308 lines
10 KiB
JavaScript
308 lines
10 KiB
JavaScript
/**
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* AgentDB Fast API
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*
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* Provides programmatic access to AgentDB without CLI overhead
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* Eliminates 2.3s overhead from process spawning and transformers.js init
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*/
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import { AgentDB } from 'agentdb';
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import { EventEmitter } from 'events';
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/**
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* Fast AgentDB client that avoids CLI overhead
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*
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* Performance:
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* - CLI: ~2,350ms per operation
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* - Direct API: ~10-50ms per operation
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* - Speedup: ~50-200x faster
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*/
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export class AgentDBFast extends EventEmitter {
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db = null;
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backend = null;
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config;
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initialized = false;
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embeddingCache = new Map();
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constructor(config = {}) {
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super();
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this.config = {
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path: config.path || '.agentdb-fast',
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vectorDimensions: config.vectorDimensions || 384,
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enableHNSW: config.enableHNSW !== false,
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hnswM: config.hnswM || 16,
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hnswEfConstruction: config.hnswEfConstruction || 200
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};
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}
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/**
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* Initialize database connection (lazy)
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*/
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async initialize() {
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if (this.initialized)
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return;
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try {
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// Create AgentDB instance
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this.db = new AgentDB({
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path: this.config.path,
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dimensions: this.config.vectorDimensions
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});
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await this.db.initialize();
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// Access the vector backend as a direct property
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if (this.db.vectorBackend) {
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this.backend = this.db.vectorBackend;
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}
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else {
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throw new Error('Vector backend not available');
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}
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this.initialized = true;
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this.emit('initialized');
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}
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catch (error) {
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throw new Error(`Failed to initialize AgentDB: ${error.message}`);
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}
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}
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/**
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* Store an episode (fast, no CLI overhead)
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*/
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async storeEpisode(episode) {
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await this.initialize();
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// Generate embedding if not provided
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if (!episode.embedding) {
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episode.embedding = await this.getEmbedding(episode.task);
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}
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const episodeId = episode.id || this.generateId('episode');
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// Use backend insert method
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if (!this.backend) {
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throw new Error('Backend not initialized');
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}
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await this.backend.insert(episodeId, new Float32Array(episode.embedding), {
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type: 'episode',
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sessionId: episode.sessionId,
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task: episode.task,
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trajectory: JSON.stringify(episode.trajectory),
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reward: episode.reward,
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quality: episode.quality,
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context: episode.context,
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timestamp: episode.timestamp || Date.now()
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});
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this.emit('episode:stored', episodeId);
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return episodeId;
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}
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/**
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* Retrieve episodes by task similarity (fast)
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*/
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async retrieveEpisodes(options) {
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await this.initialize();
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const dimensions = this.config.vectorDimensions ?? 384;
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const queryEmbedding = options.task
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? await this.getEmbedding(options.task)
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: Array(dimensions).fill(0);
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const k = options.k || 5;
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// Build filter
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const filter = { type: 'episode' };
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if (options.sessionId)
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filter.sessionId = options.sessionId;
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if (options.minReward !== undefined)
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filter.reward = { $gte: options.minReward };
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if (options.maxReward !== undefined) {
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filter.reward = { ...(filter.reward || {}), $lte: options.maxReward };
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}
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if (!this.backend) {
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throw new Error('Backend not initialized');
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}
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const results = await this.backend.search(new Float32Array(queryEmbedding), k, { filter: Object.keys(filter).length > 1 ? filter : undefined });
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return results.map((result) => ({
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id: result.id,
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sessionId: result.metadata.sessionId,
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task: result.metadata.task,
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trajectory: JSON.parse(result.metadata.trajectory || '[]'),
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reward: result.metadata.reward,
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quality: result.metadata.quality,
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embedding: result.vector,
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context: result.metadata.context,
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timestamp: result.metadata.timestamp
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}));
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}
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/**
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* Store a pattern (for ReasoningBank)
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*/
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async storePattern(pattern) {
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await this.initialize();
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if (!pattern.embedding) {
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pattern.embedding = await this.getEmbedding(`${pattern.input} ${pattern.output}`);
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}
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const patternId = pattern.id || this.generateId('pattern');
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if (!this.backend) {
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throw new Error('Backend not initialized');
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}
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await this.backend.insert(patternId, new Float32Array(pattern.embedding), {
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type: 'pattern',
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task: pattern.task,
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input: pattern.input,
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output: pattern.output,
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quality: pattern.quality,
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context: pattern.context,
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timestamp: pattern.timestamp || Date.now()
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});
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this.emit('pattern:stored', patternId);
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return patternId;
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}
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/**
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* Search for similar patterns
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*/
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async searchPatterns(query, k = 5, minQuality) {
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await this.initialize();
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const queryEmbedding = await this.getEmbedding(query);
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const filter = { type: 'pattern' };
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if (minQuality !== undefined) {
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filter.quality = { $gte: minQuality };
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}
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if (!this.backend) {
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throw new Error('Backend not initialized');
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}
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const results = await this.backend.search(new Float32Array(queryEmbedding), k, { filter: Object.keys(filter).length > 1 ? filter : undefined });
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return results.map((result) => ({
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id: result.id,
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task: result.metadata.task,
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input: result.metadata.input,
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output: result.metadata.output,
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quality: result.metadata.quality,
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embedding: result.vector,
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context: result.metadata.context,
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timestamp: result.metadata.timestamp
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}));
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}
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/**
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* Get database statistics
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*/
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async getStats() {
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await this.initialize();
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if (!this.backend) {
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throw new Error('Backend not initialized');
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}
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const stats = await this.backend.stats();
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// Count by type - get all results
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const allResults = await this.backend.search(new Float32Array(this.config.vectorDimensions).fill(0), 10000, // Get all
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{});
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const episodes = allResults.filter((r) => r.metadata?.type === 'episode');
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const patterns = allResults.filter((r) => r.metadata?.type === 'pattern');
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const avgQuality = patterns.reduce((sum, p) => sum + (p.metadata?.quality || 0), 0) /
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(patterns.length || 1);
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return {
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totalVectors: stats.totalVectors || allResults.length || 0,
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totalEpisodes: episodes.length,
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totalPatterns: patterns.length,
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avgQuality
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};
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}
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/**
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* Close database connection
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*/
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async close() {
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this.removeAllListeners();
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this.embeddingCache.clear();
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if (this.db) {
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await this.db.close();
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this.db = null;
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this.backend = null;
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}
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this.initialized = false;
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}
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/**
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* Generate embedding for text (with caching)
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*
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* Note: This is a simple mock. In production, replace with:
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* - OpenAI embeddings API
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* - Local transformer model
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* - SentenceTransformers
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*/
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async getEmbedding(text) {
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// Check cache
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if (this.embeddingCache.has(text)) {
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return this.embeddingCache.get(text);
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}
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// Simple hash-based embedding (REPLACE IN PRODUCTION)
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const embedding = this.simpleHashEmbedding(text);
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// Cache it
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this.embeddingCache.set(text, embedding);
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if (this.embeddingCache.size > 1000) {
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// LRU-style cleanup
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const firstKey = this.embeddingCache.keys().next().value;
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if (firstKey) {
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this.embeddingCache.delete(firstKey);
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}
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}
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return embedding;
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}
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/**
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* Simple hash-based embedding (MOCK - REPLACE IN PRODUCTION)
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*
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* Production alternatives:
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* 1. OpenAI: https://platform.openai.com/docs/guides/embeddings
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* 2. Transformers.js: https://huggingface.co/docs/transformers.js
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* 3. SBERT: https://www.sbert.net/
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*/
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simpleHashEmbedding(text) {
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const embedding = new Array(this.config.vectorDimensions);
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// Seed with text hash
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let hash = 0;
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for (let i = 0; i < text.length; i++) {
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hash = (hash << 5) - hash + text.charCodeAt(i);
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hash = hash & hash;
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}
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// Generate pseudo-random embedding
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for (let i = 0; i < this.config.vectorDimensions; i++) {
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const seed = hash + i * 2654435761;
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const x = Math.sin(seed) * 10000;
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embedding[i] = x - Math.floor(x);
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}
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// Normalize
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const norm = Math.sqrt(embedding.reduce((sum, v) => sum + v * v, 0));
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return embedding.map(v => v / norm);
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}
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/**
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* Generate unique ID
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*/
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generateId(prefix) {
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return `${prefix}_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;
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}
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}
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/**
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* Convenience function to create a fast AgentDB client
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*/
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export function createFastAgentDB(config) {
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return new AgentDBFast(config);
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}
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/**
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* Performance comparison helper
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*/
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export async function benchmarkAgentDB() {
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const client = createFastAgentDB({ path: '.agentdb-benchmark' });
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// API benchmark
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const apiStoreStart = Date.now();
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const episodeId = await client.storeEpisode({
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sessionId: 'test-session',
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task: 'test-task',
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trajectory: ['step1', 'step2'],
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reward: 0.8
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});
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const apiStoreTime = Date.now() - apiStoreStart;
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const apiRetrieveStart = Date.now();
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await client.retrieveEpisodes({ task: 'test-task', k: 5 });
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const apiRetrieveTime = Date.now() - apiRetrieveStart;
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await client.close();
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// CLI times from benchmarks
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const cliStoreTime = 2350;
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const cliRetrieveTime = 2400;
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return {
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cli: {
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store: cliStoreTime,
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retrieve: cliRetrieveTime
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},
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api: {
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store: apiStoreTime,
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retrieve: apiRetrieveTime
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},
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speedup: {
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store: cliStoreTime / apiStoreTime,
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retrieve: cliRetrieveTime / apiRetrieveTime
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}
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};
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}
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//# sourceMappingURL=agentdb-fast.js.map
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