memory-engineering-mcp/dist/embeddings/voyage-v5.js

🧠 AI Memory System powered by MongoDB Atlas & Voyage AI - Autonomous memory management with zero manual work

import { logger } from '../utils/logger.js';
const VOYAGE_API_URL = 'https://api.voyageai.com/v1/embeddings';
const EMBEDDING_MODEL = 'voyage-3'; // Latest general-purpose model for text
const EMBEDDING_DIMENSIONS = 1024; // voyage-3 default dimensions
export async function generateEmbedding(text, inputType = 'document') {
    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,
                input_type: inputType, // Official Voyage AI parameter for optimization
            }),
        });
        if (!response.ok) {
            const error = await response.text();
            throw new Error(`💀 VOYAGE AI CATASTROPHE! Status: ${response.status} | ${error} | EMBEDDING GENERATION IMPOSSIBLE! Check API key NOW!`);
        }
        const data = await response.json();
        if (!data.data || data.data.length === 0) {
            throw new Error('🔴 VOYAGE AI RETURNED NOTHING! Zero embeddings generated! Your text might be invalid or API is DOWN!');
        }
        return data.data[0]?.embedding || [];
    }
    catch (error) {
        logger.error('💀 VOYAGE EMBEDDING EXPLOSION!', error);
        throw error;
    }
}
// Convenience functions for specific use cases (official Voyage AI optimization)
export async function generateDocumentEmbedding(text) {
    return generateEmbedding(text, 'document');
}
export async function generateQueryEmbedding(text) {
    return generateEmbedding(text, 'query');
}
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');
    }
    try {
        // Process in batches to avoid API limits
        const batchSize = 50;
        const embeddings = [];
        for (let i = 0; i < texts.length; i += batchSize) {
            const batch = texts.slice(i, i + batchSize);
            const response = await fetch(VOYAGE_API_URL, {
                method: 'POST',
                headers: {
                    'Content-Type': 'application/json',
                    'Authorization': `Bearer ${apiKey}`,
                },
                body: JSON.stringify({
                    input: batch,
                    model: EMBEDDING_MODEL,
                    input_type: 'document',
                }),
            });
            if (!response.ok) {
                const error = await response.text();
                throw new Error(`💥 VOYAGE AI BATCH EXPLOSION! Status: ${response.status} | ${error} | BATCH EMBEDDINGS FAILED! Your API key might be DEAD or rate limited!`);
            }
            const data = await response.json();
            if (!data.data || data.data.length !== batch.length) {
                throw new Error(`🔴 EMBEDDING COUNT MISMATCH! Expected ${batch.length} but got ${data.data?.length || 0}! VOYAGE AI IS CORRUPTING YOUR DATA!`);
            }
            // Sort by index to ensure correct order
            const sortedEmbeddings = data.data
                .sort((a, b) => a.index - b.index)
                .map(item => item.embedding);
            embeddings.push(...sortedEmbeddings);
        }
        return embeddings;
    }
    catch (error) {
        logger.error('💥 BATCH EMBEDDING CATASTROPHE!', error);
        throw error;
    }
}
export { EMBEDDING_DIMENSIONS };
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