import { OpenAI } from 'openai';
import { EmbeddingProvider } from './types.js';
import { Logger } from '../utils/Logger.js';
/**
* OpenAI Embedding Client for Baby-SkyNet
* Provides text embeddings using OpenAI's embedding models
* Compatible with ChromaDB's EmbeddingFunction interface
*/
export class OpenAIEmbeddingClient implements EmbeddingProvider {
private client: OpenAI;
private model: string;
constructor(apiKey?: string, model: string = 'text-embedding-3-small') {
if (!apiKey) {
Logger.error('OpenAIEmbeddingClient constructor failed - API key required');
throw new Error('OpenAI API key is required');
}
this.client = new OpenAI({
apiKey: apiKey
});
this.model = model;
Logger.info('OpenAIEmbeddingClient initialized', {
model: this.model,
hasApiKey: !!apiKey
});
}
/**
* Generate embeddings for multiple texts (ChromaDB standard)
* @param texts - Array of input texts to embed
* @returns Promise<number[][]> - Array of embedding vectors
*/
async generate(texts: string[]): Promise<number[][]> {
Logger.debug('Generating OpenAI embeddings', {
model: this.model,
textCount: texts.length,
totalLength: texts.reduce((sum, text) => sum + text.length, 0)
});
try {
const response = await this.client.embeddings.create({
model: this.model,
input: texts,
encoding_format: 'float'
});
if (!response.data || response.data.length === 0) {
Logger.error('OpenAI embedding generation failed - no data received', {
model: this.model,
textCount: texts.length
});
throw new Error('No embedding data received from OpenAI');
}
// Sort by index to maintain order (OpenAI might return out of order)
const sortedEmbeddings = response.data
.sort((a: any, b: any) => a.index - b.index)
.map((item: any) => item.embedding);
Logger.success('OpenAI embeddings generated successfully', {
model: this.model,
textCount: texts.length,
embeddingCount: sortedEmbeddings.length,
dimensions: sortedEmbeddings[0]?.length || 0
});
return sortedEmbeddings;
} catch (error) {
Logger.error('OpenAI embedding generation failed', {
model: this.model,
textCount: texts.length,
error: error instanceof Error ? error.message : 'Unknown error'
});
throw new Error(`Failed to generate embeddings: ${error instanceof Error ? error.message : 'Unknown error'}`);
}
}
/**
* Generate embedding for a single text (convenience method)
* @param text - Input text to embed
* @returns Promise<number[]> - Embedding vector
*/
private async embedSingle(text: string): Promise<number[]> {
const results = await this.generate([text]);
return results[0];
}
/**
* Get information about the current embedding model
* @returns Object with model details
*/
getModelInfo(): { provider: string; model: string; dimensions: number } {
// text-embedding-3-small: 1536 dimensions
// text-embedding-3-large: 3072 dimensions
const dimensions = this.model === 'text-embedding-3-large' ? 3072 : 1536;
return {
provider: 'openai',
model: this.model,
dimensions: dimensions
};
}
/**
* Test the connection to OpenAI embedding service
* @returns Promise<boolean> - True if connection successful
*/
async testConnection(): Promise<boolean> {
Logger.info('Testing OpenAI embedding connection', { model: this.model });
try {
Logger.debug('OpenAI connection test details', {
hasKey: !!this.client.apiKey,
keyPrefix: this.client.apiKey ? this.client.apiKey.substring(0, 8) + '...' : 'MISSING',
model: this.model
});
await this.embedSingle('Test connection');
Logger.success('OpenAI embedding connection test successful', { model: this.model });
return true;
} catch (error) {
Logger.error('OpenAI embedding connection test failed', {
model: this.model,
error: error instanceof Error ? error.message : String(error)
});
return false;
}
}
}
