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* AI Discovery Engine
* Schema-aware intelligence for discovering relevant cubes and fields
*/
import type { CubeMetadata } from '../types/metadata'
import { QUERY_SCHEMAS } from './schemas'
/**
* Discovery result for a cube
*/
export interface CubeDiscoveryResult {
cube: string
title: string
description?: string
relevanceScore: number
matchedOn: ('name' | 'title' | 'description' | 'exampleQuestions' | 'measures' | 'dimensions')[]
suggestedMeasures: string[]
suggestedDimensions: string[]
// Analysis capabilities
capabilities: {
query: true
funnel: boolean
flow: boolean
retention: boolean
}
// Config for advanced modes (only present if capabilities exist)
analysisConfig?: {
candidateBindingKeys: Array<{
dimension: string
description?: string
}>
candidateTimeDimensions: Array<{
dimension: string
description?: string
}>
candidateEventDimensions: Array<{
dimension: string
description?: string
}>
}
// Hints for AI on next steps
hints?: string[]
// Query schemas (included when capabilities.funnel/flow/retention is true)
querySchemas?: typeof QUERY_SCHEMAS
}
/**
* Discovery request options
*/
export interface DiscoveryOptions {
/** Topic or intent to search for */
topic?: string
/** Natural language intent */
intent?: string
/** Maximum number of results */
limit?: number
/** Minimum relevance score (0-1) */
minScore?: number
}
/**
* Calculate Levenshtein distance between two strings
*/
function levenshteinDistance(a: string, b: string): number {
const matrix: number[][] = []
for (let i = 0; i <= b.length; i++) {
matrix[i] = [i]
}
for (let j = 0; j <= a.length; j++) {
matrix[0][j] = j
}
for (let i = 1; i <= b.length; i++) {
for (let j = 1; j <= a.length; j++) {
if (b.charAt(i - 1) === a.charAt(j - 1)) {
matrix[i][j] = matrix[i - 1][j - 1]
} else {
matrix[i][j] = Math.min(
matrix[i - 1][j - 1] + 1,
matrix[i][j - 1] + 1,
matrix[i - 1][j] + 1
)
}
}
}
return matrix[b.length][a.length]
}
/**
* Calculate fuzzy match score between two strings (0-1, higher is better)
*/
function fuzzyMatchScore(query: string, target: string): number {
const q = query.toLowerCase().trim()
const t = target.toLowerCase().trim()
// Exact match
if (q === t) return 1.0
// Contains match
if (t.includes(q)) return 0.9
// Word boundary match
const words = t.split(/[\s_-]+/)
for (const word of words) {
Iif (word === q) return 0.85
Iif (word.startsWith(q)) return 0.75
}
// Levenshtein-based fuzzy match
const distance = levenshteinDistance(q, t)
const maxLen = Math.max(q.length, t.length)
const similarity = 1 - distance / maxLen
return similarity > 0.5 ? similarity * 0.7 : 0
}
/**
* Match a query against an array of strings (names, synonyms, etc.)
*/
function matchAgainstArray(query: string, targets: string[]): number {
let bestScore = 0
for (const target of targets) {
const score = fuzzyMatchScore(query, target)
if (score > bestScore) {
bestScore = score
}
}
return bestScore
}
/**
* Extract keywords from a natural language query
*/
function extractKeywords(text: string): string[] {
// Common stop words to filter out
const stopWords = new Set([
'a', 'an', 'the', 'is', 'are', 'was', 'were', 'be', 'been', 'being',
'have', 'has', 'had', 'do', 'does', 'did', 'will', 'would', 'could',
'should', 'may', 'might', 'must', 'can', 'and', 'or', 'but', 'if',
'then', 'else', 'when', 'where', 'why', 'how', 'what', 'which', 'who',
'this', 'that', 'these', 'those', 'i', 'me', 'my', 'we', 'our', 'you',
'your', 'he', 'she', 'it', 'they', 'them', 'their', 'in', 'on', 'at',
'to', 'for', 'of', 'with', 'by', 'from', 'up', 'down', 'out', 'over',
'under', 'about', 'into', 'through', 'during', 'before', 'after',
'above', 'below', 'between', 'show', 'me', 'get', 'find', 'list',
'give', 'tell', 'display', 'want', 'need', 'see', 'know'
])
return text
.toLowerCase()
.replace(/[^\w\s]/g, ' ')
.split(/\s+/)
.filter(word => word.length > 2 && !stopWords.has(word))
}
/**
* Score a cube against discovery criteria
*/
function scoreCube(
cube: CubeMetadata,
keywords: string[]
): { score: number; matchedOn: CubeDiscoveryResult['matchedOn']; suggestedMeasures: string[]; suggestedDimensions: string[] } {
let totalScore = 0
const matchedOn: CubeDiscoveryResult['matchedOn'] = []
const measureScores: Map<string, number> = new Map()
const dimensionScores: Map<string, number> = new Map()
for (const keyword of keywords) {
// Match cube name
const nameScore = fuzzyMatchScore(keyword, cube.name)
if (nameScore > 0.5) {
totalScore += nameScore * 2 // Weight cube name matches higher
Eif (!matchedOn.includes('name')) matchedOn.push('name')
}
// Match cube title
const titleScore = fuzzyMatchScore(keyword, cube.title)
if (titleScore > 0.5) {
totalScore += titleScore * 1.5
Eif (!matchedOn.includes('title')) matchedOn.push('title')
}
// Match cube description
if (cube.description) {
const descScore = fuzzyMatchScore(keyword, cube.description)
if (descScore > 0.3) {
totalScore += descScore
if (!matchedOn.includes('description')) matchedOn.push('description')
}
}
// Match example questions
if (cube.exampleQuestions) {
for (const question of cube.exampleQuestions) {
const qScore = fuzzyMatchScore(keyword, question)
if (qScore > 0.3) {
totalScore += qScore * 1.5 // Example questions are valuable
if (!matchedOn.includes('exampleQuestions')) matchedOn.push('exampleQuestions')
}
}
}
// Match measures
for (const measure of cube.measures) {
let measureScore = 0
// Match measure name (without cube prefix)
const measureName = measure.name.split('.').pop() || measure.name
measureScore = Math.max(measureScore, fuzzyMatchScore(keyword, measureName))
// Match measure title
measureScore = Math.max(measureScore, fuzzyMatchScore(keyword, measure.title))
// Match measure description
if (measure.description) {
measureScore = Math.max(measureScore, fuzzyMatchScore(keyword, measure.description) * 0.8)
}
// Match measure synonyms
if (measure.synonyms) {
measureScore = Math.max(measureScore, matchAgainstArray(keyword, measure.synonyms))
}
if (measureScore > 0.4) {
totalScore += measureScore
if (!matchedOn.includes('measures')) matchedOn.push('measures')
const currentScore = measureScores.get(measure.name) || 0
measureScores.set(measure.name, Math.max(currentScore, measureScore))
}
}
// Match dimensions
for (const dimension of cube.dimensions) {
let dimScore = 0
// Match dimension name (without cube prefix)
const dimName = dimension.name.split('.').pop() || dimension.name
dimScore = Math.max(dimScore, fuzzyMatchScore(keyword, dimName))
// Match dimension title
dimScore = Math.max(dimScore, fuzzyMatchScore(keyword, dimension.title))
// Match dimension description
Iif (dimension.description) {
dimScore = Math.max(dimScore, fuzzyMatchScore(keyword, dimension.description) * 0.8)
}
// Match dimension synonyms
if (dimension.synonyms) {
dimScore = Math.max(dimScore, matchAgainstArray(keyword, dimension.synonyms))
}
if (dimScore > 0.4) {
totalScore += dimScore
if (!matchedOn.includes('dimensions')) matchedOn.push('dimensions')
const currentScore = dimensionScores.get(dimension.name) || 0
dimensionScores.set(dimension.name, Math.max(currentScore, dimScore))
}
}
}
// Normalize score
const normalizedScore = Math.min(1, totalScore / (keywords.length * 2))
// Get top suggested measures and dimensions
const suggestedMeasures = Array.from(measureScores.entries())
.sort((a, b) => b[1] - a[1])
.slice(0, 5)
.map(([name]) => name)
const suggestedDimensions = Array.from(dimensionScores.entries())
.sort((a, b) => b[1] - a[1])
.slice(0, 5)
.map(([name]) => name)
return { score: normalizedScore, matchedOn, suggestedMeasures, suggestedDimensions }
}
/**
* Detect analysis capabilities from cube metadata
*/
function detectCapabilities(cube: CubeMetadata): CubeDiscoveryResult['capabilities'] {
// Check if cube has explicit eventStream meta
const hasEventStream = !!(cube.meta?.eventStream)
// Check if cube has time dimensions (needed for analysis modes)
const hasTimeDimension = cube.dimensions.some(d => d.type === 'time')
// Check for potential binding keys (dimensions that could identify entities)
const hasPotentialBindingKey = cube.dimensions.some(d =>
d.name.toLowerCase().includes('id') ||
d.type === 'number' ||
(cube.meta?.eventStream?.bindingKey && d.name === cube.meta.eventStream.bindingKey)
)
// Analysis modes available if explicit eventStream OR has needed dimensions
const supportsAnalysisModes = hasEventStream || (hasTimeDimension && hasPotentialBindingKey)
return {
query: true,
funnel: supportsAnalysisModes,
flow: supportsAnalysisModes,
retention: supportsAnalysisModes
}
}
/**
* Build analysis config with candidate dimensions
*/
function buildAnalysisConfig(cube: CubeMetadata): CubeDiscoveryResult['analysisConfig'] | undefined {
const capabilities = detectCapabilities(cube)
// Only include config if analysis modes are available
if (!capabilities.funnel && !capabilities.flow && !capabilities.retention) {
return undefined
}
// Candidate binding keys: explicit from meta, or inferred from dimension names
const candidateBindingKeys: Array<{ dimension: string; description?: string }> = []
// Check explicit eventStream config first
if (cube.meta?.eventStream?.bindingKey) {
const bindingDim = cube.dimensions.find(d => d.name === cube.meta?.eventStream?.bindingKey)
candidateBindingKeys.push({
dimension: cube.meta.eventStream.bindingKey,
description: bindingDim?.description || 'Configured binding key'
})
}
// Add dimensions with 'id' in name as candidates
for (const dim of cube.dimensions) {
const dimShortName = dim.name.split('.').pop()?.toLowerCase() || ''
if (dimShortName.includes('id') && !candidateBindingKeys.some(c => c.dimension === dim.name)) {
candidateBindingKeys.push({
dimension: dim.name,
description: dim.description || `Potential entity identifier`
})
}
}
// Candidate time dimensions
const candidateTimeDimensions: Array<{ dimension: string; description?: string }> = []
// Check explicit eventStream config first
if (cube.meta?.eventStream?.timeDimension) {
const timeDim = cube.dimensions.find(d => d.name === cube.meta?.eventStream?.timeDimension)
candidateTimeDimensions.push({
dimension: cube.meta.eventStream.timeDimension,
description: timeDim?.description || 'Configured time dimension'
})
}
// Add all time dimensions as candidates
for (const dim of cube.dimensions) {
if (dim.type === 'time' && !candidateTimeDimensions.some(c => c.dimension === dim.name)) {
candidateTimeDimensions.push({
dimension: dim.name,
description: dim.description
})
}
}
// Candidate event dimensions (string dimensions that could represent event types)
const candidateEventDimensions: Array<{ dimension: string; description?: string }> = []
for (const dim of cube.dimensions) {
const dimShortName = dim.name.split('.').pop()?.toLowerCase() || ''
if (dim.type === 'string' && (
dimShortName.includes('type') ||
dimShortName.includes('event') ||
dimShortName.includes('status') ||
dimShortName.includes('state') ||
dimShortName.includes('action')
)) {
candidateEventDimensions.push({
dimension: dim.name,
description: dim.description || 'Potential event type dimension'
})
}
}
return {
candidateBindingKeys,
candidateTimeDimensions,
candidateEventDimensions
}
}
/**
* Generate hints for AI on next steps
*/
function generateHints(_cube: CubeMetadata, analysisConfig?: CubeDiscoveryResult['analysisConfig']): string[] {
const hints: string[] = []
if (!analysisConfig) {
return hints
}
// Hint about choosing binding key if multiple options
if (analysisConfig.candidateBindingKeys.length > 1) {
hints.push('Choose bindingKey based on what entity to track through the analysis')
}
// Hint about discovering event types
if (analysisConfig.candidateEventDimensions.length > 0) {
const eventDim = analysisConfig.candidateEventDimensions[0].dimension
hints.push(`Query ${eventDim} dimension to discover available values for funnel steps`)
}
// General workflow hint
hints.push('Use /mcp/load with a standard query to discover dimension values before building analysis queries')
return hints
}
/**
* Discover relevant cubes based on topic or intent
*/
export function discoverCubes(
metadata: CubeMetadata[],
options: DiscoveryOptions = {}
): CubeDiscoveryResult[] {
const { topic, intent, limit = 10, minScore = 0.1 } = options
// Combine topic and intent into search text
const searchText = [topic, intent].filter(Boolean).join(' ')
if (!searchText.trim()) {
// Return all cubes with basic info if no search criteria
return metadata.slice(0, limit).map(cube => {
const capabilities = detectCapabilities(cube)
const analysisConfig = buildAnalysisConfig(cube)
const hints = generateHints(cube, analysisConfig)
const hasAnalysisModes = capabilities.funnel || capabilities.flow || capabilities.retention
return {
cube: cube.name,
title: cube.title,
description: cube.description,
relevanceScore: 1,
matchedOn: [] as CubeDiscoveryResult['matchedOn'],
suggestedMeasures: cube.measures.slice(0, 5).map(m => m.name),
suggestedDimensions: cube.dimensions.slice(0, 5).map(d => d.name),
capabilities,
analysisConfig,
hints: hints.length > 0 ? hints : undefined,
querySchemas: hasAnalysisModes ? QUERY_SCHEMAS : undefined
}
})
}
// Extract keywords from search text
const keywords = extractKeywords(searchText)
Iif (keywords.length === 0) {
return []
}
// Score each cube
const results: CubeDiscoveryResult[] = []
for (const cube of metadata) {
const { score, matchedOn, suggestedMeasures, suggestedDimensions } = scoreCube(cube, keywords)
if (score >= minScore) {
const capabilities = detectCapabilities(cube)
const analysisConfig = buildAnalysisConfig(cube)
const hints = generateHints(cube, analysisConfig)
// Only include schemas if analysis modes are available
const hasAnalysisModes = capabilities.funnel || capabilities.flow || capabilities.retention
results.push({
cube: cube.name,
title: cube.title,
description: cube.description,
relevanceScore: score,
matchedOn,
suggestedMeasures,
suggestedDimensions,
capabilities,
analysisConfig,
hints: hints.length > 0 ? hints : undefined,
querySchemas: hasAnalysisModes ? QUERY_SCHEMAS : undefined
})
}
}
// Sort by relevance and limit
return results
.sort((a, b) => b.relevanceScore - a.relevanceScore)
.slice(0, limit)
}
/**
* Find the best matching field across all cubes
*/
export function findBestFieldMatch(
metadata: CubeMetadata[],
fieldName: string,
fieldType?: 'measure' | 'dimension'
): { field: string; cube: string; score: number; type: 'measure' | 'dimension' } | null {
let bestMatch: { field: string; cube: string; score: number; type: 'measure' | 'dimension' } | null = null
for (const cube of metadata) {
// Check measures
Iif (!fieldType || fieldType === 'measure') {
for (const measure of cube.measures) {
const measureName = measure.name.split('.').pop() || measure.name
let score = fuzzyMatchScore(fieldName, measureName)
score = Math.max(score, fuzzyMatchScore(fieldName, measure.title))
if (measure.synonyms) {
score = Math.max(score, matchAgainstArray(fieldName, measure.synonyms))
}
if (score > 0.5 && (!bestMatch || score > bestMatch.score)) {
bestMatch = { field: measure.name, cube: cube.name, score, type: 'measure' }
}
}
}
// Check dimensions
Eif (!fieldType || fieldType === 'dimension') {
for (const dimension of cube.dimensions) {
const dimName = dimension.name.split('.').pop() || dimension.name
let score = fuzzyMatchScore(fieldName, dimName)
score = Math.max(score, fuzzyMatchScore(fieldName, dimension.title))
if (dimension.synonyms) {
score = Math.max(score, matchAgainstArray(fieldName, dimension.synonyms))
}
if (score > 0.5 && (!bestMatch || score > bestMatch.score)) {
bestMatch = { field: dimension.name, cube: cube.name, score, type: 'dimension' }
}
}
}
}
return bestMatch
}
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