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`limit`: 返回结果数量（可选，默认 10，最大 50） +- `corpus`: 搜索范围（可选，默认 'memory'） + +**示例：** +``` +搜索关于 OpenClaw 的记忆 +``` + +AI 会执行： +```json +{ + "action": "memory_search", + "params": { + "query": "OpenClaw", + "limit": 5 + } +} +``` + +返回结果包含相似度分数（0-1），按相关度排序。 + +### 13. memory_get - 精确读取记忆文件 + +按路径精确读取记忆文件的内容片段，支持行号范围。 + +**参数：** +- `path`: 文件路径（必需） +- `fromLine`: 起始行号（可选，1-based） +- `lines`: 读取行数（可选，默认全部，最大 500） + +**示例：** +``` +读取 MEMORY.md 第 1-20 行 +``` + +AI 会执行： +```json +{ + "action": "memory_get", + "params": { + "path": "MEMORY.md", + "fromLine": 1, + "lines": 20 + } +} +``` + ## 使用原则 1. **选择性记忆**：只记住重要和持久的信息 diff --git a/ts/graph_memory.db-shm b/ts/graph_memory.db-shm new file mode 100644 index 0000000..25bc820 Binary files /dev/null and b/ts/graph_memory.db-shm differ diff --git a/ts/graph_memory.db-wal b/ts/graph_memory.db-wal new file mode 100644 index 0000000..0510ffa Binary files /dev/null and b/ts/graph_memory.db-wal differ diff --git a/ts/package-lock.json b/ts/package-lock.json 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"@img/sharp-libvips-linuxmusl-x64": "1.2.4", + "@img/sharp-linux-arm": "0.34.5", + "@img/sharp-linux-arm64": "0.34.5", + "@img/sharp-linux-ppc64": "0.34.5", + "@img/sharp-linux-riscv64": "0.34.5", + "@img/sharp-linux-s390x": "0.34.5", + "@img/sharp-linux-x64": "0.34.5", + "@img/sharp-linuxmusl-arm64": "0.34.5", + "@img/sharp-linuxmusl-x64": "0.34.5", + "@img/sharp-wasm32": "0.34.5", + "@img/sharp-win32-arm64": "0.34.5", + "@img/sharp-win32-ia32": "0.34.5", + "@img/sharp-win32-x64": "0.34.5" + } + }, "node_modules/siginfo": { "version": "2.0.0", "resolved": "https://registry.npmjs.org/siginfo/-/siginfo-2.0.0.tgz", @@ -1487,6 +2416,15 @@ "simple-concat": "^1.0.0" } }, + "node_modules/simple-swizzle": { + "version": "0.2.4", + "resolved": "https://registry.npmjs.org/simple-swizzle/-/simple-swizzle-0.2.4.tgz", + "integrity": "sha512-nAu1WFPQSMNr2Zn9PGSZK9AGn4t/y97lEm+MXTtUDwfP0ksAIX4nO+6ruD9Jwut4C49SB1Ws+fbXsm/yScWOHw==", + "license": "MIT", + "dependencies": { + "is-arrayish": "^0.3.1" + } + }, "node_modules/source-map-js": { "version": "1.2.1", "resolved": "https://registry.npmjs.org/source-map-js/-/source-map-js-1.2.1.tgz", @@ -1508,6 +2446,17 @@ "integrity": "sha512-5GS12FdOZNliM5mAOxFRg7Ir0pWz8MdpYm6AY6VPkGpbA7ZzmbzNcBJQ0GPvvyWgcY7QAhCgf9Uy89I03faLkg==", "dev": true }, + "node_modules/streamx": { + "version": "2.25.0", + "resolved": "https://registry.npmjs.org/streamx/-/streamx-2.25.0.tgz", + "integrity": "sha512-0nQuG6jf1w+wddNEEXCF4nTg3LtufWINB5eFEN+5TNZW7KWJp6x87+JFL43vaAUPyCfH1wID+mNVyW6OHtFamg==", + "license": "MIT", + "dependencies": { + "events-universal": "^1.0.0", + "fast-fifo": "^1.3.2", + "text-decoder": "^1.1.0" + } + }, "node_modules/string_decoder": { "version": "1.3.0", "resolved": "https://registry.npmjs.org/string_decoder/-/string_decoder-1.3.0.tgz", @@ -1550,6 +2499,24 @@ "node": ">=6" } }, + "node_modules/teex": { + "version": "1.0.1", + "resolved": "https://registry.npmjs.org/teex/-/teex-1.0.1.tgz", + "integrity": "sha512-eYE6iEI62Ni1H8oIa7KlDU6uQBtqr4Eajni3wX7rpfXD8ysFx8z0+dri+KWEPWpBsxXfxu58x/0jvTVT1ekOSg==", + "license": "MIT", + "dependencies": { + "streamx": "^2.12.5" + } + }, + "node_modules/text-decoder": { + "version": "1.2.7", + "resolved": "https://registry.npmjs.org/text-decoder/-/text-decoder-1.2.7.tgz", + "integrity": "sha512-vlLytXkeP4xvEq2otHeJfSQIRyWxo/oZGEbXrtEEF9Hnmrdly59sUbzZ/QgyWuLYHctCHxFF4tRQZNQ9k60ExQ==", + "license": "Apache-2.0", + "dependencies": { + "b4a": "^1.6.4" + } + }, "node_modules/tinybench": { "version": "2.9.0", "resolved": "https://registry.npmjs.org/tinybench/-/tinybench-2.9.0.tgz", @@ -1589,6 +2556,13 @@ "node": ">=14.0.0" } }, + "node_modules/tslib": { + "version": "2.8.1", + "resolved": "https://registry.npmjs.org/tslib/-/tslib-2.8.1.tgz", + "integrity": "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w==", + "license": "0BSD", + "optional": true + }, "node_modules/tunnel-agent": { "version": "0.6.0", "resolved": "https://registry.npmjs.org/tunnel-agent/-/tunnel-agent-0.6.0.tgz", @@ -1616,8 +2590,7 @@ "node_modules/undici-types": { "version": "7.19.2", "resolved": "https://registry.npmjs.org/undici-types/-/undici-types-7.19.2.tgz", - "integrity": "sha512-qYVnV5OEm2AW8cJMCpdV20CDyaN3g0AjDlOGf1OW4iaDEx8MwdtChUp4zu4H0VP3nDRF/8RKWH+IPp9uW0YGZg==", - "dev": true + "integrity": "sha512-qYVnV5OEm2AW8cJMCpdV20CDyaN3g0AjDlOGf1OW4iaDEx8MwdtChUp4zu4H0VP3nDRF/8RKWH+IPp9uW0YGZg==" }, "node_modules/util-deprecate": { "version": "1.0.2", diff --git a/ts/package.json b/ts/package.json index ccbf526..04395b6 100644 --- a/ts/package.json +++ b/ts/package.json @@ -3,7 +3,9 @@ "version": "1.0.0", "type": "module", "openclaw": { - "extensions": ["./dist/plugin-entry.js"], + "extensions": [ + "./dist/plugin-entry.js" + ], "compat": { "pluginApi": ">=2026.3.24-beta.2", "minGatewayVersion": "2026.3.24-beta.2" @@ -19,7 +21,9 @@ }, "dependencies": { "@sinclair/typebox": "^0.34.49", + "@xenova/transformers": "^2.17.2", "better-sqlite3": "^12.9.0", + "sharp": "^0.34.5", "yaml": "^2.8.3" }, "devDependencies": { diff --git a/ts/src/runtime/core/graph_memory/graph_database.ts b/ts/src/runtime/core/graph_memory/graph_database.ts index fc81c29..0e1b212 100644 --- a/ts/src/runtime/core/graph_memory/graph_database.ts +++ b/ts/src/runtime/core/graph_memory/graph_database.ts @@ -1,4 +1,7 @@ import Database from 'better-sqlite3'; +import { + SemanticSearchEngine +} from './semantic_search.js'; import type { Entity, Relation, RecallParams, CommitParams, PurgeParams, RecallResult, CommitResult, PurgeResult, MemoryStats @@ -7,14 +10,20 @@ import type { export class GraphDatabase { private db: Database.Database; private sessionId: string; + private semanticSearch: SemanticSearchEngine; constructor(dbPath?: string, sessionId?: string) { this.db = new Database(dbPath || 'graph_memory.db'); this.sessionId = sessionId || `session-${Date.now()}`; this.db.pragma('journal_mode = WAL'); + this.semanticSearch = new SemanticSearchEngine(this.db); this.initialize(); } + getSemanticSearch(): SemanticSearchEngine { + return this.semanticSearch; + } + private initialize(): void { this.db.exec(` CREATE TABLE IF NOT EXISTS entities ( diff --git a/ts/src/runtime/core/graph_memory/index.ts b/ts/src/runtime/core/graph_memory/index.ts index 7fd6fd8..85f17ff 100644 --- a/ts/src/runtime/core/graph_memory/index.ts +++ b/ts/src/runtime/core/graph_memory/index.ts @@ -1,3 +1,4 @@ export * from './types.js'; +export * from './semantic_search.js'; export * from './graph_database.js'; export { MemoryService } from './memory_service.js'; diff --git a/ts/src/runtime/core/graph_memory/memory_service.ts b/ts/src/runtime/core/graph_memory/memory_service.ts index bfba4e0..2b45332 100644 --- a/ts/src/runtime/core/graph_memory/memory_service.ts +++ b/ts/src/runtime/core/graph_memory/memory_service.ts @@ -365,6 +365,35 @@ export class MemoryService { }; } + async storeSemanticMemory(text: string, source?: string, sourceLine?: number): Promise { + const id = this.generateId(); + const semanticSearch = this.db.getSemanticSearch(); + const embedding = await semanticSearch.generateEmbedding(text); + semanticSearch.storeEmbedding(id, text, embedding, source, sourceLine); + return id; + } + + async semanticSearch(query: string, limit: number = 10): Promise> { + const semanticSearch = this.db.getSemanticSearch(); + const queryEmbedding = await semanticSearch.generateEmbedding(query); + const results = semanticSearch.searchSimilar(queryEmbedding, limit); + return results.map(r => ({ + id: r.id, + text: r.text, + source: r.source || undefined, + similarity: Math.round(r.similarity * 1000) / 1000 + })); + } + + async readMemoryFragment(path: string, fromLine?: number, lines?: number): Promise { + const content = fs.readFileSync(path, 'utf-8'); + if (fromLine !== undefined && lines !== undefined) { + const allLines = content.split('\n'); + return allLines.slice(fromLine - 1, fromLine - 1 + lines).join('\n'); + } + return content; + } + // ========== Utility ========== setSessionId(sessionId: string): void { @@ -374,4 +403,8 @@ export class MemoryService { getSessionId(): string { return this.db.getSessionId(); } + + private generateId(): string { + return `${Date.now()}-${Math.random().toString(36).slice(2, 11)}`; + } } diff --git a/ts/src/runtime/core/graph_memory/semantic_search.ts b/ts/src/runtime/core/graph_memory/semantic_search.ts new file mode 100644 index 0000000..deaef02 --- /dev/null +++ b/ts/src/runtime/core/graph_memory/semantic_search.ts @@ -0,0 +1,86 @@ +import Database from 'better-sqlite3'; + +export interface SemanticMemory { + id: string; + text: string; + embedding: Float32Array; + source: string; + sourceLine?: number; + createdAt: Date; +} + +export interface SearchResult { + id: string; + text: string; + source: string; + sourceLine?: number; + similarity: number; +} + +export class SemanticSearchEngine { + private db: Database.Database; + private embeddingModel: any; + private modelReady: boolean = false; + + constructor(db: Database.Database) { + this.db = db; + this.initialize(); + } + + private initialize(): void { + this.db.exec(` + CREATE TABLE IF NOT EXISTS embeddings ( + id TEXT PRIMARY KEY, + text TEXT NOT NULL, + embedding BLOB NOT NULL, + source TEXT, + source_line INTEGER, + created_at TEXT DEFAULT (datetime('now')) + ); + CREATE INDEX IF NOT EXISTS idx_embeddings_source ON embeddings(source); + `); + } + + async loadModel(): Promise { + if (this.modelReady) return; + const { pipeline } = await import('@xenova/transformers') as any; + this.embeddingModel = await pipeline('feature-extraction', 'Xenova/all-MiniLM-L6-v2'); + this.modelReady = true; + } + + async generateEmbedding(text: string): Promise { + await this.loadModel(); + const output = await this.embeddingModel(text, { pooling: 'mean', normalize: true }); + return new Float32Array(output.data); + } + + storeEmbedding(id: string, text: string, embedding: Float32Array, source?: string, sourceLine?: number): void { + const stmt = this.db.prepare(` + INSERT OR REPLACE INTO embeddings (id, text, embedding, source, source_line) + VALUES (?, ?, ?, ?, ?) + `); + stmt.run(id, text, Buffer.from(embedding.buffer), source || null, sourceLine || null); + } + + searchSimilar(queryEmbedding: Float32Array, limit: number = 10): SearchResult[] { + const rows = this.db.prepare('SELECT id, text, embedding, source, source_line FROM embeddings').all(); + const results = rows.map((row: any) => ({ + id: row.id, + text: row.text, + source: row.source, + sourceLine: row.source_line, + similarity: cosineSimilarity(queryEmbedding, new Float32Array(row.embedding.buffer)) + })); + return results.sort((a: SearchResult, b: SearchResult) => b.similarity - a.similarity).slice(0, limit); + } +} + +export function cosineSimilarity(a: Float32Array, b: Float32Array): number { + let dot = 0, normA = 0, normB = 0; + for (let i = 0; i < a.length; i++) { + dot += a[i] * b[i]; + normA += a[i] * a[i]; + normB += b[i] * b[i]; + } + return dot / (Math.sqrt(normA) * Math.sqrt(normB)); +} diff --git a/ts/src/runtime/core/tools/builtin/graph_memory_tool.ts b/ts/src/runtime/core/tools/builtin/graph_memory_tool.ts index ea3c36e..a1d1863 100644 --- a/ts/src/runtime/core/tools/builtin/graph_memory_tool.ts +++ b/ts/src/runtime/core/tools/builtin/graph_memory_tool.ts @@ -12,7 +12,8 @@ export const GraphMemoryToolSchema = Type.Object({ 'persona_update', 'persona_clear', 'task_create', 'task_set_state', 'task_delete', 'task_link_info', 'context_rewrite', 'working_memory_chain', - 'task_node_create', 'task_node_get_recent', 'task_node_get_chain' + 'task_node_create', 'task_node_get_recent', 'task_node_get_chain', + 'memory_search', 'memory_get' ] }), params: Type.Object({ @@ -70,7 +71,15 @@ export const GraphMemoryToolSchema = Type.Object({ key_facts: Type.Optional(Type.Array(Type.String({ description: '关键事实' }), { description: '关键事实数组' })), raw_context: Type.Optional(Type.String({ description: '原始上下文（存档用）' })), limit: Type.Optional(Type.Number({ description: '限制数量' })), - from_node_id: Type.Optional(Type.Number({ description: '起始节点ID' })) + from_node_id: Type.Optional(Type.Number({ description: '起始节点ID' })), + query: Type.Optional(Type.String({ description: '语义搜索查询' })), + corpus: Type.Optional(Type.String({ + enum: ['memory', 'wiki', 'all'], + description: '搜索语料范围' + })), + path: Type.Optional(Type.String({ description: '记忆文件路径' })), + fromLine: Type.Optional(Type.Number({ description: '起始行号' })), + lines: Type.Optional(Type.Number({ description: '读取行数' })) }, { description: '操作参数' }) }); @@ -93,9 +102,8 @@ const GRAPH_MEMORY_TOOL_DESCRIPTION = `图记忆工具 - 让 AI 拥有真正的 - task_link_info: 关联信息（必需参数: task_id, info_node） - context_rewrite: 压缩上下文为关键记忆（必需参数: context; 可选: maxEntities, summary） - working_memory_chain: 获取工作记忆链（可选参数: maxDepth, recentOnly） -- task_node_create: 创建任务节点并链接到链（必需参数: session_id, turn_id, summary, key_facts; 可选: raw_context） -- task_node_get_recent: 获取最近N个任务节点（必需参数: session_id; 可选: limit） -- task_node_get_chain: 获取完整任务链（必需参数: session_id; 可选: from_node_id）`; +- memory_search: 语义向量搜索（必需参数: query; 可选: limit, corpus） +- memory_get: 精确读取记忆文件片段（必需参数: path; 可选: fromLine, lines）`; // ==================== 参数验证 ==================== @@ -321,6 +329,35 @@ function validatePersonaClearParams(params: Record): Validation return errors; } +function validateMemorySearchParams(params: Record): ValidationError[] { + const errors: ValidationError[] = []; + + if (!params.query || typeof params.query !== 'string' || params.query.trim() === '') { + errors.push({ field: 'query', message: 'memory_search 操作必需提供 query 字符串' }); + } + if (params.limit !== undefined && (typeof params.limit !== 'number' || params.limit < 1 || params.limit > 50)) { + errors.push({ field: 'limit', message: 'limit 必须在 1-50 之间' }); + } + + return errors; +} + +function validateMemoryGetParams(params: Record): ValidationError[] { + const errors: ValidationError[] = []; + + if (!params.path || typeof params.path !== 'string' || params.path.trim() === '') { + errors.push({ field: 'path', message: 'memory_get 操作必需提供 path 字符串' }); + } + if (params.fromLine !== undefined && (typeof params.fromLine !== 'number' || params.fromLine < 1)) { + errors.push({ field: 'fromLine', message: 'fromLine 必须是正整数' }); + } + if (params.lines !== undefined && (typeof params.lines !== 'number' || params.lines < 1 || params.lines > 500)) { + errors.push({ field: 'lines', message: 'lines 必须在 1-500 之间' }); + } + + return errors; +} + function validateParams(action: string, params: Record): ValidationError[] { switch (action) { case 'recall': return validateRecallParams(params); @@ -337,6 +374,8 @@ function validateParams(action: string, params: Record): Valida case 'task_node_create': return validateTaskNodeCreateParams(params); case 'task_node_get_recent': return validateTaskNodeGetRecentParams(params); case 'task_node_get_chain': return validateTaskNodeGetChainParams(params); + case 'memory_search': return validateMemorySearchParams(params); + case 'memory_get': return validateMemoryGetParams(params); default: return []; } } @@ -518,6 +557,23 @@ export function createGraphMemoryTool(dbPath?: string, sessionId?: string) { params.from_node_id as number | undefined ); + case 'memory_search': { + const results = await service.semanticSearch( + params.query as string, + params.limit as number | undefined + ); + return { results, count: results.length }; + } + + case 'memory_get': { + const content = await service.readMemoryFragment( + params.path as string, + params.fromLine as number | undefined, + params.lines as number | undefined + ); + return { content, path: params.path }; + } + case 'archive': return service.archive(params.days as number | undefined); diff --git a/ts/tests/semantic_search.test.ts b/ts/tests/semantic_search.test.ts new file mode 100644 index 0000000..51be2ee --- /dev/null +++ b/ts/tests/semantic_search.test.ts @@ -0,0 +1,188 @@ +import { describe, it, expect, beforeEach, afterEach, vi } from 'vitest'; +import Database from 'better-sqlite3'; + +vi.mock('@xenova/transformers', () => ({ + pipeline: vi.fn().mockImplementation(() => { + const mockModel = (text: string, opts: any) => { + const arr = new Float32Array(384); + const seed = text.split('').reduce((a, c) => a + c.charCodeAt(0), 0); + for (let i = 0; i < 384; i++) { + arr[i] = Math.sin((seed + i) * 0.1); + } + return { data: arr }; + }; + mockModel.to = function() { + return this; + }; + return mockModel; + }), +})); + +import { SemanticSearchEngine, cosineSimilarity } from '/home/program/TrulyMEM-TrueHumanMEM/ts/dist/runtime/core/graph_memory/semantic_search.js'; + +const TEST_DB_PATH = '/tmp/test_semantic_search.db'; + +describe('SemanticSearchEngine', () => { + let db: Database.Database; + let engine: SemanticSearchEngine; + + beforeEach(async () => { + try { + const fs = await import('fs'); + if (fs.existsSync(TEST_DB_PATH)) { + fs.unlinkSync(TEST_DB_PATH); + } + if (fs.existsSync(`${TEST_DB_PATH}-wal`)) { + fs.unlinkSync(`${TEST_DB_PATH}-wal`); + } + if (fs.existsSync(`${TEST_DB_PATH}-shm`)) { + fs.unlinkSync(`${TEST_DB_PATH}-shm`); + } + } catch {} + db = new Database(TEST_DB_PATH); + engine = new SemanticSearchEngine(db); + }); + + afterEach(() => { + if (db) { + db.close(); + } + }); + + describe('initialization', () => { + it('creates embeddings table on initialization', () => { + const tableInfo = db.prepare("SELECT name FROM sqlite_master WHERE type='table' AND name='embeddings'").get(); + expect(tableInfo).toBeDefined(); + }); + + it('creates index on source column', () => { + const indexInfo = db.prepare("SELECT name FROM sqlite_master WHERE type='index' AND name='idx_embeddings_source'").get(); + expect(indexInfo).toBeDefined(); + }); + }); + + describe('generateEmbedding', () => { + it('generates 384 dimensional embedding', async () => { + const embedding = await engine.generateEmbedding('hello world'); + expect(embedding.length).toBe(384); + }); + + it('generates consistent embeddings for same text', async () => { + const emb1 = await engine.generateEmbedding('test'); + const emb2 = await engine.generateEmbedding('test'); + expect(emb1.length).toBe(emb2.length); + const similarity = cosineSimilarity(emb1, emb2); + expect(similarity).toBeCloseTo(1, 3); + }); + + it('generates different embeddings for different text', async () => { + const emb1 = await engine.generateEmbedding('hello'); + const emb2 = await engine.generateEmbedding('world'); + const similarity = cosineSimilarity(emb1, emb2); + expect(similarity).not.toBe(1); + }); + }); + + describe('storeEmbedding', () => { + it('stores embedding to SQLite', async () => { + const embedding = await engine.generateEmbedding('test'); + engine.storeEmbedding('test-id', 'test text', embedding, 'test-source', 1); + + const row = db.prepare('SELECT * FROM embeddings WHERE id = ?').get('test-id') as any; + expect(row).toBeDefined(); + expect(row.text).toBe('test text'); + expect(row.source).toBe('test-source'); + expect(row.source_line).toBe(1); + }); + + it('replaces existing embedding with same id', async () => { + const emb1 = await engine.generateEmbedding('text1'); + engine.storeEmbedding('dup-id', 'text 1', emb1); + + const emb2 = await engine.generateEmbedding('text2'); + engine.storeEmbedding('dup-id', 'text 2', emb2); + + const row = db.prepare('SELECT text FROM embeddings WHERE id = ?').get('dup-id') as any; + expect(row.text).toBe('text 2'); + }); + }); + + describe('searchSimilar', () => { + beforeEach(async () => { + const emb1 = await engine.generateEmbedding('machine learning'); + const emb2 = await engine.generateEmbedding('deep learning'); + const emb3 = await engine.generateEmbedding('hello world'); + + engine.storeEmbedding('item-1', 'machine learning', emb1, 'source1', 1); + engine.storeEmbedding('item-2', 'deep learning neural network', emb2, 'source2', 2); + engine.storeEmbedding('item-3', 'hello world', emb3, 'source3', 3); + }); + + it('finds similar embeddings using cosine similarity', async () => { + const query = await engine.generateEmbedding('neural networks'); + const results = engine.searchSimilar(query, 10); + + expect(results.length).toBeGreaterThan(0); + expect(results[0].id).toBeDefined(); + expect(typeof results[0].similarity).toBe('number'); + }); + + it('returns results sorted by similarity descending', async () => { + const query = await engine.generateEmbedding('training'); + const results = engine.searchSimilar(query, 10); + + for (let i = 1; i < results.length; i++) { + expect(results[i - 1].similarity).toBeGreaterThanOrEqual(results[i].similarity); + } + }); + + it('respects limit parameter', async () => { + const query = await engine.generateEmbedding('test query'); + const results = engine.searchSimilar(query, 2); + + expect(results.length).toBeLessThanOrEqual(2); + }); + + it('includes source and sourceLine in results', async () => { + const query = await engine.generateEmbedding('test'); + const results = engine.searchSimilar(query, 1); + + expect(results[0].source).toBeDefined(); + }); + }); + + describe('cosineSimilarity', () => { + it('returns 1 for identical vectors', () => { + const a = new Float32Array([1, 0, 0]); + const b = new Float32Array([1, 0, 0]); + expect(cosineSimilarity(a, b)).toBeCloseTo(1); + }); + + it('returns -1 for opposite vectors', () => { + const a = new Float32Array([1, 0, 0]); + const b = new Float32Array([-1, 0, 0]); + expect(cosineSimilarity(a, b)).toBeCloseTo(-1); + }); + + it('returns 0 for orthogonal vectors', () => { + const a = new Float32Array([1, 0, 0]); + const b = new Float32Array([0, 1, 0]); + expect(cosineSimilarity(a, b)).toBeCloseTo(0); + }); + + it('returns value between -1 and 1 for random vectors', () => { + const a = new Float32Array([0.5, 0.3, 0.7]); + const b = new Float32Array([0.2, 0.8, 0.1]); + const similarity = cosineSimilarity(a, b); + expect(similarity).toBeGreaterThanOrEqual(-1); + expect(similarity).toBeLessThanOrEqual(1); + }); + + it('handles 384 dimensional vectors', () => { + const a = new Float32Array(384).fill(0.1); + const b = new Float32Array(384).fill(0.1); + const similarity = cosineSimilarity(a, b); + expect(similarity).toBeCloseTo(1); + }); + }); +}); \ No newline at end of file