
error: `Failed to delete file: ${(error as Error).message}`,
}
}
}
// Record to tombstone (even if file didn't exist locally - it might exist on production)
tombstoneRecorded = await recordToTombstone(COLUMN_CLASSIFIER_TOMBSTONE, relativePath)
return {
success: true,
deleted,
tombstoneRecorded,
error: tombstoneRecorded ? undefined : 'Warning: deletion not recorded to tombstone',
}
}
/**
* Delete a boundary detector training sample.
*
* Deletes the image file (PNG or JPG) and its JSON annotation,
* and records the deletion to the tombstone file.
*
* @param deviceId - The device subdirectory (e.g., "default", "passive-practice-remote")
* @param baseName - The base filename without extension (e.g., "1234567890_abc123")
*/
export async function deleteBoundaryDetectorSample(
deviceId: string,
baseName: string
): Promise<DeletionResult> {
// Validate inputs
if (!deviceId || deviceId.includes('..') || deviceId.includes('/') || deviceId.includes('\\')) {
return {
success: false,
deleted: false,
tombstoneRecorded: false,
error: 'Invalid deviceId',
}
}
if (!baseName || baseName.includes('..') || baseName.includes('/') || baseName.includes('\\')) {
return {
success: false,
deleted: false,
tombstoneRecorded: false,
error: 'Invalid baseName',
}
}
const deviceDir = path.join(BOUNDARY_DETECTOR_DIR, deviceId)
const pngPath = path.join(deviceDir, `${baseName}.png`)
const jpgPath = path.join(deviceDir, `${baseName}.jpg`)
const jsonPath = path.join(deviceDir, `${baseName}.json`)
let deleted = false
let imageExtension: 'png' | 'jpg' | null = null
// Try to delete PNG version
try {
await fs.unlink(pngPath)
deleted = true
imageExtension = 'png'
} catch (error) {
if ((error as NodeJS.ErrnoException).code !== 'ENOENT') {
return {
success: false,
deleted: false,
tombstoneRecorded: false,
error: `Failed to delete PNG: ${(error as Error).message}`,
}
}
}
// Try to delete JPG version
try {
await fs.unlink(jpgPath)
deleted = true
imageExtension = 'jpg'
} catch (error) {
if ((error as NodeJS.ErrnoException).code !== 'ENOENT') {
return {
success: false,
deleted: false,
tombstoneRecorded: false,
error: `Failed to delete JPG: ${(error as Error).message}`,
}
}
}
// Try to delete JSON annotation
try {
await fs.unlink(jsonPath)
deleted = true
} catch (error) {
if ((error as NodeJS.ErrnoException).code !== 'ENOENT') {
// Log but don't fail - the image is the primary file
console.error('[trainingDataDeletion] Failed to delete JSON:', error)
}
}
// Record to tombstone
// We record both PNG and JPG patterns to be safe
let tombstoneRecorded = false
const pngRelativePath = `${deviceId}/${baseName}.png`
const jpgRelativePath = `${deviceId}/${baseName}.jpg`
// Record the actual extension if known, otherwise record both
if (imageExtension === 'png') {
tombstoneRecorded = await recordToTombstone(BOUNDARY_DETECTOR_TOMBSTONE, pngRelativePath)
} else if (imageExtension === 'jpg') {
tombstoneRecorded = await recordToTombstone(BOUNDARY_DETECTOR_TOMBSTONE, jpgRelativePath)
} else {
// Unknown extension - record both to be safe
const pngRecorded = await recordToTombstone(BOUNDARY_DETECTOR_TOMBSTONE, pngRelativePath)
const jpgRecorded = await recordToTombstone(BOUNDARY_DETECTOR_TOMBSTONE, jpgRelativePath)
tombstoneRecorded = pngRecorded || jpgRecorded
}
return {
success: true,
deleted,
tombstoneRecorded,
error: tombstoneRecorded ? undefined : 'Warning: deletion not recorded to tombstone',
}
}
/**
* Read the list of deleted files from a tombstone.
*
* @param modelType - Which model's tombstone to read
* @returns Set of relative paths that have been deleted
*/
export async function readTombstone(
modelType: 'column-classifier' | 'boundary-detector'
): Promise<Set<string>> {
const tombstonePath =
modelType === 'column-classifier' ? COLUMN_CLASSIFIER_TOMBSTONE : BOUNDARY_DETECTOR_TOMBSTONE
try {
const content = await fs.readFile(tombstonePath, 'utf-8')
const lines = content.split('\n').filter((line) => line.trim())
return new Set(lines)
} catch {
// File doesn't exist yet - no deletions recorded
return new Set()
}
}
/**
* Initialize a tombstone file if it doesn't exist.
*
* This should be called at the start of a sync operation to ensure
* the tombstone file exists. This prevents the scenario where:
* 1. User deletes files locally before ever syncing
* 2. User syncs from production
* 3. Deleted files reappear because there was no tombstone to record them
*
* By creating the tombstone file on first sync, we ensure that any
* subsequent deletions will be properly recorded.
*
* @param modelType - Which model's tombstone to initialize
* @returns True if initialized (created or already existed), false on error
*/
export async function initializeTombstone(
modelType: 'column-classifier' | 'boundary-detector'
): Promise<boolean> {
const tombstonePath =
modelType === 'column-classifier' ? COLUMN_CLASSIFIER_TOMBSTONE : BOUNDARY_DETECTOR_TOMBSTONE
try {
// Check if file already exists
try {
await fs.access(tombstonePath)
// File exists, nothing to do
return true
} catch {
// File doesn't exist, create it
}
// Ensure parent directory exists
await fs.mkdir(path.dirname(tombstonePath), { recursive: true })
// Create empty tombstone file
await fs.writeFile(tombstonePath, '')
console.log(`[trainingDataDeletion] Initialized tombstone: ${tombstonePath}`)
return true
} catch (error) {
console.error('[trainingDataDeletion] Failed to initialize tombstone:', error)
return false
}
}
export interface PruneTombstoneResult {
success: boolean
/** Number of entries before pruning */
entriesBefore: number
/** Number of entries after pruning */
entriesAfter: number
/** Number of entries removed */
entriesPruned: number
/** Error message if pruning failed */
error?: string
}
/**
* Prune tombstone entries that no longer exist on production.
*
* IMPORTANT: This function requires a verified set of remote files.
* The caller MUST have successfully connected to production and retrieved
* the file list before calling this function. If SSH connection fails,
* do NOT call this function - it would incorrectly prune all entries.
*
* The pruning logic:
* - If a tombstoned file still exists on production → keep the entry
* - If a tombstoned file no longer exists on production → remove the entry
* (no point excluding a file that doesn't exist)
*
* @param modelType - Which model's tombstone to prune
* @param remoteFiles - Set of file paths that exist on production (MUST be from successful SSH)
* @returns Result with pruning statistics
*/
export async function pruneTombstone(
modelType: 'column-classifier' | 'boundary-detector',
remoteFiles: Set<string>
): Promise<PruneTombstoneResult> {
const tombstonePath =
modelType === 'column-classifier' ? COLUMN_CLASSIFIER_TOMBSTONE : BOUNDARY_DETECTOR_TOMBSTONE
try {
// Read current tombstone entries
const currentEntries = await readTombstone(modelType)
const entriesBefore = currentEntries.size
if (entriesBefore === 0) {
return {
success: true,
entriesBefore: 0,
entriesAfter: 0,
entriesPruned: 0,
}
}
// Keep only entries that still exist on production
// (if file doesn't exist on production, no need to exclude it from sync)
const entriesToKeep: string[] = []
for (const entry of currentEntries) {
if (remoteFiles.has(entry)) {
entriesToKeep.push(entry)
}
}
const entriesAfter = entriesToKeep.length
const entriesPruned = entriesBefore - entriesAfter
// Only write if something changed
if (entriesPruned > 0) {
// Write the pruned tombstone (with trailing newline if non-empty)
const content = entriesToKeep.length > 0 ? entriesToKeep.join('\n') + '\n' : ''
await fs.writeFile(tombstonePath, content)
console.log(
`[trainingDataDeletion] Pruned tombstone for ${modelType}: ` +
`${entriesPruned} entries removed, ${entriesAfter} remaining`
)
}
return {
success: true,
entriesBefore,
entriesAfter,
entriesPruned,
}
} catch (error) {
console.error('[trainingDataDeletion] Failed to prune tombstone:', error)
return {
success: false,
entriesBefore: 0,
entriesAfter: 0,
entriesPruned: 0,
error: error instanceof Error ? error.message : 'Unknown error',
}
}
}
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