const fetch = require('node-fetch').default; const { setAdditionalHeadersByType } = require('../additional-headers'); const { TEXTGEN_TYPES } = require('../constants'); /** * Gets the vector for the given text from LlamaCpp * @param {string[]} texts - The array of texts to get the vectors for * @param {string} apiUrl - The API URL * @param {import('../users').UserDirectoryList} directories - The directories object for the user * @returns {Promise} - The array of vectors for the texts */ async function getLlamaCppBatchVector(texts, apiUrl, directories) { const url = new URL(apiUrl); url.pathname = '/v1/embeddings'; const headers = {}; setAdditionalHeadersByType(headers, TEXTGEN_TYPES.LLAMACPP, apiUrl, directories); const response = await fetch(url, { method: 'POST', headers: { 'Content-Type': 'application/json', ...headers, }, body: JSON.stringify({ input: texts }), }); if (!response.ok) { const responseText = await response.text(); throw new Error(`LlamaCpp: Failed to get vector for text: ${response.statusText} ${responseText}`); } const data = await response.json(); if (!Array.isArray(data?.data)) { throw new Error('API response was not an array'); } // Sort data by x.index to ensure the order is correct data.data.sort((a, b) => a.index - b.index); const vectors = data.data.map(x => x.embedding); return vectors; } /** * Gets the vector for the given text from LlamaCpp * @param {string} text - The text to get the vector for * @param {string} apiUrl - The API URL * @param {import('../users').UserDirectoryList} directories - The directories object for the user * @returns {Promise} - The vector for the text */ async function getLlamaCppVector(text, apiUrl, directories) { const vectors = await getLlamaCppBatchVector([text], apiUrl, directories); return vectors[0]; } module.exports = { getLlamaCppBatchVector, getLlamaCppVector, };