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77 lines
2.0 KiB
JavaScript
77 lines
2.0 KiB
JavaScript
const fetch = require('node-fetch').default;
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const { SECRET_KEYS, readSecret } = require('./endpoints/secrets');
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const SOURCES = {
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'mistral': {
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secretKey: SECRET_KEYS.MISTRAL,
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url: 'api.mistral.ai',
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model: 'mistral-embed',
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},
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'openai': {
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secretKey: SECRET_KEYS.OPENAI,
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url: 'api.openai.com',
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model: 'text-embedding-ada-002',
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},
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'togetherai': {
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secretKey: SECRET_KEYS.TOGETHERAI,
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url: 'api.togetherai.xyz',
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model: 'togethercomputer/GPT-NeoXT-Chat-Base-20B',
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},
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};
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/**
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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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* @param {string} source - The source of the vector
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* @returns {Promise<number[]>} - The vector for the text
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*/
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async function getOpenAIVector(text, source) {
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const config = SOURCES[source];
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if (!config) {
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console.log('Unknown source', source);
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throw new Error('Unknown source');
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}
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const key = readSecret(config.secretKey);
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if (!key) {
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console.log('No API key found');
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throw new Error('No API key found');
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}
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const url = config.url;
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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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Authorization: `Bearer ${key}`,
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},
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body: JSON.stringify({
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input: text,
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model: config.model,
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}),
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});
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if (!response.ok) {
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const text = await response.text();
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console.log('API request failed', response.statusText, text);
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throw new Error('API request failed');
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}
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const data = await response.json();
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const vector = data?.data[0]?.embedding;
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if (!Array.isArray(vector)) {
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console.log('API response was not an array');
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throw new Error('API response was not an array');
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}
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return vector;
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}
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module.exports = {
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getOpenAIVector,
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};
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