import { EmbeddingProvider } from './types.js';
/**
* OpenAI Embedding Provider
* Uses native fetch to avoid adding the heavy openai npm package dependency.
* Minimal implementation focusing on high ROI and low bloat.
*/
export class OpenAIEmbeddingProvider implements EmbeddingProvider {
readonly name = 'openai';
readonly dimensions = 1536; // Default for text-embedding-3-small
constructor(
readonly modelName: string = 'text-embedding-3-small',
private apiKey?: string,
private apiEndpoint: string = 'https://api.openai.com/v1'
) { }
async initialize(): Promise<void> {
if (!this.apiKey) {
throw new Error(
'OpenAI API key is missing. Set OPENAI_API_KEY environment variable or configure it in the MCP settings.'
);
}
}
isReady(): boolean {
return !!this.apiKey;
}
async embed(text: string): Promise<number[]> {
const batch = await this.embedBatch([text]);
return batch[0];
}
async embedBatch(texts: string[]): Promise<number[][]> {
if (!texts.length) return [];
try {
const response = await fetch(`${this.apiEndpoint}/embeddings`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': `Bearer ${this.apiKey}`
},
body: JSON.stringify({
model: this.modelName,
input: texts,
encoding_format: 'float'
})
});
if (!response.ok) {
const error = await response.text();
throw new Error(`OpenAI API Error ${response.status}: ${error}`);
}
const data = await response.json() as any;
// OpenAI guarantees order matches input
return data.data.map((item: any) => item.embedding);
} catch (error) {
console.error('OpenAI Embedding Failed:', error);
throw error;
}
}
}
