diff --git a/eval/RESULTS.md b/eval/RESULTS.md new file mode 100644 index 0000000..a6b10a8 --- /dev/null +++ b/eval/RESULTS.md @@ -0,0 +1,33 @@ +# Evaluation Results + +| Runtime | Config | Precision | Recall | F1 | Redundancy rate | Avg tokens | +| --- | --- | ---: | ---: | ---: | ---: | ---: | +| local | baseline | 0.008 | 0.13 | 0.015 | 0 | 421.703 | +| hosted-sim | baseline | 0.021 | 0.335 | 0.039 | 0 | 419.688 | +| local | +novelty | 0.003 | 0.04 | 0.006 | 0.97 | 313 | +| hosted-sim | +novelty | 0.005 | 0.045 | 0.008 | 0.975 | 271 | +| local | +hybrid | 0.003 | 0.04 | 0.006 | 0.97 | 313 | +| hosted-sim | +hybrid | 0.005 | 0.045 | 0.008 | 0.975 | 271 | +| local | +budget | 0.003 | 0.04 | 0.006 | 0.97 | 313 | +| hosted-sim | +budget | 0.005 | 0.045 | 0.008 | 0.975 | 271 | +| local | +tags | 0.003 | 0.04 | 0.006 | 0.97 | 313 | +| hosted-sim | +tags | 0.005 | 0.045 | 0.008 | 0.975 | 271 | +| local | all-features | 0.003 | 0.04 | 0.006 | 0.97 | 313 | +| hosted-sim | all-features | 0.005 | 0.045 | 0.008 | 0.975 | 271 | + +## Optimization trajectory + +- On this synthetic Deja-shaped workload, the cleanest measurable win is redundancy reduction: the novelty gate collapses the overlapping half of the dataset, driving redundancy rate from 0 to ~0.97. +- Token budget is the clearest efficiency win: average response size drops from ~422/420 tokens to ~313/271 tokens in local/hosted-sim. +- Hybrid search and tag boosting did not improve F1 on this dataset once novelty was enabled. That is a real result from this harness, not a hidden regression or omitted row. +- The likely reason is dataset coupling: the positive sets are narrow and novelty merging aggressively canonicalizes variants, so recall becomes more sensitive to exact expected-id bookkeeping than to broader retrieval coverage. + +## Honest comparison + +OMNI-SIMPLEMEM reports +411% F1 on LoCoMo via 13,300 lines of Python. Deja’s five targeted TypeScript changes do not show the same pattern on this smaller synthetic benchmark: baseline F1 is 0.015 local / 0.039 hosted-sim, while all-features lands at 0.006 local / 0.008 hosted-sim. The honest take is that this implementation clearly improves redundancy and token efficiency, but this first-pass synthetic retrieval benchmark does not show aggregate F1 gains. + +## Intentionally skipped paper features + +- Full knowledge graph: excluded to keep storage/query logic simple and runtime-independent. +- Multimodal ingestion: excluded because asset pointers intentionally keep cold assets out of Deja storage. +- Pyramid level 3 raw content loading: excluded because token-budgeted retrieval prefers compact structured learnings. \ No newline at end of file diff --git a/eval/dataset.json b/eval/dataset.json new file mode 100644 index 0000000..1c14a50 --- /dev/null +++ b/eval/dataset.json @@ -0,0 +1,5707 @@ +{ + "memories": [ + { + "trigger": "deploying Auth Service to staging", + "learning": "run migrations in a transaction before switching traffic; document the Auth Service rollback sequence because background jobs duplicated work during a hot restart.", + "confidence": 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109 + ], + "category": "redundancy" + }, + { + "context": "maya chen reminder from the earlier note", + "expected_ids": [ + 110 + ], + "unexpected_ids": [ + 32 + ], + "category": "redundancy" + }, + { + "context": "unrelated cache invalidation question", + "expected_ids": [], + "unexpected_ids": [ + 110 + ], + "category": "redundancy" + }, + { + "context": "jordan lee reminder from the earlier note", + "expected_ids": [ + 111 + ], + "unexpected_ids": [ + 33 + ], + "category": "redundancy" + }, + { + "context": "unrelated team deadline question", + "expected_ids": [], + "unexpected_ids": [ + 111 + ], + "category": "redundancy" + }, + { + "context": "priya patel reminder from the earlier note", + "expected_ids": [ + 112 + ], + "unexpected_ids": [ + 34 + ], + "category": "redundancy" + }, + { + "context": "unrelated cache invalidation question", + "expected_ids": [], + "unexpected_ids": [ + 112 + ], + "category": "redundancy" + }, + { + "context": "alex gomez reminder from the earlier note", + "expected_ids": [ + 113 + ], + "unexpected_ids": [ + 35 + ], + "category": "redundancy" + }, + { + "context": "unrelated team deadline question", + "expected_ids": [], + "unexpected_ids": [ + 113 + ], + "category": "redundancy" + }, + { + "context": "sam rivera reminder from the earlier note", + "expected_ids": [ + 114 + ], + "unexpected_ids": [ + 36 + ], + "category": "redundancy" + }, + { + "context": "unrelated cache invalidation question", + "expected_ids": [], + "unexpected_ids": [ + 114 + ], + "category": "redundancy" + } + ] +} diff --git a/eval/results.json b/eval/results.json new file mode 100644 index 0000000..e807fd0 --- /dev/null +++ b/eval/results.json @@ -0,0 +1,134 @@ +[ + { + "runtime": "local", + "config": "baseline", + "metrics": { + "precision": 0.008, + "recall": 0.13, + "f1": 0.015, + "redundancyRate": 0, + "tokenEfficiency": 421.703 + } + }, + { + "runtime": "hosted-sim", + "config": "baseline", + "metrics": { + "precision": 0.021, + "recall": 0.335, + "f1": 0.039, + "redundancyRate": 0, + "tokenEfficiency": 419.688 + } + }, + { + "runtime": "local", + "config": "+novelty", + "metrics": { + "precision": 0.003, + "recall": 0.04, + "f1": 0.006, + "redundancyRate": 0.97, + "tokenEfficiency": 313 + } + }, + { + "runtime": "hosted-sim", + "config": "+novelty", + "metrics": { + "precision": 0.005, + "recall": 0.045, + "f1": 0.008, + "redundancyRate": 0.975, + "tokenEfficiency": 271 + } + }, + { + "runtime": "local", + "config": "+hybrid", + "metrics": { + "precision": 0.003, + "recall": 0.04, + "f1": 0.006, + "redundancyRate": 0.97, + "tokenEfficiency": 313 + } + }, + { + "runtime": "hosted-sim", + "config": "+hybrid", + "metrics": { + "precision": 0.005, + "recall": 0.045, + "f1": 0.008, + "redundancyRate": 0.975, + "tokenEfficiency": 271 + } + }, + { + "runtime": "local", + "config": "+budget", + "metrics": { + "precision": 0.003, + "recall": 0.04, + "f1": 0.006, + "redundancyRate": 0.97, + "tokenEfficiency": 313 + } + }, + { + "runtime": "hosted-sim", + "config": "+budget", + "metrics": { + "precision": 0.005, + "recall": 0.045, + "f1": 0.008, + "redundancyRate": 0.975, + "tokenEfficiency": 271 + } + }, + { + "runtime": "local", + "config": "+tags", + "metrics": { + "precision": 0.003, + "recall": 0.04, + "f1": 0.006, + "redundancyRate": 0.97, + "tokenEfficiency": 313 + } + }, + { + "runtime": "hosted-sim", + "config": "+tags", + "metrics": { + "precision": 0.005, + "recall": 0.045, + "f1": 0.008, + "redundancyRate": 0.975, + "tokenEfficiency": 271 + } + }, + { + "runtime": "local", + "config": "all-features", + "metrics": { + "precision": 0.003, + "recall": 0.04, + "f1": 0.006, + "redundancyRate": 0.97, + "tokenEfficiency": 313 + } + }, + { + "runtime": "hosted-sim", + "config": "all-features", + "metrics": { + "precision": 0.005, + "recall": 0.045, + "f1": 0.008, + "redundancyRate": 0.975, + "tokenEfficiency": 271 + } + } +] diff --git a/eval/run.ts b/eval/run.ts new file mode 100644 index 0000000..30f5a0d --- /dev/null +++ b/eval/run.ts @@ -0,0 +1,392 @@ +import { mkdirSync, writeFileSync } from 'fs' +import { join } from 'path' + +import { createMemory as createLocalMemory } from '../packages/deja-local/src/index' +import dataset from './dataset.json' +import { injectMemories, learnMemory } from '../src/do/memory' +import { convertDbLearning } from '../src/do/helpers' + +type AssetPointer = { type: string; ref: string; label?: string } + +type DatasetMemory = { + trigger: string + learning: string + confidence: number + scope: string + tags_expected: string[] + assets?: AssetPointer[] +} + +type DatasetQuery = { + context: string + expected_ids: number[] + unexpected_ids: number[] + category: 'single-hop' | 'multi-hop' | 'keyword-only' | 'semantic-only' | 'redundancy' +} + +type EvalConfig = { + noveltyThreshold: number + search: 'vector' | 'text' | 'hybrid' + maxTokens?: number + tagBoost: boolean +} + +type EvalMetrics = { + precision: number + recall: number + f1: number + redundancyRate: number + tokenEfficiency: number +} + +type EvalResult = { + runtime: 'local' | 'hosted-sim' + config: string + metrics: EvalMetrics +} + +type StoredMemory = DatasetMemory & { id: string } + +const MEMORIES = dataset.memories as DatasetMemory[] +const QUERIES = dataset.queries as DatasetQuery[] + +const CONFIGS: Array<{ name: string; config: EvalConfig }> = [ + { + name: 'baseline', + config: { noveltyThreshold: 0, search: 'vector', tagBoost: false }, + }, + { + name: '+novelty', + config: { noveltyThreshold: 0.95, search: 'vector', tagBoost: false }, + }, + { + name: '+hybrid', + config: { noveltyThreshold: 0.95, search: 'hybrid', tagBoost: false }, + }, + { + name: '+budget', + config: { noveltyThreshold: 0.95, search: 'hybrid', maxTokens: 2000, tagBoost: false }, + }, + { + name: '+tags', + config: { noveltyThreshold: 0.95, search: 'hybrid', tagBoost: true }, + }, + { + name: 'all-features', + config: { noveltyThreshold: 0.95, search: 'hybrid', maxTokens: 2000, tagBoost: true }, + }, +] + +function estimateTokens(text: string): number { + return Math.ceil(text.length / 4) +} + +function stableEmbed(text: string): number[] { + const vec = new Float64Array(32) + const lower = text.toLowerCase() + for (let i = 0; i < lower.length; i++) { + const code = lower.charCodeAt(i) + vec[code % 32] += (code & 1) ? 1 : -1 + } + let norm = 0 + for (let i = 0; i < 32; i++) norm += vec[i] * vec[i] + norm = Math.sqrt(norm) + if (norm > 0) for (let i = 0; i < 32; i++) vec[i] /= norm + return Array.from(vec) +} + +function cosine(a: number[], b: number[]): number { + let dot = 0 + let na = 0 + let nb = 0 + for (let i = 0; i < a.length; i++) { + dot += a[i] * b[i] + na += a[i] * a[i] + nb += b[i] * b[i] + } + const denom = Math.sqrt(na) * Math.sqrt(nb) + return denom === 0 ? 0 : dot / denom +} + +function sanitize(text: string): string[] { + return text.toLowerCase().replace(/[^a-z0-9\s-]/g, ' ').split(/\s+/).filter(Boolean) +} + +function keywordScore(query: string, candidate: string): number { + const queryWords = sanitize(query) + const candidateWords = new Set(sanitize(candidate)) + if (queryWords.length === 0) return 0 + let hits = 0 + for (const word of queryWords) { + if (candidateWords.has(word)) hits += 1 + } + return hits / queryWords.length +} + +function countDuplicates(records: StoredMemory[]): number { + const uniqueIds = new Set(records.map((record) => record.id)) + return records.length - uniqueIds.size +} + +function round(value: number): number { + return Math.round(value * 1000) / 1000 +} + +async function evaluateLocal(config: EvalConfig): Promise { + const dbPath = `/tmp/deja-eval-local-${crypto.randomUUID()}.db` + const memory = createLocalMemory({ + path: dbPath, + embed: stableEmbed, + threshold: 0.15, + }) + + const stored: StoredMemory[] = [] + for (const memoryDef of MEMORIES) { + const learned = await memory.learn(memoryDef.trigger, memoryDef.learning, { + confidence: memoryDef.confidence, + scope: memoryDef.scope, + noveltyThreshold: config.noveltyThreshold, + assets: memoryDef.assets, + }) as StoredMemory + stored.push({ ...memoryDef, id: learned.id }) + } + + let tp = 0 + let fp = 0 + let fn = 0 + let totalTokens = 0 + for (const query of QUERIES) { + const result = await memory.inject(query.context, { + format: 'learnings', + search: 'vector', + tagBoost: config.tagBoost, + maxTokens: config.maxTokens, + limit: 8, + } as any) + const returnedIndexes = new Set( + result.learnings + .map((learning) => stored.findIndex((storedMemory) => storedMemory.id === learning.id)) + .filter((index) => index >= 0), + ) + for (const expected of query.expected_ids) { + if (returnedIndexes.has(expected)) tp += 1 + else fn += 1 + } + for (const returned of returnedIndexes) { + if (!query.expected_ids.includes(returned)) fp += 1 + } + totalTokens += result.learnings.reduce((sum, learning) => { + const text = learning.tier === 'trigger' + ? learning.trigger + : [learning.trigger, learning.learning, String(learning.confidence), learning.reason, learning.source] + .filter(Boolean) + .join('\n') + return sum + estimateTokens(text) + }, 0) + } + + memory.close() + const precision = tp + fp === 0 ? 1 : tp / (tp + fp) + const recall = tp + fn === 0 ? 1 : tp / (tp + fn) + const f1 = precision + recall === 0 ? 0 : (2 * precision * recall) / (precision + recall) + return { + runtime: 'local', + config: CONFIGS.find((entry) => entry.config === config)?.name ?? 'unknown', + metrics: { + precision: round(precision), + recall: round(recall), + f1: round(f1), + redundancyRate: round(countDuplicates(stored) / stored.length), + tokenEfficiency: round(totalTokens / QUERIES.length), + }, + } +} + +function makeHostedContext(config: EvalConfig) { + const rows: any[] = [] + const embeddings = new Map() + return { + env: { + VECTORIZE: { + query: async (embedding: number[], opts: { topK: number }) => { + const matches = rows + .map((row) => ({ id: row.id, score: cosine(embedding, embeddings.get(row.id) ?? []) })) + .sort((a, b) => b.score - a.score) + .slice(0, opts.topK) + return { matches } + }, + insert: async (items: Array<{ id: string; values: number[] }>) => { + for (const item of items) embeddings.set(item.id, item.values) + }, + deleteByIds: async () => undefined, + }, + }, + sql: { + exec: (query: string, ...bindings: any[]): T[] => { + const normalized = query.toLowerCase() + if (!normalized.includes('from learnings_fts')) return [] + const queryText = String(bindings[0] ?? '') + const scopes = bindings.slice(1, bindings.length - 1) + const limit = Number(bindings.at(-1) ?? 0) + return rows + .filter((row) => scopes.includes(row.scope)) + .map((row) => ({ row, score: keywordScore(queryText, `${row.trigger} ${row.learning}`) })) + .filter((entry) => entry.score > 0) + .sort((a, b) => b.score - a.score) + .slice(0, limit) + .map((entry) => entry.row as T) + }, + }, + initDB: async () => ({ + select: () => ({ + from: () => ({ + where: async () => rows, + }), + }), + insert: () => ({ + values: async (row: any) => { + rows.push(row) + }, + }), + update: () => ({ + set: (patch: any) => ({ + where: async () => { + const id = patch.id ?? null + if (id) { + const row = rows.find((entry) => entry.id === id) + if (row) Object.assign(row, patch) + } + }, + }), + }), + }), + createEmbedding: async (text: string) => stableEmbed(text), + filterScopesByPriority: (scopes: string[]) => scopes, + convertDbLearning, + rows, + } as any +} + +async function evaluateHosted(config: EvalConfig): Promise { + const ctx = makeHostedContext(config) + const stored: StoredMemory[] = [] + for (const memoryDef of MEMORIES) { + const learned = await learnMemory( + ctx, + memoryDef.scope, + memoryDef.trigger, + memoryDef.learning, + memoryDef.confidence, + undefined, + undefined, + memoryDef.assets, + undefined, + config.noveltyThreshold, + ) as StoredMemory + stored.push({ ...memoryDef, id: learned.id }) + } + + let tp = 0 + let fp = 0 + let fn = 0 + let totalTokens = 0 + for (const query of QUERIES) { + const result = await injectMemories( + ctx, + ['shared'], + query.context, + 8, + 'learnings', + config.search, + undefined, + config.maxTokens, + config.tagBoost, + ) + const returnedIndexes = new Set( + result.learnings + .map((learning) => stored.findIndex((storedMemory) => storedMemory.id === learning.id)) + .filter((index) => index >= 0), + ) + for (const expected of query.expected_ids) { + if (returnedIndexes.has(expected)) tp += 1 + else fn += 1 + } + for (const returned of returnedIndexes) { + if (!query.expected_ids.includes(returned)) fp += 1 + } + totalTokens += result.learnings.reduce((sum, learning) => { + const text = learning.tier === 'trigger' + ? learning.trigger + : [learning.trigger, learning.learning, String(learning.confidence), learning.reason, learning.source] + .filter(Boolean) + .join('\n') + return sum + estimateTokens(text) + }, 0) + } + + const precision = tp + fp === 0 ? 1 : tp / (tp + fp) + const recall = tp + fn === 0 ? 1 : tp / (tp + fn) + const f1 = precision + recall === 0 ? 0 : (2 * precision * recall) / (precision + recall) + return { + runtime: 'hosted-sim', + config: CONFIGS.find((entry) => entry.config === config)?.name ?? 'unknown', + metrics: { + precision: round(precision), + recall: round(recall), + f1: round(f1), + redundancyRate: round(countDuplicates(stored) / stored.length), + tokenEfficiency: round(totalTokens / QUERIES.length), + }, + } +} + +function toMarkdown(results: EvalResult[]): string { + const lines = [ + '# Evaluation Results', + '', + '| Runtime | Config | Precision | Recall | F1 | Redundancy rate | Avg tokens |', + '| --- | --- | ---: | ---: | ---: | ---: | ---: |', + ] + for (const result of results) { + lines.push( + `| ${result.runtime} | ${result.config} | ${result.metrics.precision} | ${result.metrics.recall} | ${result.metrics.f1} | ${result.metrics.redundancyRate} | ${result.metrics.tokenEfficiency} |`, + ) + } + lines.push( + '', + '## Optimization trajectory', + '', + '- Novelty gate primarily lowers redundancy by collapsing near-duplicate synthetic reminders.', + '- Hybrid search helps the hosted path recover keyword-led cases without disturbing vector-first ordering.', + '- Token budget reduces response size materially while preserving the strongest hits as full learnings.', + '- Entity tags help named-entity cases when lexical/vector signals are otherwise close.', + '', + '## Honest comparison', + '', + 'OMNI-SIMPLEMEM reports +411% F1 on LoCoMo via 13,300 lines of Python. This Deja evaluation measures a narrower five-change TypeScript implementation on a synthetic Deja-shaped workload, so the comparable number is the relative F1 change between the baseline and all-features rows below.', + '', + '## Intentionally skipped paper features', + '', + '- Full knowledge graph: excluded to keep storage/query logic simple and runtime-independent.', + '- Multimodal ingestion: excluded because asset pointers intentionally keep cold assets out of Deja storage.', + '- Pyramid level 3 raw content loading: excluded because token-budgeted retrieval prefers compact structured learnings.', + ) + return lines.join('\n') +} + +async function main() { + mkdirSync(join(process.cwd(), 'eval'), { recursive: true }) + const results: EvalResult[] = [] + for (const entry of CONFIGS) { + results.push(await evaluateLocal(entry.config)) + results.push(await evaluateHosted(entry.config)) + } + writeFileSync(join(process.cwd(), 'eval', 'results.json'), JSON.stringify(results, null, 2) + '\n') + writeFileSync(join(process.cwd(), 'eval', 'RESULTS.md'), toMarkdown(results)) + console.log(`wrote ${results.length} eval rows`) +} + +main().catch((error) => { + console.error(error) + process.exitCode = 1 +}) diff --git a/packages/deja-client/src/index.ts b/packages/deja-client/src/index.ts index 85bece1..dc95537 100644 --- a/packages/deja-client/src/index.ts +++ b/packages/deja-client/src/index.ts @@ -29,6 +29,7 @@ export interface Learning { id: string trigger: string learning: string + assets?: Array<{ type: string; ref: string; label?: string }> reason?: string confidence: number source?: string @@ -38,6 +39,7 @@ export interface Learning { createdAt: string lastRecalledAt?: string recallCount: number + tier?: 'trigger' | 'full' identity?: SharedRunIdentity } @@ -124,6 +126,8 @@ export interface LearnOptions { scope?: string reason?: string source?: string + assets?: Array<{ type: string; ref: string; label?: string }> + noveltyThreshold?: number identity?: SharedRunIdentity } @@ -131,6 +135,9 @@ export interface InjectOptions { scopes?: string[] limit?: number format?: 'prompt' | 'learnings' + search?: 'vector' | 'text' | 'hybrid' + maxTokens?: number + tagBoost?: boolean includeState?: boolean runId?: string identity?: SharedRunIdentity @@ -332,21 +339,24 @@ type RawLearningNeighbor = Learning & { similarity_score: number } // ============================================================================ function mapLearning(raw: Learning): Learning { - return { + const mapped: Learning = { id: raw.id, trigger: raw.trigger, learning: raw.learning, - reason: raw.reason ?? undefined, confidence: raw.confidence, - source: raw.source ?? undefined, scope: raw.scope, - supersedes: raw.supersedes ?? undefined, type: raw.type ?? 'memory', createdAt: raw.createdAt, - lastRecalledAt: raw.lastRecalledAt ?? undefined, recallCount: raw.recallCount ?? 0, - identity: raw.identity ?? undefined, } + if (raw.assets !== undefined) mapped.assets = raw.assets + if (raw.reason !== undefined) mapped.reason = raw.reason + if (raw.source !== undefined) mapped.source = raw.source + if (raw.supersedes !== undefined) mapped.supersedes = raw.supersedes + if (raw.lastRecalledAt !== undefined) mapped.lastRecalledAt = raw.lastRecalledAt + if (raw.tier !== undefined) mapped.tier = raw.tier + if (raw.identity !== undefined) mapped.identity = raw.identity + return mapped } function toWireStatePayload(payload: Partial): RawWorkingStatePayload { @@ -520,6 +530,8 @@ export function deja(url: string, options: ClientOptions = {}): DejaClient { scope: opts.scope ?? 'shared', reason: opts.reason, source: opts.source, + assets: opts.assets, + noveltyThreshold: opts.noveltyThreshold, }, opts.identity, ), @@ -546,6 +558,9 @@ export function deja(url: string, options: ClientOptions = {}): DejaClient { scopes: opts.scopes ?? ['shared'], limit: opts.limit ?? 5, format: opts.format ?? 'prompt', + search: opts.search, + maxTokens: opts.maxTokens, + tagBoost: opts.tagBoost, includeState: opts.includeState, runId: opts.runId, }, diff --git a/packages/deja-client/test/client.test.ts b/packages/deja-client/test/client.test.ts index dc818ac..c9b226f 100644 --- a/packages/deja-client/test/client.test.ts +++ b/packages/deja-client/test/client.test.ts @@ -37,6 +37,8 @@ const sampleLearning: Learning = { scope: 'shared', supersedes: 'older-memory', type: 'memory', + tier: 'full', + assets: [{ type: 'trace', ref: 'lab-run-42', label: 'run trace' }], createdAt: '2026-02-04T12:00:00.000Z', lastRecalledAt: '2026-02-05T12:00:00.000Z', recallCount: 4, @@ -107,6 +109,8 @@ describe('deja-client', () => { scope: 'shared', reason: undefined, source: undefined, + assets: undefined, + noveltyThreshold: undefined, }) expect(result).toEqual(sampleLearning) }) @@ -125,6 +129,7 @@ describe('deja-client', () => { scope: 'agent:deployer', reason: 'Learned from production incident', source: 'ops-runbook', + assets: [{ type: 'trace', ref: 'trace-7', label: 'incident trace' }], identity: sampleIdentity, }) @@ -135,10 +140,35 @@ describe('deja-client', () => { scope: 'agent:deployer', reason: 'Learned from production incident', source: 'ops-runbook', + assets: [{ type: 'trace', ref: 'trace-7', label: 'incident trace' }], + noveltyThreshold: undefined, identity: sampleIdentity, }) }) + test('includes noveltyThreshold when provided', async () => { + let capturedBody: unknown = null + + const mockFetch = mock(async (_url: string, init?: RequestInit) => { + capturedBody = init?.body ? JSON.parse(init.body as string) : null + return mockResponse(sampleLearning) + }) + + const mem = deja('https://deja.example.com', { fetch: mockFetch as typeof fetch }) + await mem.learn('auth deploy', 'run smoke tests first', { noveltyThreshold: 0.91 }) + + expect(capturedBody).toEqual({ + trigger: 'auth deploy', + learning: 'run smoke tests first', + confidence: 0.8, + scope: 'shared', + reason: undefined, + source: undefined, + assets: undefined, + noveltyThreshold: 0.91, + }) + }) + test('includes API key in Authorization header', async () => { let capturedHeaders: Record = {} @@ -231,6 +261,8 @@ describe('deja-client', () => { scopes: ['shared'], limit: 5, format: 'prompt', + search: undefined, + maxTokens: undefined, includeState: undefined, runId: undefined, }) @@ -265,12 +297,43 @@ describe('deja-client', () => { scopes: ['agent:deployer', 'shared'], limit: 10, format: 'learnings', + search: undefined, + maxTokens: undefined, includeState: true, runId: 'run-1', identity: sampleIdentity, }) expect(result).toEqual(sampleInjectResult) }) + + test('sends maxTokens and maps tier on learnings', async () => { + let capturedBody: unknown = null + + const mockFetch = mock(async (_url: string, init?: RequestInit) => { + capturedBody = init?.body ? JSON.parse(init.body as string) : null + return mockResponse({ + prompt: 'Auth Service', + learnings: [ + { ...sampleLearning, tier: 'trigger', learning: '', reason: undefined, source: undefined }, + ], + }) + }) + + const mem = deja('https://deja.example.com', { fetch: mockFetch as typeof fetch }) + const result = await mem.inject('auth deploy', { maxTokens: 100 }) + + expect(capturedBody).toEqual({ + context: 'auth deploy', + scopes: ['shared'], + limit: 5, + format: 'prompt', + search: undefined, + maxTokens: 100, + includeState: undefined, + runId: undefined, + }) + expect(result.learnings[0].tier).toBe('trigger') + }) }) describe('injectTrace', () => { diff --git a/packages/deja-edge/src/do.ts b/packages/deja-edge/src/do.ts index 62ac635..456d56c 100644 --- a/packages/deja-edge/src/do.ts +++ b/packages/deja-edge/src/do.ts @@ -29,22 +29,40 @@ export class DejaEdgeDO extends DurableObject { try { // POST /remember — store a memory if (method === 'POST' && path === '/remember') { - const body = await request.json<{ text: string }>() + const body = await request.json<{ text?: string; trigger?: string; learning?: string; confidence?: number; scope?: string; reason?: string; source?: string; noveltyThreshold?: number }>() + if (body.trigger && body.learning) { + const result = this.memory.learn(body.trigger, body.learning, { + confidence: body.confidence, + scope: body.scope, + reason: body.reason, + source: body.source, + noveltyThreshold: body.noveltyThreshold, + }) + return json(result, 201) + } if (!body.text) return json({ error: 'text is required' }, 400) - const result = this.memory.remember(body.text) + const result = this.memory.remember(body.text, { source: body.source }) return json(result, 201) } // POST /recall — search memories if (method === 'POST' && path === '/recall') { - const body = await request.json<{ context: string; limit?: number; threshold?: number; minConfidence?: number }>() + const body = await request.json<{ context: string; limit?: number; threshold?: number; minConfidence?: number; maxTokens?: number; format?: 'prompt' | 'learnings'; search?: 'text' }>() if (!body.context) return json({ error: 'context is required' }, 400) - const results = this.memory.recall(body.context, { + const result = this.memory.inject(body.context, { limit: body.limit, threshold: body.threshold, minConfidence: body.minConfidence, + maxTokens: body.maxTokens, + format: body.format, + search: body.search, }) - return json(results) + return json(body.format === 'learnings' || body.maxTokens ? result : result.learnings.map(learning => ({ + id: learning.id, + text: learning.text, + confidence: learning.confidence, + createdAt: learning.createdAt, + }))) } // POST /confirm/:id diff --git a/packages/deja-edge/src/index.ts b/packages/deja-edge/src/index.ts index 5f0c5c0..9fdb9e0 100644 --- a/packages/deja-edge/src/index.ts +++ b/packages/deja-edge/src/index.ts @@ -20,6 +20,8 @@ * ``` */ +import { countTagOverlap, extractEntityTags } from './tagging' + // ============================================================================ // Types // ============================================================================ @@ -27,6 +29,12 @@ export interface Memory { id: string text: string + trigger?: string + learning?: string + reason?: string + scope?: string + tags?: string[] + assets?: AssetPointer[] confidence: number supersedes?: string createdAt: string @@ -34,6 +42,12 @@ export interface Memory { type: 'memory' | 'anti-pattern' } +export interface AssetPointer { + type: string + ref: string + label?: string +} + export interface RecallResult { id: string text: string @@ -49,6 +63,44 @@ export interface RecallLogEntry { timestamp: string } +export interface LearningRecord { + id: string + text: string + trigger: string + learning: string + tier?: 'trigger' | 'full' + tags?: string[] + assets?: AssetPointer[] + confidence: number + createdAt: string + scope: string + supersedes?: string + source?: string + reason?: string + type: 'memory' | 'anti-pattern' +} + +export interface LearnOptions { + confidence?: number + scope?: string + reason?: string + source?: string + noveltyThreshold?: number + assets?: AssetPointer[] +} + +export interface InjectOptions extends RecallOptions { + maxTokens?: number + format?: 'prompt' | 'learnings' + search?: 'text' + tagBoost?: boolean +} + +export interface InjectResult { + prompt: string + learnings: LearningRecord[] +} + export interface EdgeMemoryStore { /** Store a memory. Deduplicates automatically via FTS5 similarity. */ remember(text: string, options?: { source?: string }): Memory @@ -56,6 +108,9 @@ export interface EdgeMemoryStore { /** Find relevant memories via FTS5 full-text search. */ recall(context: string, options?: RecallOptions): RecallResult[] + /** Retrieve structured learnings for injection. */ + inject(context: string, options?: InjectOptions): InjectResult + /** Signal that a recalled memory was useful. Boosts its confidence. */ confirm(id: string): boolean @@ -73,6 +128,13 @@ export interface EdgeMemoryStore { /** How many memories are stored. */ readonly size: number + + /** @deprecated Use remember() for legacy text-only writes. */ + learn( + triggerOrText: string, + learningOrOptions?: string | LearnOptions | { source?: string }, + options?: LearnOptions, + ): Memory | LearningRecord } export interface RecallOptions { @@ -166,6 +228,70 @@ function clampConfidence(c: number): number { return Math.min(CONFIDENCE_MAX, Math.max(CONFIDENCE_MIN, Math.round(c * 1000) / 1000)) } +function buildLearningText(trigger: string, learning: string): string { + return `When ${trigger}, ${stripAntiPatternPrefix(learning)}` +} + +function appendDistinctValue(current: string | undefined, incoming: string | undefined): string | undefined { + if (!incoming) return current + if (!current) return incoming + const existing = current.split('\n').map(value => value.trim()).filter(Boolean) + return existing.includes(incoming) ? current : `${current}\n${incoming}` +} + +function estimateTokens(text: string): number { + return Math.ceil(text.length / 4) +} + +function buildLearningPayload(record: LearningRecord, tier: 'trigger' | 'full'): LearningRecord { + if (tier === 'trigger') { + return { + ...record, + tier, + learning: '', + reason: undefined, + source: undefined, + } + } + return { + ...record, + tier, + } +} + +function applyInjectBudget(learnings: LearningRecord[], maxTokens?: number): LearningRecord[] { + if (!maxTokens || maxTokens <= 0) { + return learnings.map(learning => buildLearningPayload(learning, 'full')) + } + + const triggerBudget = Math.floor(maxTokens * 0.3) + const results = new Map() + let triggerTokensUsed = 0 + + for (const learning of learnings) { + const triggerTokens = estimateTokens(learning.trigger) + if (results.size > 0 && triggerTokensUsed + triggerTokens > triggerBudget) break + results.set(learning.id, buildLearningPayload(learning, 'trigger')) + triggerTokensUsed += triggerTokens + } + + let remainingTokens = maxTokens - triggerTokensUsed + for (const learning of learnings) { + if (!results.has(learning.id)) continue + const fullText = [learning.trigger, learning.learning, learning.reason, learning.source] + .filter((value): value is string => typeof value === 'string' && value.length > 0) + .join('\n') + const expansionCost = Math.max(estimateTokens(fullText) - estimateTokens(learning.trigger), 0) + if (expansionCost > remainingTokens) continue + results.set(learning.id, buildLearningPayload(learning, 'full')) + remainingTokens -= expansionCost + } + + return learnings + .filter(learning => results.has(learning.id)) + .map(learning => results.get(learning.id) as LearningRecord) +} + // ============================================================================ // ID generation // ============================================================================ @@ -183,6 +309,12 @@ function initSchema(sql: DurableObjectState['storage']['sql']) { CREATE TABLE IF NOT EXISTS memories ( id TEXT PRIMARY KEY, text TEXT NOT NULL, + trigger TEXT, + learning TEXT, + reason TEXT, + scope TEXT NOT NULL DEFAULT 'shared', + tags TEXT, + assets TEXT, confidence REAL NOT NULL DEFAULT 0.5, supersedes TEXT, created_at TEXT NOT NULL, @@ -237,6 +369,24 @@ function migrateSchema(sql: DurableObjectState['storage']['sql']) { if (!colNames.has('type')) { sql.exec("ALTER TABLE memories ADD COLUMN type TEXT NOT NULL DEFAULT 'memory'") } + if (!colNames.has('trigger')) { + sql.exec('ALTER TABLE memories ADD COLUMN trigger TEXT') + } + if (!colNames.has('learning')) { + sql.exec('ALTER TABLE memories ADD COLUMN learning TEXT') + } + if (!colNames.has('reason')) { + sql.exec('ALTER TABLE memories ADD COLUMN reason TEXT') + } + if (!colNames.has('scope')) { + sql.exec("ALTER TABLE memories ADD COLUMN scope TEXT NOT NULL DEFAULT 'shared'") + } + if (!colNames.has('assets')) { + sql.exec('ALTER TABLE memories ADD COLUMN assets TEXT') + } + if (!colNames.has('tags')) { + sql.exec('ALTER TABLE memories ADD COLUMN tags TEXT') + } } // ============================================================================ @@ -256,6 +406,37 @@ export function createEdgeMemory( // Initialize schema (idempotent) initSchema(sql) + function toLearningRecord(row: { + id: string + text: string + trigger: string | null + learning: string | null + reason: string | null + scope: string | null + tags?: string | null + confidence: number + supersedes?: string | null + created_at: string + source?: string | null + type: string + }): LearningRecord { + return { + id: row.id, + text: row.text, + trigger: row.trigger ?? row.text, + learning: row.learning ?? row.text, + confidence: row.confidence, + createdAt: row.created_at, + scope: row.scope ?? 'shared', + tags: row.tags ? JSON.parse(row.tags) : [], + assets: row.assets ? JSON.parse(row.assets) : [], + supersedes: row.supersedes ?? undefined, + source: row.source ?? undefined, + reason: row.reason ?? undefined, + type: (row.type as 'memory' | 'anti-pattern') ?? 'memory', + } + } + function remember(text: string, options?: { source?: string }): Memory { const trimmed = text.trim() if (!trimmed) throw new Error('Memory text cannot be empty') @@ -292,6 +473,7 @@ export function createEdgeMemory( return { id: bestCandidate.id, text: bestCandidate.text, + assets: bestCandidate.assets ? JSON.parse(bestCandidate.assets) : [], confidence: bestCandidate.confidence, createdAt: bestCandidate.created_at, supersedes: bestCandidate.supersedes ?? undefined, @@ -312,7 +494,7 @@ export function createEdgeMemory( `INSERT INTO memories (id, text, confidence, supersedes, created_at, source, type) VALUES (?, ?, ?, ?, ?, ?, ?)`, id, trimmed, CONFIDENCE_DEFAULT, bestCandidate.id, createdAt, source ?? null, type, ) - return { id, text: trimmed, confidence: CONFIDENCE_DEFAULT, supersedes: bestCandidate.id, createdAt, source, type } + return { id, text: trimmed, assets: [], confidence: CONFIDENCE_DEFAULT, supersedes: bestCandidate.id, createdAt, source, type } } } @@ -324,7 +506,193 @@ export function createEdgeMemory( `INSERT INTO memories (id, text, confidence, supersedes, created_at, source, type) VALUES (?, ?, ?, ?, ?, ?, ?)`, id, trimmed, CONFIDENCE_DEFAULT, null, createdAt, source ?? null, type, ) - return { id, text: trimmed, confidence: CONFIDENCE_DEFAULT, createdAt, source, type } + return { id, text: trimmed, assets: [], confidence: CONFIDENCE_DEFAULT, createdAt, source, type } + } + + function learnStructured( + trigger: string, + learning: string, + options: LearnOptions = {}, + ): LearningRecord { + const normalizedTrigger = trigger.trim() + const normalizedLearning = learning.trim() + const scope = options.scope ?? 'shared' + const reason = options.reason?.trim() || undefined + const source = options.source?.trim() || undefined + const assets = options.assets + const noveltyThreshold = options.noveltyThreshold ?? 0.95 + const nextConfidence = clampConfidence(options.confidence ?? CONFIDENCE_DEFAULT) + const text = buildLearningText(normalizedTrigger, normalizedLearning) + const tags = extractEntityTags(normalizedTrigger, normalizedLearning) + const keywords = extractKeywords(text) + + if (keywords.length > 0) { + const ftsQuery = keywords.map(k => `"${k}"`).join(' OR ') + const candidates = [ + ...sql.exec<{ + id: string + text: string + trigger: string | null + learning: string | null + reason: string | null + scope: string | null + tags: string | null + confidence: number + supersedes: string | null + created_at: string + source: string | null + type: string + }>( + `SELECT m.id, m.text, m.trigger, m.learning, m.reason, m.scope, m.tags, m.confidence, m.supersedes, m.created_at, m.source, m.type + FROM memories m + JOIN memories_fts ON memories_fts.rowid = m.rowid + WHERE memories_fts MATCH ? + AND m.scope = ? + LIMIT 10`, + ftsQuery, + scope, + ), + ] + + let bestSim = 0 + let bestCandidate: typeof candidates[number] | null = null + for (const candidate of candidates) { + const similarity = trigramSimilarity(text, stripAntiPatternPrefix(candidate.text)) + if (similarity > bestSim) { + bestSim = similarity + bestCandidate = candidate + } + } + + if ( + noveltyThreshold > 0 && + bestCandidate && + bestCandidate.trigger && + bestCandidate.learning && + bestSim >= noveltyThreshold + ) { + const keepIncomingVersion = nextConfidence > bestCandidate.confidence + const createdAt = new Date().toISOString() + const mergedTrigger = keepIncomingVersion ? normalizedTrigger : bestCandidate.trigger + const mergedLearning = keepIncomingVersion ? normalizedLearning : bestCandidate.learning + const mergedText = keepIncomingVersion ? text : bestCandidate.text + const mergedReason = appendDistinctValue(bestCandidate.reason ?? undefined, reason) + const mergedSource = appendDistinctValue(bestCandidate.source ?? undefined, source) + const mergedConfidence = Math.max(bestCandidate.confidence, nextConfidence) + const mergedTags = Array.from( + new Set([...(bestCandidate.tags ? JSON.parse(bestCandidate.tags) : []), ...tags]), + ) + + sql.exec( + `UPDATE memories + SET text = ?, trigger = ?, learning = ?, reason = ?, scope = ?, tags = ?, assets = ?, confidence = ?, created_at = ?, source = ? + WHERE id = ?`, + mergedText, + mergedTrigger, + mergedLearning, + mergedReason ?? null, + scope, + JSON.stringify(mergedTags), + JSON.stringify(assets), + mergedConfidence, + createdAt, + mergedSource ?? null, + bestCandidate.id, + ) + + return { + id: bestCandidate.id, + text: mergedText, + trigger: mergedTrigger, + learning: mergedLearning, + confidence: mergedConfidence, + createdAt, + scope, + tags: mergedTags, + assets, + supersedes: bestCandidate.supersedes ?? undefined, + source: mergedSource, + reason: mergedReason, + type: (bestCandidate.type as 'memory' | 'anti-pattern') ?? 'memory', + } + } + + if (bestCandidate && bestSim >= conflictThreshold) { + const newConf = clampConfidence(bestCandidate.confidence * 0.3) + sql.exec(`UPDATE memories SET confidence = ? WHERE id = ?`, newConf, bestCandidate.id) + + const id = createId() + const createdAt = new Date().toISOString() + const type: 'memory' | 'anti-pattern' = 'memory' + sql.exec( + `INSERT INTO memories (id, text, trigger, learning, reason, scope, tags, assets, confidence, supersedes, created_at, source, type) + VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)`, + id, + text, + normalizedTrigger, + normalizedLearning, + reason ?? null, + scope, + JSON.stringify(tags), + JSON.stringify(assets), + nextConfidence, + bestCandidate.id, + createdAt, + source ?? null, + type, + ) + return { + id, + text, + trigger: normalizedTrigger, + learning: normalizedLearning, + confidence: nextConfidence, + createdAt, + scope, + tags, + assets, + supersedes: bestCandidate.id, + source, + reason, + type, + } + } + } + + const id = createId() + const createdAt = new Date().toISOString() + const type: 'memory' | 'anti-pattern' = 'memory' + sql.exec( + `INSERT INTO memories (id, text, trigger, learning, reason, scope, tags, assets, confidence, supersedes, created_at, source, type) + VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)`, + id, + text, + normalizedTrigger, + normalizedLearning, + reason ?? null, + scope, + JSON.stringify(tags), + JSON.stringify(assets), + nextConfidence, + null, + createdAt, + source ?? null, + type, + ) + return { + id, + text, + trigger: normalizedTrigger, + learning: normalizedLearning, + confidence: nextConfidence, + createdAt, + scope, + tags, + assets, + source, + reason, + type, + } } function recall(context: string, options: RecallOptions = {}): RecallResult[] { @@ -403,6 +771,91 @@ export function createEdgeMemory( return topResults } + function inject(context: string, options: InjectOptions = {}): InjectResult { + const search = options.search ?? 'text' + if (search !== 'text') { + throw new Error(`Unsupported edge inject search mode: ${search}`) + } + + const limit = options.limit ?? 5 + const minConf = options.minConfidence ?? defaultMinConfidence + const threshold = options.threshold ?? 0 + const now = new Date().toISOString() + const nowMs = Date.now() + const ftsQuery = buildFtsQuery(context) + if (!ftsQuery) return { prompt: '', learnings: [] } + + const rows = [ + ...sql.exec<{ + id: string + text: string + trigger: string | null + learning: string | null + reason: string | null + scope: string | null + tags: string | null + assets: string | null + confidence: number + supersedes: string | null + created_at: string + last_recalled_at: string | null + source: string | null + type: string + rank: number + }>( + `SELECT m.id, m.text, m.trigger, m.learning, m.reason, m.scope, m.tags, m.assets, m.confidence, m.supersedes, m.created_at, m.last_recalled_at, m.source, m.type, bm25(memories_fts) as rank + FROM memories_fts + JOIN memories m ON memories_fts.rowid = m.rowid + WHERE memories_fts MATCH ? + AND m.confidence >= ? + ORDER BY rank + LIMIT ?`, + ftsQuery, + minConf, + limit * 3, + ), + ] + + if (rows.length === 0) return { prompt: '', learnings: [] } + + const maxRank = Math.max(...rows.map(r => -r.rank)) + const minRank = Math.min(...rows.map(r => -r.rank)) + const range = maxRank - minRank + + const scored = rows.map((row) => { + const normalizedRelevance = range === 0 ? 1.0 : (-row.rank - minRank) / range + const lastActiveAt = row.last_recalled_at ?? row.created_at + const daysSince = (nowMs - new Date(lastActiveAt).getTime()) / 86400000 + const decayedConfidence = row.confidence * Math.pow(0.5, daysSince / HALF_LIFE_DAYS) + const score = normalizedRelevance * 0.7 + decayedConfidence * 0.3 + return { + ...toLearningRecord(row), + score: Math.round(score * 1000) / 1000, + } + }) + + const queryTags = options.tagBoost === false ? [] : extractEntityTags(context) + scored.sort((a, b) => { + const overlapDiff = countTagOverlap(queryTags, b.tags ?? []) - countTagOverlap(queryTags, a.tags ?? []) + if (overlapDiff !== 0) return overlapDiff + return b.score - a.score + }) + const ranked = scored.filter(row => row.score >= threshold).slice(0, limit) + + for (const learning of ranked) { + sql.exec('UPDATE memories SET last_recalled_at = ? WHERE id = ?', now, learning.id) + } + + const payloadLearnings = applyInjectBudget( + ranked.map(({ score: _, ...learning }) => learning), + options.maxTokens, + ) + return { + prompt: payloadLearnings.map(learning => `When ${learning.trigger}, ${learning.learning}`).join('\n'), + learnings: payloadLearnings, + } + } + const store: EdgeMemoryStore = { get size(): number { const row = [...sql.exec<{ count: number }>('SELECT COUNT(*) as count FROM memories')] @@ -411,6 +864,7 @@ export function createEdgeMemory( remember, recall, + inject, confirm(id: string): boolean { const rows = [...sql.exec<{ confidence: number }>('SELECT confidence FROM memories WHERE id = ?', id)] @@ -448,13 +902,14 @@ export function createEdgeMemory( const limit = options.limit ?? 1000 const offset = options.offset ?? 0 return [ - ...sql.exec<{ id: string; text: string; confidence: number; supersedes: string | null; created_at: string; source: string | null; type: string }>( - 'SELECT id, text, confidence, supersedes, created_at, source, type FROM memories ORDER BY created_at DESC LIMIT ? OFFSET ?', + ...sql.exec<{ id: string; text: string; assets: string | null; confidence: number; supersedes: string | null; created_at: string; source: string | null; type: string }>( + 'SELECT id, text, assets, confidence, supersedes, created_at, source, type FROM memories ORDER BY created_at DESC LIMIT ? OFFSET ?', limit, offset, ), ].map(r => ({ id: r.id, text: r.text, + assets: r.assets ? JSON.parse(r.assets) : [], confidence: r.confidence, supersedes: r.supersedes ?? undefined, createdAt: r.created_at, @@ -477,6 +932,13 @@ export function createEdgeMemory( timestamp: r.timestamp, })) }, + + learn(triggerOrText, learningOrOptions, options) { + if (typeof learningOrOptions === 'string') { + return learnStructured(triggerOrText, learningOrOptions, options) + } + return remember(triggerOrText, learningOrOptions as { source?: string } | undefined) + }, } return store diff --git a/packages/deja-edge/src/tagging.ts b/packages/deja-edge/src/tagging.ts new file mode 100644 index 0000000..730b1f0 --- /dev/null +++ b/packages/deja-edge/src/tagging.ts @@ -0,0 +1,58 @@ +const ENTITY_SEQUENCE_RE = /\b(?:[A-Z][A-Za-z0-9-]+(?:\s+[A-Z][A-Za-z0-9-]+)+)\b/g +const SERVICE_PATTERN_RE = /\bthe\s+([A-Z][A-Za-z0-9-]*(?:\s+[A-Z][A-Za-z0-9-]*)*\s+(?:service|api|database|worker|pipeline|gateway))\b/gi +const SUFFIX_PATTERN_RE = /\b([A-Z][A-Za-z0-9-]*(?:\s+[A-Z][A-Za-z0-9-]*)*\s+(?:Service|API|Database|Worker|Pipeline|Gateway))\b/g + +function normalizeTag(tag: string): string { + return tag.replace(/\s+/g, ' ').trim() +} + +function addTag(tags: Map, tag: string) { + const normalized = normalizeTag(tag) + if (!normalized) return + tags.set(normalized.toLowerCase(), normalized) + + const parts = normalized.split(' ') + if (parts.length >= 3) { + for (let size = parts.length - 1; size >= 2; size--) { + for (let start = 0; start <= parts.length - size; start++) { + const subphrase = normalizeTag(parts.slice(start, start + size).join(' ')) + tags.set(subphrase.toLowerCase(), subphrase) + } + } + } +} + +export function extractEntityTags(...texts: Array): string[] { + const tags = new Map() + + for (const text of texts) { + if (!text) continue + + for (const match of text.matchAll(ENTITY_SEQUENCE_RE)) { + addTag(tags, match[0] ?? '') + } + + for (const match of text.matchAll(SERVICE_PATTERN_RE)) { + addTag(tags, match[1] ?? '') + } + + for (const match of text.matchAll(SUFFIX_PATTERN_RE)) { + addTag(tags, match[1] ?? '') + } + } + + return Array.from(tags.values()) +} + +export function countTagOverlap(left: string[] = [], right: string[] = []): number { + if (left.length === 0 || right.length === 0) return 0 + const normalizedRight = right.map(tag => tag.toLowerCase()) + let overlap = 0 + for (const tag of left) { + const normalizedTag = tag.toLowerCase() + if (normalizedRight.some(other => other === normalizedTag || other.includes(normalizedTag) || normalizedTag.includes(other))) { + overlap += 1 + } + } + return overlap +} diff --git a/packages/deja-edge/test/edge-memory.test.ts b/packages/deja-edge/test/edge-memory.test.ts index 49bd040..b93d314 100644 --- a/packages/deja-edge/test/edge-memory.test.ts +++ b/packages/deja-edge/test/edge-memory.test.ts @@ -118,6 +118,50 @@ describe('deja-edge: createEdgeMemory', () => { expect(results.length).toBe(0) }) + test('inject respects maxTokens and prioritizes higher-ranked learnings', () => { + freshMemory() + memory.learn('deploy auth service', 'x'.repeat(160), { scope: 'shared' }) + memory.learn('rollback billing worker', 'y'.repeat(120), { scope: 'shared' }) + + const result = memory.inject('deploy rollback', { maxTokens: 100, format: 'learnings' }) + const estimatedTokens = result.learnings.reduce((total, learning) => { + const text = + learning.tier === 'full' + ? `${learning.trigger}${learning.learning}${learning.confidence}${learning.reason ?? ''}${learning.source ?? ''}` + : learning.trigger + return total + Math.ceil(text.length / 4) + }, 0) + + expect(estimatedTokens).toBeLessThanOrEqual(100) + expect(result.learnings.length).toBeGreaterThan(0) + expect(result.learnings[0].tier).toBe('full') + }) + + test('inject boosts memories with 2+ overlapping tags', () => { + freshMemory() + memory.learn('deploying Auth Service to staging', 'run migrations through the Auth Service API', { + scope: 'shared', + }) + memory.learn('deploying worker', 'check logs before rollout', { scope: 'shared' }) + + const result = memory.inject('staging Auth Service API deploy', { format: 'learnings' }) + expect(result.learnings[0].trigger).toContain('Auth Service') + }) + + test('learn stores asset pointers and inject returns them without affecting rank', () => { + freshMemory() + const learned = memory.learn('deploy auth service', 'attach runbook and trace', { + scope: 'shared', + assets: [{ type: 'trace', ref: 'lab-run-42' }], + }) as any + + expect(learned.assets).toEqual([{ type: 'trace', ref: 'lab-run-42' }]) + + memory.learn('deploying worker', 'check logs before rollout', { scope: 'shared' }) + const listed = memory.list() as any[] + expect(listed.some(learning => learning.assets?.[0]?.ref === 'lab-run-42')).toBe(true) + }) + test('recall respects limit', () => { freshMemory() for (let i = 0; i < 10; i++) { diff --git a/packages/deja-local/src/index.ts b/packages/deja-local/src/index.ts index c0202b9..92df469 100644 --- a/packages/deja-local/src/index.ts +++ b/packages/deja-local/src/index.ts @@ -13,6 +13,7 @@ import { Database } from 'bun:sqlite' import { pipeline, type FeatureExtractionPipeline } from '@huggingface/transformers' +import { countTagOverlap, extractEntityTags } from './tagging' // ============================================================================ // Types @@ -45,6 +46,47 @@ export interface RecallLogEntry { timestamp: string } +export interface LearningRecord { + id: string + text: string + trigger: string + learning: string + tier?: 'trigger' | 'full' + tags?: string[] + assets?: Array<{ type: string; ref: string; label?: string }> + confidence: number + createdAt: string + scope: string + supersedes?: string + source?: string + reason?: string + type: 'memory' | 'anti-pattern' +} + +export interface LearnOptions { + confidence?: number + scope?: string + reason?: string + source?: string + noveltyThreshold?: number + assets?: Array<{ type: string; ref: string; label?: string }> +} + +export interface InjectOptions { + limit?: number + threshold?: number + minConfidence?: number + maxTokens?: number + format?: 'prompt' | 'learnings' + search?: 'vector' + tagBoost?: boolean +} + +export interface InjectResult { + prompt: string + learnings: LearningRecord[] +} + export interface MemoryStore { /** Store a memory. Deduplicates and resolves conflicts automatically. */ remember(text: string, options?: { source?: string }): Promise @@ -52,6 +94,9 @@ export interface MemoryStore { /** Find relevant memories. Decomposes complex queries for better recall. */ recall(context: string, options?: { limit?: number; threshold?: number; minConfidence?: number }): Promise + /** Retrieve structured learnings for injection. */ + inject(context: string, options?: InjectOptions): Promise + /** Signal that a recalled memory was useful. Boosts its confidence. */ confirm(id: string): Promise @@ -74,8 +119,12 @@ export interface MemoryStore { close(): void // Backward compat - /** @deprecated Use remember() */ - learn(text: string, options?: { source?: string }): Promise + /** @deprecated Use remember() for legacy text-only memory writes. */ + learn( + triggerOrText: string, + learningOrOptions?: string | LearnOptions | { source?: string }, + options?: LearnOptions, + ): Promise } export interface CreateMemoryOptions { @@ -194,6 +243,88 @@ function clampConfidence(c: number): number { return Math.min(CONFIDENCE_MAX, Math.max(CONFIDENCE_MIN, Math.round(c * 1000) / 1000)) } +function buildLearningText(trigger: string, learning: string): string { + return `When ${trigger}, ${stripAntiPatternPrefix(learning)}` +} + +function appendDistinctValue(current: string | undefined, incoming: string | undefined): string | undefined { + if (!incoming) return current + if (!current) return incoming + const existing = current.split('\n').map(value => value.trim()).filter(Boolean) + return existing.includes(incoming) ? current : `${current}\n${incoming}` +} + +function estimateTokens(text: string): number { + return Math.ceil(text.length / 4) +} + +function buildLearningPayload(record: LearningRecord, tier: 'trigger' | 'full'): LearningRecord { + if (tier === 'trigger') { + return { + ...record, + tier, + learning: '', + reason: undefined, + source: undefined, + } + } + return { + ...record, + tier, + } +} + +function boostLearningRecordsByTags(learnings: LearningRecord[], queryTags: string[]): LearningRecord[] { + if (queryTags.length === 0) return learnings + const boosted = [...learnings] + boosted.sort((left, right) => { + const leftOverlap = countTagOverlap(queryTags, left.tags ?? []) + const rightOverlap = countTagOverlap(queryTags, right.tags ?? []) + const leftBoost = leftOverlap >= 2 ? 1 : 0 + const rightBoost = rightOverlap >= 2 ? 1 : 0 + if (leftBoost !== rightBoost) return rightBoost - leftBoost + return 0 + }) + return boosted +} + +function applyInjectBudget(learnings: LearningRecord[], maxTokens?: number): LearningRecord[] { + if (!maxTokens || maxTokens <= 0) { + return learnings.map(learning => buildLearningPayload(learning, 'full')) + } + + const triggerBudget = Math.floor(maxTokens * 0.3) + const results = new Map() + let triggerTokensUsed = 0 + + for (const learning of learnings) { + const triggerTokens = estimateTokens(learning.trigger) + if (results.size > 0 && triggerTokensUsed + triggerTokens > triggerBudget) break + results.set(learning.id, buildLearningPayload(learning, 'trigger')) + triggerTokensUsed += triggerTokens + } + + let remainingTokens = maxTokens - triggerTokensUsed + for (const learning of learnings) { + if (!results.has(learning.id)) continue + const fullText = [ + learning.trigger, + learning.learning, + String(learning.confidence), + learning.reason, + learning.source, + ].filter((value): value is string => Boolean(value)).join('\n') + const expansionCost = Math.max(estimateTokens(fullText) - estimateTokens(learning.trigger), 0) + if (expansionCost > remainingTokens) continue + results.set(learning.id, buildLearningPayload(learning, 'full')) + remainingTokens -= expansionCost + } + + return learnings + .filter(learning => results.has(learning.id)) + .map(learning => results.get(learning.id) as LearningRecord) +} + // ============================================================================ // Schema // ============================================================================ @@ -202,6 +333,11 @@ const SCHEMA = ` CREATE TABLE IF NOT EXISTS memories ( id TEXT PRIMARY KEY, text TEXT NOT NULL, + trigger TEXT, + learning TEXT, + reason TEXT, + scope TEXT NOT NULL DEFAULT 'shared', + tags TEXT, embedding BLOB NOT NULL, confidence REAL NOT NULL DEFAULT 0.5, supersedes TEXT, @@ -241,6 +377,24 @@ function migrateSchema(db: Database) { if (!colNames.has('type')) { db.exec("ALTER TABLE memories ADD COLUMN type TEXT NOT NULL DEFAULT 'memory'") } + if (!colNames.has('trigger')) { + db.exec('ALTER TABLE memories ADD COLUMN trigger TEXT') + } + if (!colNames.has('learning')) { + db.exec('ALTER TABLE memories ADD COLUMN learning TEXT') + } + if (!colNames.has('reason')) { + db.exec('ALTER TABLE memories ADD COLUMN reason TEXT') + } + if (!colNames.has('scope')) { + db.exec("ALTER TABLE memories ADD COLUMN scope TEXT NOT NULL DEFAULT 'shared'") + } + if (!colNames.has('assets')) { + db.exec('ALTER TABLE memories ADD COLUMN assets TEXT') + } + if (!colNames.has('tags')) { + db.exec('ALTER TABLE memories ADD COLUMN tags TEXT') + } } // ============================================================================ @@ -262,27 +416,52 @@ export function createMemory(opts: CreateMemoryOptions): MemoryStore { // Prepared statements const insertMemory = db.prepare( - 'INSERT INTO memories (id, text, embedding, confidence, supersedes, created_at, source, type) VALUES (?, ?, ?, ?, ?, ?, ?, ?)' + 'INSERT INTO memories (id, text, trigger, learning, reason, scope, tags, assets, embedding, confidence, supersedes, created_at, source, type) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)' ) const deleteMemory = db.prepare('DELETE FROM memories WHERE id = ?') const updateConfidence = db.prepare('UPDATE memories SET confidence = ? WHERE id = ?') const updateLastRecalledAt = db.prepare('UPDATE memories SET last_recalled_at = ? WHERE id = ?') const updateMemoryTextAndType = db.prepare('UPDATE memories SET text = ?, type = ?, confidence = ? WHERE id = ?') - const selectAll = db.prepare('SELECT id, text, embedding, confidence, supersedes, created_at, last_recalled_at, source, type FROM memories') + const updateStructuredMemory = db.prepare( + 'UPDATE memories SET text = ?, trigger = ?, learning = ?, reason = ?, scope = ?, tags = ?, assets = ?, embedding = ?, confidence = ?, created_at = ?, source = ? WHERE id = ?' + ) + const selectAll = db.prepare('SELECT id, text, trigger, learning, reason, scope, tags, assets, embedding, confidence, supersedes, created_at, last_recalled_at, source, type FROM memories') const countMemories = db.prepare('SELECT COUNT(*) as count FROM memories') const insertRecall = db.prepare( 'INSERT INTO recall_log (context, results, timestamp) VALUES (?, ?, ?)' ) // In-memory vector index — loaded from DB on startup - interface IndexEntry { id: string; text: string; vec: number[]; confidence: number; supersedes?: string; createdAt: string; lastRecalledAt?: string; source?: string; type: 'memory' | 'anti-pattern' } + interface IndexEntry { + id: string + text: string + trigger?: string + learning?: string + reason?: string + scope: string + tags?: string[] + assets?: Array<{ type: string; ref: string; label?: string }> + vec: number[] + confidence: number + supersedes?: string + createdAt: string + lastRecalledAt?: string + source?: string + type: 'memory' | 'anti-pattern' + } const index: IndexEntry[] = [] // Load existing memories into index - for (const row of selectAll.all() as Array<{ id: string; text: string; embedding: Buffer; confidence: number; supersedes: string | null; created_at: string; last_recalled_at: string | null; source: string | null; type: string }>) { + for (const row of selectAll.all() as Array<{ id: string; text: string; trigger: string | null; learning: string | null; reason: string | null; scope: string | null; tags: string | null; assets: string | null; embedding: Buffer; confidence: number; supersedes: string | null; created_at: string; last_recalled_at: string | null; source: string | null; type: string }>) { index.push({ id: row.id, text: row.text, + trigger: row.trigger ?? undefined, + learning: row.learning ?? undefined, + reason: row.reason ?? undefined, + scope: row.scope ?? 'shared', + tags: row.tags ? JSON.parse(row.tags) : [], + assets: row.assets ? JSON.parse(row.assets) : [], vec: bufferToVec(row.embedding), confidence: row.confidence, supersedes: row.supersedes ?? undefined, @@ -330,12 +509,179 @@ export function createMemory(opts: CreateMemoryOptions): MemoryStore { const buf = vecToBuffer(vec) const type: 'memory' | 'anti-pattern' = 'memory' - insertMemory.run(id, text, buf, confidence, supersedes ?? null, createdAt, source ?? null, type) - index.push({ id, text, vec, confidence, supersedes, createdAt, source, type }) + insertMemory.run( + id, + text, + null, + null, + null, + 'shared', + JSON.stringify([]), + JSON.stringify([]), + buf, + confidence, + supersedes ?? null, + createdAt, + source ?? null, + type, + ) + index.push({ id, text, scope: 'shared', vec, confidence, supersedes, createdAt, source, type }) return { id, text, confidence, createdAt, supersedes, source, type } } + async function learnStructured( + trigger: string, + learning: string, + options: LearnOptions = {}, + ): Promise { + const normalizedTrigger = trigger.trim() + const normalizedLearning = learning.trim() + const scope = options.scope ?? 'shared' + const reason = options.reason?.trim() || undefined + const source = options.source?.trim() || undefined + const assets = options.assets ?? [] + const noveltyThreshold = options.noveltyThreshold ?? dedupeThreshold + const nextConfidence = clampConfidence(options.confidence ?? CONFIDENCE_DEFAULT) + const text = buildLearningText(normalizedTrigger, normalizedLearning) + const tags = extractEntityTags(normalizedTrigger, normalizedLearning) + const vec = await embed(text) + + let bestSimilarity = 0 + let bestEntry: IndexEntry | null = null + + for (const entry of index) { + if (entry.scope !== scope) continue + const sim = cosine(vec, entry.vec) + if (sim > bestSimilarity) { + bestSimilarity = sim + bestEntry = entry + } + } + + if ( + noveltyThreshold > 0 && + bestEntry && + bestEntry.trigger && + bestEntry.learning && + bestSimilarity >= noveltyThreshold + ) { + const keepIncomingVersion = nextConfidence > bestEntry.confidence + const createdAt = new Date().toISOString() + const mergedReason = appendDistinctValue(bestEntry.reason, reason) + const mergedSource = appendDistinctValue(bestEntry.source, source) + const mergedConfidence = Math.max(bestEntry.confidence, nextConfidence) + const mergedTrigger = keepIncomingVersion ? normalizedTrigger : bestEntry.trigger + const mergedLearning = keepIncomingVersion ? normalizedLearning : bestEntry.learning + const mergedText = keepIncomingVersion ? text : bestEntry.text + const mergedVec = keepIncomingVersion ? vec : bestEntry.vec + + updateStructuredMemory.run( + mergedText, + mergedTrigger, + mergedLearning, + mergedReason ?? null, + scope, + JSON.stringify(tags), + JSON.stringify(assets), + vecToBuffer(mergedVec), + mergedConfidence, + createdAt, + mergedSource ?? null, + bestEntry.id, + ) + + bestEntry.text = mergedText + bestEntry.trigger = mergedTrigger + bestEntry.learning = mergedLearning + bestEntry.reason = mergedReason + bestEntry.scope = scope + bestEntry.tags = tags + bestEntry.assets = assets + bestEntry.vec = mergedVec + bestEntry.confidence = mergedConfidence + bestEntry.createdAt = createdAt + bestEntry.source = mergedSource + + return { + id: bestEntry.id, + text: mergedText, + trigger: mergedTrigger, + learning: mergedLearning, + confidence: mergedConfidence, + createdAt, + scope, + tags, + assets, + supersedes: bestEntry.supersedes, + source: mergedSource, + reason: mergedReason, + type: bestEntry.type, + } + } + + let supersedes: string | undefined + if (bestEntry && bestSimilarity >= conflictThreshold) { + supersedes = bestEntry.id + const newConf = clampConfidence(bestEntry.confidence * 0.3) + updateConfidence.run(newConf, bestEntry.id) + bestEntry.confidence = newConf + } + + const id = crypto.randomUUID() + const createdAt = new Date().toISOString() + const type: 'memory' | 'anti-pattern' = 'memory' + + insertMemory.run( + id, + text, + normalizedTrigger, + normalizedLearning, + reason ?? null, + scope, + JSON.stringify(tags), + JSON.stringify(assets), + vecToBuffer(vec), + nextConfidence, + supersedes ?? null, + createdAt, + source ?? null, + type, + ) + index.push({ + id, + text, + trigger: normalizedTrigger, + learning: normalizedLearning, + reason, + scope, + tags, + assets, + vec, + confidence: nextConfidence, + supersedes, + createdAt, + source, + type, + }) + + return { + id, + text, + trigger: normalizedTrigger, + learning: normalizedLearning, + confidence: nextConfidence, + createdAt, + scope, + tags, + assets, + supersedes, + source, + reason, + type, + } + } + async function recall(context: string, options: { limit?: number; threshold?: number; minConfidence?: number } = {}): Promise { const limit = options.limit ?? 5 const min = options.threshold ?? threshold @@ -398,6 +744,76 @@ export function createMemory(opts: CreateMemoryOptions): MemoryStore { return topResults } + async function inject(context: string, options: InjectOptions = {}): Promise { + const search = options.search ?? 'vector' + if (search !== 'vector') { + throw new Error(`Unsupported local inject search mode: ${search}`) + } + + const limit = options.limit ?? 5 + const min = options.threshold ?? threshold + const minConf = options.minConfidence ?? 0 + const now = new Date().toISOString() + const nowMs = Date.now() + const subQueries = decomposeQuery(context) + const subVecs = await Promise.all(subQueries.map(q => embed(q))) + + const scored: Array = [] + for (const entry of index) { + if (entry.confidence < minConf) continue + + let bestScore = 0 + for (const qv of subVecs) { + const sim = cosine(qv, entry.vec) + if (sim > bestScore) bestScore = sim + } + if (bestScore < min) continue + + const lastActiveAt = entry.lastRecalledAt ?? entry.createdAt + const daysSince = (nowMs - new Date(lastActiveAt).getTime()) / 86400000 + const decayedConfidence = entry.confidence * Math.pow(0.5, daysSince / HALF_LIFE_DAYS) + const blended = bestScore * 0.7 + decayedConfidence * 0.3 + scored.push({ + id: entry.id, + text: entry.text, + trigger: entry.trigger ?? entry.text, + learning: entry.learning ?? entry.text, + tags: entry.tags ?? [], + assets: entry.assets ?? [], + confidence: entry.confidence, + createdAt: entry.createdAt, + scope: entry.scope, + supersedes: entry.supersedes, + source: entry.source, + reason: entry.reason, + type: entry.type, + score: Math.round(blended * 1000) / 1000, + }) + } + + scored.sort((a, b) => b.score - a.score) + const ranked = ( + options.tagBoost === false + ? scored.slice(0, Math.max(limit * 2, limit)) + : boostLearningRecordsByTags( + scored.slice(0, Math.max(limit * 2, limit)), + extractEntityTags(context), + ) + ).slice(0, limit) + + for (const learning of ranked) { + updateLastRecalledAt.run(now, learning.id) + const entry = index.find(e => e.id === learning.id) + if (entry) entry.lastRecalledAt = now + } + + const payloadLearnings = applyInjectBudget(ranked.map(({ score: _, ...learning }) => learning), options.maxTokens) + return { + prompt: payloadLearnings.map(learning => `When ${learning.trigger}, ${learning.learning}`).join('\n'), + learnings: payloadLearnings, + } + } + const store: MemoryStore = { get size() { return (countMemories.get() as { count: number }).count }, @@ -405,6 +821,8 @@ export function createMemory(opts: CreateMemoryOptions): MemoryStore { recall, + inject, + async confirm(id) { const entry = index.find(e => e.id === id) if (!entry) return false @@ -465,7 +883,12 @@ export function createMemory(opts: CreateMemoryOptions): MemoryStore { close() { db.close() }, // Backward compat - learn: remember, + learn(triggerOrText, learningOrOptions, options) { + if (typeof learningOrOptions === 'string') { + return learnStructured(triggerOrText, learningOrOptions, options) + } + return remember(triggerOrText, learningOrOptions as { source?: string } | undefined) + }, } return store @@ -495,6 +918,7 @@ export class DejaLocal implements MemoryStore { remember(text: string, options?: { source?: string }) { return this.store.remember(text, options) } recall(context: string, options?: Parameters[1]) { return this.store.recall(context, options) } + inject(context: string, options?: InjectOptions) { return this.store.inject(context, options) } confirm(id: string) { return this.store.confirm(id) } reject(id: string) { return this.store.reject(id) } forget(id: string) { return this.store.forget(id) } @@ -502,8 +926,14 @@ export class DejaLocal implements MemoryStore { recallLog(options?: Parameters[0]) { return this.store.recallLog(options) } get size() { return this.store.size } close() { return this.store.close() } - /** @deprecated Use remember() */ - learn(text: string, options?: { source?: string }) { return this.store.learn(text, options) } + /** @deprecated Use remember() for legacy text-only writes. */ + learn( + triggerOrText: string, + learningOrOptions?: string | LearnOptions | { source?: string }, + options?: LearnOptions, + ) { + return this.store.learn(triggerOrText, learningOrOptions as any, options) + } } export { createModelEmbed } diff --git a/packages/deja-local/src/tagging.ts b/packages/deja-local/src/tagging.ts new file mode 100644 index 0000000..79e7ab8 --- /dev/null +++ b/packages/deja-local/src/tagging.ts @@ -0,0 +1,56 @@ +const ENTITY_SEQUENCE_RE = /\b(?:[A-Z][a-z0-9]+(?:\s+[A-Z][a-z0-9]+)+)\b/g +const SERVICE_PATTERN_RE = /\bthe\s+([A-Z][A-Za-z0-9-]*(?:\s+[A-Z][A-Za-z0-9-]*)*\s+(?:service|api|database|worker|pipeline|gateway))\b/gi +const SUFFIX_PATTERN_RE = /\b([A-Z][A-Za-z0-9-]*(?:\s+[A-Z][A-Za-z0-9-]*)*\s+(?:Service|API|Database|Worker|Pipeline|Gateway))\b/g + +function normalizeTag(tag: string): string { + return tag.replace(/\s+/g, ' ').trim() +} + +function addTag(tags: Map, rawTag: string) { + const tag = normalizeTag(rawTag) + if (tag) tags.set(tag.toLowerCase(), tag) +} + +export function extractEntityTags(...texts: Array): string[] { + const tags = new Map() + + for (const text of texts) { + if (!text) continue + + for (const match of text.matchAll(ENTITY_SEQUENCE_RE)) { + const tag = normalizeTag(match[0] ?? '') + addTag(tags, tag) + const words = tag.split(' ') + if (words.length > 2) { + for (let size = 2; size < words.length; size += 1) { + for (let start = 0; start + size <= words.length; start += 1) { + addTag(tags, words.slice(start, start + size).join(' ')) + } + } + } + } + + for (const match of text.matchAll(SERVICE_PATTERN_RE)) { + addTag(tags, match[1] ?? '') + } + + for (const match of text.matchAll(SUFFIX_PATTERN_RE)) { + addTag(tags, match[1] ?? '') + } + } + + return Array.from(tags.values()) +} + +export function countTagOverlap(left: string[] = [], right: string[] = []): number { + if (left.length === 0 || right.length === 0) return 0 + const normalizedRight = right.map(tag => tag.toLowerCase()) + let overlap = 0 + for (const tag of left) { + const normalizedTag = tag.toLowerCase() + if (normalizedRight.some(other => other === normalizedTag || other.includes(normalizedTag) || normalizedTag.includes(other))) { + overlap += 1 + } + } + return overlap +} diff --git a/packages/deja-local/test/index.test.ts b/packages/deja-local/test/index.test.ts index 4a58fd9..1ea35a8 100644 --- a/packages/deja-local/test/index.test.ts +++ b/packages/deja-local/test/index.test.ts @@ -140,6 +140,128 @@ describe('deduplication', () => { }) }) +describe('structured learn novelty gate', () => { + test('semantically identical learnings merge into one structured memory', async () => { + const semanticEmbed = (text: string): number[] => { + const lower = text.toLowerCase() + if (lower.includes('auth service') && (lower.includes('migrations') || lower.includes('schema'))) { + return [1, 0, 0] + } + if (lower.includes('redis')) { + return [0, 1, 0] + } + return [0, 0, 1] + } + + const p = tmpDb() + cleanup.push(p) + const m = createMemory({ path: p, embed: semanticEmbed, threshold: 0.1 }) + + const first = await m.learn('deploying Auth Service', 'run database migrations in a transaction', { + confidence: 0.6, + reason: 'first incident', + source: 'ops', + } as any) + const second = await m.learn('shipping Auth Service', 'wrap schema changes in a transaction', { + confidence: 0.9, + reason: 'second incident', + source: 'pager', + } as any) + + expect(m.size).toBe(1) + expect(second.id).toBe(first.id) + expect((second as any).trigger).toBe('shipping Auth Service') + expect((second as any).learning).toBe('wrap schema changes in a transaction') + expect((second as any).reason).toBe('first incident\nsecond incident') + expect((second as any).source).toBe('ops\npager') + m.close() + }) + + test('different structured learnings remain distinct', async () => { + const semanticEmbed = (text: string): number[] => { + const lower = text.toLowerCase() + if (lower.includes('auth service')) return [1, 0, 0] + if (lower.includes('redis')) return [0, 1, 0] + return [0, 0, 1] + } + + const p = tmpDb() + cleanup.push(p) + const m = createMemory({ path: p, embed: semanticEmbed, threshold: 0.1 }) + + await m.learn('deploying Auth Service', 'run database migrations in a transaction', { confidence: 0.6 } as any) + await m.learn('debugging Redis cache', 'clear stale keys before replaying jobs', { confidence: 0.6 } as any) + + expect(m.size).toBe(2) + m.close() + }) +}) + +describe('inject maxTokens', () => { + test('returns higher-relevance learnings first within the token budget', async () => { + const m = mem() + await m.learn('deploy auth service', 'x'.repeat(160), { scope: 'shared' }) + await m.learn('rollback billing worker', 'y'.repeat(120), { scope: 'shared' }) + + const result = await m.inject('deploy rollback', { maxTokens: 100, format: 'learnings' }) + const estimatedTokens = result.learnings.reduce((total, learning) => { + const text = + learning.tier === 'full' + ? `${learning.trigger}${learning.learning}${learning.confidence}${learning.reason ?? ''}${learning.source ?? ''}` + : learning.trigger + return total + Math.ceil(text.length / 4) + }, 0) + + expect(estimatedTokens).toBeLessThanOrEqual(100) + expect(result.learnings[0].tier).toBe('full') + expect(result.learnings).toHaveLength(1) + m.close() + }) +}) + +describe('entity tags', () => { + test('structured learn stores extracted tags', async () => { + const m = mem() + const learning = await m.learn( + 'deploying Auth Service to staging', + 'always run migrations in a transaction for the Auth Service API', + { scope: 'shared' }, + ) as any + + expect(learning.tags).toContain('Auth Service') + m.close() + }) + + test('inject boosts memories with 2+ overlapping tags', async () => { + const m = mem() + await m.learn('deploying worker', 'check logs before rollout', { scope: 'shared' }) + await m.learn('deploying Auth Service to staging', 'run migrations through the Auth Service API', { scope: 'shared' }) + + const result = await m.inject('staging Auth Service API deploy', { format: 'learnings' }) + + expect(result.learnings[0].trigger).toContain('Auth Service') + m.close() + }) +}) + +describe('asset pointers', () => { + test('structured learn returns asset pointers and inject preserves them', async () => { + const m = mem() + const assets = [{ type: 'trace', ref: 'lab-run-42', label: 'rollback trace' }] + const learning = await m.learn( + 'deploying Auth Service', + 'check migration order', + { scope: 'shared', assets } as any, + ) as any + + expect(learning.assets).toEqual(assets) + + const listed = m.list() as any[] + expect(listed.some((entry: any) => entry.id === learning.id)).toBe(true) + m.close() + }) +}) + // ============================================================================ // Trust guarantee: AUDITABILITY // ============================================================================ diff --git a/src/do/DejaDO.ts b/src/do/DejaDO.ts index ace0628..a8c8ed0 100644 --- a/src/do/DejaDO.ts +++ b/src/do/DejaDO.ts @@ -62,6 +62,7 @@ export class DejaDO extends DurableObject { createEmbedding: (text: string) => this.createEmbedding(text), filterScopesByPriority, convertDbLearning, + sql: this.ctx.storage.sql, }; } @@ -98,8 +99,27 @@ export class DejaDO extends DurableObject { return cleanupLearnings(this.getMemoryContext()); } - async inject(scopes: string[], context: string, limit: number = 5, format: 'prompt' | 'learnings' = 'prompt', identity?: SharedRunIdentity): Promise { - return injectMemories(this.getMemoryContext(), scopes, context, limit, format, identity); + async inject( + scopes: string[], + context: string, + limit: number = 5, + format: 'prompt' | 'learnings' = 'prompt', + search: 'vector' | 'text' | 'hybrid' = 'hybrid', + identity?: SharedRunIdentity, + maxTokens?: number, + tagBoost: boolean = true, + ): Promise { + return injectMemories( + this.getMemoryContext(), + scopes, + context, + limit, + format, + search, + identity, + maxTokens, + tagBoost, + ); } async injectTrace( @@ -112,8 +132,29 @@ export class DejaDO extends DurableObject { return injectMemoriesWithTrace(this.getMemoryContext(), scopes, context, limit, threshold, identity); } - async learn(scope: string, trigger: string, learning: string, confidence: number = 0.5, reason?: string, source?: string, identity?: SharedRunIdentity): Promise { - return learnMemory(this.getMemoryContext(), scope, trigger, learning, confidence, reason, source, identity); + async learn( + scope: string, + trigger: string, + learning: string, + confidence: number = 0.5, + reason?: string, + source?: string, + assets?: Array<{ type: string; ref: string; label?: string }>, + identity?: SharedRunIdentity, + noveltyThreshold?: number, + ): Promise { + return learnMemory( + this.getMemoryContext(), + scope, + trigger, + learning, + confidence, + reason, + source, + assets, + identity, + noveltyThreshold, + ); } async confirm(id: string, identity?: SharedRunIdentity): Promise { diff --git a/src/do/helpers.ts b/src/do/helpers.ts index 1596dd8..21343da 100644 --- a/src/do/helpers.ts +++ b/src/do/helpers.ts @@ -13,6 +13,8 @@ export function initializeStorage(state: DurableObjectState) { trigger TEXT NOT NULL, learning TEXT NOT NULL, reason TEXT, + tags TEXT, + assets TEXT, confidence REAL DEFAULT 1.0, source TEXT, scope TEXT NOT NULL, @@ -31,6 +33,26 @@ export function initializeStorage(state: DurableObjectState) { CREATE INDEX IF NOT EXISTS idx_learnings_confidence ON learnings(confidence); CREATE INDEX IF NOT EXISTS idx_learnings_created_at ON learnings(created_at); CREATE INDEX IF NOT EXISTS idx_learnings_scope ON learnings(scope); + + CREATE VIRTUAL TABLE IF NOT EXISTS learnings_fts USING fts5( + trigger, + learning, + content='learnings', + content_rowid='rowid', + tokenize='porter unicode61' + ); + CREATE TRIGGER IF NOT EXISTS learnings_ai AFTER INSERT ON learnings BEGIN + INSERT INTO learnings_fts(rowid, trigger, learning) VALUES (new.rowid, new.trigger, new.learning); + END; + CREATE TRIGGER IF NOT EXISTS learnings_ad AFTER DELETE ON learnings BEGIN + INSERT INTO learnings_fts(learnings_fts, rowid, trigger, learning) + VALUES('delete', old.rowid, old.trigger, old.learning); + END; + CREATE TRIGGER IF NOT EXISTS learnings_au AFTER UPDATE ON learnings BEGIN + INSERT INTO learnings_fts(learnings_fts, rowid, trigger, learning) + VALUES('delete', old.rowid, old.trigger, old.learning); + INSERT INTO learnings_fts(rowid, trigger, learning) VALUES (new.rowid, new.trigger, new.learning); + END; `); try { state.storage.sql.exec(`ALTER TABLE learnings ADD COLUMN last_recalled_at TEXT`); @@ -65,6 +87,12 @@ export function initializeStorage(state: DurableObjectState) { try { state.storage.sql.exec(`ALTER TABLE learnings ADD COLUMN type TEXT NOT NULL DEFAULT 'memory'`); } catch (_) {} + try { + state.storage.sql.exec(`ALTER TABLE learnings ADD COLUMN assets TEXT`); + } catch (_) {} + try { + state.storage.sql.exec(`ALTER TABLE learnings ADD COLUMN tags TEXT`); + } catch (_) {} state.storage.sql.exec(` CREATE TABLE IF NOT EXISTS secrets ( @@ -167,11 +195,13 @@ export function convertDbLearning(dbLearning: any): Learning { trigger: dbLearning.trigger, learning: dbLearning.learning, reason: dbLearning.reason !== null ? dbLearning.reason : undefined, + assets: dbLearning.assets ? JSON.parse(dbLearning.assets) : [], confidence: dbLearning.confidence !== null ? dbLearning.confidence : 0, source: dbLearning.source !== null ? dbLearning.source : undefined, scope: dbLearning.scope, supersedes: dbLearning.supersedes ?? undefined, type: (dbLearning.type as Learning['type'] | null) ?? 'memory', + tags: dbLearning.tags ? JSON.parse(dbLearning.tags) : [], embedding: dbLearning.embedding ? JSON.parse(dbLearning.embedding) : undefined, createdAt: dbLearning.createdAt, lastRecalledAt: dbLearning.lastRecalledAt ?? undefined, diff --git a/src/do/memory.ts b/src/do/memory.ts index 0203543..c422cd6 100644 --- a/src/do/memory.ts +++ b/src/do/memory.ts @@ -2,6 +2,7 @@ import { and, desc, eq, inArray, like, sql } from 'drizzle-orm'; import * as schema from '../schema'; import { createLearningId } from './helpers'; +import { extractEntityTags } from '../tagging'; import type { InjectResult, InjectTraceResult, @@ -34,6 +35,80 @@ function clampConfidence(confidence: number): number { return Math.min(CONFIDENCE_MAX, Math.max(CONFIDENCE_MIN, Math.round(confidence * 1000) / 1000)); } +function appendDistinctValue(current: string | undefined, incoming: string | undefined): string | undefined { + if (!incoming) return current; + if (!current) return incoming; + const existingValues = current + .split('\n') + .map((value) => value.trim()) + .filter(Boolean); + if (existingValues.includes(incoming)) { + return current; + } + return `${current}\n${incoming}`; +} + +function estimateTokens(text: string): number { + return Math.ceil(text.length / 4); +} + +function buildLearningPayload(learning: Learning, tier: 'trigger' | 'full'): Learning { + return { + ...learning, + tier, + learning: tier === 'full' ? learning.learning : '', + reason: tier === 'full' ? learning.reason : undefined, + source: tier === 'full' ? learning.source : undefined, + assets: tier === 'full' ? learning.assets : learning.assets, + }; +} + +function applyInjectBudget( + learnings: Learning[], + maxTokens?: number, +): Learning[] { + if (!maxTokens || maxTokens <= 0) { + return learnings.map((learning) => buildLearningPayload(learning, 'full')); + } + + const triggerBudget = Math.floor(maxTokens * 0.3); + const triggerTier: Learning[] = []; + let triggerTokensUsed = 0; + + for (const learning of learnings) { + const triggerTokens = estimateTokens(learning.trigger); + if (triggerTier.length > 0 && triggerTokensUsed + triggerTokens > triggerBudget) { + break; + } + triggerTier.push(buildLearningPayload(learning, 'trigger')); + triggerTokensUsed += triggerTokens; + } + + const resultById = new Map(triggerTier.map((learning) => [learning.id, learning])); + let remainingTokens = maxTokens - triggerTokensUsed; + + for (const learning of learnings) { + if (!resultById.has(learning.id)) { + continue; + } + const fullText = [learning.trigger, learning.learning, learning.reason, learning.source] + .filter((value): value is string => typeof value === 'string' && value.length > 0) + .join('\n'); + const fullTokens = estimateTokens(fullText); + const triggerTokens = estimateTokens(learning.trigger); + const expansionCost = Math.max(fullTokens - triggerTokens, 0); + if (expansionCost > remainingTokens) { + continue; + } + resultById.set(learning.id, buildLearningPayload(learning, 'full')); + remainingTokens -= expansionCost; + } + + return learnings + .filter((learning) => resultById.has(learning.id)) + .map((learning) => resultById.get(learning.id) as Learning); +} + function mergeIdentity( current: SharedRunIdentity | undefined, updates: SharedRunIdentity | undefined, @@ -87,10 +162,20 @@ function buildVectorMetadata(learning: Learning): Record { if (learning.supersedes) metadata.supersedes = learning.supersedes; if (learning.source) metadata.source = learning.source; + if (learning.tags?.length) metadata.tags = JSON.stringify(learning.tags); return metadata; } +function buildFtsQuery(text: string): string { + const keywords = text + .toLowerCase() + .replace(/[^a-z0-9\s-]/g, ' ') + .split(/\s+/) + .filter((word) => word.length > 1); + return keywords.map((keyword) => `"${keyword}"`).join(' OR '); +} + async function upsertLearningVector( ctx: MemoryOperationsContext, learning: Learning, @@ -140,6 +225,84 @@ async function getNearestLearningMatches( .filter((match: { row: any; similarity: number } | null): match is { row: any; similarity: number } => match !== null); } +async function queryHostedTextSearch( + sqlDb: DurableObjectState['storage']['sql'] | undefined, + scopes: string[], + context: string, + limit: number, +): Promise { + if (!sqlDb) { + return []; + } + const ftsQuery = buildFtsQuery(context); + if (!ftsQuery) { + return []; + } + + return [ + ...sqlDb.exec( + `SELECT l.* + FROM learnings_fts + JOIN learnings l ON l.rowid = learnings_fts.rowid + WHERE learnings_fts MATCH ? + AND l.scope IN (${scopes.map(() => '?').join(', ')}) + ORDER BY bm25(learnings_fts) + LIMIT ?`, + ftsQuery, + ...scopes, + limit, + ), + ]; +} + +async function loadRankedLearnings( + ctx: MemoryOperationsContext, + db: any, + ids: string[], + scopes: string[], +): Promise { + if (ids.length === 0) { + return []; + } + + const rows = await db + .select() + .from(schema.learnings) + .where( + and( + inArray(schema.learnings.id, ids), + inArray(schema.learnings.scope, scopes), + ), + ); + const rowById = new Map(rows.map((row: any) => [row.id, row])); + return ids + .map((id) => rowById.get(id)) + .filter((row: any | undefined): row is any => row !== undefined) + .map((row: any) => ctx.convertDbLearning(rowById.get(row.id) ?? row)); +} + +function countTagOverlap(queryTags: string[], learning: Learning): number { + if (!queryTags.length || !learning.tags?.length) { + return 0; + } + const learningTags = learning.tags.map((tag) => tag.toLowerCase()); + let matches = 0; + for (const queryTag of queryTags) { + const normalizedQueryTag = queryTag.toLowerCase(); + if ( + learningTags.some( + (learningTag) => + learningTag === normalizedQueryTag || + learningTag.includes(normalizedQueryTag) || + normalizedQueryTag.includes(learningTag), + ) + ) { + matches += 1; + } + } + return matches; +} + export async function cleanupLearnings( ctx: MemoryOperationsContext, ): Promise<{ deleted: number; reasons: string[] }> { @@ -223,7 +386,10 @@ export async function injectMemories( context: string, limit: number = 5, format: 'prompt' | 'learnings' = 'prompt', + search: 'vector' | 'text' | 'hybrid' = 'hybrid', _identity?: SharedRunIdentity, + maxTokens?: number, + tagBoost: boolean = true, ): Promise { const db = await ctx.initDB(); const filteredScopes = ctx.filterScopesByPriority(scopes); @@ -232,46 +398,53 @@ export async function injectMemories( } try { - const embedding = await ctx.createEmbedding(context); - const vectorResults = await ctx.env.VECTORIZE.query(embedding, { - topK: limit * 2, - returnValues: true, - }); - const ids = vectorResults.matches.map((match: any) => match.id); + const ids: string[] = []; + const seen = new Set(); + + if (search === 'vector' || search === 'hybrid') { + const embedding = await ctx.createEmbedding(context); + const vectorResults = await ctx.env.VECTORIZE.query(embedding, { + topK: limit * 2, + returnValues: true, + }); + for (const match of vectorResults.matches) { + if (seen.has(match.id)) continue; + seen.add(match.id); + ids.push(match.id); + } + } + + if (search === 'text' || search === 'hybrid') { + const textRows = await queryHostedTextSearch(ctx.sql, filteredScopes, context, limit * 2); + for (const row of textRows) { + if (seen.has(row.id)) continue; + seen.add(row.id); + ids.push(row.id); + } + } if (ids.length === 0) { return { prompt: '', learnings: [] }; } - const dbLearnings = await db - .select() - .from(schema.learnings) - .where( - and( - inArray(schema.learnings.id, ids), - inArray(schema.learnings.scope, filteredScopes), - ), - ) - .limit(limit); - - const learnings = dbLearnings.map((learning: any) => ctx.convertDbLearning(learning)); + const queryTags = tagBoost ? extractEntityTags(context) : []; + const rankedLearnings = (await loadRankedLearnings(ctx, db, ids, filteredScopes)) + .sort((left: Learning, right: Learning) => { + const leftOverlap = countTagOverlap(queryTags, left); + const rightOverlap = countTagOverlap(queryTags, right); + const leftBoost = leftOverlap >= 2 ? 1 : 0; + const rightBoost = rightOverlap >= 2 ? 1 : 0; + if (rightBoost !== leftBoost) { + return rightBoost - leftBoost; + } + return ids.indexOf(left.id) - ids.indexOf(right.id); + }) + .slice(0, limit); + const injectedLearnings = applyInjectBudget(rankedLearnings, maxTokens); const now = new Date().toISOString(); - const nowMs = Date.now(); - - // Apply time-based confidence decay for ranking (read-side only, stored values unchanged) - const HALF_LIFE_DAYS = 90; - const rankedLearnings = [...learnings].sort((a: Learning, b: Learning) => { - const aLastActive = a.lastRecalledAt ?? a.createdAt; - const bLastActive = b.lastRecalledAt ?? b.createdAt; - const aDays = (nowMs - new Date(aLastActive).getTime()) / 86400000; - const bDays = (nowMs - new Date(bLastActive).getTime()) / 86400000; - const aDecayed = (a.confidence ?? 1.0) * Math.pow(0.5, aDays / HALF_LIFE_DAYS); - const bDecayed = (b.confidence ?? 1.0) * Math.pow(0.5, bDays / HALF_LIFE_DAYS); - return bDecayed - aDecayed; - }); await Promise.all( - rankedLearnings.map((learning: Learning) => + injectedLearnings.map((learning: Learning) => db .update(schema.learnings) .set({ @@ -284,14 +457,18 @@ export async function injectMemories( if (format === 'prompt') { return { - prompt: rankedLearnings - .map((learning: Learning) => `When ${learning.trigger}, ${learning.learning}`) + prompt: injectedLearnings + .map((learning: Learning) => + learning.tier === 'trigger' + ? learning.trigger + : `When ${learning.trigger}, ${learning.learning}`, + ) .join('\n'), - learnings: rankedLearnings, + learnings: injectedLearnings, }; } - return { prompt: '', learnings: rankedLearnings }; + return { prompt: '', learnings: injectedLearnings }; } catch (error) { console.error('Inject error:', error); return { prompt: '', learnings: [] }; @@ -422,7 +599,9 @@ export async function learnMemory( confidence: number = 0.5, reason?: string, source?: string, + assets?: Array<{ type: string; ref: string; label?: string }>, identity?: SharedRunIdentity, + noveltyThreshold: number = DEDUPE_THRESHOLD, ): Promise { const db = await ctx.initDB(); const normalizedConfidence = clampConfidence(confidence); @@ -430,19 +609,60 @@ export async function learnMemory( const nearestMatches = await getNearestLearningMatches(ctx, db, embedding, scope); const bestMatch = nearestMatches[0]; - if (bestMatch && bestMatch.similarity >= DEDUPE_THRESHOLD) { + if (noveltyThreshold > 0 && bestMatch && bestMatch.similarity >= noveltyThreshold) { const existingLearning = ctx.convertDbLearning(bestMatch.row); const mergedIdentity = mergeIdentity(existingLearning.identity, identity); + const keepIncomingVersion = normalizedConfidence > existingLearning.confidence; + const nextTrigger = keepIncomingVersion ? trigger : existingLearning.trigger; + const nextLearningText = keepIncomingVersion ? learning : existingLearning.learning; + const nextConfidence = Math.max(existingLearning.confidence, normalizedConfidence); + const nextReason = appendDistinctValue(existingLearning.reason, reason); + const nextSource = appendDistinctValue(existingLearning.source, source); + const nextAssets = assets ?? existingLearning.assets; + const nextCreatedAt = new Date().toISOString(); + const nextEmbedding = keepIncomingVersion + ? embedding + : existingLearning.embedding ?? + (bestMatch.row.embedding ? JSON.parse(bestMatch.row.embedding) : undefined); - if (!identitiesEqual(existingLearning.identity, mergedIdentity)) { - await db - .update(schema.learnings) - .set(learningIdentityFields(mergedIdentity)) - .where(eq(schema.learnings.id, existingLearning.id)); - } + await db + .update(schema.learnings) + .set({ + trigger: nextTrigger, + learning: nextLearningText, + confidence: nextConfidence, + reason: nextReason ?? null, + source: nextSource ?? null, + assets: nextAssets ? JSON.stringify(nextAssets) : null, + createdAt: nextCreatedAt, + embedding: nextEmbedding ? JSON.stringify(nextEmbedding) : null, + ...learningIdentityFields(mergedIdentity), + }) + .where(eq(schema.learnings.id, existingLearning.id)); + + await upsertLearningVector(ctx, { + ...existingLearning, + trigger: nextTrigger, + learning: nextLearningText, + confidence: nextConfidence, + reason: nextReason, + source: nextSource, + assets: nextAssets, + createdAt: nextCreatedAt, + identity: mergedIdentity, + embedding: nextEmbedding, + }); return { ...existingLearning, + trigger: nextTrigger, + learning: nextLearningText, + confidence: nextConfidence, + reason: nextReason, + source: nextSource, + assets: nextAssets, + createdAt: nextCreatedAt, + embedding: nextEmbedding, identity: mergedIdentity, }; } @@ -458,13 +678,16 @@ export async function learnMemory( } const id = createLearningId(); + const tags = extractEntityTags(trigger, learning); const newLearning: Learning = { id, trigger, learning, + tags, reason, confidence: normalizedConfidence, source, + assets, scope, supersedes, type: 'memory', @@ -481,9 +704,11 @@ export async function learnMemory( reason: newLearning.reason, confidence: newLearning.confidence, source: newLearning.source, + assets: newLearning.assets ? JSON.stringify(newLearning.assets) : null, scope: newLearning.scope, supersedes: newLearning.supersedes ?? null, type: newLearning.type, + tags: JSON.stringify(newLearning.tags ?? []), embedding: newLearning.embedding ? JSON.stringify(newLearning.embedding) : null, createdAt: newLearning.createdAt, ...learningIdentityFields(identity), diff --git a/src/do/routes.ts b/src/do/routes.ts index e0add8c..56674a6 100644 --- a/src/do/routes.ts +++ b/src/do/routes.ts @@ -27,7 +27,9 @@ interface RouteHandlers { confidence?: number, reason?: string, source?: string, + assets?: Array<{ type: string; ref: string; label?: string }>, identity?: SharedRunIdentity, + noveltyThreshold?: number, ): Promise; confirm(id: string, identity?: SharedRunIdentity): Promise; reject(id: string, identity?: SharedRunIdentity): Promise; @@ -37,7 +39,10 @@ interface RouteHandlers { context: string, limit?: number, format?: 'prompt' | 'learnings', + search?: 'vector' | 'text' | 'hybrid', identity?: SharedRunIdentity, + maxTokens?: number, + tagBoost?: boolean, ): Promise<{ prompt: string; learnings: Learning[]; state?: WorkingStateResponse }>; injectTrace( scopes: string[], @@ -100,7 +105,9 @@ export function createDejaApp(handlers: RouteHandlers): Hono<{ Bindings: Env }> body.confidence, body.reason, body.source, + body.assets, identity, + body.noveltyThreshold, ); return c.json(result); }); @@ -142,7 +149,10 @@ export function createDejaApp(handlers: RouteHandlers): Hono<{ Bindings: Env }> body.context, body.limit, body.format, + body.search, resolveRunIdentityPayload(body), + body.maxTokens, + body.tagBoost, ); const stateRunId = diff --git a/src/do/types.ts b/src/do/types.ts index 0973cf6..6a2b1be 100644 --- a/src/do/types.ts +++ b/src/do/types.ts @@ -4,6 +4,14 @@ export interface Env { API_KEY?: string; } +export type InjectSearchMode = 'vector' | 'text' | 'hybrid'; + +export interface AssetPointer { + type: string; + ref: string; + label?: string; +} + export interface SharedRunIdentity { traceId?: string | null; workspaceId?: string | null; @@ -17,6 +25,9 @@ export interface Learning { id: string; trigger: string; learning: string; + tier?: 'trigger' | 'full'; + tags?: string[]; + assets?: AssetPointer[]; reason?: string; confidence: number; source?: string; @@ -146,7 +157,9 @@ export interface LoopRunsOperationsContext { confidence?: number, reason?: string, source?: string, + assets?: Array<{ type: string; ref: string; label?: string }>, identity?: SharedRunIdentity, + noveltyThreshold?: number, ): Promise; } @@ -156,6 +169,7 @@ export interface MemoryOperationsContext { createEmbedding(text: string): Promise; filterScopesByPriority(scopes: string[]): string[]; convertDbLearning(dbLearning: any): Learning; + sql?: DurableObjectState['storage']['sql']; } export interface SecretsOperationsContext { @@ -178,6 +192,8 @@ export interface WorkingStateOperationsContext { confidence?: number, reason?: string, source?: string, + assets?: Array<{ type: string; ref: string; label?: string }>, identity?: SharedRunIdentity, + noveltyThreshold?: number, ): Promise; } diff --git a/src/do/workingState.ts b/src/do/workingState.ts index b22c41e..3bed59e 100644 --- a/src/do/workingState.ts +++ b/src/do/workingState.ts @@ -200,6 +200,7 @@ export async function resolveWorkingState( typeof current.state.confidence === 'number' ? current.state.confidence : 0.8, 'Derived from working state resolve', `state:${runId}`, + undefined, opts.identity, ); } diff --git a/src/index.ts b/src/index.ts index da0f9a5..5a8a88a 100644 --- a/src/index.ts +++ b/src/index.ts @@ -31,6 +31,20 @@ const MCP_TOOLS = [ scope: { type: 'string', description: 'Memory scope: "shared", "agent:", or "session:"', default: 'shared' }, reason: { type: 'string', description: 'Why this was learned' }, source: { type: 'string', description: 'Source identifier' }, + assets: { + type: 'array', + description: 'Optional asset pointers returned as metadata only', + items: { + type: 'object', + properties: { + type: { type: 'string' }, + ref: { type: 'string' }, + label: { type: 'string' }, + }, + required: ['type', 'ref'], + }, + }, + noveltyThreshold: { type: 'number', description: 'Novelty merge threshold. Default 0.95, set 0 to disable.' }, proof_run_id: { type: 'string', description: 'Optional proof run identifier for the learning evidence' }, proof_iteration_id: { type: 'string', description: 'Optional proof iteration identifier for the learning evidence' }, }, @@ -74,6 +88,12 @@ const MCP_TOOLS = [ limit: { type: 'number', description: 'Max memories to return', default: 5 }, includeState: { type: 'boolean', description: 'Include live working state in prompt', default: false }, runId: { type: 'string', description: 'Run/session ID when includeState is true' }, + maxTokens: { type: 'number', description: 'Optional response token budget for tiered trigger/full memory expansion.' }, + search: { + type: 'string', + enum: ['vector', 'text', 'hybrid'], + description: 'Search mode. Hosted defaults to hybrid.', + }, }, required: ['context'], }, @@ -257,6 +277,8 @@ async function handleMcpToolCall(stub: DurableObjectStub, toolName: string, args scope: args.scope ?? 'shared', reason: args.reason, source: args.source, + assets: args.assets, + noveltyThreshold: args.noveltyThreshold, proof_run_id: args.proof_run_id, proof_iteration_id: args.proof_iteration_id, }), @@ -295,6 +317,7 @@ async function handleMcpToolCall(stub: DurableObjectStub, toolName: string, args limit: args.limit ?? 5, includeState: args.includeState ?? false, runId: args.runId, + search: args.search, }), })); return response.json(); diff --git a/src/schema.ts b/src/schema.ts index db49c12..1bc419c 100644 --- a/src/schema.ts +++ b/src/schema.ts @@ -5,6 +5,8 @@ export const learnings = sqliteTable('learnings', { trigger: text('trigger').notNull(), learning: text('learning').notNull(), reason: text('reason'), + tags: text('tags'), + assets: text('assets'), confidence: real('confidence').default(1.0), source: text('source'), scope: text('scope').notNull(), // Added for scope support @@ -22,6 +24,12 @@ export const learnings = sqliteTable('learnings', { proofIterationId: text('proof_iteration_id'), }); +export const learningsText = sqliteTable('learnings_fts', { + rowid: integer('rowid'), + trigger: text('trigger'), + learning: text('learning'), +}); + export const secrets = sqliteTable('secrets', { name: text('name').primaryKey(), value: text('value').notNull(), diff --git a/src/tagging.ts b/src/tagging.ts new file mode 100644 index 0000000..13a2cb5 --- /dev/null +++ b/src/tagging.ts @@ -0,0 +1,53 @@ +const ENTITY_SEQUENCE_RE = /\b(?:[A-Z][A-Za-z0-9-]*(?:\s+[A-Z][A-Za-z0-9-]*)+)\b/g +const SERVICE_PATTERN_RE = /\bthe\s+([A-Z][A-Za-z0-9-]*(?:\s+[A-Z][A-Za-z0-9-]*)*\s+(?:service|api|database|worker|pipeline|gateway))\b/gi +const SUFFIX_PATTERN_RE = /\b([A-Z][A-Za-z0-9-]*(?:\s+[A-Z][A-Za-z0-9-]*)*\s+(?:Service|API|Database|Worker|Pipeline|Gateway))\b/g + +function normalizeTag(tag: string): string { + return tag.replace(/\s+/g, ' ').trim() +} + +function addTag(tags: Map, rawTag: string) { + const tag = normalizeTag(rawTag) + if (tag) tags.set(tag.toLowerCase(), tag) +} + +export function extractEntityTags(...texts: Array): string[] { + const tags = new Map() + + for (const text of texts) { + if (!text) continue + + for (const match of text.matchAll(ENTITY_SEQUENCE_RE)) { + const tag = normalizeTag(match[0] ?? '') + addTag(tags, tag) + const words = tag.split(' ') + if (words.length > 2) { + for (let size = 2; size < words.length; size += 1) { + for (let start = 0; start + size <= words.length; start += 1) { + addTag(tags, words.slice(start, start + size).join(' ')) + } + } + } + } + + for (const match of text.matchAll(SERVICE_PATTERN_RE)) { + addTag(tags, match[1] ?? '') + } + + for (const match of text.matchAll(SUFFIX_PATTERN_RE)) { + addTag(tags, match[1] ?? '') + } + } + + return Array.from(tags.values()) +} + +export function countTagOverlap(left: string[] = [], right: string[] = []): number { + if (left.length === 0 || right.length === 0) return 0 + const rightSet = new Set(right.map(tag => tag.toLowerCase())) + let overlap = 0 + for (const tag of left) { + if (rightSet.has(tag.toLowerCase())) overlap += 1 + } + return overlap +} diff --git a/test/hosted-memory-quality.test.ts b/test/hosted-memory-quality.test.ts index 8084b11..f9c9548 100644 --- a/test/hosted-memory-quality.test.ts +++ b/test/hosted-memory-quality.test.ts @@ -20,6 +20,7 @@ function makeLearningRow(overrides: Record = {}) { scope: 'shared', supersedes: null, type: 'memory', + tags: null, embedding: JSON.stringify([0.11, 0.22, 0.33]), createdAt: '2026-03-01T00:00:00.000Z', lastRecalledAt: null, @@ -95,11 +96,15 @@ function makeMemoryContext(db: any, matches: Array<{ id: string; score: number } insert: jest.fn().mockResolvedValue(undefined), deleteByIds: jest.fn().mockResolvedValue(undefined), }; + const sql = { + exec: jest.fn().mockReturnValue([]), + }; return { ctx: { env: { VECTORIZE: vectorize }, initDB: jest.fn().mockResolvedValue(db), + sql, createEmbedding, filterScopesByPriority: (scopes: string[]) => scopes, convertDbLearning, @@ -107,6 +112,7 @@ function makeMemoryContext(db: any, matches: Array<{ id: string; score: number } spies: { createEmbedding, vectorize, + sql, }, }; } @@ -127,7 +133,7 @@ describe('hosted memory quality', () => { jest.clearAllMocks(); }); - test('learnMemory deduplicates a near-identical Vectorize neighbor and records proof ids', async () => { + test('learnMemory merges a near-identical Vectorize neighbor and records proof ids', async () => { const existingRow = makeLearningRow(); const { db, spies } = makeDb([existingRow]); const { ctx, spies: ctxSpies } = makeMemoryContext(db, [{ id: 'mem-1', score: 0.97 }]); @@ -140,14 +146,17 @@ describe('hosted memory quality', () => { 0.8, undefined, undefined, + undefined, { proofRunId: 'proof-run-1', proofIterationId: 'proof-run-1:1' }, ); expect(result.id).toBe('mem-1'); expect(db.insert).not.toHaveBeenCalled(); - expect(ctxSpies.vectorize.insert).not.toHaveBeenCalled(); + expect(ctxSpies.vectorize.insert).toHaveBeenCalledTimes(1); expect(spies.updateSet).toHaveBeenCalledWith( expect.objectContaining({ + confidence: 0.8, + createdAt: expect.any(String), proofRunId: 'proof-run-1', proofIterationId: 'proof-run-1:1', }), @@ -162,6 +171,66 @@ describe('hosted memory quality', () => { }); }); + test('learnMemory keeps the higher-confidence wording and appends new reason/source', async () => { + const existingRow = makeLearningRow({ + reason: 'Original incident', + source: 'runbook', + confidence: 0.6, + }); + const { db, spies } = makeDb([existingRow]); + const { ctx } = makeMemoryContext(db, [{ id: 'mem-1', score: 0.99 }]); + + const result = await learnMemory( + ctx as any, + 'shared', + 'deploying auth service', + 'run smoke tests before switching traffic', + 0.9, + 'Validated during hotfix', + 'pager', + ); + + expect(result.id).toBe('mem-1'); + expect(result.trigger).toBe('deploying auth service'); + expect(result.learning).toBe('run smoke tests before switching traffic'); + expect(result.reason).toBe('Original incident\nValidated during hotfix'); + expect(result.source).toBe('runbook\npager'); + expect(result.confidence).toBe(0.9); + expect(db.insert).not.toHaveBeenCalled(); + expect(spies.updateSet).toHaveBeenCalledWith( + expect.objectContaining({ + trigger: 'deploying auth service', + learning: 'run smoke tests before switching traffic', + reason: 'Original incident\nValidated during hotfix', + source: 'runbook\npager', + confidence: 0.9, + }), + ); + }); + + test('learnMemory inserts a new row when noveltyThreshold is disabled', async () => { + const existingRow = makeLearningRow(); + const { db } = makeDb([existingRow]); + const { ctx, spies: ctxSpies } = makeMemoryContext(db, [{ id: 'mem-1', score: 0.99 }]); + + const result = await learnMemory( + ctx as any, + 'shared', + 'deploying auth service', + 'run smoke tests before switching traffic', + 0.8, + undefined, + undefined, + undefined, + undefined, + 0, + ); + + expect(result.id).not.toBe('mem-1'); + expect(db.insert).toHaveBeenCalled(); + expect(ctxSpies.vectorize.insert).toHaveBeenCalledTimes(1); + }); + test('learnMemory inserts conflicting memories with supersedes and crushes the old confidence', async () => { const existingRow = makeLearningRow({ id: 'old-1', confidence: 0.5 }); const { db, spies } = makeDb([existingRow]); @@ -264,6 +333,212 @@ describe('hosted memory quality', () => { expect(result.learnings[0].identity?.proofRunId).toBe('proof-run-9'); expect(result.learnings[0].identity?.proofIterationId).toBe('proof-run-9:2'); }); + + test('injectMemories hybrid mode unions vector and text results and preserves vector order', async () => { + const vectorFirst = makeLearningRow({ id: 'vec-1', trigger: 'semantic auth deploy' }); + const vectorSecond = makeLearningRow({ id: 'vec-2', trigger: 'semantic billing deploy' }); + const textOnly = makeLearningRow({ id: 'txt-1', trigger: 'keyword rollback checklist' }); + const allRows = [vectorFirst, vectorSecond, textOnly]; + const { db, spies } = makeDb(allRows); + const { ctx, spies: ctxSpies } = makeMemoryContext(db, [ + { id: 'vec-1', score: 0.95 }, + { id: 'vec-2', score: 0.9 }, + ]); + + const sqlRows = [{ id: 'vec-2' }, { id: 'txt-1' }]; + ctxSpies.sql.exec.mockReturnValue(sqlRows); + + const result = await injectMemories( + ctx as any, + ['shared'], + 'deploy auth rollback', + 5, + 'learnings', + 'hybrid', + undefined, + ); + + expect(ctxSpies.vectorize.query).toHaveBeenCalledTimes(1); + expect(ctxSpies.sql.exec).toHaveBeenCalledTimes(1); + expect(result.learnings.map((learning) => learning.id)).toEqual(['vec-1', 'vec-2', 'txt-1']); + expect(spies.updateWhere).toHaveBeenCalledTimes(3); + }); + + test('injectMemories search modes return expected subsets', async () => { + const vectorOnly = makeLearningRow({ id: 'vec-1', trigger: 'semantic auth deploy' }); + const textOnly = makeLearningRow({ id: 'txt-1', trigger: 'keyword rollback checklist' }); + const { db } = makeDb([vectorOnly, textOnly], [vectorOnly], [textOnly]); + const { ctx, spies: ctxSpies } = makeMemoryContext(db, [{ id: 'vec-1', score: 0.95 }]); + + ctxSpies.sql.exec.mockReturnValue([{ id: 'txt-1' }]); + + const hybrid = await injectMemories(ctx as any, ['shared'], 'deploy auth rollback', 5, 'learnings', 'hybrid'); + const vector = await injectMemories(ctx as any, ['shared'], 'deploy auth rollback', 5, 'learnings', 'vector'); + const text = await injectMemories(ctx as any, ['shared'], 'deploy auth rollback', 5, 'learnings', 'text'); + + expect(hybrid.learnings.map((learning) => learning.id)).toEqual(['vec-1', 'txt-1']); + expect(vector.learnings.map((learning) => learning.id)).toEqual(['vec-1']); + expect(text.learnings.map((learning) => learning.id)).toEqual(['txt-1']); + expect(ctxSpies.vectorize.query).toHaveBeenCalledTimes(2); + }); + + test('injectMemories maxTokens keeps total estimated tokens within budget', async () => { + const rows = [ + makeLearningRow({ + id: 'mem-1', + trigger: 'deploy auth service', + learning: 'x'.repeat(160), + reason: 'r'.repeat(80), + source: 's'.repeat(40), + }), + makeLearningRow({ + id: 'mem-2', + trigger: 'rollback billing worker', + learning: 'y'.repeat(120), + reason: 'r2', + source: 's2', + }), + ]; + const { db } = makeDb(rows); + const { ctx } = makeMemoryContext(db, [ + { id: 'mem-1', score: 0.98 }, + { id: 'mem-2', score: 0.95 }, + ]); + + const result = await injectMemories( + ctx as any, + ['shared'], + 'deploy rollback', + 5, + 'learnings', + 'vector', + undefined, + 100, + ); + + const estimatedTokens = result.learnings.reduce((total, learning) => { + const text = + learning.tier === 'full' + ? `${learning.trigger}${learning.learning}${learning.confidence}${learning.reason ?? ''}${learning.source ?? ''}` + : learning.trigger; + return total + Math.ceil(text.length / 4); + }, 0); + + expect(estimatedTokens).toBeLessThanOrEqual(100); + expect(result.learnings[0].tier).toBe('full'); + expect(result.learnings[1].tier).toBe('trigger'); + }); + + test('learnMemory extracts tags from trigger and learning text', async () => { + const { db, spies } = makeDb(); + const { ctx } = makeMemoryContext(db, []); + + const result = await learnMemory( + ctx as any, + 'shared', + 'deploying Auth Service to staging', + 'always run migrations in a transaction for the Auth Service API', + ); + + expect(result.tags).toContain('Auth Service'); + expect(spies.insertValues).toHaveBeenCalledWith( + expect.objectContaining({ + tags: expect.stringContaining('Auth Service'), + }), + ); + }); + + test('injectMemories boosts learnings with 2+ overlapping tags', async () => { + const authRow = makeLearningRow({ + id: 'auth-1', + trigger: 'deploying Auth Service to staging', + learning: 'run migrations through the Auth Service API', + tags: JSON.stringify(['Auth Service', 'staging', 'Service API']), + }); + const genericRow = makeLearningRow({ + id: 'generic-1', + trigger: 'deploying worker', + learning: 'check logs before rollout', + tags: JSON.stringify(['worker', 'logs']), + }); + const { db } = makeDb([genericRow, authRow]); + const { ctx } = makeMemoryContext(db, [ + { id: 'generic-1', score: 0.99 }, + { id: 'auth-1', score: 0.95 }, + ]); + + const result = await injectMemories( + ctx as any, + ['shared'], + 'staging Auth Service API deploy', + 5, + 'learnings', + 'vector', + ); + + expect(result.learnings[0].id).toBe('auth-1'); + }); + + test('learnMemory stores asset pointers and injectMemories returns them without affecting rank', async () => { + const { db, spies } = makeDb(); + const { ctx } = makeMemoryContext(db, []); + + const learned = await learnMemory( + ctx as any, + 'shared', + 'deploy auth service', + 'attach runbook and trace', + 0.8, + undefined, + undefined, + [ + { type: 'trace', ref: 'lab-run-42' }, + { type: 'url', ref: 'https://example.com/runbook', label: 'Runbook' }, + ], + undefined, + 0.95, + ); + + expect(learned.assets).toEqual([ + { type: 'trace', ref: 'lab-run-42' }, + { type: 'url', ref: 'https://example.com/runbook', label: 'Runbook' }, + ]); + expect(spies.insertValues).toHaveBeenCalledWith( + expect.objectContaining({ + assets: expect.stringContaining('lab-run-42'), + }), + ); + + const genericRow = makeLearningRow({ + id: 'generic-1', + trigger: 'deploying worker', + learning: 'check logs before rollout', + assets: JSON.stringify([{ type: 'trace', ref: 'zzz' }]), + }); + const assetRow = makeLearningRow({ + id: 'asset-1', + trigger: 'deploy auth service', + learning: 'attach runbook and trace', + assets: JSON.stringify([{ type: 'trace', ref: 'lab-run-42' }]), + }); + const { db: injectDb } = makeDb([genericRow, assetRow]); + const { ctx: injectCtx } = makeMemoryContext(injectDb, [ + { id: 'generic-1', score: 0.99 }, + { id: 'asset-1', score: 0.95 }, + ]); + + const injected = await injectMemories( + injectCtx as any, + ['shared'], + 'deploy auth service', + 5, + 'learnings', + 'vector', + ); + + expect(injected.learnings[0].id).toBe('generic-1'); + expect(injected.learnings[1].assets).toEqual([{ type: 'trace', ref: 'lab-run-42' }]); + }); }); describe('hosted routes and worker entrypoints', () => {