From 1b06b1ca87eb48682402762f78b87855cd0c04e9 Mon Sep 17 00:00:00 2001 From: Lisa Date: Fri, 20 Mar 2026 17:32:48 +0100 Subject: [PATCH 1/6] feat: importance-weighted retention and contradiction detection MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Add two ANCS-inspired features as opt-in options: - importanceScoring: scores messages by forward-reference density, decision/correction content, and recency. High-importance messages are preserved outside the recency window. forceConverge truncates low-importance messages first. - contradictionDetection: detects later messages that correct earlier ones (via topic overlap + correction signal patterns). Superseded messages are compressed with a provenance annotation linking to the correction. Both features are off by default — zero impact on existing behavior. 28 new tests (540 total), zero TS errors. --- src/compress.ts | 133 ++++++++++++++++++++- src/contradiction.ts | 230 ++++++++++++++++++++++++++++++++++++ src/importance.ts | 129 ++++++++++++++++++++ src/index.ts | 12 ++ src/types.ts | 27 ++++- tests/ancs-features.test.ts | 224 +++++++++++++++++++++++++++++++++++ tests/contradiction.test.ts | 110 +++++++++++++++++ tests/importance.test.ts | 105 ++++++++++++++++ 8 files changed, 967 insertions(+), 3 deletions(-) create mode 100644 src/contradiction.ts create mode 100644 src/importance.ts create mode 100644 tests/ancs-features.test.ts create mode 100644 tests/contradiction.test.ts create mode 100644 tests/importance.test.ts diff --git a/src/compress.ts b/src/compress.ts index fa61c5c..e1b7c98 100644 --- a/src/compress.ts +++ b/src/compress.ts @@ -1,5 +1,11 @@ import { classifyMessage, HARD_T0_REASONS } from './classify.js'; import { analyzeDuplicates, analyzeFuzzyDuplicates, type DedupAnnotation } from './dedup.js'; +import { + computeImportance, + DEFAULT_IMPORTANCE_THRESHOLD, + type ImportanceMap, +} from './importance.js'; +import { analyzeContradictions, type ContradictionAnnotation } from './contradiction.js'; import type { Classifier, ClassifierResult, @@ -463,8 +469,10 @@ type Classified = { preserved: boolean; codeSplit?: boolean; dedup?: DedupAnnotation; + contradiction?: ContradictionAnnotation; patternPreserved?: boolean; llmPreserved?: boolean; + importancePreserved?: boolean; traceReason?: string; adapterMatch?: FormatAdapter; }; @@ -551,6 +559,9 @@ function classifyAll( adapters?: FormatAdapter[], observationThreshold?: number, counter?: (msg: Message) => number, + importanceScores?: ImportanceMap, + importanceThreshold?: number, + contradictionAnnotations?: Map, ): Classified[] { const recencyStart = Math.max(0, messages.length - recencyWindow); @@ -581,6 +592,23 @@ function classifyAll( ) { return { msg, preserved: true, ...(trace && { traceReason: 'already_compressed' }) }; } + // Importance-based preservation: high-importance messages preserved even outside recency + if ( + importanceScores && + importanceThreshold != null && + !largeObservation && + importanceScores.has(idx) + ) { + const score = importanceScores.get(idx)!; + if (score >= importanceThreshold) { + return { + msg, + preserved: true, + importancePreserved: true, + ...(trace && { traceReason: `importance:${score.toFixed(2)}` }), + }; + } + } if (dedupAnnotations?.has(idx)) { const ann = dedupAnnotations.get(idx)!; return { @@ -592,6 +620,18 @@ function classifyAll( }), }; } + // Contradiction: earlier message superseded by a later correction + if (contradictionAnnotations?.has(idx)) { + const ann = contradictionAnnotations.get(idx)!; + return { + msg, + preserved: false, + contradiction: ann, + ...(trace && { + traceReason: `contradicted:${ann.signal}`, + }), + }; + } if (content.includes('```')) { const segments = splitCodeAndProse(content); const totalProse = segments @@ -681,6 +721,8 @@ function computeStats( messagesPatternPreserved?: number, messagesLlmClassified?: number, messagesLlmPreserved?: number, + messagesContradicted?: number, + messagesImportancePreserved?: number, ): CompressResult['compression'] { const originalTotalChars = originalMessages.reduce((sum, m) => sum + contentLength(m), 0); const compressedTotalChars = resultMessages.reduce((sum, m) => sum + contentLength(m), 0); @@ -710,6 +752,12 @@ function computeStats( ...(messagesLlmPreserved && messagesLlmPreserved > 0 ? { messages_llm_preserved: messagesLlmPreserved } : {}), + ...(messagesContradicted && messagesContradicted > 0 + ? { messages_contradicted: messagesContradicted } + : {}), + ...(messagesImportancePreserved && messagesImportancePreserved > 0 + ? { messages_importance_preserved: messagesImportancePreserved } + : {}), }; } @@ -840,6 +888,20 @@ function* compressGen( const trace = options.trace ?? false; + // Importance scoring (ANCS-inspired) + const importanceScores = options.importanceScoring ? computeImportance(messages) : undefined; + const importanceThreshold = options.importanceThreshold ?? DEFAULT_IMPORTANCE_THRESHOLD; + + // Contradiction detection (ANCS-inspired) + let contradictionAnnotations: Map | undefined; + if (options.contradictionDetection) { + contradictionAnnotations = analyzeContradictions( + messages, + options.contradictionTopicThreshold ?? 0.15, + preserveRoles, + ); + } + const classified = classifyAll( messages, preserveRoles, @@ -852,6 +914,9 @@ function* compressGen( options.adapters, options.observationThreshold, options.observationThreshold != null ? counter : undefined, + importanceScores, + importanceScores ? importanceThreshold : undefined, + contradictionAnnotations, ); const result: Message[] = []; @@ -861,6 +926,8 @@ function* compressGen( let messagesPreserved = 0; let messagesDeduped = 0; let messagesFuzzyDeduped = 0; + let messagesContradicted = 0; + let messagesImportancePreserved = 0; let messagesPatternPreserved = 0; let messagesLlmPreserved = 0; let i = 0; @@ -873,6 +940,7 @@ function* compressGen( messagesPreserved++; if (classified[i].patternPreserved) messagesPatternPreserved++; if (classified[i].llmPreserved) messagesLlmPreserved++; + if (classified[i].importancePreserved) messagesImportancePreserved++; if (trace) { const inChars = contentLength(msg); decisions.push({ @@ -918,6 +986,50 @@ function* compressGen( continue; } + // Contradiction: superseded message — compress with annotation + if (classified[i].contradiction) { + const annotation = classified[i].contradiction!; + const supersederId = messages[annotation.supersededByIndex].id; + const content = typeof msg.content === 'string' ? msg.content : ''; + const contentBudget = computeBudget(content.length); + const summaryText: string = yield { text: content, budget: contentBudget }; + let tag = `[cce:superseded by ${supersederId} (${annotation.signal}) — ${summaryText}]`; + // If full tag doesn't fit, use compact format + if (tag.length >= content.length) { + tag = `[cce:superseded by ${supersederId} — ${annotation.signal}]`; + } + + if (tag.length >= content.length) { + result.push(msg); + messagesPreserved++; + if (trace) { + decisions.push({ + messageId: msg.id, + messageIndex: i, + action: 'preserved', + reason: 'contradiction_reverted', + inputChars: content.length, + outputChars: content.length, + }); + } + } else { + result.push(buildCompressedMessage(msg, [msg.id], tag, sourceVersion, verbatim, [msg])); + messagesContradicted++; + if (trace) { + decisions.push({ + messageId: msg.id, + messageIndex: i, + action: 'contradicted', + reason: `contradicted:${annotation.signal}`, + inputChars: content.length, + outputChars: tag.length, + }); + } + } + i++; + continue; + } + // Code-split: extract fences verbatim, summarize surrounding prose if (classified[i].codeSplit) { const content = typeof msg.content === 'string' ? msg.content : ''; @@ -1122,6 +1234,8 @@ function* compressGen( messagesPatternPreserved, llmResults?.size, messagesLlmPreserved, + messagesContradicted, + messagesImportancePreserved, ); if (trace) { @@ -1234,6 +1348,7 @@ function forceConvergePass( sourceVersion: number, counter: (msg: Message) => number, trace?: boolean, + importanceScores?: ImportanceMap, ): CompressResult { if (cr.fits) return cr; @@ -1252,8 +1367,18 @@ function forceConvergePass( candidates.push({ idx: i, contentLen: content.length }); } - // Sort by content length descending (biggest savings first) - candidates.sort((a, b) => b.contentLen - a.contentLen); + // Sort by importance ascending (low-importance first), then by content length descending + // This ensures low-value messages get truncated before high-value ones + if (importanceScores) { + candidates.sort((a, b) => { + const impA = importanceScores.get(a.idx) ?? 0; + const impB = importanceScores.get(b.idx) ?? 0; + if (Math.abs(impA - impB) > 0.05) return impA - impB; // lower importance first + return b.contentLen - a.contentLen; // then bigger savings first + }); + } else { + candidates.sort((a, b) => b.contentLen - a.contentLen); + } // Clone messages and verbatim for mutation const messages = cr.messages.map((m) => ({ @@ -1371,6 +1496,7 @@ function compressSyncWithBudget( if (!result.fits && options.forceConverge) { const preserveRoles = new Set(options.preserve ?? ['system']); + const impScores = options.importanceScoring ? computeImportance(messages) : undefined; result = forceConvergePass( result, tokenBudget, @@ -1378,6 +1504,7 @@ function compressSyncWithBudget( sourceVersion, counter, options.trace, + impScores, ); } @@ -1445,6 +1572,7 @@ async function compressAsyncWithBudget( if (!result.fits && options.forceConverge) { const preserveRoles = new Set(options.preserve ?? ['system']); + const impScores = options.importanceScoring ? computeImportance(messages) : undefined; result = forceConvergePass( result, tokenBudget, @@ -1452,6 +1580,7 @@ async function compressAsyncWithBudget( sourceVersion, counter, options.trace, + impScores, ); } diff --git a/src/contradiction.ts b/src/contradiction.ts new file mode 100644 index 0000000..9d66c13 --- /dev/null +++ b/src/contradiction.ts @@ -0,0 +1,230 @@ +/** + * Contradiction detection — identifies messages that correct or override + * earlier messages on the same topic. + * + * When two messages have high topic overlap but opposing directives, + * the earlier one is marked for compression while the later one + * (the correction) is preserved. + * + * Inspired by ANCS conflict detection (pairwise scanning with topic-overlap gating). + */ + +import type { Message } from './types.js'; + +export type ContradictionAnnotation = { + /** Index of the later message that supersedes this one. */ + supersededByIndex: number; + /** Topic overlap score (0–1). */ + topicOverlap: number; + /** Which correction signal was detected. */ + signal: string; +}; + +// ── Topic overlap (word-level Jaccard, fast) ────────────────────── + +function extractTopicWords(content: string): Set { + const words = new Set(); + // Extract meaningful words (3+ chars, not common stopwords) + const matches = content.toLowerCase().match(/\b[a-z]{3,}\b/g); + if (matches) { + for (const w of matches) { + if (!STOP_WORDS.has(w)) words.add(w); + } + } + return words; +} + +function wordJaccard(a: Set, b: Set): number { + if (a.size === 0 && b.size === 0) return 0; + let intersection = 0; + for (const w of a) { + if (b.has(w)) intersection++; + } + const union = a.size + b.size - intersection; + return union === 0 ? 0 : intersection / union; +} + +// ── Correction signal detection ─────────────────────────────────── + +/** Patterns that indicate a message is correcting/overriding earlier content. */ +const CORRECTION_PATTERNS: Array<{ re: RegExp; label: string }> = [ + { re: /\b(?:actually|correction)[,.:]/i, label: 'explicit_correction' }, + { re: /\bno[,.]?\s+(?:use|it's|that's|it should|we should)/i, label: 'negation_directive' }, + { re: /\b(?:instead|rather)[,.]?\s+(?:use|do|we|you)/i, label: 'instead_directive' }, + { re: /\b(?:scratch that|disregard|ignore)\b/i, label: 'retraction' }, + { re: /\bdon'?t\s+(?:use|do|add|include|import)\b/i, label: 'dont_directive' }, + { re: /\bnot\s+\w+[,.]?\s+(?:but|use|go with)\b/i, label: 'not_but_pattern' }, + { re: /\bwait[,.]\s/i, label: 'wait_correction' }, + { re: /\bsorry[,.]\s+(?:I|that|the)/i, label: 'sorry_correction' }, + { re: /\bI was wrong\b/i, label: 'self_correction' }, + { re: /\blet me (?:correct|rephrase|clarify)\b/i, label: 'rephrase' }, +]; + +function detectCorrectionSignal(content: string): string | null { + for (const { re, label } of CORRECTION_PATTERNS) { + if (re.test(content)) return label; + } + return null; +} + +// ── Main API ────────────────────────────────────────────────────── + +/** + * Scan messages for contradictions: later messages that correct earlier ones. + * + * Returns a map of message indices to contradiction annotations. + * Only the *earlier* (superseded) message gets annotated — the later + * message (the correction) is left untouched for preservation. + * + * @param messages - The message array to scan. + * @param topicThreshold - Minimum word-level Jaccard for topic overlap. Default: 0.15. + * @param preserveRoles - Roles to skip (e.g. 'system'). + */ +export function analyzeContradictions( + messages: Message[], + topicThreshold = 0.15, + preserveRoles?: Set, +): Map { + const annotations = new Map(); + + // Extract topic words per message + const topics: Array<{ index: number; words: Set; content: string }> = []; + for (let i = 0; i < messages.length; i++) { + const msg = messages[i]; + const content = typeof msg.content === 'string' ? msg.content : ''; + if (preserveRoles && msg.role && preserveRoles.has(msg.role)) continue; + if (content.length < 50) continue; // skip very short messages + if ( + content.startsWith('[summary:') || + content.startsWith('[summary#') || + content.startsWith('[truncated') + ) + continue; + + topics.push({ index: i, words: extractTopicWords(content), content }); + } + + // For each message with a correction signal, find the most-overlapping earlier message + for (let ti = 1; ti < topics.length; ti++) { + const later = topics[ti]; + const signal = detectCorrectionSignal(later.content); + if (!signal) continue; + + let bestOverlap = 0; + let bestEarlierIdx = -1; + + for (let ei = ti - 1; ei >= 0; ei--) { + const earlier = topics[ei]; + // Same role check — corrections usually come from the same speaker + if ( + messages[earlier.index].role && + messages[later.index].role && + messages[earlier.index].role !== messages[later.index].role + ) { + // Cross-role corrections are also valid (user correcting assistant) + // but we require higher topic overlap + const overlap = wordJaccard(earlier.words, later.words); + if (overlap >= topicThreshold * 1.5 && overlap > bestOverlap) { + bestOverlap = overlap; + bestEarlierIdx = earlier.index; + } + } else { + const overlap = wordJaccard(earlier.words, later.words); + if (overlap >= topicThreshold && overlap > bestOverlap) { + bestOverlap = overlap; + bestEarlierIdx = earlier.index; + } + } + } + + if (bestEarlierIdx >= 0 && !annotations.has(bestEarlierIdx)) { + annotations.set(bestEarlierIdx, { + supersededByIndex: later.index, + topicOverlap: bestOverlap, + signal, + }); + } + } + + return annotations; +} + +// ── Stopwords (small set, just enough to avoid noise) ───────────── + +const STOP_WORDS = new Set([ + 'the', + 'and', + 'for', + 'are', + 'but', + 'not', + 'you', + 'all', + 'can', + 'had', + 'her', + 'was', + 'one', + 'our', + 'out', + 'has', + 'his', + 'how', + 'its', + 'let', + 'may', + 'new', + 'now', + 'old', + 'see', + 'way', + 'who', + 'did', + 'get', + 'got', + 'him', + 'she', + 'too', + 'use', + 'that', + 'this', + 'with', + 'have', + 'from', + 'they', + 'been', + 'said', + 'each', + 'make', + 'like', + 'just', + 'over', + 'such', + 'take', + 'than', + 'them', + 'very', + 'some', + 'could', + 'would', + 'about', + 'there', + 'these', + 'other', + 'into', + 'more', + 'also', + 'what', + 'when', + 'will', + 'which', + 'their', + 'then', + 'here', + 'were', + 'being', + 'does', + 'doing', + 'done', + 'should', +]); diff --git a/src/importance.ts b/src/importance.ts new file mode 100644 index 0000000..20b381b --- /dev/null +++ b/src/importance.ts @@ -0,0 +1,129 @@ +/** + * Message importance scoring — ANCS-inspired per-message importance + * beyond positional recency. + * + * Factors: + * 1. Forward-reference density: how many later messages reference this message's entities + * 2. Decision/directive content: messages with requirements, constraints, corrections + * 3. Correction recency: messages that override earlier content get boosted + * + * Used by compress() when `importanceScoring: true` to: + * - Preserve high-importance messages outside the recency window + * - Order forceConverge truncation (low-importance first) + */ + +import type { Message } from './types.js'; + +// ── Entity extraction (lightweight, no external deps) ───────────── + +const CAMEL_RE = /\b[a-z]+(?:[A-Z][a-z]+)+\b/g; +const PASCAL_RE = /\b[A-Z][a-z]+(?:[A-Z][a-z]+)+\b/g; +const SNAKE_RE = /\b[a-z]+(?:_[a-z]+)+\b/g; +const VOWELLESS_RE = /\b[bcdfghjklmnpqrstvwxz]{3,}\b/gi; +const FILE_REF_RE = /\S+\.\w+:\d+/g; + +function extractMessageEntities(content: string): Set { + const entities = new Set(); + for (const re of [CAMEL_RE, PASCAL_RE, SNAKE_RE, VOWELLESS_RE, FILE_REF_RE]) { + const matches = content.match(re); + if (matches) { + for (const m of matches) entities.add(m.toLowerCase()); + } + } + return entities; +} + +// ── Decision / directive detection ──────────────────────────────── + +const DECISION_RE = + /\b(?:must|should|require[ds]?|always|never|do not|don't|instead|use\s+\w+\s+(?:instead|rather)|the\s+(?:approach|solution|fix|answer)\s+is|decided? to|we(?:'ll| will)\s+(?:go with|use|implement))\b/i; + +const CORRECTION_RE = + /\b(?:actually|correction|no[,.]?\s+(?:use|it's|that's|the)|wait[,.]|sorry[,.]|instead[,.]|not\s+\w+[,.]?\s+(?:but|use|it's)|scratch that|disregard|ignore (?:that|my|the previous))\b/i; + +const CONSTRAINT_RE = + /\b(?:constraint|limitation|boundary|deadline|blocker|requirement|prerequisite|dependency|breaking change|backwards? compat)\b/i; + +/** Content-based importance signals (0–1 range contributions). */ +export function scoreContentSignals(content: string): number { + let score = 0; + if (DECISION_RE.test(content)) score += 0.15; + if (CORRECTION_RE.test(content)) score += 0.25; // corrections are high-value + if (CONSTRAINT_RE.test(content)) score += 0.1; + return Math.min(score, 0.4); // cap content signal contribution +} + +// ── Forward-reference graph ─────────────────────────────────────── + +export type ImportanceMap = Map; + +/** + * Compute per-message importance scores for a message array. + * + * Algorithm: + * 1. Extract entities from each message + * 2. Build forward-reference counts: for each message, count how many + * later messages share at least one entity + * 3. Normalize reference counts to 0–1, combine with content signals + * + * Returns a Map. + */ +export function computeImportance(messages: Message[]): ImportanceMap { + const scores = new Map(); + if (messages.length === 0) return scores; + + // Extract entities per message + const entitySets: Array> = []; + for (const msg of messages) { + const content = typeof msg.content === 'string' ? msg.content : ''; + entitySets.push(extractMessageEntities(content)); + } + + // Count forward references: how many later messages share entities with this one + const refCounts = new Array(messages.length).fill(0); + let maxRefs = 0; + + for (let i = 0; i < messages.length; i++) { + const myEntities = entitySets[i]; + if (myEntities.size === 0) continue; + + for (let j = i + 1; j < messages.length; j++) { + const theirEntities = entitySets[j]; + let shared = false; + for (const e of myEntities) { + if (theirEntities.has(e)) { + shared = true; + break; + } + } + if (shared) { + refCounts[i]++; + } + } + if (refCounts[i] > maxRefs) maxRefs = refCounts[i]; + } + + // Compute combined score per message + for (let i = 0; i < messages.length; i++) { + const content = typeof messages[i].content === 'string' ? (messages[i].content as string) : ''; + + // Reference score: normalized 0–0.5 + const refScore = maxRefs > 0 ? (refCounts[i] / maxRefs) * 0.5 : 0; + + // Content signal score: 0–0.4 + const contentScore = scoreContentSignals(content); + + // Recency bonus: slight boost for more recent messages (0–0.1) + const recencyScore = (i / Math.max(messages.length - 1, 1)) * 0.1; + + scores.set(i, Math.min(1, refScore + contentScore + recencyScore)); + } + + return scores; +} + +/** + * Default importance threshold for preservation. + * Messages scoring above this are preserved even outside the recency window. + */ +export const DEFAULT_IMPORTANCE_THRESHOLD = 0.35; diff --git a/src/index.ts b/src/index.ts index 2d39d11..9789316 100644 --- a/src/index.ts +++ b/src/index.ts @@ -19,6 +19,18 @@ export { // Format adapters export { CodeAdapter, StructuredOutputAdapter } from './adapters.js'; +// Importance scoring (ANCS-inspired) +export { + computeImportance, + scoreContentSignals, + DEFAULT_IMPORTANCE_THRESHOLD, +} from './importance.js'; +export type { ImportanceMap } from './importance.js'; + +// Contradiction detection (ANCS-inspired) +export { analyzeContradictions } from './contradiction.js'; +export type { ContradictionAnnotation } from './contradiction.js'; + // Types export type { Classifier, diff --git a/src/types.ts b/src/types.ts index ba85344..190869a 100644 --- a/src/types.ts +++ b/src/types.ts @@ -46,7 +46,14 @@ export interface FormatAdapter { export type CompressDecision = { messageId: string; messageIndex: number; - action: 'preserved' | 'compressed' | 'deduped' | 'fuzzy_deduped' | 'truncated' | 'code_split'; + action: + | 'preserved' + | 'compressed' + | 'deduped' + | 'fuzzy_deduped' + | 'truncated' + | 'code_split' + | 'contradicted'; reason: string; inputChars: number; outputChars: number; @@ -99,6 +106,20 @@ export type CompressOptions = { * Messages exceeding this are compressed even if in the recency window. * System-role and tool_calls messages are always exempt. */ observationThreshold?: number; + /** Enable importance-weighted retention. When true, messages are scored by + * forward-reference density, decision/correction content, and recency. + * High-importance messages are preserved even outside the recency window, + * and forceConverge truncates low-importance messages first. Default: false. */ + importanceScoring?: boolean; + /** Importance threshold for preservation (0–1). Messages scoring above this + * are preserved even outside the recency window. Default: 0.35. */ + importanceThreshold?: number; + /** Enable contradiction detection. When true, later messages that correct + * earlier ones cause the earlier message to be compressed while the + * correction is preserved. Default: false. */ + contradictionDetection?: boolean; + /** Topic overlap threshold for contradiction detection (0–1). Default: 0.15. */ + contradictionTopicThreshold?: number; }; export type VerbatimMap = Record; @@ -133,6 +154,10 @@ export type CompressResult = { messages_llm_classified?: number; /** Messages where LLM decided to preserve (when classifier is provided). */ messages_llm_preserved?: number; + /** Messages superseded by a later correction (when contradictionDetection is enabled). */ + messages_contradicted?: number; + /** Messages preserved due to high importance score (when importanceScoring is enabled). */ + messages_importance_preserved?: number; decisions?: CompressDecision[]; }; /** diff --git a/tests/ancs-features.test.ts b/tests/ancs-features.test.ts new file mode 100644 index 0000000..9d8980b --- /dev/null +++ b/tests/ancs-features.test.ts @@ -0,0 +1,224 @@ +import { describe, it, expect } from 'vitest'; +import { compress } from '../src/compress.js'; +import { analyzeContradictions } from '../src/contradiction.js'; +import type { Message } from '../src/types.js'; + +function msg(id: string, content: string, role = 'user'): Message { + return { id, index: 0, role, content }; +} + +describe('importanceScoring integration', () => { + it('preserves high-importance messages outside recency window', () => { + const messages: Message[] = [ + // Message 0: high-importance — referenced by later messages, contains decision + // Pure prose, no structural patterns, long enough to compress + msg( + 'decision', + 'The engineering team decided that the fetchData helper in the service layer should always use exponential backoff when retrying failed network requests against the upstream provider because we observed cascading failures during peak traffic periods last quarter.', + ), + // Messages 1-4: filler prose (also long enough to compress) + msg( + 'filler1', + 'I looked at the weekly performance reports and everything seems to be running within acceptable parameters for this quarter so far with no unexpected anomalies in the monitoring data.', + ), + msg( + 'filler2', + 'The retrospective meeting covered a lot of ground about our processes and we agreed to revisit the topic next month to evaluate whether the proposed changes have been effective in reducing cycle times.', + ), + msg( + 'ref1', + 'The fetchData helper needs proper error categorization so transient failures get retried but permanent errors like authentication failures surface immediately to the calling code.', + ), + msg( + 'ref2', + 'When the fetchData retry logic exhausts all attempts it should publish a structured event to the dead letter queue so the operations team can investigate and potentially replay the failed requests.', + ), + ]; + + // Without importance scoring: message 0 is outside recency window (rw=2), gets compressed + const withoutImportance = compress(messages, { recencyWindow: 2, trace: true }); + const msg0DecisionWithout = withoutImportance.compression.decisions?.find( + (d) => d.messageId === 'decision', + ); + const isCompressedWithout = msg0DecisionWithout?.action === 'compressed'; + + // With importance scoring: message 0 should be preserved due to high forward-reference count + const withImportance = compress(messages, { + recencyWindow: 2, + importanceScoring: true, + importanceThreshold: 0.25, + trace: true, + }); + const msg0DecisionWith = withImportance.compression.decisions?.find( + (d) => d.messageId === 'decision', + ); + + // The important message should be compressed without importance, preserved with it + expect(isCompressedWithout).toBe(true); + expect(msg0DecisionWith?.action).toBe('preserved'); + expect(msg0DecisionWith?.reason).toContain('importance'); + + // Stats should reflect importance preservation + expect(withImportance.compression.messages_importance_preserved).toBeGreaterThan(0); + }); + + it('does nothing when importanceScoring is false (default)', () => { + const messages: Message[] = [ + msg('1', 'We must use the fetchData function for all API communication in the application.'), + msg('2', 'The fetchData function handles retries and error reporting for the service layer.'), + msg( + '3', + 'Generic filler message about unrelated topics that adds nothing to the conversation.', + ), + ]; + + const result = compress(messages, { recencyWindow: 1 }); + expect(result.compression.messages_importance_preserved).toBeUndefined(); + }); +}); + +describe('contradictionDetection integration', () => { + it('analyzeContradictions finds the contradiction in test messages', () => { + const messages: Message[] = [ + msg( + 'old', + 'Use Redis for the caching layer in the application server with a TTL of 3600 seconds for session data and user preferences. Configure the connection pool with a maximum of 20 connections.', + ), + msg( + 'correction', + 'Actually, use Memcached instead for the caching layer in the application server. Redis is overkill for simple key-value session storage and Memcached has lower memory overhead for this use case.', + ), + ]; + const annotations = analyzeContradictions(messages); + expect(annotations.size).toBeGreaterThan(0); + expect(annotations.has(0)).toBe(true); + }); + + it('compresses superseded messages when correction is detected', () => { + const messages: Message[] = [ + msg( + 'old', + 'Use Redis for the caching layer in the application server with a TTL of 3600 seconds for session data and user preferences. Configure the connection pool with a maximum of 20 connections.', + ), + msg( + 'filler', + 'The deployment pipeline runs automated tests before pushing to the staging environment. It includes unit tests, integration tests, and end-to-end tests that verify all critical user flows.', + ), + msg( + 'correction', + 'Actually, use Memcached instead for the caching layer in the application server. Redis is overkill for simple key-value session storage and Memcached has lower memory overhead for this use case.', + ), + msg( + 'recent', + 'The frontend needs some styling updates for the new dashboard components. The color scheme should match the design system and all interactive elements need hover states.', + ), + ]; + + const result = compress(messages, { + recencyWindow: 2, + contradictionDetection: true, + trace: true, + }); + + // The old Redis message should be compressed with superseded annotation + const oldMsg = result.messages.find((m) => m.id === 'old'); + expect(oldMsg?.content).toContain('superseded'); + + // The correction should be preserved (it's in recency or important) + const correctionMsg = result.messages.find((m) => m.id === 'correction'); + expect(correctionMsg?.content).toContain('Memcached'); + + // Stats + if (result.compression.messages_contradicted) { + expect(result.compression.messages_contradicted).toBeGreaterThan(0); + } + }); + + it('does nothing when contradictionDetection is false (default)', () => { + const messages: Message[] = [ + msg( + 'old', + 'Use Redis for the caching layer in the application server with a TTL of 3600 seconds.', + ), + msg( + 'correction', + 'Actually, use Memcached instead for the caching layer in the application server.', + ), + ]; + + const result = compress(messages, { recencyWindow: 1 }); + expect(result.compression.messages_contradicted).toBeUndefined(); + }); + + it('stores verbatim for contradicted messages', () => { + const messages: Message[] = [ + msg( + 'old', + 'Use Redis for the caching layer in the application server with a TTL of 3600 seconds for session data and user preferences. Configure the connection pool with a maximum of 20 connections.', + ), + msg( + 'correction', + 'Actually, use Memcached instead for the caching layer in the application server. Redis is overkill for simple key-value session storage and Memcached has lower memory overhead.', + ), + ]; + + const result = compress(messages, { + recencyWindow: 1, + contradictionDetection: true, + }); + + // If old message was contradicted, its original should be in verbatim + if (result.compression.messages_contradicted && result.compression.messages_contradicted > 0) { + expect(result.verbatim['old']).toBeDefined(); + expect(result.verbatim['old'].content).toContain('Redis'); + } + }); +}); + +describe('combined features', () => { + it('importance + contradiction work together', () => { + const messages: Message[] = [ + msg( + 'important', + 'We must use the fetchData function with retry logic for all API calls in the service.', + ), + msg( + 'superseded', + 'Use Redis for caching all responses from the fetchData function in the application.', + ), + msg( + 'ref', + 'The fetchData function needs proper error handling for timeout and network failure cases.', + ), + msg( + 'correction', + 'Actually, use Memcached instead of Redis for caching fetchData responses in the app.', + ), + msg( + 'recent', + 'The CI pipeline should run all tests including the new fetchData integration tests.', + ), + ]; + + const result = compress(messages, { + recencyWindow: 1, + importanceScoring: true, + importanceThreshold: 0.2, + contradictionDetection: true, + }); + + // 'important' should be preserved (high forward references to fetchData) + const importantMsg = result.messages.find((m) => m.id === 'important'); + expect(importantMsg?.content).toContain('fetchData'); + + // 'superseded' should be contradicted + const supersededMsg = result.messages.find((m) => m.id === 'superseded'); + if (supersededMsg?.content?.includes('superseded')) { + expect(supersededMsg.content).toContain('superseded'); + } + + // 'correction' should be preserved + const correctionMsg = result.messages.find((m) => m.id === 'correction'); + expect(correctionMsg?.content).toContain('Memcached'); + }); +}); diff --git a/tests/contradiction.test.ts b/tests/contradiction.test.ts new file mode 100644 index 0000000..d85351f --- /dev/null +++ b/tests/contradiction.test.ts @@ -0,0 +1,110 @@ +import { describe, it, expect } from 'vitest'; +import { analyzeContradictions } from '../src/contradiction.js'; +import type { Message } from '../src/types.js'; + +function msg(id: string, content: string, role = 'user', index = 0): Message { + return { id, index, role, content }; +} + +describe('analyzeContradictions', () => { + it('returns empty map when no contradictions', () => { + const messages: Message[] = [ + msg('1', 'We should use PostgreSQL for the database layer in the backend.'), + msg('2', 'The frontend needs React with TypeScript for type safety in components.'), + ]; + const result = analyzeContradictions(messages); + expect(result.size).toBe(0); + }); + + it('detects explicit correction with "actually"', () => { + const messages: Message[] = [ + msg('1', 'Use Redis for the caching layer in the application server.'), + msg('2', 'Actually, use Memcached instead for the caching layer.'), + ]; + const result = analyzeContradictions(messages); + expect(result.size).toBe(1); + expect(result.has(0)).toBe(true); + expect(result.get(0)!.supersededByIndex).toBe(1); + expect(result.get(0)!.signal).toBe('explicit_correction'); + }); + + it('detects "don\'t use" directives', () => { + const messages: Message[] = [ + msg('1', 'Import lodash for utility functions in the helper module.'), + msg('2', "Don't use lodash for utility functions, write them from scratch."), + ]; + const result = analyzeContradictions(messages); + expect(result.size).toBe(1); + expect(result.get(0)!.signal).toBe('dont_directive'); + }); + + it('detects "instead" directives', () => { + const messages: Message[] = [ + msg('1', 'Deploy the service on AWS Lambda for the serverless backend.'), + msg('2', 'Instead, use Google Cloud Run for the serverless backend deployment.'), + ]; + const result = analyzeContradictions(messages); + expect(result.size).toBe(1); + expect(result.get(0)!.signal).toBe('instead_directive'); + }); + + it('detects retraction patterns', () => { + const messages: Message[] = [ + msg('1', 'Add the feature flag for the new dashboard module.'), + msg('2', 'Scratch that, we are removing the feature flag for the dashboard.'), + ]; + const result = analyzeContradictions(messages); + expect(result.size).toBe(1); + expect(result.get(0)!.signal).toBe('retraction'); + }); + + it('requires topic overlap — unrelated corrections are not matched', () => { + const messages: Message[] = [ + msg('1', 'The database schema uses PostgreSQL with normalized tables.'), + msg('2', 'Actually, the frontend color scheme should be darker blue.'), + ]; + const result = analyzeContradictions(messages); + expect(result.size).toBe(0); + }); + + it('skips short messages', () => { + const messages: Message[] = [msg('1', 'Use Redis.'), msg('2', 'Actually, use Memcached.')]; + const result = analyzeContradictions(messages); + expect(result.size).toBe(0); // both < 50 chars + }); + + it('skips preserved roles', () => { + const messages: Message[] = [ + msg('1', 'You are a helpful assistant that always uses Redis for caching.', 'system'), + msg('2', 'Actually, use Memcached instead of Redis for the caching layer.'), + ]; + const result = analyzeContradictions(messages, 0.15, new Set(['system'])); + expect(result.size).toBe(0); + }); + + it('only supersedes the most-overlapping earlier message', () => { + const messages: Message[] = [ + msg('1', 'Use Redis for caching data in the application server.'), + msg('2', 'Use Postgres for the primary data store and queries.'), + msg('3', 'Actually, use Memcached instead for caching data in the app.'), + ]; + const result = analyzeContradictions(messages); + // Should supersede message 1 (caching), not message 2 (data store) + if (result.size > 0) { + expect(result.has(0)).toBe(true); + expect(result.has(1)).toBe(false); + } + }); + + it('returns topicOverlap score', () => { + const messages: Message[] = [ + msg('1', 'Use Redis for the caching layer in the application server backend.'), + msg('2', 'Actually, use Memcached for the caching layer in the application backend.'), + ]; + const result = analyzeContradictions(messages); + if (result.size > 0) { + expect(result.get(0)!.topicOverlap).toBeGreaterThan(0); + expect(result.get(0)!.topicOverlap).toBeLessThanOrEqual(1); + } + }); +}); diff --git a/tests/importance.test.ts b/tests/importance.test.ts new file mode 100644 index 0000000..b467639 --- /dev/null +++ b/tests/importance.test.ts @@ -0,0 +1,105 @@ +import { describe, it, expect } from 'vitest'; +import { + computeImportance, + scoreContentSignals, + DEFAULT_IMPORTANCE_THRESHOLD, +} from '../src/importance.js'; +import type { Message } from '../src/types.js'; + +function msg(id: string, content: string, role = 'user'): Message { + return { id, index: 0, role, content }; +} + +describe('scoreContentSignals', () => { + it('returns 0 for plain prose', () => { + expect(scoreContentSignals('The weather is nice today.')).toBe(0); + }); + + it('scores decision content', () => { + const score = scoreContentSignals('We must use PostgreSQL for the database.'); + expect(score).toBeGreaterThan(0); + }); + + it('scores correction content highest', () => { + const correctionScore = scoreContentSignals('Actually, use Redis instead of Memcached.'); + const decisionScore = scoreContentSignals('We should use Redis for caching.'); + expect(correctionScore).toBeGreaterThan(decisionScore); + }); + + it('scores constraint content', () => { + const score = scoreContentSignals('There is a hard deadline for this feature.'); + expect(score).toBeGreaterThan(0); + }); + + it('caps at 0.40', () => { + // Message with all signals + const score = scoreContentSignals( + 'Actually, we must use PostgreSQL. This is a hard requirement and a blocker for the deadline.', + ); + expect(score).toBeLessThanOrEqual(0.4); + }); +}); + +describe('computeImportance', () => { + it('returns empty map for empty messages', () => { + const scores = computeImportance([]); + expect(scores.size).toBe(0); + }); + + it('gives higher score to messages referenced by later messages', () => { + const messages: Message[] = [ + msg('1', 'We should use the fetchData function to get results from the API.'), + msg('2', 'The fetchData function needs error handling for timeout cases.'), + msg('3', 'Also add retry logic to fetchData for network failures.'), + msg('4', 'The weather looks nice today and I had a great lunch.'), + ]; + + const scores = computeImportance(messages); + + // Message 1 mentions fetchData which is referenced by messages 2 and 3 + const score1 = scores.get(0)!; + const score4 = scores.get(3)!; + expect(score1).toBeGreaterThan(score4); + }); + + it('gives recency bonus to later messages', () => { + const messages: Message[] = [ + msg('1', 'Some generic content about nothing in particular here.'), + msg('2', 'Another generic message about different unrelated topics.'), + ]; + + const scores = computeImportance(messages); + // Message 2 (index 1) should have higher recency than message 1 (index 0) + expect(scores.get(1)!).toBeGreaterThan(scores.get(0)!); + }); + + it('boosts messages with decision/correction content', () => { + const messages: Message[] = [ + msg('1', 'The sky is blue and the grass is green today.'), + msg('2', 'We must always validate user input before processing.'), + ]; + + const scores = computeImportance(messages); + expect(scores.get(1)!).toBeGreaterThan(scores.get(0)!); + }); + + it('all scores are in 0–1 range', () => { + const messages: Message[] = [ + msg('1', 'Actually, we must use the fetchData function. This is a hard requirement.'), + msg('2', 'The fetchData function handles all API calls.'), + msg('3', 'Make sure fetchData has retry logic.'), + ]; + + const scores = computeImportance(messages); + for (const [_, score] of scores) { + expect(score).toBeGreaterThanOrEqual(0); + expect(score).toBeLessThanOrEqual(1); + } + }); +}); + +describe('DEFAULT_IMPORTANCE_THRESHOLD', () => { + it('is 0.35', () => { + expect(DEFAULT_IMPORTANCE_THRESHOLD).toBe(0.35); + }); +}); From 0fc30a13f30f5f210d16c3f5a7614ee644054553 Mon Sep 17 00:00:00 2001 From: Lisa Date: Fri, 20 Mar 2026 17:37:58 +0100 Subject: [PATCH 2/6] docs: document importance scoring and contradiction detection - CLAUDE.md: add importance and contradiction modules to architecture - CHANGELOG.md: add [Unreleased] section with both features - api-reference.md: add 4 new CompressOptions, 2 new CompressResult stats, new exports section for importance/contradiction - compression-pipeline.md: add importance + contradiction to classification order, add contradiction output format --- CHANGELOG.md | 9 ++++ CLAUDE.md | 4 +- docs/api-reference.md | 86 ++++++++++++++++++++++-------------- docs/compression-pipeline.md | 28 +++++++++--- 4 files changed, 86 insertions(+), 41 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index eae046c..357c5f1 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -5,6 +5,15 @@ All notable changes to this project will be documented in this file. The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/), and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## [Unreleased] + +### Added + +- **Importance-weighted retention** (`importanceScoring: true`) — per-message importance scoring based on forward-reference density (how many later messages share entities with this one), decision/correction content signals, and recency. Messages scoring above `importanceThreshold` (default 0.35) are preserved even outside the recency window. `forceConverge` truncates low-importance messages first. New stats: `messages_importance_preserved`. +- **Contradiction detection** (`contradictionDetection: true`) — detects later messages that correct or override earlier ones using topic-overlap gating (word-level Jaccard) and correction signal patterns (`actually`, `don't use`, `instead`, `scratch that`, etc.). Superseded messages are compressed with a provenance annotation (`[cce:superseded by ...]`) linking to the correction. New stats: `messages_contradicted`. New decision action: `contradicted`. +- New exports: `computeImportance`, `scoreContentSignals`, `DEFAULT_IMPORTANCE_THRESHOLD`, `analyzeContradictions` for standalone use outside `compress()`. +- New types: `ImportanceMap`, `ContradictionAnnotation`. + ## [1.1.0] - 2026-03-19 ### Added diff --git a/CLAUDE.md b/CLAUDE.md index 1131aa9..ff6597e 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -34,7 +34,9 @@ messages → classify → dedup → merge → summarize → size guard → resul - **classify** (`src/classify.ts`) — three-tier classification (T0 = preserve verbatim, T2 = compressible prose, T3 = filler/removable). Uses structural pattern detection (code fences, JSON, YAML, LaTeX), SQL/API-key anchors, and prose density scoring. - **dedup** (`src/dedup.ts`) — exact (djb2 hash + full comparison) and fuzzy (line-level Jaccard similarity) duplicate detection. Earlier duplicates are replaced with compact references. -- **compress** (`src/compress.ts`) — orchestrator. Handles message merging, code-bearing message splitting (prose compressed, fences preserved inline), budget binary search over `recencyWindow`, and `forceConverge` hard-truncation. +- **importance** (`src/importance.ts`) — per-message importance scoring: forward-reference density (how many later messages share entities), decision/correction content signals, and recency bonus. High-importance messages resist compression even outside recency window. Opt-in via `importanceScoring: true`. +- **contradiction** (`src/contradiction.ts`) — detects later messages that correct/override earlier ones (topic-overlap gating + correction signal patterns like "actually", "don't use", "instead"). Superseded messages are compressed with provenance annotations. Opt-in via `contradictionDetection: true`. +- **compress** (`src/compress.ts`) — orchestrator. Handles message merging, code-bearing message splitting (prose compressed, fences preserved inline), budget binary search over `recencyWindow`, and `forceConverge` hard-truncation (importance-aware ordering when `importanceScoring` is on). - **summarize** (internal in `compress.ts`) — deterministic sentence scoring: rewards technical identifiers (camelCase, snake_case), emphasis phrases, status words; penalizes filler. Paragraph-aware to keep topic boundaries. - **summarizer** (`src/summarizer.ts`) — LLM-powered summarization. `createSummarizer` wraps an LLM call with a prompt template. `createEscalatingSummarizer` adds three-level fallback: normal → aggressive → deterministic. - **expand** (`src/expand.ts`) — `uncompress()` restores originals from a `VerbatimMap` or lookup function. Supports recursive expansion for multi-round compression chains (max depth 10). diff --git a/docs/api-reference.md b/docs/api-reference.md index db29d4c..63cbf21 100644 --- a/docs/api-reference.md +++ b/docs/api-reference.md @@ -16,6 +16,18 @@ export type { StoreLookup } from './expand.js'; export { createSummarizer, createEscalatingSummarizer } from './summarizer.js'; export { createClassifier, createEscalatingClassifier } from './classifier.js'; +// Importance scoring +export { + computeImportance, + scoreContentSignals, + DEFAULT_IMPORTANCE_THRESHOLD, +} from './importance.js'; +export type { ImportanceMap } from './importance.js'; + +// Contradiction detection +export { analyzeContradictions } from './contradiction.js'; +export type { ContradictionAnnotation } from './contradiction.js'; + // Types export type { Classifier, @@ -61,43 +73,49 @@ function compress( ### CompressOptions -| Option | Type | Default | Description | -| ------------------ | -------------------------------------- | --------------------- | ------------------------------------------------------------------------------------------------------------------------------ | -| `preserve` | `string[]` | `['system']` | Roles to never compress | -| `recencyWindow` | `number` | `4` | Protect the last N messages from compression | -| `sourceVersion` | `number` | `0` | Version tag for [provenance tracking](provenance.md) | -| `summarizer` | `Summarizer` | - | LLM-powered summarizer. When provided, `compress()` returns a `Promise`. See [LLM integration](llm-integration.md) | -| `tokenBudget` | `number` | - | Target token count. Binary-searches `recencyWindow` to fit. See [Token budget](token-budget.md) | -| `minRecencyWindow` | `number` | `0` | Floor for `recencyWindow` when using `tokenBudget` | -| `dedup` | `boolean` | `true` | Replace earlier exact-duplicate messages with a compact reference. See [Deduplication](deduplication.md) | -| `fuzzyDedup` | `boolean` | `false` | Detect near-duplicate messages using line-level similarity. See [Deduplication](deduplication.md) | -| `fuzzyThreshold` | `number` | `0.85` | Similarity threshold for fuzzy dedup (0-1) | -| `embedSummaryId` | `boolean` | `false` | Embed `summary_id` in compressed content for downstream reference. See [Provenance](provenance.md) | -| `forceConverge` | `boolean` | `false` | Hard-truncate non-recency messages when binary search bottoms out. See [Token budget](token-budget.md) | -| `preservePatterns` | `Array<{ re: RegExp; label: string }>` | - | Custom regex patterns that force hard T0 preservation. See [Preservation rules](preservation-rules.md) | -| `classifier` | `Classifier` | - | LLM-powered classifier. When provided, `compress()` returns a `Promise`. See [LLM integration](llm-integration.md) | -| `classifierMode` | `'hybrid' \| 'full'` | `'hybrid'` | Classification mode. `'hybrid'`: heuristics first, LLM for prose. `'full'`: LLM for all eligible. Ignored without `classifier` | -| `tokenCounter` | `(msg: Message) => number` | `defaultTokenCounter` | Custom token counter per message. See [Token budget](token-budget.md) | +| Option | Type | Default | Description | +| ----------------------------- | -------------------------------------- | --------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `preserve` | `string[]` | `['system']` | Roles to never compress | +| `recencyWindow` | `number` | `4` | Protect the last N messages from compression | +| `sourceVersion` | `number` | `0` | Version tag for [provenance tracking](provenance.md) | +| `summarizer` | `Summarizer` | - | LLM-powered summarizer. When provided, `compress()` returns a `Promise`. See [LLM integration](llm-integration.md) | +| `tokenBudget` | `number` | - | Target token count. Binary-searches `recencyWindow` to fit. See [Token budget](token-budget.md) | +| `minRecencyWindow` | `number` | `0` | Floor for `recencyWindow` when using `tokenBudget` | +| `dedup` | `boolean` | `true` | Replace earlier exact-duplicate messages with a compact reference. See [Deduplication](deduplication.md) | +| `fuzzyDedup` | `boolean` | `false` | Detect near-duplicate messages using line-level similarity. See [Deduplication](deduplication.md) | +| `fuzzyThreshold` | `number` | `0.85` | Similarity threshold for fuzzy dedup (0-1) | +| `embedSummaryId` | `boolean` | `false` | Embed `summary_id` in compressed content for downstream reference. See [Provenance](provenance.md) | +| `forceConverge` | `boolean` | `false` | Hard-truncate non-recency messages when binary search bottoms out. See [Token budget](token-budget.md) | +| `preservePatterns` | `Array<{ re: RegExp; label: string }>` | - | Custom regex patterns that force hard T0 preservation. See [Preservation rules](preservation-rules.md) | +| `classifier` | `Classifier` | - | LLM-powered classifier. When provided, `compress()` returns a `Promise`. See [LLM integration](llm-integration.md) | +| `classifierMode` | `'hybrid' \| 'full'` | `'hybrid'` | Classification mode. `'hybrid'`: heuristics first, LLM for prose. `'full'`: LLM for all eligible. Ignored without `classifier` | +| `tokenCounter` | `(msg: Message) => number` | `defaultTokenCounter` | Custom token counter per message. See [Token budget](token-budget.md) | +| `importanceScoring` | `boolean` | `false` | Score messages by forward-reference density, decision/correction content, and recency. High-importance messages are preserved outside the recency window. `forceConverge` truncates low-importance first | +| `importanceThreshold` | `number` | `0.35` | Importance score threshold for preservation (0–1). Only used when `importanceScoring: true` | +| `contradictionDetection` | `boolean` | `false` | Detect later messages that correct/override earlier ones. Superseded messages are compressed with a provenance annotation | +| `contradictionTopicThreshold` | `number` | `0.15` | Word-level Jaccard threshold for topic overlap in contradiction detection (0–1) | ### CompressResult -| Field | Type | Description | -| ---------------------------------------- | ---------------------- | ----------------------------------------------------------------------------------- | -| `messages` | `Message[]` | Compressed message array | -| `verbatim` | `VerbatimMap` | Original messages keyed by ID. Must be persisted atomically with `messages` | -| `compression.original_version` | `number` | Mirrors `sourceVersion` | -| `compression.ratio` | `number` | Character-based compression ratio. >1 means savings | -| `compression.token_ratio` | `number` | Token-based compression ratio. >1 means savings | -| `compression.messages_compressed` | `number` | Messages that were compressed | -| `compression.messages_preserved` | `number` | Messages kept as-is | -| `compression.messages_deduped` | `number \| undefined` | Exact duplicates replaced (when `dedup: true`) | -| `compression.messages_fuzzy_deduped` | `number \| undefined` | Near-duplicates replaced (when `fuzzyDedup: true`) | -| `compression.messages_pattern_preserved` | `number \| undefined` | Messages preserved by `preservePatterns` (when patterns are provided) | -| `compression.messages_llm_classified` | `number \| undefined` | Messages classified by LLM (when `classifier` is provided) | -| `compression.messages_llm_preserved` | `number \| undefined` | Messages where LLM decided to preserve (when `classifier` is provided) | -| `fits` | `boolean \| undefined` | Whether result fits within `tokenBudget`. Present when `tokenBudget` is set | -| `tokenCount` | `number \| undefined` | Estimated token count. Present when `tokenBudget` is set | -| `recencyWindow` | `number \| undefined` | The `recencyWindow` the binary search settled on. Present when `tokenBudget` is set | +| Field | Type | Description | +| ------------------------------------------- | ---------------------- | ----------------------------------------------------------------------------------- | +| `messages` | `Message[]` | Compressed message array | +| `verbatim` | `VerbatimMap` | Original messages keyed by ID. Must be persisted atomically with `messages` | +| `compression.original_version` | `number` | Mirrors `sourceVersion` | +| `compression.ratio` | `number` | Character-based compression ratio. >1 means savings | +| `compression.token_ratio` | `number` | Token-based compression ratio. >1 means savings | +| `compression.messages_compressed` | `number` | Messages that were compressed | +| `compression.messages_preserved` | `number` | Messages kept as-is | +| `compression.messages_deduped` | `number \| undefined` | Exact duplicates replaced (when `dedup: true`) | +| `compression.messages_fuzzy_deduped` | `number \| undefined` | Near-duplicates replaced (when `fuzzyDedup: true`) | +| `compression.messages_pattern_preserved` | `number \| undefined` | Messages preserved by `preservePatterns` (when patterns are provided) | +| `compression.messages_llm_classified` | `number \| undefined` | Messages classified by LLM (when `classifier` is provided) | +| `compression.messages_llm_preserved` | `number \| undefined` | Messages where LLM decided to preserve (when `classifier` is provided) | +| `compression.messages_contradicted` | `number \| undefined` | Messages superseded by a later correction (when `contradictionDetection: true`) | +| `compression.messages_importance_preserved` | `number \| undefined` | Messages preserved due to high importance score (when `importanceScoring: true`) | +| `fits` | `boolean \| undefined` | Whether result fits within `tokenBudget`. Present when `tokenBudget` is set | +| `tokenCount` | `number \| undefined` | Estimated token count. Present when `tokenBudget` is set | +| `recencyWindow` | `number \| undefined` | The `recencyWindow` the binary search settled on. Present when `tokenBudget` is set | ### Example diff --git a/docs/compression-pipeline.md b/docs/compression-pipeline.md index da9c5ec..f23dac2 100644 --- a/docs/compression-pipeline.md +++ b/docs/compression-pipeline.md @@ -36,12 +36,14 @@ The classifier (`classifyAll`) applies rules in this order: 3. Has `tool_calls` -> preserved 4. Content < 120 chars -> preserved 5. Already compressed (`[summary:`, `[summary#`, or `[truncated` prefix) -> preserved -6. Marked as duplicate by dedup analysis -> dedup path -7. Contains code fences with >= 80 chars of prose -> code-split path -8. Has code fences with < 80 chars prose -> preserved -9. Classified as hard T0 (code, JSON, SQL, API keys, etc.) -> preserved -10. Valid JSON -> preserved -11. Everything else -> compress +6. High importance score (when `importanceScoring: true`, score >= `importanceThreshold`) -> preserved +7. Marked as duplicate by dedup analysis -> dedup path +8. Superseded by a later correction (when `contradictionDetection: true`) -> contradiction path +9. Contains code fences with >= 80 chars of prose -> code-split path +10. Has code fences with < 80 chars prose -> preserved +11. Classified as hard T0 (code, JSON, SQL, API keys, etc.) -> preserved +12. Valid JSON -> preserved +13. Everything else -> compress See [Preservation rules](preservation-rules.md) for classification tiers and the hard vs. soft T0 distinction. @@ -169,6 +171,20 @@ With `embedSummaryId: true`: [cce:near-dup of {keepTargetId} — {contentLength} chars, ~{similarity}% match] ``` +### Contradiction format + +When `contradictionDetection: true`, messages superseded by a later correction: + +``` +[cce:superseded by {correctionMessageId} ({signal}) — {summaryText}] +``` + +If the full format doesn't fit, falls back to compact: + +``` +[cce:superseded by {correctionMessageId} — {signal}] +``` + ### Force-converge format ``` From 13cd5058ad39bf23927691fd7008242deec55675 Mon Sep 17 00:00:00 2001 From: Lisa Date: Fri, 20 Mar 2026 18:43:26 +0100 Subject: [PATCH 3/6] feat(bench): add ANCS benchmark section, IDF-weighted Dice similarity MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - Add iterative design scenario with architectural corrections to exercise contradiction detection and importance scoring - Add ANCS Features benchmark section comparing baseline vs importance vs contradiction vs combined, with round-trip verification - Add AncsResult type, regression comparison, and doc generation - Replace hardcoded English stopword list with IDF-weighted filtering (language-agnostic, adapts to message content) - Switch from Jaccard to Sørensen-Dice similarity (better sensitivity for short-document topic overlap) - Use smoothed IDF log(1+N/df) with fallback to unweighted Dice for < 3 documents --- bench/baseline.ts | 106 +++++++++++++++++++ bench/run.ts | 246 +++++++++++++++++++++++++++++++++++++++++++ src/contradiction.ts | 204 ++++++++++++++++------------------- 3 files changed, 444 insertions(+), 112 deletions(-) diff --git a/bench/baseline.ts b/bench/baseline.ts index e2cb6f4..4cfee0f 100644 --- a/bench/baseline.ts +++ b/bench/baseline.ts @@ -46,6 +46,15 @@ export interface RetentionResult { structuralRetention: number; } +export interface AncsResult { + baselineRatio: number; + importanceRatio: number; + contradictionRatio: number; + combinedRatio: number; + importancePreserved: number; + contradicted: number; +} + export interface BenchmarkResults { basic: Record; tokenBudget: Record; @@ -53,6 +62,7 @@ export interface BenchmarkResults { fuzzyDedup: Record; bundleSize: Record; retention?: Record; + ancs?: Record; } export interface Baseline { @@ -413,6 +423,71 @@ export function compareResults( checkNum(regressions, 'fuzzyDedup', name, 'ratio', exp.ratio, act.ratio, tolerance); } + // ANCS + if (baseline.ancs && current.ancs) { + for (const [name, exp] of Object.entries(baseline.ancs)) { + const act = current.ancs[name]; + if (!act) { + missing(regressions, 'ancs', name); + continue; + } + checkNum( + regressions, + 'ancs', + name, + 'baselineRatio', + exp.baselineRatio, + act.baselineRatio, + tolerance, + ); + checkNum( + regressions, + 'ancs', + name, + 'importanceRatio', + exp.importanceRatio, + act.importanceRatio, + tolerance, + ); + checkNum( + regressions, + 'ancs', + name, + 'contradictionRatio', + exp.contradictionRatio, + act.contradictionRatio, + tolerance, + ); + checkNum( + regressions, + 'ancs', + name, + 'combinedRatio', + exp.combinedRatio, + act.combinedRatio, + tolerance, + ); + checkNum( + regressions, + 'ancs', + name, + 'importancePreserved', + exp.importancePreserved, + act.importancePreserved, + tolerance, + ); + checkNum( + regressions, + 'ancs', + name, + 'contradicted', + exp.contradicted, + act.contradicted, + tolerance, + ); + } + } + // Bundle size for (const [name, exp] of Object.entries(baseline.bundleSize ?? {})) { const act = current.bundleSize?.[name]; @@ -652,6 +727,7 @@ const SHORT_NAMES: Record = { 'Technical explanation': 'Technical', 'Structured content': 'Structured', 'Agentic coding session': 'Agentic', + 'Iterative design': 'Iterative', }; function shortName(name: string): string { @@ -864,6 +940,29 @@ function generateDedupSection(r: BenchmarkResults): string[] { return lines; } +function generateAncsSection(r: BenchmarkResults): string[] { + if (!r.ancs || Object.keys(r.ancs).length === 0) return []; + + const lines: string[] = []; + lines.push('## ANCS-Inspired Features'); + lines.push(''); + lines.push( + '> Importance scoring preserves high-value messages outside the recency window. ' + + 'Contradiction detection compresses superseded messages.', + ); + lines.push(''); + lines.push( + '| Scenario | Baseline | +Importance | +Contradiction | Combined | Imp. Preserved | Contradicted |', + ); + lines.push('| --- | ---: | ---: | ---: | ---: | ---: | ---: |'); + for (const [name, v] of Object.entries(r.ancs)) { + lines.push( + `| ${name} | ${fix(v.baselineRatio)} | ${fix(v.importanceRatio)} | ${fix(v.contradictionRatio)} | ${fix(v.combinedRatio)} | ${v.importancePreserved} | ${v.contradicted} |`, + ); + } + return lines; +} + function generateTokenBudgetSection(r: BenchmarkResults): string[] { const lines: string[] = []; const entries = Object.entries(r.tokenBudget); @@ -1113,6 +1212,13 @@ export function generateBenchmarkDocs(baselinesDir: string, outputPath: string): lines.push(...generateDedupSection(latest.results)); lines.push(''); + // --- ANCS --- + const ancsSection = generateAncsSection(latest.results); + if (ancsSection.length > 0) { + lines.push(...ancsSection); + lines.push(''); + } + // --- Token budget --- lines.push(...generateTokenBudgetSection(latest.results)); lines.push(''); diff --git a/bench/run.ts b/bench/run.ts index eb9fcbb..ce56ecf 100644 --- a/bench/run.ts +++ b/bench/run.ts @@ -787,6 +787,147 @@ function agenticCodingSession(): Scenario { }; } +function iterativeDesign(): Scenario { + // Simulates a real design conversation where: + // 1. Early messages establish important architectural decisions (importance scoring target) + // 2. Some decisions get corrected/overridden later (contradiction detection target) + // 3. Filler prose separates the signals + const filler = + 'The team has been making steady progress on the overall project timeline and the stakeholders ' + + 'are generally satisfied with the direction things are heading. We should continue to monitor the ' + + 'situation and adjust our approach as needed based on feedback from the beta testing group.'; + + return { + name: 'Iterative design', + messages: [ + msg('system', 'You are a senior architect helping design a data pipeline.'), + // Important early decision — referenced by many later messages + msg( + 'user', + 'We need to decide on the message queue. I think we should use the RabbitMQ broker with ' + + 'the AMQP protocol for our data pipeline because it supports complex routing topologies ' + + 'and has mature client libraries for our TypeScript and Python services.', + ), + msg( + 'assistant', + 'RabbitMQ with AMQP is a solid choice for the data pipeline. The exchange-based routing ' + + 'model lets you fan out events to multiple consumers without duplicating publish logic. ' + + 'For the TypeScript services, use the amqplib client with channel pooling to avoid ' + + 'connection churn. For Python, pika is the standard. Make sure to configure publisher ' + + 'confirms and consumer acknowledgments to prevent message loss.', + ), + // Filler + msg('user', filler), + msg( + 'assistant', + 'That sounds like a reasonable assessment of the current project state. Keeping an eye on ' + + 'the beta feedback loop is important for catching issues early. The weekly sync should give ' + + 'enough visibility into any blockers that arise during the testing phase.', + ), + // Another important decision — serialization format + msg( + 'user', + 'For the serialization format in the data pipeline, lets use Protocol Buffers with the ' + + 'protobuf-ts generator for the TypeScript side. The schema evolution story is better ' + + 'than JSON and the binary encoding saves bandwidth on the RabbitMQ broker.', + ), + msg( + 'assistant', + 'Protocol Buffers are a strong fit here. The protobuf-ts generator produces clean ' + + 'TypeScript interfaces with full type safety. Define your schemas in a shared proto ' + + 'directory and generate both TypeScript and Python stubs from CI. Use proto3 syntax ' + + 'and leverage the optional keyword for fields that might be added later. This keeps ' + + 'backward compatibility without the versioning headaches of Avro.', + ), + // More filler + msg( + 'user', + 'The onboarding documentation for new developers needs some updates. Several sections ' + + 'reference the old deployment process and the screenshots are from the previous version ' + + 'of the admin dashboard.', + ), + msg( + 'assistant', + 'Updating the onboarding docs should be a priority before the next hiring cycle. Have each ' + + 'recent joiner flag the sections that confused them during their own onboarding, then use ' + + 'those annotations to prioritize which pages to rewrite first. Screenshots can be automated ' + + 'with a headless browser script that captures the current UI state on each release.', + ), + // CONTRADICTION: override the RabbitMQ decision (shares vocabulary with original) + msg( + 'user', + 'Actually, we need to change the message queue broker for our data pipeline. The RabbitMQ ' + + 'broker with AMQP protocol cannot handle our throughput requirements for the TypeScript ' + + 'and Python services. We should use Apache Kafka as the message broker instead because ' + + 'the partitioned log model supports complex routing topologies at higher scale and the ' + + 'client libraries are mature.', + ), + msg( + 'assistant', + "Good call switching to Kafka after the load test validated the concern. Kafka's " + + 'partitioned log gives you the horizontal scaling RabbitMQ was missing. Use the kafkajs ' + + 'client for TypeScript with the confluent-kafka-python library for the Python services. ' + + 'Partition your topics by the pipeline entity ID to preserve ordering within each entity. ' + + 'You will need to update the protobuf message wrappers to include Kafka headers for ' + + 'tracing.', + ), + // Forward reference to the Kafka decision + msg( + 'user', + 'How should we handle dead letter processing in Kafka? When a consumer fails to process ' + + 'a message from the data pipeline after retries, we need a recovery path.', + ), + msg( + 'assistant', + 'In Kafka, dead letter handling is a consumer-side concern unlike RabbitMQ which has ' + + 'built-in DLX support. Implement a retry topic pattern: after N failed attempts, the ' + + 'consumer publishes the message to a dedicated retry topic with a backoff delay header. ' + + 'A separate retry consumer reads from the retry topic and re-publishes to the original ' + + 'topic after the delay expires. After the final retry, send to a dead letter topic that ' + + 'feeds into an alert and manual review workflow.', + ), + // CONTRADICTION: override the protobuf decision (shares vocabulary with original) + msg( + 'user', + 'Actually, the protobuf-ts generator for the serialization format in the data pipeline ' + + 'has a bug with our nested message types. Lets switch to using Avro instead of Protocol ' + + 'Buffers for the TypeScript side. The schema evolution story with the Confluent schema ' + + 'registry is better and the binary encoding saves bandwidth on the Kafka broker.', + ), + msg( + 'assistant', + 'Avro with the Confluent Schema Registry is the standard pairing for Kafka pipelines. ' + + 'The avsc library handles Avro encoding and schema resolution in Node. Register schemas ' + + 'on first produce and cache the schema ID for subsequent messages. The wire format is ' + + 'a magic byte, the 4-byte schema ID, then the Avro-encoded payload. This is a better ' + + 'fit than protobuf for the Kafka ecosystem since the schema registry handles evolution.', + ), + // Forward references + msg( + 'user', + 'Can the Avro schemas we define for Kafka also be used to validate the REST API request ' + + 'bodies in the ingestion service?', + ), + msg( + 'assistant', + 'Yes, you can share the Avro schemas between the Kafka producers and the REST validation ' + + 'layer. The avsc library can compile an Avro schema into a validator function that checks ' + + 'incoming JSON payloads. This gives you a single source of truth for the data pipeline ' + + 'message format — the same schema validates HTTP input and serializes Kafka output.', + ), + ], + }; +} + +// --------------------------------------------------------------------------- +// ANCS scenario builder (uses existing + new scenarios) +// --------------------------------------------------------------------------- + +function buildAncsScenarios(): Scenario[] { + nextId = 10000; // offset to avoid ID collisions + return [deepConversation(), agenticCodingSession(), iterativeDesign()]; +} + // --------------------------------------------------------------------------- // Runner // --------------------------------------------------------------------------- @@ -1185,6 +1326,111 @@ async function run(): Promise { process.exit(1); } + // --------------------------------------------------------------------------- + // ANCS-inspired features (importance scoring + contradiction detection) + // --------------------------------------------------------------------------- + + console.log(); + console.log('ANCS Features (importanceScoring + contradictionDetection)'); + + const ancsScenarios = buildAncsScenarios(); + + const ancsHeader = [ + 'Scenario'.padEnd(cols.name), + 'Msgs'.padStart(5), + 'Base R'.padStart(7), + '+Imp R'.padStart(7), + '+Con R'.padStart(7), + 'Both R'.padStart(7), + 'ImpP'.padStart(5), + 'Ctrd'.padStart(5), + 'R/T'.padStart(cols.rt), + 'Time'.padStart(cols.time), + ].join(' '); + const ancsSep = '-'.repeat(ancsHeader.length); + + console.log(ancsSep); + console.log(ancsHeader); + console.log(ancsSep); + + if (!benchResults.ancs) benchResults.ancs = {}; + let ancsFails = 0; + + for (const scenario of ancsScenarios) { + const t0 = performance.now(); + + // Baseline: small recency window to leave room for ANCS features to act + const baseline = compress(scenario.messages, { recencyWindow: 2 }); + + // Importance only + const withImportance = compress(scenario.messages, { + recencyWindow: 2, + importanceScoring: true, + importanceThreshold: 0.25, + }); + + // Contradiction only + const withContradiction = compress(scenario.messages, { + recencyWindow: 2, + contradictionDetection: true, + }); + + // Combined + const combined = compress(scenario.messages, { + recencyWindow: 2, + importanceScoring: true, + importanceThreshold: 0.25, + contradictionDetection: true, + }); + + const t1 = performance.now(); + + // Round-trip on combined (strictest test) + const er = uncompress(combined.messages, combined.verbatim); + const rt = + JSON.stringify(scenario.messages) === JSON.stringify(er.messages) && + er.missing_ids.length === 0 + ? 'PASS' + : 'FAIL'; + if (rt === 'FAIL') ancsFails++; + + // Report per-feature stats from their individual runs (not combined, + // where importance can shadow contradictions) + const impPreserved = withImportance.compression.messages_importance_preserved ?? 0; + const contradicted = withContradiction.compression.messages_contradicted ?? 0; + + console.log( + [ + scenario.name.padEnd(cols.name), + String(scenario.messages.length).padStart(5), + baseline.compression.ratio.toFixed(2).padStart(7), + withImportance.compression.ratio.toFixed(2).padStart(7), + withContradiction.compression.ratio.toFixed(2).padStart(7), + combined.compression.ratio.toFixed(2).padStart(7), + String(impPreserved).padStart(5), + String(contradicted).padStart(5), + rt.padStart(cols.rt), + ((t1 - t0).toFixed(2) + 'ms').padStart(cols.time), + ].join(' '), + ); + + benchResults.ancs[scenario.name] = { + baselineRatio: baseline.compression.ratio, + importanceRatio: withImportance.compression.ratio, + contradictionRatio: withContradiction.compression.ratio, + combinedRatio: combined.compression.ratio, + importancePreserved: impPreserved, + contradicted, + }; + } + + console.log(ancsSep); + + if (ancsFails > 0) { + console.error(`FAIL: ${ancsFails} ANCS scenario(s) failed round-trip`); + process.exit(1); + } + // --------------------------------------------------------------------------- // Bundle size // --------------------------------------------------------------------------- diff --git a/src/contradiction.ts b/src/contradiction.ts index 9d66c13..6818c98 100644 --- a/src/contradiction.ts +++ b/src/contradiction.ts @@ -20,28 +20,89 @@ export type ContradictionAnnotation = { signal: string; }; -// ── Topic overlap (word-level Jaccard, fast) ────────────────────── +// ── Topic overlap (IDF-weighted Sørensen-Dice) ────────────────── -function extractTopicWords(content: string): Set { +/** Extract all lowercase words (3+ chars) from content. */ +function extractRawWords(content: string): Set { const words = new Set(); - // Extract meaningful words (3+ chars, not common stopwords) const matches = content.toLowerCase().match(/\b[a-z]{3,}\b/g); if (matches) { - for (const w of matches) { - if (!STOP_WORDS.has(w)) words.add(w); - } + for (const w of matches) words.add(w); } return words; } -function wordJaccard(a: Set, b: Set): number { +/** + * Compute IDF weights for all words across a set of documents. + * Uses BM25-style IDF: `log((N - df + 0.5) / (df + 0.5))`. + * + * Language-agnostic: common words get low weight regardless of language. + * No hardcoded stopword list needed. + * + * Returns null when there are fewer than 3 documents — IDF needs enough + * documents to distinguish common from rare words. + */ +function computeIdfWeights(documents: Set[]): Map | null { + const n = documents.length; + if (n < 3) return null; + + const df = new Map(); + for (const doc of documents) { + for (const word of doc) { + df.set(word, (df.get(word) ?? 0) + 1); + } + } + + const idf = new Map(); + for (const [word, count] of df) { + // Smoothed IDF: log(1 + N/df). Gentler than BM25's `log((N-df+0.5)/(df+0.5))` + // which is too aggressive for small document sets (zeroes out words at N/2). + // A word in all N docs gets log(2) ≈ 0.69; a word in 1 doc gets log(1+N). + idf.set(word, Math.log(1 + n / count)); + } + return idf; +} + +/** + * IDF-weighted Sørensen-Dice similarity. + * + * Dice = 2 * weightedIntersection / (weightedA + weightedB) + * + * Compared to unweighted Jaccard: + * - Dice weights shared terms more heavily (2x numerator), better for short docs + * - IDF weighting means rare/topical words dominate, common words contribute ~0 + * + * When IDF is null (too few documents for reliable DF), falls back to + * unweighted Dice (all words weight 1). + */ +function weightedDice(a: Set, b: Set, idf: Map | null): number { if (a.size === 0 && b.size === 0) return 0; - let intersection = 0; + + // Unweighted Dice when IDF is unavailable + if (!idf) { + let intersection = 0; + for (const w of a) { + if (b.has(w)) intersection++; + } + const denom = a.size + b.size; + return denom === 0 ? 0 : (2 * intersection) / denom; + } + + let weightedIntersection = 0; + let weightedA = 0; + let weightedB = 0; + for (const w of a) { - if (b.has(w)) intersection++; + const weight = idf.get(w) ?? 0; + weightedA += weight; + if (b.has(w)) weightedIntersection += weight; } - const union = a.size + b.size - intersection; - return union === 0 ? 0 : intersection / union; + for (const w of b) { + weightedB += idf.get(w) ?? 0; + } + + const denom = weightedA + weightedB; + return denom === 0 ? 0 : (2 * weightedIntersection) / denom; } // ── Correction signal detection ─────────────────────────────────── @@ -77,7 +138,7 @@ function detectCorrectionSignal(content: string): string | null { * message (the correction) is left untouched for preservation. * * @param messages - The message array to scan. - * @param topicThreshold - Minimum word-level Jaccard for topic overlap. Default: 0.15. + * @param topicThreshold - Minimum IDF-weighted Dice similarity for topic overlap. Default: 0.15. * @param preserveRoles - Roles to skip (e.g. 'system'). */ export function analyzeContradictions( @@ -87,8 +148,8 @@ export function analyzeContradictions( ): Map { const annotations = new Map(); - // Extract topic words per message - const topics: Array<{ index: number; words: Set; content: string }> = []; + // Pass 1: extract raw words per eligible message + const eligible: Array<{ index: number; words: Set; content: string }> = []; for (let i = 0; i < messages.length; i++) { const msg = messages[i]; const content = typeof msg.content === 'string' ? msg.content : ''; @@ -101,9 +162,15 @@ export function analyzeContradictions( ) continue; - topics.push({ index: i, words: extractTopicWords(content), content }); + eligible.push({ index: i, words: extractRawWords(content), content }); } + // Pass 2: compute IDF weights (language-agnostic — common words get low weight) + const idf = computeIdfWeights(eligible.map((e) => e.words)); + + // Use eligible directly as topics (IDF handles weighting, no filtering needed) + const topics = eligible; + // For each message with a correction signal, find the most-overlapping earlier message for (let ti = 1; ti < topics.length; ti++) { const later = topics[ti]; @@ -115,25 +182,18 @@ export function analyzeContradictions( for (let ei = ti - 1; ei >= 0; ei--) { const earlier = topics[ei]; - // Same role check — corrections usually come from the same speaker - if ( + const overlap = weightedDice(earlier.words, later.words, idf); + + // Cross-role corrections (user correcting assistant) require higher overlap + const crossRole = messages[earlier.index].role && messages[later.index].role && - messages[earlier.index].role !== messages[later.index].role - ) { - // Cross-role corrections are also valid (user correcting assistant) - // but we require higher topic overlap - const overlap = wordJaccard(earlier.words, later.words); - if (overlap >= topicThreshold * 1.5 && overlap > bestOverlap) { - bestOverlap = overlap; - bestEarlierIdx = earlier.index; - } - } else { - const overlap = wordJaccard(earlier.words, later.words); - if (overlap >= topicThreshold && overlap > bestOverlap) { - bestOverlap = overlap; - bestEarlierIdx = earlier.index; - } + messages[earlier.index].role !== messages[later.index].role; + const effectiveThreshold = crossRole ? topicThreshold * 1.5 : topicThreshold; + + if (overlap >= effectiveThreshold && overlap > bestOverlap) { + bestOverlap = overlap; + bestEarlierIdx = earlier.index; } } @@ -148,83 +208,3 @@ export function analyzeContradictions( return annotations; } - -// ── Stopwords (small set, just enough to avoid noise) ───────────── - -const STOP_WORDS = new Set([ - 'the', - 'and', - 'for', - 'are', - 'but', - 'not', - 'you', - 'all', - 'can', - 'had', - 'her', - 'was', - 'one', - 'our', - 'out', - 'has', - 'his', - 'how', - 'its', - 'let', - 'may', - 'new', - 'now', - 'old', - 'see', - 'way', - 'who', - 'did', - 'get', - 'got', - 'him', - 'she', - 'too', - 'use', - 'that', - 'this', - 'with', - 'have', - 'from', - 'they', - 'been', - 'said', - 'each', - 'make', - 'like', - 'just', - 'over', - 'such', - 'take', - 'than', - 'them', - 'very', - 'some', - 'could', - 'would', - 'about', - 'there', - 'these', - 'other', - 'into', - 'more', - 'also', - 'what', - 'when', - 'will', - 'which', - 'their', - 'then', - 'here', - 'were', - 'being', - 'does', - 'doing', - 'done', - 'should', -]); From 3fff0b10d8b457d20ce4d755665f6bf0ee45f94f Mon Sep 17 00:00:00 2001 From: Lisa Date: Fri, 20 Mar 2026 19:05:02 +0100 Subject: [PATCH 4/6] fix: lint error, stale docs, and identifier extraction in contradiction MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - Fix unused `_` binding in importance test (use `.values()` iterator) - Fix stale JSDoc referencing BM25 when formula is smoothed IDF - Fix API docs referencing Jaccard when similarity is IDF-weighted Dice - Add camelCase/PascalCase/snake_case extraction to contradiction topic words — these identifiers carry the most topic signal - Document importanceScoring + tokenBudget interaction in API reference --- docs/api-reference.md | 42 ++++++++++++++++++++-------------------- src/contradiction.ts | 18 ++++++++++++----- tests/importance.test.ts | 2 +- 3 files changed, 35 insertions(+), 27 deletions(-) diff --git a/docs/api-reference.md b/docs/api-reference.md index 63cbf21..d2d3aaf 100644 --- a/docs/api-reference.md +++ b/docs/api-reference.md @@ -73,27 +73,27 @@ function compress( ### CompressOptions -| Option | Type | Default | Description | -| ----------------------------- | -------------------------------------- | --------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `preserve` | `string[]` | `['system']` | Roles to never compress | -| `recencyWindow` | `number` | `4` | Protect the last N messages from compression | -| `sourceVersion` | `number` | `0` | Version tag for [provenance tracking](provenance.md) | -| `summarizer` | `Summarizer` | - | LLM-powered summarizer. When provided, `compress()` returns a `Promise`. See [LLM integration](llm-integration.md) | -| `tokenBudget` | `number` | - | Target token count. Binary-searches `recencyWindow` to fit. See [Token budget](token-budget.md) | -| `minRecencyWindow` | `number` | `0` | Floor for `recencyWindow` when using `tokenBudget` | -| `dedup` | `boolean` | `true` | Replace earlier exact-duplicate messages with a compact reference. See [Deduplication](deduplication.md) | -| `fuzzyDedup` | `boolean` | `false` | Detect near-duplicate messages using line-level similarity. See [Deduplication](deduplication.md) | -| `fuzzyThreshold` | `number` | `0.85` | Similarity threshold for fuzzy dedup (0-1) | -| `embedSummaryId` | `boolean` | `false` | Embed `summary_id` in compressed content for downstream reference. See [Provenance](provenance.md) | -| `forceConverge` | `boolean` | `false` | Hard-truncate non-recency messages when binary search bottoms out. See [Token budget](token-budget.md) | -| `preservePatterns` | `Array<{ re: RegExp; label: string }>` | - | Custom regex patterns that force hard T0 preservation. See [Preservation rules](preservation-rules.md) | -| `classifier` | `Classifier` | - | LLM-powered classifier. When provided, `compress()` returns a `Promise`. See [LLM integration](llm-integration.md) | -| `classifierMode` | `'hybrid' \| 'full'` | `'hybrid'` | Classification mode. `'hybrid'`: heuristics first, LLM for prose. `'full'`: LLM for all eligible. Ignored without `classifier` | -| `tokenCounter` | `(msg: Message) => number` | `defaultTokenCounter` | Custom token counter per message. See [Token budget](token-budget.md) | -| `importanceScoring` | `boolean` | `false` | Score messages by forward-reference density, decision/correction content, and recency. High-importance messages are preserved outside the recency window. `forceConverge` truncates low-importance first | -| `importanceThreshold` | `number` | `0.35` | Importance score threshold for preservation (0–1). Only used when `importanceScoring: true` | -| `contradictionDetection` | `boolean` | `false` | Detect later messages that correct/override earlier ones. Superseded messages are compressed with a provenance annotation | -| `contradictionTopicThreshold` | `number` | `0.15` | Word-level Jaccard threshold for topic overlap in contradiction detection (0–1) | +| Option | Type | Default | Description | +| ----------------------------- | -------------------------------------- | --------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `preserve` | `string[]` | `['system']` | Roles to never compress | +| `recencyWindow` | `number` | `4` | Protect the last N messages from compression | +| `sourceVersion` | `number` | `0` | Version tag for [provenance tracking](provenance.md) | +| `summarizer` | `Summarizer` | - | LLM-powered summarizer. When provided, `compress()` returns a `Promise`. See [LLM integration](llm-integration.md) | +| `tokenBudget` | `number` | - | Target token count. Binary-searches `recencyWindow` to fit. See [Token budget](token-budget.md) | +| `minRecencyWindow` | `number` | `0` | Floor for `recencyWindow` when using `tokenBudget` | +| `dedup` | `boolean` | `true` | Replace earlier exact-duplicate messages with a compact reference. See [Deduplication](deduplication.md) | +| `fuzzyDedup` | `boolean` | `false` | Detect near-duplicate messages using line-level similarity. See [Deduplication](deduplication.md) | +| `fuzzyThreshold` | `number` | `0.85` | Similarity threshold for fuzzy dedup (0-1) | +| `embedSummaryId` | `boolean` | `false` | Embed `summary_id` in compressed content for downstream reference. See [Provenance](provenance.md) | +| `forceConverge` | `boolean` | `false` | Hard-truncate non-recency messages when binary search bottoms out. See [Token budget](token-budget.md) | +| `preservePatterns` | `Array<{ re: RegExp; label: string }>` | - | Custom regex patterns that force hard T0 preservation. See [Preservation rules](preservation-rules.md) | +| `classifier` | `Classifier` | - | LLM-powered classifier. When provided, `compress()` returns a `Promise`. See [LLM integration](llm-integration.md) | +| `classifierMode` | `'hybrid' \| 'full'` | `'hybrid'` | Classification mode. `'hybrid'`: heuristics first, LLM for prose. `'full'`: LLM for all eligible. Ignored without `classifier` | +| `tokenCounter` | `(msg: Message) => number` | `defaultTokenCounter` | Custom token counter per message. See [Token budget](token-budget.md) | +| `importanceScoring` | `boolean` | `false` | Score messages by forward-reference density, decision/correction content, and recency. High-importance messages are preserved outside the recency window. `forceConverge` truncates low-importance first. **Note:** preserving extra messages reduces compression ratio, which may make `tokenBudget` harder to meet | +| `importanceThreshold` | `number` | `0.35` | Importance score threshold for preservation (0–1). Only used when `importanceScoring: true` | +| `contradictionDetection` | `boolean` | `false` | Detect later messages that correct/override earlier ones. Superseded messages are compressed with a provenance annotation | +| `contradictionTopicThreshold` | `number` | `0.15` | IDF-weighted Dice similarity threshold for topic overlap in contradiction detection (0–1) | ### CompressResult diff --git a/src/contradiction.ts b/src/contradiction.ts index 6818c98..72974b5 100644 --- a/src/contradiction.ts +++ b/src/contradiction.ts @@ -22,19 +22,27 @@ export type ContradictionAnnotation = { // ── Topic overlap (IDF-weighted Sørensen-Dice) ────────────────── -/** Extract all lowercase words (3+ chars) from content. */ +/** Extract topic words from content: plain words (3+ chars) plus technical identifiers. */ function extractRawWords(content: string): Set { const words = new Set(); - const matches = content.toLowerCase().match(/\b[a-z]{3,}\b/g); - if (matches) { - for (const w of matches) words.add(w); + // Plain lowercase words (3+ chars) + const plain = content.toLowerCase().match(/\b[a-z]{3,}\b/g); + if (plain) { + for (const w of plain) words.add(w); + } + // camelCase, PascalCase, snake_case — lowercased for uniform matching + const identifiers = content.match( + /\b[a-z]+(?:[A-Z][a-z]+)+\b|\b[A-Z][a-z]+(?:[A-Z][a-z]+)+\b|\b[a-z]+(?:_[a-z]+)+\b/g, + ); + if (identifiers) { + for (const id of identifiers) words.add(id.toLowerCase()); } return words; } /** * Compute IDF weights for all words across a set of documents. - * Uses BM25-style IDF: `log((N - df + 0.5) / (df + 0.5))`. + * Uses smoothed IDF: `log(1 + N/df)`. * * Language-agnostic: common words get low weight regardless of language. * No hardcoded stopword list needed. diff --git a/tests/importance.test.ts b/tests/importance.test.ts index b467639..fb6aa79 100644 --- a/tests/importance.test.ts +++ b/tests/importance.test.ts @@ -91,7 +91,7 @@ describe('computeImportance', () => { ]; const scores = computeImportance(messages); - for (const [_, score] of scores) { + for (const score of scores.values()) { expect(score).toBeGreaterThanOrEqual(0); expect(score).toBeLessThanOrEqual(1); } From f0b6a6f610f6fe2a26369c067e0eb260772fbd35 Mon Sep 17 00:00:00 2001 From: Lisa Date: Fri, 20 Mar 2026 19:05:20 +0100 Subject: [PATCH 5/6] chore: update baseline and benchmark docs for v1.1.0 + ANCS features --- bench/baselines/current.json | 48 ++++- bench/baselines/history/v1.1.0.json | 312 ++++++++++++++++++++++++++++ docs/benchmark-results.md | 304 ++++++++++++++------------- 3 files changed, 511 insertions(+), 153 deletions(-) create mode 100644 bench/baselines/history/v1.1.0.json diff --git a/bench/baselines/current.json b/bench/baselines/current.json index 0df7740..7fdf03b 100644 --- a/bench/baselines/current.json +++ b/bench/baselines/current.json @@ -1,6 +1,6 @@ { "version": "1.1.0", - "generated": "2026-03-20T15:50:37.630Z", + "generated": "2026-03-20T18:05:08.551Z", "results": { "basic": { "Coding assistant": { @@ -200,8 +200,12 @@ "gzipBytes": 4452 }, "compress.js": { - "bytes": 48312, - "gzipBytes": 10901 + "bytes": 53439, + "gzipBytes": 11671 + }, + "contradiction.js": { + "bytes": 7700, + "gzipBytes": 2717 }, "dedup.js": { "bytes": 10260, @@ -215,9 +219,13 @@ "bytes": 11923, "gzipBytes": 2941 }, + "importance.js": { + "bytes": 4759, + "gzipBytes": 1849 + }, "index.js": { - "bytes": 608, - "gzipBytes": 311 + "bytes": 854, + "gzipBytes": 405 }, "summarizer.js": { "bytes": 2542, @@ -228,8 +236,8 @@ "gzipBytes": 31 }, "total": { - "bytes": 96252, - "gzipBytes": 26383 + "bytes": 114084, + "gzipBytes": 31813 } }, "retention": { @@ -273,6 +281,32 @@ "entityRetention": 0.918918918918919, "structuralRetention": 1 } + }, + "ancs": { + "Deep conversation": { + "baselineRatio": 2.3650251770931128, + "importanceRatio": 2.3650251770931128, + "contradictionRatio": 2.3650251770931128, + "combinedRatio": 2.3650251770931128, + "importancePreserved": 0, + "contradicted": 0 + }, + "Agentic coding session": { + "baselineRatio": 1.4749403341288783, + "importanceRatio": 1.2383115148276784, + "contradictionRatio": 1.4749403341288783, + "combinedRatio": 1.2383115148276784, + "importancePreserved": 4, + "contradicted": 0 + }, + "Iterative design": { + "baselineRatio": 1.6188055908513341, + "importanceRatio": 1.2567200986436498, + "contradictionRatio": 1.61572606214331, + "combinedRatio": 1.2567200986436498, + "importancePreserved": 6, + "contradicted": 2 + } } } } diff --git a/bench/baselines/history/v1.1.0.json b/bench/baselines/history/v1.1.0.json new file mode 100644 index 0000000..7fdf03b --- /dev/null +++ b/bench/baselines/history/v1.1.0.json @@ -0,0 +1,312 @@ +{ + "version": "1.1.0", + "generated": "2026-03-20T18:05:08.551Z", + "results": { + "basic": { + "Coding assistant": { + "ratio": 1.9385451505016722, + "tokenRatio": 1.9275362318840579, + "compressed": 5, + "preserved": 8 + }, + "Long Q&A": { + "ratio": 4.902912621359223, + "tokenRatio": 4.87689713322091, + "compressed": 4, + "preserved": 6 + }, + "Tool-heavy": { + "ratio": 1.4128440366972477, + "tokenRatio": 1.4043583535108959, + 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-_Auto-generated by `npm run bench:save`. Do not edit manually._ +*Auto-generated by `npm run bench:save`. Do not edit manually.* **v1.1.0** · Generated: 2026-03-20 -![avg ratio](https://img.shields.io/badge/avg%20ratio-2.01x-blue) ![best](https://img.shields.io/badge/best-4.90x-blue) ![scenarios](https://img.shields.io/badge/scenarios-8-blue) ![round-trip](https://img.shields.io/badge/round--trip-all_PASS-brightgreen) ![gzip](https://img.shields.io/badge/gzip-25.8%20KB-blue) +![avg ratio](https://img.shields.io/badge/avg%20ratio-2.01x-blue) ![best](https://img.shields.io/badge/best-4.90x-blue) ![scenarios](https://img.shields.io/badge/scenarios-8-blue) ![round-trip](https://img.shields.io/badge/round--trip-all_PASS-brightgreen) ![gzip](https://img.shields.io/badge/gzip-31.1%20KB-blue) ## Summary -| Metric | Value | -| -------------------- | -------- | -| Scenarios | 8 | -| Average compression | 2.01x | -| Best compression | 4.90x | +| Metric | Value | +| --- | --- | +| Scenarios | 8 | +| Average compression | 2.01x | +| Best compression | 4.90x | | Round-trip integrity | all PASS | ```mermaid @@ -35,16 +35,16 @@ xychart-beta bar [1.94, 4.90, 1.41, 1.00, 2.50, 1.00, 1.86, 1.48] ``` -| Scenario | Ratio | Reduction | Token Ratio | Messages | Compressed | Preserved | -| ---------------------- | ----: | --------: | ----------: | -------: | ---------: | --------: | -| Coding assistant | 1.94 | 48% | 1.93 | 13 | 5 | 8 | -| Long Q&A | 4.90 | 80% | 4.88 | 10 | 4 | 6 | -| Tool-heavy | 1.41 | 29% | 1.40 | 18 | 2 | 16 | -| Short conversation | 1.00 | 0% | 1.00 | 7 | 0 | 7 | -| Deep conversation | 2.50 | 60% | 2.49 | 51 | 50 | 1 | -| Technical explanation | 1.00 | 0% | 1.00 | 11 | 0 | 11 | -| Structured content | 1.86 | 46% | 1.85 | 12 | 2 | 10 | -| Agentic coding session | 1.48 | 32% | 1.47 | 33 | 2 | 31 | +| Scenario | Ratio | Reduction | Token Ratio | Messages | Compressed | Preserved | +| --- | ---: | ---: | ---: | ---: | ---: | ---: | +| Coding assistant | 1.94 | 48% | 1.93 | 13 | 5 | 8 | +| Long Q&A | 4.90 | 80% | 4.88 | 10 | 4 | 6 | +| Tool-heavy | 1.41 | 29% | 1.40 | 18 | 2 | 16 | +| Short conversation | 1.00 | 0% | 1.00 | 7 | 0 | 7 | +| Deep conversation | 2.50 | 60% | 2.49 | 51 | 50 | 1 | +| Technical explanation | 1.00 | 0% | 1.00 | 11 | 0 | 11 | +| Structured content | 1.86 | 46% | 1.85 | 12 | 2 | 10 | +| Agentic coding session | 1.48 | 32% | 1.47 | 33 | 2 | 31 | ## Deduplication Impact @@ -57,60 +57,72 @@ xychart-beta bar [4.90, 1.48] ``` -_First bar: no dedup · Second bar: with dedup_ +*First bar: no dedup · Second bar: with dedup* -| Scenario | No Dedup (rw=0) | Dedup (rw=0) | No Dedup (rw=4) | Dedup (rw=4) | Deduped | -| ---------------------- | --------------: | -----------: | --------------: | -----------: | ------: | -| Coding assistant | 1.94 | 1.94 | 1.61 | 1.61 | 0 | -| Long Q&A | 4.00 | 4.90 | 1.76 | 1.92 | 1 | -| Tool-heavy | 1.41 | 1.41 | 1.41 | 1.41 | 0 | -| Short conversation | 1.00 | 1.00 | 1.00 | 1.00 | 0 | -| Deep conversation | 2.50 | 2.50 | 2.24 | 2.24 | 0 | -| Technical explanation | 1.00 | 1.00 | 1.00 | 1.00 | 0 | -| Structured content | 1.86 | 1.86 | 1.33 | 1.33 | 0 | -| Agentic coding session | 1.20 | 1.48 | 1.20 | 1.48 | 4 | +| Scenario | No Dedup (rw=0) | Dedup (rw=0) | No Dedup (rw=4) | Dedup (rw=4) | Deduped | +| --- | ---: | ---: | ---: | ---: | ---: | +| Coding assistant | 1.94 | 1.94 | 1.61 | 1.61 | 0 | +| Long Q&A | 4.00 | 4.90 | 1.76 | 1.92 | 1 | +| Tool-heavy | 1.41 | 1.41 | 1.41 | 1.41 | 0 | +| Short conversation | 1.00 | 1.00 | 1.00 | 1.00 | 0 | +| Deep conversation | 2.50 | 2.50 | 2.24 | 2.24 | 0 | +| Technical explanation | 1.00 | 1.00 | 1.00 | 1.00 | 0 | +| Structured content | 1.86 | 1.86 | 1.33 | 1.33 | 0 | +| Agentic coding session | 1.20 | 1.48 | 1.20 | 1.48 | 4 | ### Fuzzy Dedup -| Scenario | Exact Deduped | Fuzzy Deduped | Ratio | vs Base | -| ---------------------- | ------------: | ------------: | ----: | ------: | -| Coding assistant | 0 | 0 | 1.94 | - | -| Long Q&A | 1 | 0 | 4.90 | - | -| Tool-heavy | 0 | 0 | 1.41 | - | -| Short conversation | 0 | 0 | 1.00 | - | -| Deep conversation | 0 | 0 | 2.50 | - | -| Technical explanation | 0 | 0 | 1.00 | - | -| Structured content | 0 | 0 | 1.86 | - | -| Agentic coding session | 4 | 2 | 2.35 | +59% | +| Scenario | Exact Deduped | Fuzzy Deduped | Ratio | vs Base | +| --- | ---: | ---: | ---: | ---: | +| Coding assistant | 0 | 0 | 1.94 | - | +| Long Q&A | 1 | 0 | 4.90 | - | +| Tool-heavy | 0 | 0 | 1.41 | - | +| Short conversation | 0 | 0 | 1.00 | - | +| Deep conversation | 0 | 0 | 2.50 | - | +| Technical explanation | 0 | 0 | 1.00 | - | +| Structured content | 0 | 0 | 1.86 | - | +| Agentic coding session | 4 | 2 | 2.35 | +59% | + +## ANCS-Inspired Features + +> Importance scoring preserves high-value messages outside the recency window. Contradiction detection compresses superseded messages. + +| Scenario | Baseline | +Importance | +Contradiction | Combined | Imp. Preserved | Contradicted | +| --- | ---: | ---: | ---: | ---: | ---: | ---: | +| Deep conversation | 2.37 | 2.37 | 2.37 | 2.37 | 0 | 0 | +| Agentic coding session | 1.47 | 1.24 | 1.47 | 1.24 | 4 | 0 | +| Iterative design | 1.62 | 1.26 | 1.62 | 1.26 | 6 | 2 | ## Token Budget Target: **2000 tokens** · 1/4 fit -| Scenario | Dedup | Tokens | Fits | recencyWindow | Compressed | Preserved | Deduped | -| ---------------------- | ----- | -----: | ---- | ------------: | ---------: | --------: | ------: | -| Deep conversation | no | 3188 | no | 0 | 50 | 1 | 0 | -| Deep conversation | yes | 3188 | no | 0 | 50 | 1 | 0 | -| Agentic coding session | no | 2223 | no | 0 | 4 | 33 | 0 | -| Agentic coding session | yes | 1900 | yes | 9 | 1 | 32 | 4 | +| Scenario | Dedup | Tokens | Fits | recencyWindow | Compressed | Preserved | Deduped | +| --- | --- | ---: | --- | ---: | ---: | ---: | ---: | +| Deep conversation | no | 3188 | no | 0 | 50 | 1 | 0 | +| Deep conversation | yes | 3188 | no | 0 | 50 | 1 | 0 | +| Agentic coding session | no | 2223 | no | 0 | 4 | 33 | 0 | +| Agentic coding session | yes | 1900 | yes | 9 | 1 | 32 | 4 | ## Bundle Size > Zero-dependency ESM library — tracked per-file to catch regressions. -| File | Size | Gzip | -| ------------- | ------: | ------: | -| adapters.js | 4.1 KB | 1.3 KB | -| classifier.js | 4.5 KB | 1.6 KB | -| classify.js | 10.7 KB | 4.3 KB | -| compress.js | 47.2 KB | 10.6 KB | -| dedup.js | 10.0 KB | 2.8 KB | -| expand.js | 2.7 KB | 934 B | -| feedback.js | 11.6 KB | 2.9 KB | -| index.js | 608 B | 311 B | -| summarizer.js | 2.5 KB | 993 B | -| types.js | 11 B | 31 B | -| **total** | 94.0 KB | 25.8 KB | +| File | Size | Gzip | +| --- | ---: | ---: | +| adapters.js | 4.1 KB | 1.3 KB | +| classifier.js | 4.5 KB | 1.6 KB | +| classify.js | 10.7 KB | 4.3 KB | +| compress.js | 52.2 KB | 11.4 KB | +| contradiction.js | 7.5 KB | 2.7 KB | +| dedup.js | 10.0 KB | 2.8 KB | +| expand.js | 2.7 KB | 934 B | +| feedback.js | 11.6 KB | 2.9 KB | +| importance.js | 4.6 KB | 1.8 KB | +| index.js | 854 B | 405 B | +| summarizer.js | 2.5 KB | 993 B | +| types.js | 11 B | 31 B | +| **total** | 111.4 KB | 31.1 KB | ## LLM vs Deterministic @@ -172,10 +184,10 @@ Agentic coding session Det ████████░░░░░░░░░ ### Provider Summary -| Provider | Model | Avg Ratio | Avg vsDet | Round-trip | Budget Fits | Avg Time | -| -------- | ------------ | --------: | --------: | ---------- | ----------- | -------: | -| ollama | llama3.2 | 2.09x | 0.96 | all PASS | 1/4 | 4.2s | -| openai | gpt-4.1-mini | 2.09x | 0.92 | all PASS | 2/4 | 8.1s | +| Provider | Model | Avg Ratio | Avg vsDet | Round-trip | Budget Fits | Avg Time | +| --- | --- | ---: | ---: | --- | --- | ---: | +| ollama | llama3.2 | 2.09x | 0.96 | all PASS | 1/4 | 4.2s | +| openai | gpt-4.1-mini | 2.09x | 0.92 | all PASS | 2/4 | 8.1s | > **Key findings:** > LLM wins on prose-heavy scenarios: Deep conversation, Technical explanation @@ -183,125 +195,125 @@ Agentic coding session Det ████████░░░░░░░░░ ### ollama (llama3.2) -_Generated: 2026-02-25_ +*Generated: 2026-02-25*
Scenario details -| Scenario | Method | Char Ratio | Token Ratio | vsDet | Compressed | Preserved | Round-trip | Time | -| ---------------------- | ------------- | ---------: | ----------: | ----: | ---------: | --------: | ---------- | ----: | -| Coding assistant | deterministic | 1.68 | 1.67 | - | 5 | 8 | PASS | 0ms | -| | llm-basic | 1.48 | 1.48 | 0.88 | 5 | 8 | PASS | 5.9s | -| | llm-escalate | 1.55 | 1.55 | 0.92 | 5 | 8 | PASS | 3.0s | -| Long Q&A | deterministic | 6.16 | 6.11 | - | 4 | 6 | PASS | 1ms | -| | llm-basic | 4.31 | 4.28 | 0.70 | 4 | 6 | PASS | 4.1s | -| | llm-escalate | 4.49 | 4.46 | 0.73 | 4 | 6 | PASS | 3.7s | -| Tool-heavy | deterministic | 1.30 | 1.29 | - | 2 | 16 | PASS | 2ms | -| | llm-basic | 1.12 | 1.11 | 0.86 | 2 | 16 | PASS | 2.3s | -| | llm-escalate | 1.28 | 1.28 | 0.99 | 2 | 16 | PASS | 2.8s | -| Deep conversation | deterministic | 2.12 | 2.12 | - | 50 | 1 | PASS | 3ms | -| | llm-basic | 3.12 | 3.11 | 1.47 | 50 | 1 | PASS | 22.7s | -| | llm-escalate | 3.28 | 3.26 | 1.54 | 50 | 1 | PASS | 23.3s | -| Technical explanation | deterministic | 1.00 | 1.00 | - | 0 | 11 | PASS | 1ms | -| | llm-basic | 1.00 | 1.00 | 1.00 | 0 | 11 | PASS | 3.2s | -| | llm-escalate | 1.00 | 1.00 | 1.00 | 2 | 9 | PASS | 785ms | -| Structured content | deterministic | 1.93 | 1.92 | - | 2 | 10 | PASS | 0ms | -| | llm-basic | 1.46 | 1.45 | 0.75 | 2 | 10 | PASS | 3.5s | -| | llm-escalate | 1.38 | 1.38 | 0.71 | 2 | 10 | PASS | 3.7s | -| Agentic coding session | deterministic | 1.43 | 1.43 | - | 2 | 31 | PASS | 1ms | -| | llm-basic | 1.35 | 1.34 | 0.94 | 2 | 31 | PASS | 3.3s | -| | llm-escalate | 1.40 | 1.40 | 0.98 | 2 | 31 | PASS | 5.4s | +| Scenario | Method | Char Ratio | Token Ratio | vsDet | Compressed | Preserved | Round-trip | Time | +| --- | --- | ---: | ---: | ---: | ---: | ---: | --- | ---: | +| Coding assistant | deterministic | 1.68 | 1.67 | - | 5 | 8 | PASS | 0ms | +| | llm-basic | 1.48 | 1.48 | 0.88 | 5 | 8 | PASS | 5.9s | +| | llm-escalate | 1.55 | 1.55 | 0.92 | 5 | 8 | PASS | 3.0s | +| Long Q&A | deterministic | 6.16 | 6.11 | - | 4 | 6 | PASS | 1ms | +| | llm-basic | 4.31 | 4.28 | 0.70 | 4 | 6 | PASS | 4.1s | +| | llm-escalate | 4.49 | 4.46 | 0.73 | 4 | 6 | PASS | 3.7s | +| Tool-heavy | deterministic | 1.30 | 1.29 | - | 2 | 16 | PASS | 2ms | +| | llm-basic | 1.12 | 1.11 | 0.86 | 2 | 16 | PASS | 2.3s | +| | llm-escalate | 1.28 | 1.28 | 0.99 | 2 | 16 | PASS | 2.8s | +| Deep conversation | deterministic | 2.12 | 2.12 | - | 50 | 1 | PASS | 3ms | +| | llm-basic | 3.12 | 3.11 | 1.47 | 50 | 1 | PASS | 22.7s | +| | llm-escalate | 3.28 | 3.26 | 1.54 | 50 | 1 | PASS | 23.3s | +| Technical explanation | deterministic | 1.00 | 1.00 | - | 0 | 11 | PASS | 1ms | +| | llm-basic | 1.00 | 1.00 | 1.00 | 0 | 11 | PASS | 3.2s | +| | llm-escalate | 1.00 | 1.00 | 1.00 | 2 | 9 | PASS | 785ms | +| Structured content | deterministic | 1.93 | 1.92 | - | 2 | 10 | PASS | 0ms | +| | llm-basic | 1.46 | 1.45 | 0.75 | 2 | 10 | PASS | 3.5s | +| | llm-escalate | 1.38 | 1.38 | 0.71 | 2 | 10 | PASS | 3.7s | +| Agentic coding session | deterministic | 1.43 | 1.43 | - | 2 | 31 | PASS | 1ms | +| | llm-basic | 1.35 | 1.34 | 0.94 | 2 | 31 | PASS | 3.3s | +| | llm-escalate | 1.40 | 1.40 | 0.98 | 2 | 31 | PASS | 5.4s | #### Token Budget (target: 2000 tokens) -| Scenario | Method | Tokens | Fits | recencyWindow | Ratio | Round-trip | Time | -| ---------------------- | ------------- | -----: | ----- | ------------: | ----: | ---------- | -----: | -| Deep conversation | deterministic | 3738 | false | 0 | 2.12 | PASS | 12ms | -| | llm-escalate | 2593 | false | 0 | 3.08 | PASS | 132.0s | -| Agentic coding session | deterministic | 1957 | true | 9 | 1.36 | PASS | 2ms | -| | llm-escalate | 2003 | false | 9 | 1.33 | PASS | 4.1s | +| Scenario | Method | Tokens | Fits | recencyWindow | Ratio | Round-trip | Time | +| --- | --- | ---: | --- | ---: | ---: | --- | ---: | +| Deep conversation | deterministic | 3738 | false | 0 | 2.12 | PASS | 12ms | +| | llm-escalate | 2593 | false | 0 | 3.08 | PASS | 132.0s | +| Agentic coding session | deterministic | 1957 | true | 9 | 1.36 | PASS | 2ms | +| | llm-escalate | 2003 | false | 9 | 1.33 | PASS | 4.1s |
### openai (gpt-4.1-mini) -_Generated: 2026-02-25_ +*Generated: 2026-02-25*
Scenario details -| Scenario | Method | Char Ratio | Token Ratio | vsDet | Compressed | Preserved | Round-trip | Time | -| ---------------------- | ------------- | ---------: | ----------: | ----: | ---------: | --------: | ---------- | ----: | -| Coding assistant | deterministic | 1.68 | 1.67 | - | 5 | 8 | PASS | 0ms | -| | llm-basic | 1.64 | 1.63 | 0.98 | 5 | 8 | PASS | 5.6s | -| | llm-escalate | 1.63 | 1.63 | 0.97 | 5 | 8 | PASS | 6.0s | -| Long Q&A | deterministic | 6.16 | 6.11 | - | 4 | 6 | PASS | 1ms | -| | llm-basic | 5.37 | 5.33 | 0.87 | 4 | 6 | PASS | 5.9s | -| | llm-escalate | 5.35 | 5.31 | 0.87 | 4 | 6 | PASS | 7.0s | -| Tool-heavy | deterministic | 1.30 | 1.29 | - | 2 | 16 | PASS | 0ms | -| | llm-basic | 1.11 | 1.10 | 0.85 | 2 | 16 | PASS | 3.5s | -| | llm-escalate | 1.12 | 1.12 | 0.86 | 2 | 16 | PASS | 5.3s | -| Deep conversation | deterministic | 2.12 | 2.12 | - | 50 | 1 | PASS | 3ms | -| | llm-basic | 2.34 | 2.33 | 1.10 | 50 | 1 | PASS | 50.4s | -| | llm-escalate | 2.37 | 2.36 | 1.11 | 50 | 1 | PASS | 50.8s | -| Technical explanation | deterministic | 1.00 | 1.00 | - | 0 | 11 | PASS | 1ms | -| | llm-basic | 1.00 | 1.00 | 1.00 | 1 | 10 | PASS | 2.6s | -| | llm-escalate | 1.00 | 1.00 | 1.00 | 1 | 10 | PASS | 3.3s | -| Structured content | deterministic | 1.93 | 1.92 | - | 2 | 10 | PASS | 0ms | -| | llm-basic | 1.23 | 1.23 | 0.64 | 2 | 10 | PASS | 10.2s | -| | llm-escalate | 1.29 | 1.29 | 0.67 | 2 | 10 | PASS | 4.8s | -| Agentic coding session | deterministic | 1.43 | 1.43 | - | 2 | 31 | PASS | 1ms | -| | llm-basic | 1.43 | 1.43 | 1.00 | 2 | 31 | PASS | 5.8s | -| | llm-escalate | 1.32 | 1.32 | 0.93 | 1 | 32 | PASS | 9.5s | +| Scenario | Method | Char Ratio | Token Ratio | vsDet | Compressed | Preserved | Round-trip | Time | +| --- | --- | ---: | ---: | ---: | ---: | ---: | --- | ---: | +| Coding assistant | deterministic | 1.68 | 1.67 | - | 5 | 8 | PASS | 0ms | +| | llm-basic | 1.64 | 1.63 | 0.98 | 5 | 8 | PASS | 5.6s | +| | llm-escalate | 1.63 | 1.63 | 0.97 | 5 | 8 | PASS | 6.0s | +| Long Q&A | deterministic | 6.16 | 6.11 | - | 4 | 6 | PASS | 1ms | +| | llm-basic | 5.37 | 5.33 | 0.87 | 4 | 6 | PASS | 5.9s | +| | llm-escalate | 5.35 | 5.31 | 0.87 | 4 | 6 | PASS | 7.0s | +| Tool-heavy | deterministic | 1.30 | 1.29 | - | 2 | 16 | PASS | 0ms | +| | llm-basic | 1.11 | 1.10 | 0.85 | 2 | 16 | PASS | 3.5s | +| | llm-escalate | 1.12 | 1.12 | 0.86 | 2 | 16 | PASS | 5.3s | +| Deep conversation | deterministic | 2.12 | 2.12 | - | 50 | 1 | PASS | 3ms | +| | llm-basic | 2.34 | 2.33 | 1.10 | 50 | 1 | PASS | 50.4s | +| | llm-escalate | 2.37 | 2.36 | 1.11 | 50 | 1 | PASS | 50.8s | +| Technical explanation | deterministic | 1.00 | 1.00 | - | 0 | 11 | PASS | 1ms | +| | llm-basic | 1.00 | 1.00 | 1.00 | 1 | 10 | PASS | 2.6s | +| | llm-escalate | 1.00 | 1.00 | 1.00 | 1 | 10 | PASS | 3.3s | +| Structured content | deterministic | 1.93 | 1.92 | - | 2 | 10 | PASS | 0ms | +| | llm-basic | 1.23 | 1.23 | 0.64 | 2 | 10 | PASS | 10.2s | +| | llm-escalate | 1.29 | 1.29 | 0.67 | 2 | 10 | PASS | 4.8s | +| Agentic coding session | deterministic | 1.43 | 1.43 | - | 2 | 31 | PASS | 1ms | +| | llm-basic | 1.43 | 1.43 | 1.00 | 2 | 31 | PASS | 5.8s | +| | llm-escalate | 1.32 | 1.32 | 0.93 | 1 | 32 | PASS | 9.5s | #### Token Budget (target: 2000 tokens) -| Scenario | Method | Tokens | Fits | recencyWindow | Ratio | Round-trip | Time | -| ---------------------- | ------------- | -----: | ----- | ------------: | ----: | ---------- | -----: | -| Deep conversation | deterministic | 3738 | false | 0 | 2.12 | PASS | 10ms | -| | llm-escalate | 3391 | false | 0 | 2.35 | PASS | 280.5s | -| Agentic coding session | deterministic | 1957 | true | 9 | 1.36 | PASS | 2ms | -| | llm-escalate | 1915 | true | 3 | 1.39 | PASS | 28.1s | +| Scenario | Method | Tokens | Fits | recencyWindow | Ratio | Round-trip | Time | +| --- | --- | ---: | --- | ---: | ---: | --- | ---: | +| Deep conversation | deterministic | 3738 | false | 0 | 2.12 | PASS | 10ms | +| | llm-escalate | 3391 | false | 0 | 2.35 | PASS | 280.5s | +| Agentic coding session | deterministic | 1957 | true | 9 | 1.36 | PASS | 2ms | +| | llm-escalate | 1915 | true | 3 | 1.39 | PASS | 28.1s |
## Version History -| Version | Date | Avg Char Ratio | Avg Token Ratio | Scenarios | -| ------- | ---------- | -------------: | --------------: | --------: | -| 1.1.0 | 2026-03-20 | 2.01 | 2.00 | 8 | -| 1.0.0 | 2026-03-10 | 2.01 | 2.00 | 8 | +| Version | Date | Avg Char Ratio | Avg Token Ratio | Scenarios | +| --- | --- | ---: | ---: | ---: | +| 1.1.0 | 2026-03-20 | 2.01 | 2.00 | 8 | +| 1.0.0 | 2026-03-10 | 2.01 | 2.00 | 8 | ### v1.0.0 → v1.1.0 > **2.01x** → **2.01x** avg compression (0.00%) -| Scenario | v1.0.0 | v1.1.0 | Change | Token Δ | | -| ---------------------- | -----: | -----: | -----: | ------: | --- | -| Coding assistant | 1.94x | 1.94x | 0.00% | 0.00% | ─ | -| Long Q&A | 4.90x | 4.90x | 0.00% | 0.00% | ─ | -| Tool-heavy | 1.41x | 1.41x | 0.00% | 0.00% | ─ | -| Short conversation | 1.00x | 1.00x | 0.00% | 0.00% | ─ | -| Deep conversation | 2.50x | 2.50x | 0.00% | 0.00% | ─ | -| Technical explanation | 1.00x | 1.00x | 0.00% | 0.00% | ─ | -| Structured content | 1.86x | 1.86x | 0.00% | 0.00% | ─ | -| Agentic coding session | 1.48x | 1.48x | 0.00% | 0.00% | ─ | +| Scenario | v1.0.0 | v1.1.0 | Change | Token Δ | | +| --- | ---: | ---: | ---: | ---: | --- | +| Coding assistant | 1.94x | 1.94x | 0.00% | 0.00% | ─| +| Long Q&A | 4.90x | 4.90x | 0.00% | 0.00% | ─| +| Tool-heavy | 1.41x | 1.41x | 0.00% | 0.00% | ─| +| Short conversation | 1.00x | 1.00x | 0.00% | 0.00% | ─| +| Deep conversation | 2.50x | 2.50x | 0.00% | 0.00% | ─| +| Technical explanation | 1.00x | 1.00x | 0.00% | 0.00% | ─| +| Structured content | 1.86x | 1.86x | 0.00% | 0.00% | ─| +| Agentic coding session | 1.48x | 1.48x | 0.00% | 0.00% | ─| -Bundle: 57.0 KB → 94.0 KB (+64.89%) +Bundle: 57.0 KB → 111.4 KB (+95.44%)
v1.0.0 (2026-03-10) — 2.01x avg -| Scenario | Char Ratio | Token Ratio | Compressed | Preserved | -| ---------------------- | ---------: | ----------: | ---------: | --------: | -| Coding assistant | 1.94 | 1.93 | 5 | 8 | -| Long Q&A | 4.90 | 4.88 | 4 | 6 | -| Tool-heavy | 1.41 | 1.40 | 2 | 16 | -| Short conversation | 1.00 | 1.00 | 0 | 7 | -| Deep conversation | 2.50 | 2.49 | 50 | 1 | -| Technical explanation | 1.00 | 1.00 | 0 | 11 | -| Structured content | 1.86 | 1.85 | 2 | 10 | -| Agentic coding session | 1.48 | 1.47 | 2 | 31 | +| Scenario | Char Ratio | Token Ratio | Compressed | Preserved | +| --- | ---: | ---: | ---: | ---: | +| Coding assistant | 1.94 | 1.93 | 5 | 8 | +| Long Q&A | 4.90 | 4.88 | 4 | 6 | +| Tool-heavy | 1.41 | 1.40 | 2 | 16 | +| Short conversation | 1.00 | 1.00 | 0 | 7 | +| Deep conversation | 2.50 | 2.49 | 50 | 1 | +| Technical explanation | 1.00 | 1.00 | 0 | 11 | +| Structured content | 1.86 | 1.85 | 2 | 10 | +| Agentic coding session | 1.48 | 1.47 | 2 | 31 |
From d21daa3fd79e85bd6166ba2181d4ccff61350c3c Mon Sep 17 00:00:00 2001 From: Lisa Date: Fri, 20 Mar 2026 19:09:36 +0100 Subject: [PATCH 6/6] chore: format benchmark-results.md --- docs/benchmark-results.md | 302 +++++++++++++++++++------------------- 1 file changed, 151 insertions(+), 151 deletions(-) diff --git a/docs/benchmark-results.md b/docs/benchmark-results.md index 45d5850..24af4a5 100644 --- a/docs/benchmark-results.md +++ b/docs/benchmark-results.md @@ -2,7 +2,7 @@ [Back to README](../README.md) | [All docs](README.md) | [Handbook](benchmarks.md) -*Auto-generated by `npm run bench:save`. Do not edit manually.* +_Auto-generated by `npm run bench:save`. Do not edit manually._ **v1.1.0** · Generated: 2026-03-20 @@ -10,11 +10,11 @@ ## Summary -| Metric | Value | -| --- | --- | -| Scenarios | 8 | -| Average compression | 2.01x | -| Best compression | 4.90x | +| Metric | Value | +| -------------------- | -------- | +| Scenarios | 8 | +| Average compression | 2.01x | +| Best compression | 4.90x | | Round-trip integrity | all PASS | ```mermaid @@ -35,16 +35,16 @@ xychart-beta bar [1.94, 4.90, 1.41, 1.00, 2.50, 1.00, 1.86, 1.48] ``` -| Scenario | Ratio | Reduction | Token Ratio | Messages | Compressed | Preserved | -| --- | ---: | ---: | ---: | ---: | ---: | ---: | -| Coding assistant | 1.94 | 48% | 1.93 | 13 | 5 | 8 | -| Long Q&A | 4.90 | 80% | 4.88 | 10 | 4 | 6 | -| Tool-heavy | 1.41 | 29% | 1.40 | 18 | 2 | 16 | -| Short conversation | 1.00 | 0% | 1.00 | 7 | 0 | 7 | -| Deep conversation | 2.50 | 60% | 2.49 | 51 | 50 | 1 | -| Technical explanation | 1.00 | 0% | 1.00 | 11 | 0 | 11 | -| Structured content | 1.86 | 46% | 1.85 | 12 | 2 | 10 | -| Agentic coding session | 1.48 | 32% | 1.47 | 33 | 2 | 31 | +| Scenario | Ratio | Reduction | Token Ratio | Messages | Compressed | Preserved | +| ---------------------- | ----: | --------: | ----------: | -------: | ---------: | --------: | +| Coding assistant | 1.94 | 48% | 1.93 | 13 | 5 | 8 | +| Long Q&A | 4.90 | 80% | 4.88 | 10 | 4 | 6 | +| Tool-heavy | 1.41 | 29% | 1.40 | 18 | 2 | 16 | +| Short conversation | 1.00 | 0% | 1.00 | 7 | 0 | 7 | +| Deep conversation | 2.50 | 60% | 2.49 | 51 | 50 | 1 | +| Technical explanation | 1.00 | 0% | 1.00 | 11 | 0 | 11 | +| Structured content | 1.86 | 46% | 1.85 | 12 | 2 | 10 | +| Agentic coding session | 1.48 | 32% | 1.47 | 33 | 2 | 31 | ## Deduplication Impact @@ -57,72 +57,72 @@ xychart-beta bar [4.90, 1.48] ``` -*First bar: no dedup · Second bar: with dedup* +_First bar: no dedup · Second bar: with dedup_ -| Scenario | No Dedup (rw=0) | Dedup (rw=0) | No Dedup (rw=4) | Dedup (rw=4) | Deduped | -| --- | ---: | ---: | ---: | ---: | ---: | -| Coding assistant | 1.94 | 1.94 | 1.61 | 1.61 | 0 | -| Long Q&A | 4.00 | 4.90 | 1.76 | 1.92 | 1 | -| Tool-heavy | 1.41 | 1.41 | 1.41 | 1.41 | 0 | -| Short conversation | 1.00 | 1.00 | 1.00 | 1.00 | 0 | -| Deep conversation | 2.50 | 2.50 | 2.24 | 2.24 | 0 | -| Technical explanation | 1.00 | 1.00 | 1.00 | 1.00 | 0 | -| Structured content | 1.86 | 1.86 | 1.33 | 1.33 | 0 | -| Agentic coding session | 1.20 | 1.48 | 1.20 | 1.48 | 4 | +| Scenario | No Dedup (rw=0) | Dedup (rw=0) | No Dedup (rw=4) | Dedup (rw=4) | Deduped | +| ---------------------- | --------------: | -----------: | --------------: | -----------: | ------: | +| Coding assistant | 1.94 | 1.94 | 1.61 | 1.61 | 0 | +| Long Q&A | 4.00 | 4.90 | 1.76 | 1.92 | 1 | +| Tool-heavy | 1.41 | 1.41 | 1.41 | 1.41 | 0 | +| Short conversation | 1.00 | 1.00 | 1.00 | 1.00 | 0 | +| Deep conversation | 2.50 | 2.50 | 2.24 | 2.24 | 0 | +| Technical explanation | 1.00 | 1.00 | 1.00 | 1.00 | 0 | +| Structured content | 1.86 | 1.86 | 1.33 | 1.33 | 0 | +| Agentic coding session | 1.20 | 1.48 | 1.20 | 1.48 | 4 | ### Fuzzy Dedup -| Scenario | Exact Deduped | Fuzzy Deduped | Ratio | vs Base | -| --- | ---: | ---: | ---: | ---: | -| Coding assistant | 0 | 0 | 1.94 | - | -| Long Q&A | 1 | 0 | 4.90 | - | -| Tool-heavy | 0 | 0 | 1.41 | - | -| Short conversation | 0 | 0 | 1.00 | - | -| Deep conversation | 0 | 0 | 2.50 | - | -| Technical explanation | 0 | 0 | 1.00 | - | -| Structured content | 0 | 0 | 1.86 | - | -| Agentic coding session | 4 | 2 | 2.35 | +59% | +| Scenario | Exact Deduped | Fuzzy Deduped | Ratio | vs Base | +| ---------------------- | ------------: | ------------: | ----: | ------: | +| Coding assistant | 0 | 0 | 1.94 | - | +| Long Q&A | 1 | 0 | 4.90 | - | +| Tool-heavy | 0 | 0 | 1.41 | - | +| Short conversation | 0 | 0 | 1.00 | - | +| Deep conversation | 0 | 0 | 2.50 | - | +| Technical explanation | 0 | 0 | 1.00 | - | +| Structured content | 0 | 0 | 1.86 | - | +| Agentic coding session | 4 | 2 | 2.35 | +59% | ## ANCS-Inspired Features > Importance scoring preserves high-value messages outside the recency window. Contradiction detection compresses superseded messages. -| Scenario | Baseline | +Importance | +Contradiction | Combined | Imp. Preserved | Contradicted | -| --- | ---: | ---: | ---: | ---: | ---: | ---: | -| Deep conversation | 2.37 | 2.37 | 2.37 | 2.37 | 0 | 0 | -| Agentic coding session | 1.47 | 1.24 | 1.47 | 1.24 | 4 | 0 | -| Iterative design | 1.62 | 1.26 | 1.62 | 1.26 | 6 | 2 | +| Scenario | Baseline | +Importance | +Contradiction | Combined | Imp. Preserved | Contradicted | +| ---------------------- | -------: | ----------: | -------------: | -------: | -------------: | -----------: | +| Deep conversation | 2.37 | 2.37 | 2.37 | 2.37 | 0 | 0 | +| Agentic coding session | 1.47 | 1.24 | 1.47 | 1.24 | 4 | 0 | +| Iterative design | 1.62 | 1.26 | 1.62 | 1.26 | 6 | 2 | ## Token Budget Target: **2000 tokens** · 1/4 fit -| Scenario | Dedup | Tokens | Fits | recencyWindow | Compressed | Preserved | Deduped | -| --- | --- | ---: | --- | ---: | ---: | ---: | ---: | -| Deep conversation | no | 3188 | no | 0 | 50 | 1 | 0 | -| Deep conversation | yes | 3188 | no | 0 | 50 | 1 | 0 | -| Agentic coding session | no | 2223 | no | 0 | 4 | 33 | 0 | -| Agentic coding session | yes | 1900 | yes | 9 | 1 | 32 | 4 | +| Scenario | Dedup | Tokens | Fits | recencyWindow | Compressed | Preserved | Deduped | +| ---------------------- | ----- | -----: | ---- | ------------: | ---------: | --------: | ------: | +| Deep conversation | no | 3188 | no | 0 | 50 | 1 | 0 | +| Deep conversation | yes | 3188 | no | 0 | 50 | 1 | 0 | +| Agentic coding session | no | 2223 | no | 0 | 4 | 33 | 0 | +| Agentic coding session | yes | 1900 | yes | 9 | 1 | 32 | 4 | ## Bundle Size > Zero-dependency ESM library — tracked per-file to catch regressions. -| File | Size | Gzip | -| --- | ---: | ---: | -| adapters.js | 4.1 KB | 1.3 KB | -| classifier.js | 4.5 KB | 1.6 KB | -| classify.js | 10.7 KB | 4.3 KB | -| compress.js | 52.2 KB | 11.4 KB | -| contradiction.js | 7.5 KB | 2.7 KB | -| dedup.js | 10.0 KB | 2.8 KB | -| expand.js | 2.7 KB | 934 B | -| feedback.js | 11.6 KB | 2.9 KB | -| importance.js | 4.6 KB | 1.8 KB | -| index.js | 854 B | 405 B | -| summarizer.js | 2.5 KB | 993 B | -| types.js | 11 B | 31 B | -| **total** | 111.4 KB | 31.1 KB | +| File | Size | Gzip | +| ---------------- | -------: | ------: | +| adapters.js | 4.1 KB | 1.3 KB | +| classifier.js | 4.5 KB | 1.6 KB | +| classify.js | 10.7 KB | 4.3 KB | +| compress.js | 52.2 KB | 11.4 KB | +| contradiction.js | 7.5 KB | 2.7 KB | +| dedup.js | 10.0 KB | 2.8 KB | +| expand.js | 2.7 KB | 934 B | +| feedback.js | 11.6 KB | 2.9 KB | +| importance.js | 4.6 KB | 1.8 KB | +| index.js | 854 B | 405 B | +| summarizer.js | 2.5 KB | 993 B | +| types.js | 11 B | 31 B | +| **total** | 111.4 KB | 31.1 KB | ## LLM vs Deterministic @@ -184,10 +184,10 @@ Agentic coding session Det ████████░░░░░░░░░ ### Provider Summary -| Provider | Model | Avg Ratio | Avg vsDet | Round-trip | Budget Fits | Avg Time | -| --- | --- | ---: | ---: | --- | --- | ---: | -| ollama | llama3.2 | 2.09x | 0.96 | all PASS | 1/4 | 4.2s | -| openai | gpt-4.1-mini | 2.09x | 0.92 | all PASS | 2/4 | 8.1s | +| Provider | Model | Avg Ratio | Avg vsDet | Round-trip | Budget Fits | Avg Time | +| -------- | ------------ | --------: | --------: | ---------- | ----------- | -------: | +| ollama | llama3.2 | 2.09x | 0.96 | all PASS | 1/4 | 4.2s | +| openai | gpt-4.1-mini | 2.09x | 0.92 | all PASS | 2/4 | 8.1s | > **Key findings:** > LLM wins on prose-heavy scenarios: Deep conversation, Technical explanation @@ -195,125 +195,125 @@ Agentic coding session Det ████████░░░░░░░░░ ### ollama (llama3.2) -*Generated: 2026-02-25* +_Generated: 2026-02-25_
Scenario details -| Scenario | Method | Char Ratio | Token Ratio | vsDet | Compressed | Preserved | Round-trip | Time | -| --- | --- | ---: | ---: | ---: | ---: | ---: | --- | ---: | -| Coding assistant | deterministic | 1.68 | 1.67 | - | 5 | 8 | PASS | 0ms | -| | llm-basic | 1.48 | 1.48 | 0.88 | 5 | 8 | PASS | 5.9s | -| | llm-escalate | 1.55 | 1.55 | 0.92 | 5 | 8 | PASS | 3.0s | -| Long Q&A | deterministic | 6.16 | 6.11 | - | 4 | 6 | PASS | 1ms | -| | llm-basic | 4.31 | 4.28 | 0.70 | 4 | 6 | PASS | 4.1s | -| | llm-escalate | 4.49 | 4.46 | 0.73 | 4 | 6 | PASS | 3.7s | -| Tool-heavy | deterministic | 1.30 | 1.29 | - | 2 | 16 | PASS | 2ms | -| | llm-basic | 1.12 | 1.11 | 0.86 | 2 | 16 | PASS | 2.3s | -| | llm-escalate | 1.28 | 1.28 | 0.99 | 2 | 16 | PASS | 2.8s | -| Deep conversation | deterministic | 2.12 | 2.12 | - | 50 | 1 | PASS | 3ms | -| | llm-basic | 3.12 | 3.11 | 1.47 | 50 | 1 | PASS | 22.7s | -| | llm-escalate | 3.28 | 3.26 | 1.54 | 50 | 1 | PASS | 23.3s | -| Technical explanation | deterministic | 1.00 | 1.00 | - | 0 | 11 | PASS | 1ms | -| | llm-basic | 1.00 | 1.00 | 1.00 | 0 | 11 | PASS | 3.2s | -| | llm-escalate | 1.00 | 1.00 | 1.00 | 2 | 9 | PASS | 785ms | -| Structured content | deterministic | 1.93 | 1.92 | - | 2 | 10 | PASS | 0ms | -| | llm-basic | 1.46 | 1.45 | 0.75 | 2 | 10 | PASS | 3.5s | -| | llm-escalate | 1.38 | 1.38 | 0.71 | 2 | 10 | PASS | 3.7s | -| Agentic coding session | deterministic | 1.43 | 1.43 | - | 2 | 31 | PASS | 1ms | -| | llm-basic | 1.35 | 1.34 | 0.94 | 2 | 31 | PASS | 3.3s | -| | llm-escalate | 1.40 | 1.40 | 0.98 | 2 | 31 | PASS | 5.4s | +| Scenario | Method | Char Ratio | Token Ratio | vsDet | Compressed | Preserved | Round-trip | Time | +| ---------------------- | ------------- | ---------: | ----------: | ----: | ---------: | --------: | ---------- | ----: | +| Coding assistant | deterministic | 1.68 | 1.67 | - | 5 | 8 | PASS | 0ms | +| | llm-basic | 1.48 | 1.48 | 0.88 | 5 | 8 | PASS | 5.9s | +| | llm-escalate | 1.55 | 1.55 | 0.92 | 5 | 8 | PASS | 3.0s | +| Long Q&A | deterministic | 6.16 | 6.11 | - | 4 | 6 | PASS | 1ms | +| | llm-basic | 4.31 | 4.28 | 0.70 | 4 | 6 | PASS | 4.1s | +| | llm-escalate | 4.49 | 4.46 | 0.73 | 4 | 6 | PASS | 3.7s | +| Tool-heavy | deterministic | 1.30 | 1.29 | - | 2 | 16 | PASS | 2ms | +| | llm-basic | 1.12 | 1.11 | 0.86 | 2 | 16 | PASS | 2.3s | +| | llm-escalate | 1.28 | 1.28 | 0.99 | 2 | 16 | PASS | 2.8s | +| Deep conversation | deterministic | 2.12 | 2.12 | - | 50 | 1 | PASS | 3ms | +| | llm-basic | 3.12 | 3.11 | 1.47 | 50 | 1 | PASS | 22.7s | +| | llm-escalate | 3.28 | 3.26 | 1.54 | 50 | 1 | PASS | 23.3s | +| Technical explanation | deterministic | 1.00 | 1.00 | - | 0 | 11 | PASS | 1ms | +| | llm-basic | 1.00 | 1.00 | 1.00 | 0 | 11 | PASS | 3.2s | +| | llm-escalate | 1.00 | 1.00 | 1.00 | 2 | 9 | PASS | 785ms | +| Structured content | deterministic | 1.93 | 1.92 | - | 2 | 10 | PASS | 0ms | +| | llm-basic | 1.46 | 1.45 | 0.75 | 2 | 10 | PASS | 3.5s | +| | llm-escalate | 1.38 | 1.38 | 0.71 | 2 | 10 | PASS | 3.7s | +| Agentic coding session | deterministic | 1.43 | 1.43 | - | 2 | 31 | PASS | 1ms | +| | llm-basic | 1.35 | 1.34 | 0.94 | 2 | 31 | PASS | 3.3s | +| | llm-escalate | 1.40 | 1.40 | 0.98 | 2 | 31 | PASS | 5.4s | #### Token Budget (target: 2000 tokens) -| Scenario | Method | Tokens | Fits | recencyWindow | Ratio | Round-trip | Time | -| --- | --- | ---: | --- | ---: | ---: | --- | ---: | -| Deep conversation | deterministic | 3738 | false | 0 | 2.12 | PASS | 12ms | -| | llm-escalate | 2593 | false | 0 | 3.08 | PASS | 132.0s | -| Agentic coding session | deterministic | 1957 | true | 9 | 1.36 | PASS | 2ms | -| | llm-escalate | 2003 | false | 9 | 1.33 | PASS | 4.1s | +| Scenario | Method | Tokens | Fits | recencyWindow | Ratio | Round-trip | Time | +| ---------------------- | ------------- | -----: | ----- | ------------: | ----: | ---------- | -----: | +| Deep conversation | deterministic | 3738 | false | 0 | 2.12 | PASS | 12ms | +| | llm-escalate | 2593 | false | 0 | 3.08 | PASS | 132.0s | +| Agentic coding session | deterministic | 1957 | true | 9 | 1.36 | PASS | 2ms | +| | llm-escalate | 2003 | false | 9 | 1.33 | PASS | 4.1s |
### openai (gpt-4.1-mini) -*Generated: 2026-02-25* +_Generated: 2026-02-25_
Scenario details -| Scenario | Method | Char Ratio | Token Ratio | vsDet | Compressed | Preserved | Round-trip | Time | -| --- | --- | ---: | ---: | ---: | ---: | ---: | --- | ---: | -| Coding assistant | deterministic | 1.68 | 1.67 | - | 5 | 8 | PASS | 0ms | -| | llm-basic | 1.64 | 1.63 | 0.98 | 5 | 8 | PASS | 5.6s | -| | llm-escalate | 1.63 | 1.63 | 0.97 | 5 | 8 | PASS | 6.0s | -| Long Q&A | deterministic | 6.16 | 6.11 | - | 4 | 6 | PASS | 1ms | -| | llm-basic | 5.37 | 5.33 | 0.87 | 4 | 6 | PASS | 5.9s | -| | llm-escalate | 5.35 | 5.31 | 0.87 | 4 | 6 | PASS | 7.0s | -| Tool-heavy | deterministic | 1.30 | 1.29 | - | 2 | 16 | PASS | 0ms | -| | llm-basic | 1.11 | 1.10 | 0.85 | 2 | 16 | PASS | 3.5s | -| | llm-escalate | 1.12 | 1.12 | 0.86 | 2 | 16 | PASS | 5.3s | -| Deep conversation | deterministic | 2.12 | 2.12 | - | 50 | 1 | PASS | 3ms | -| | llm-basic | 2.34 | 2.33 | 1.10 | 50 | 1 | PASS | 50.4s | -| | llm-escalate | 2.37 | 2.36 | 1.11 | 50 | 1 | PASS | 50.8s | -| Technical explanation | deterministic | 1.00 | 1.00 | - | 0 | 11 | PASS | 1ms | -| | llm-basic | 1.00 | 1.00 | 1.00 | 1 | 10 | PASS | 2.6s | -| | llm-escalate | 1.00 | 1.00 | 1.00 | 1 | 10 | PASS | 3.3s | -| Structured content | deterministic | 1.93 | 1.92 | - | 2 | 10 | PASS | 0ms | -| | llm-basic | 1.23 | 1.23 | 0.64 | 2 | 10 | PASS | 10.2s | -| | llm-escalate | 1.29 | 1.29 | 0.67 | 2 | 10 | PASS | 4.8s | -| Agentic coding session | deterministic | 1.43 | 1.43 | - | 2 | 31 | PASS | 1ms | -| | llm-basic | 1.43 | 1.43 | 1.00 | 2 | 31 | PASS | 5.8s | -| | llm-escalate | 1.32 | 1.32 | 0.93 | 1 | 32 | PASS | 9.5s | +| Scenario | Method | Char Ratio | Token Ratio | vsDet | Compressed | Preserved | Round-trip | Time | +| ---------------------- | ------------- | ---------: | ----------: | ----: | ---------: | --------: | ---------- | ----: | +| Coding assistant | deterministic | 1.68 | 1.67 | - | 5 | 8 | PASS | 0ms | +| | llm-basic | 1.64 | 1.63 | 0.98 | 5 | 8 | PASS | 5.6s | +| | llm-escalate | 1.63 | 1.63 | 0.97 | 5 | 8 | PASS | 6.0s | +| Long Q&A | deterministic | 6.16 | 6.11 | - | 4 | 6 | PASS | 1ms | +| | llm-basic | 5.37 | 5.33 | 0.87 | 4 | 6 | PASS | 5.9s | +| | llm-escalate | 5.35 | 5.31 | 0.87 | 4 | 6 | PASS | 7.0s | +| Tool-heavy | deterministic | 1.30 | 1.29 | - | 2 | 16 | PASS | 0ms | +| | llm-basic | 1.11 | 1.10 | 0.85 | 2 | 16 | PASS | 3.5s | +| | llm-escalate | 1.12 | 1.12 | 0.86 | 2 | 16 | PASS | 5.3s | +| Deep conversation | deterministic | 2.12 | 2.12 | - | 50 | 1 | PASS | 3ms | +| | llm-basic | 2.34 | 2.33 | 1.10 | 50 | 1 | PASS | 50.4s | +| | llm-escalate | 2.37 | 2.36 | 1.11 | 50 | 1 | PASS | 50.8s | +| Technical explanation | deterministic | 1.00 | 1.00 | - | 0 | 11 | PASS | 1ms | +| | llm-basic | 1.00 | 1.00 | 1.00 | 1 | 10 | PASS | 2.6s | +| | llm-escalate | 1.00 | 1.00 | 1.00 | 1 | 10 | PASS | 3.3s | +| Structured content | deterministic | 1.93 | 1.92 | - | 2 | 10 | PASS | 0ms | +| | llm-basic | 1.23 | 1.23 | 0.64 | 2 | 10 | PASS | 10.2s | +| | llm-escalate | 1.29 | 1.29 | 0.67 | 2 | 10 | PASS | 4.8s | +| Agentic coding session | deterministic | 1.43 | 1.43 | - | 2 | 31 | PASS | 1ms | +| | llm-basic | 1.43 | 1.43 | 1.00 | 2 | 31 | PASS | 5.8s | +| | llm-escalate | 1.32 | 1.32 | 0.93 | 1 | 32 | PASS | 9.5s | #### Token Budget (target: 2000 tokens) -| Scenario | Method | Tokens | Fits | recencyWindow | Ratio | Round-trip | Time | -| --- | --- | ---: | --- | ---: | ---: | --- | ---: | -| Deep conversation | deterministic | 3738 | false | 0 | 2.12 | PASS | 10ms | -| | llm-escalate | 3391 | false | 0 | 2.35 | PASS | 280.5s | -| Agentic coding session | deterministic | 1957 | true | 9 | 1.36 | PASS | 2ms | -| | llm-escalate | 1915 | true | 3 | 1.39 | PASS | 28.1s | +| Scenario | Method | Tokens | Fits | recencyWindow | Ratio | Round-trip | Time | +| ---------------------- | ------------- | -----: | ----- | ------------: | ----: | ---------- | -----: | +| Deep conversation | deterministic | 3738 | false | 0 | 2.12 | PASS | 10ms | +| | llm-escalate | 3391 | false | 0 | 2.35 | PASS | 280.5s | +| Agentic coding session | deterministic | 1957 | true | 9 | 1.36 | PASS | 2ms | +| | llm-escalate | 1915 | true | 3 | 1.39 | PASS | 28.1s |
## Version History -| Version | Date | Avg Char Ratio | Avg Token Ratio | Scenarios | -| --- | --- | ---: | ---: | ---: | -| 1.1.0 | 2026-03-20 | 2.01 | 2.00 | 8 | -| 1.0.0 | 2026-03-10 | 2.01 | 2.00 | 8 | +| Version | Date | Avg Char Ratio | Avg Token Ratio | Scenarios | +| ------- | ---------- | -------------: | --------------: | --------: | +| 1.1.0 | 2026-03-20 | 2.01 | 2.00 | 8 | +| 1.0.0 | 2026-03-10 | 2.01 | 2.00 | 8 | ### v1.0.0 → v1.1.0 > **2.01x** → **2.01x** avg compression (0.00%) -| Scenario | v1.0.0 | v1.1.0 | Change | Token Δ | | -| --- | ---: | ---: | ---: | ---: | --- | -| Coding assistant | 1.94x | 1.94x | 0.00% | 0.00% | ─| -| Long Q&A | 4.90x | 4.90x | 0.00% | 0.00% | ─| -| Tool-heavy | 1.41x | 1.41x | 0.00% | 0.00% | ─| -| Short conversation | 1.00x | 1.00x | 0.00% | 0.00% | ─| -| Deep conversation | 2.50x | 2.50x | 0.00% | 0.00% | ─| -| Technical explanation | 1.00x | 1.00x | 0.00% | 0.00% | ─| -| Structured content | 1.86x | 1.86x | 0.00% | 0.00% | ─| -| Agentic coding session | 1.48x | 1.48x | 0.00% | 0.00% | ─| +| Scenario | v1.0.0 | v1.1.0 | Change | Token Δ | | +| ---------------------- | -----: | -----: | -----: | ------: | --- | +| Coding assistant | 1.94x | 1.94x | 0.00% | 0.00% | ─ | +| Long Q&A | 4.90x | 4.90x | 0.00% | 0.00% | ─ | +| Tool-heavy | 1.41x | 1.41x | 0.00% | 0.00% | ─ | +| Short conversation | 1.00x | 1.00x | 0.00% | 0.00% | ─ | +| Deep conversation | 2.50x | 2.50x | 0.00% | 0.00% | ─ | +| Technical explanation | 1.00x | 1.00x | 0.00% | 0.00% | ─ | +| Structured content | 1.86x | 1.86x | 0.00% | 0.00% | ─ | +| Agentic coding session | 1.48x | 1.48x | 0.00% | 0.00% | ─ | Bundle: 57.0 KB → 111.4 KB (+95.44%)
v1.0.0 (2026-03-10) — 2.01x avg -| Scenario | Char Ratio | Token Ratio | Compressed | Preserved | -| --- | ---: | ---: | ---: | ---: | -| Coding assistant | 1.94 | 1.93 | 5 | 8 | -| Long Q&A | 4.90 | 4.88 | 4 | 6 | -| Tool-heavy | 1.41 | 1.40 | 2 | 16 | -| Short conversation | 1.00 | 1.00 | 0 | 7 | -| Deep conversation | 2.50 | 2.49 | 50 | 1 | -| Technical explanation | 1.00 | 1.00 | 0 | 11 | -| Structured content | 1.86 | 1.85 | 2 | 10 | -| Agentic coding session | 1.48 | 1.47 | 2 | 31 | +| Scenario | Char Ratio | Token Ratio | Compressed | Preserved | +| ---------------------- | ---------: | ----------: | ---------: | --------: | +| Coding assistant | 1.94 | 1.93 | 5 | 8 | +| Long Q&A | 4.90 | 4.88 | 4 | 6 | +| Tool-heavy | 1.41 | 1.40 | 2 | 16 | +| Short conversation | 1.00 | 1.00 | 0 | 7 | +| Deep conversation | 2.50 | 2.49 | 50 | 1 | +| Technical explanation | 1.00 | 1.00 | 0 | 11 | +| Structured content | 1.86 | 1.85 | 2 | 10 | +| Agentic coding session | 1.48 | 1.47 | 2 | 31 |