mongodb-memory-bank-mcp-v2/dist/embeddings/voyage.js

MongoDB-powered Memory Bank MCP server with hybrid search capabilities for AI assistants

import { logger } from '../utils/logger.js';
const VOYAGE_API_URL = 'https://api.voyageai.com/v1/embeddings';
const EMBEDDING_MODEL = 'voyage-3';
const EMBEDDING_DIMENSIONS = 1024;
export async function generateEmbedding(text) {
    const apiKey = process.env.VOYAGE_API_KEY;
    if (!apiKey) {
        throw new Error('VOYAGE_API_KEY environment variable is not set');
    }
    try {
        const response = await fetch(VOYAGE_API_URL, {
            method: 'POST',
            headers: {
                'Content-Type': 'application/json',
                'Authorization': `Bearer ${apiKey}`,
            },
            body: JSON.stringify({
                input: text,
                model: EMBEDDING_MODEL,
            }),
        });
        if (!response.ok) {
            const error = await response.text();
            throw new Error(`Voyage AI API error: ${response.status} - ${error}`);
        }
        const data = await response.json();
        if (!data.data || data.data.length === 0) {
            throw new Error('No embedding returned from Voyage AI');
        }
        const firstData = data.data[0];
        if (!firstData) {
            throw new Error('No embedding data returned from Voyage AI');
        }
        const embedding = firstData.embedding;
        if (embedding.length !== EMBEDDING_DIMENSIONS) {
            throw new Error(`Unexpected embedding dimensions: ${embedding.length} (expected ${EMBEDDING_DIMENSIONS})`);
        }
        logger.debug(`Generated embedding for text (${text.length} chars), tokens used: ${data.usage.total_tokens}`);
        return embedding;
    }
    catch (error) {
        logger.error('Error generating embedding:', error);
        throw error;
    }
}
export async function generateEmbeddings(texts) {
    const apiKey = process.env.VOYAGE_API_KEY;
    if (!apiKey) {
        throw new Error('VOYAGE_API_KEY environment variable is not set');
    }
    if (texts.length === 0) {
        return [];
    }
    try {
        const response = await fetch(VOYAGE_API_URL, {
            method: 'POST',
            headers: {
                'Content-Type': 'application/json',
                'Authorization': `Bearer ${apiKey}`,
            },
            body: JSON.stringify({
                input: texts,
                model: EMBEDDING_MODEL,
            }),
        });
        if (!response.ok) {
            const error = await response.text();
            throw new Error(`Voyage AI API error: ${response.status} - ${error}`);
        }
        const data = await response.json();
        if (!data.data || data.data.length !== texts.length) {
            throw new Error('Unexpected number of embeddings returned from Voyage AI');
        }
        // Sort by index to ensure correct order
        const sortedEmbeddings = data.data
            .sort((a, b) => a.index - b.index)
            .map(item => item.embedding);
        logger.debug(`Generated ${texts.length} embeddings, tokens used: ${data.usage.total_tokens}`);
        return sortedEmbeddings;
    }
    catch (error) {
        logger.error('Error generating embeddings:', error);
        throw error;
    }
}
export { EMBEDDING_DIMENSIONS };
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