better-qdrant-mcp-server/build/services/embeddings/openai.js

MCP server for enhanced Qdrant vector database functionality

import axios from 'axios';
import { BaseEmbeddingService } from './base.js';
export class OpenAIEmbeddingService extends BaseEmbeddingService {
    constructor(apiKey, endpoint, model) {
        super(apiKey, endpoint || 'https://api.openai.com/v1', model || 'text-embedding-ada-002');
        // OpenAI's text-embedding-ada-002 produces 1536-dimensional embeddings
        this.vectorSize = 1536;
        this.defaultModel = 'text-embedding-ada-002';
        this.defaultEndpoint = 'https://api.openai.com/v1';
        this.validateConfig();
    }
    async generateEmbeddings(texts) {
        const response = await axios.post(`${this.endpoint}/embeddings`, {
            input: texts,
            model: this.model || this.defaultModel,
        }, {
            headers: {
                'Authorization': `Bearer ${this.apiKey}`,
                'Content-Type': 'application/json',
            },
        });
        if (!response.data.data || !Array.isArray(response.data.data)) {
            throw new Error('Invalid response from OpenAI API');
        }
        return response.data.data.map((item) => {
            if (!item.embedding || !Array.isArray(item.embedding)) {
                throw new Error('Invalid embedding format in OpenAI response');
            }
            return item.embedding;
        });
    }
    requiresApiKey() {
        return true;
    }
    validateConfig() {
        if (!this.apiKey) {
            throw new Error('OpenAI API key is required');
        }
        if (!this.endpoint) {
            throw new Error('OpenAI endpoint is required');
        }
    }
}
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