refactor(web): begin implementation of quotient-path convergence via SearchQuotientCluster 🚂 #14949
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| /* | ||||||||
| * Keyman is copyright (C) SIL Global. MIT License. | ||||||||
| * | ||||||||
| * Created by jahorton on 2025-10-20 | ||||||||
| * | ||||||||
| * This file defines the predictive-text engine's SearchSpace class, which is used to | ||||||||
| * manage the search-space(s) for text corrections within the engine. | ||||||||
| */ | ||||||||
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| import { QueueComparator as Comparator, PriorityQueue } from '@keymanapp/web-utils'; | ||||||||
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There was a problem hiding this comment. Can we please directly use
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| import { LexicalModelTypes } from '@keymanapp/common-types'; | ||||||||
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| import { SearchNode, SearchResult } from './distance-modeler.js'; | ||||||||
| import { generateSpaceSeed, InputSegment, PathResult, SearchQuotientNode } from './search-quotient-node.js'; | ||||||||
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| const PATH_QUEUE_COMPARATOR: Comparator<SearchQuotientNode> = (a, b) => { | ||||||||
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| return a.currentCost - b.currentCost; | ||||||||
| } | ||||||||
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| // The set of search spaces corresponding to the same 'context' for search. | ||||||||
| // Whenever a wordbreak boundary is crossed, a new instance should be made. | ||||||||
| export class SearchQuotientCluster implements SearchQuotientNode { | ||||||||
| // While most functions can be done directly from SearchSpace, merging and splitting will need access | ||||||||
| // to SearchPath-specific members. It's also cleaner to not allow nested SearchClusters while we | ||||||||
| // haven't worked out support for such a scenario. | ||||||||
| private selectionQueue: PriorityQueue<SearchQuotientNode> = new PriorityQueue(PATH_QUEUE_COMPARATOR); | ||||||||
| readonly spaceId: number; | ||||||||
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| // We use an array and not a PriorityQueue b/c batch-heapifying at a single point in time | ||||||||
| // is cheaper than iteratively building a priority queue. | ||||||||
| /** | ||||||||
| * This tracks all paths that have reached the end of a viable input-matching path - even | ||||||||
| * those of lower cost that produce the same correction as other paths. | ||||||||
| * | ||||||||
| * When new input is received, its entries are then used to append edges to the path in order | ||||||||
| * to find potential paths to reach a new viable end. | ||||||||
| */ | ||||||||
| private completedPaths?: SearchNode[] = []; | ||||||||
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| /** | ||||||||
| * Acts as a Map that prevents duplicating a correction-search path if reached | ||||||||
| * more than once. | ||||||||
| */ | ||||||||
| protected get processedEdgeSet(): {[pathKey: string]: boolean} { | ||||||||
| return this._processedEdgeSet; | ||||||||
| } | ||||||||
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| private _processedEdgeSet?: {[pathKey: string]: boolean} = {}; | ||||||||
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| /** | ||||||||
| * Provides a heuristic for the base cost at each depth if the best | ||||||||
| * individual input were taken at that level. | ||||||||
| */ | ||||||||
| readonly lowestPossibleSingleCost: number; | ||||||||
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| /** | ||||||||
| * Constructs a fresh SearchSpace instance for used in predictive-text correction | ||||||||
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| * and suggestion searches. | ||||||||
| * @param baseSpaceId | ||||||||
| * @param model | ||||||||
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| */ | ||||||||
| constructor(inboundPaths: SearchQuotientNode[]) { | ||||||||
| if(inboundPaths.length == 0) { | ||||||||
| throw new Error("SearchCluster requires an array with at least one SearchPath"); | ||||||||
| } | ||||||||
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| let lowestPossibleSingleCost = Number.POSITIVE_INFINITY; | ||||||||
| const firstPath = inboundPaths[0]; | ||||||||
| const inputCount = firstPath.inputCount; | ||||||||
| const codepointLength = firstPath.codepointLength; | ||||||||
| const sourceRangeKey = firstPath.sourceRangeKey; | ||||||||
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| for(let path of inboundPaths) { | ||||||||
| if(path.inputCount != inputCount || path.codepointLength != codepointLength) { | ||||||||
| throw new Error(`SearchPath does not share same properties as others in the cluster: inputCount ${path.inputCount} vs ${inputCount}, codepointLength ${path.codepointLength} vs ${codepointLength}`); | ||||||||
| } | ||||||||
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| // If there's a source-range key mismatch - via mismatch in count or in actual ID, we have an error. | ||||||||
| if(path.sourceRangeKey != sourceRangeKey) { | ||||||||
| throw new Error(`SearchPath does not share the same source identifiers as others in the cluster`); | ||||||||
| } | ||||||||
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| lowestPossibleSingleCost = Math.min(lowestPossibleSingleCost, path.lowestPossibleSingleCost); | ||||||||
| } | ||||||||
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| this.spaceId = generateSpaceSeed(); | ||||||||
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| this.lowestPossibleSingleCost = lowestPossibleSingleCost; | ||||||||
| this.completedPaths = inboundPaths.flatMap(p => p.previousResults).map(r => r.node); | ||||||||
| this.selectionQueue.enqueueAll(inboundPaths); | ||||||||
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| return; | ||||||||
| } | ||||||||
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| public get inputCount(): number { | ||||||||
| return this.selectionQueue.peek()?.inputCount ?? 0; | ||||||||
| } | ||||||||
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| public get bestExample(): {text: string, p: number} { | ||||||||
| const bestPrefixes = this.selectionQueue.toArray().map(p => p.bestExample); | ||||||||
| return bestPrefixes.reduce((max, curr) => max.p < curr.p ? curr : max); | ||||||||
| } | ||||||||
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| public get parents(): SearchQuotientNode[] { | ||||||||
| return this.selectionQueue.toArray().slice(); | ||||||||
| } | ||||||||
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| increaseMaxEditDistance() { | ||||||||
| // By extracting the entries from the priority queue and increasing distance outside of it as a batch job, | ||||||||
| // we get an O(N) implementation, rather than the O(N log N) that would result from maintaining the original queue. | ||||||||
| const entries = this.selectionQueue.toArray(); | ||||||||
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| entries.forEach((path) => path.increaseMaxEditDistance()); | ||||||||
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| // Since we just modified the stored instances, and the costs may have shifted, we need to re-heapify. | ||||||||
| this.selectionQueue = new PriorityQueue<SearchQuotientNode>(PATH_QUEUE_COMPARATOR, entries.slice()); | ||||||||
| } | ||||||||
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| /** | ||||||||
| * When true, this indicates that the currently-represented portion of context | ||||||||
| * has fat-finger data available, which itself indicates that the user has | ||||||||
| * corrections enabled. | ||||||||
| */ | ||||||||
| get correctionsEnabled(): boolean { | ||||||||
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| const paths = this.selectionQueue.toArray(); | ||||||||
| // When corrections are disabled, the Web engine will only provide individual Transforms | ||||||||
| // for an input, not a distribution. No distributions means we shouldn't do corrections. | ||||||||
| return !!paths.find(p => p.correctionsEnabled); | ||||||||
| } | ||||||||
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| public get currentCost(): number { | ||||||||
| return this.selectionQueue.peek()?.currentCost ?? Number.POSITIVE_INFINITY; | ||||||||
| } | ||||||||
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| /** | ||||||||
| * Retrieves the lowest-cost / lowest-distance edge from the selection queue, | ||||||||
| * checks its validity as a correction to the input text, and reports on what | ||||||||
| * sort of result the edge's destination node represents. | ||||||||
| * @returns | ||||||||
| */ | ||||||||
| public handleNextNode(): PathResult { | ||||||||
| const bestPath = this.selectionQueue.dequeue(); | ||||||||
| const currentResult = bestPath.handleNextNode(); | ||||||||
| this.selectionQueue.enqueue(bestPath); | ||||||||
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| if(currentResult.type == 'complete') { | ||||||||
| this.completedPaths?.push(currentResult.finalNode); | ||||||||
| currentResult.spaceId = this.spaceId; | ||||||||
| } | ||||||||
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| return currentResult; | ||||||||
| } | ||||||||
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| public get previousResults(): SearchResult[] { | ||||||||
| return this.completedPaths?.map((n => new SearchResult(n, this.spaceId))) ?? []; | ||||||||
| } | ||||||||
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| get model(): LexicalModelTypes.LexicalModel { | ||||||||
| return this.parents[0].model; | ||||||||
| } | ||||||||
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| get codepointLength(): number { | ||||||||
| return this.parents[0].codepointLength; | ||||||||
| } | ||||||||
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| get inputSegments(): InputSegment[] { | ||||||||
| return this.parents[0].inputSegments; | ||||||||
| }; | ||||||||
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| /** | ||||||||
| * Gets a compact string-based representation of `inputRange` that | ||||||||
| * maps compatible token source ranges to each other. | ||||||||
| */ | ||||||||
| get sourceRangeKey(): string { | ||||||||
| return this.parents[0].sourceRangeKey; | ||||||||
| } | ||||||||
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| merge(space: SearchQuotientNode): SearchQuotientNode { | ||||||||
| throw new Error('Method not implemented.'); | ||||||||
| } | ||||||||
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| split(charIndex: number): [SearchQuotientNode, SearchQuotientNode] { | ||||||||
| throw new Error('Method not implemented.'); | ||||||||
| } | ||||||||
| } | ||||||||
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Shouldn't this be ?