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synced 2025-01-05 13:36:47 +01:00
added mistral vector support (off the back of oai's)
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@ -394,7 +394,8 @@ async function getSavedHashes(collectionId) {
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*/
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async function insertVectorItems(collectionId, items) {
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if (settings.source === 'openai' && !secret_state[SECRET_KEYS.OPENAI] ||
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settings.source === 'palm' && !secret_state[SECRET_KEYS.MAKERSUITE]) {
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settings.source === 'palm' && !secret_state[SECRET_KEYS.MAKERSUITE] ||
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settings.source === 'mistral' && !secret_state[SECRET_KEYS.MISTRALAI]) {
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throw new Error('Vectors: API key missing', { cause: 'api_key_missing' });
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}
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@ -13,6 +13,7 @@
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<option value="transformers">Local (Transformers)</option>
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<option value="openai">OpenAI</option>
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<option value="palm">Google MakerSuite (PaLM)</option>
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<option value="mistral">MistralAI</option>
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</select>
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</div>
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@ -12,8 +12,9 @@ const { jsonParser } = require('../express-common');
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*/
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async function getVector(source, text) {
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switch (source) {
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case 'mistral':
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case 'openai':
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return require('../openai-vectors').getOpenAIVector(text);
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return require('../openai-vectors').getOpenAIVector(text, source);
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case 'transformers':
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return require('../embedding').getTransformersVector(text);
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case 'palm':
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@ -2,19 +2,21 @@ const fetch = require('node-fetch').default;
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const { SECRET_KEYS, readSecret } = require('./endpoints/secrets');
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/**
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* Gets the vector for the given text from OpenAI ada model
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* Gets the vector for the given text from an OpenAI compatible endpoint.
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* @param {string} text - The text to get the vector for
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* @returns {Promise<number[]>} - The vector for the text
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*/
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async function getOpenAIVector(text) {
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const key = readSecret(SECRET_KEYS.OPENAI);
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async function getOpenAIVector(text, source) {
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const isMistral = source === 'mistral';
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const key = readSecret(isMistral ? SECRET_KEYS.MISTRALAI : SECRET_KEYS.OPENAI);
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if (!key) {
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console.log('No OpenAI key found');
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throw new Error('No OpenAI key found');
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}
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const response = await fetch('https://api.openai.com/v1/embeddings', {
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const url = isMistral ? 'api.mistral.ai' : 'api.openai.com';
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const response = await fetch(`https://${url}/v1/embeddings`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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@ -22,7 +24,7 @@ async function getOpenAIVector(text) {
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},
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body: JSON.stringify({
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input: text,
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model: 'text-embedding-ada-002',
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model: isMistral ? 'mistral-embed' : 'text-embedding-ada-002',
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}),
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});
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