| import fetch from 'node-fetch'; |
| import { setAdditionalHeadersByType } from '../additional-headers.js'; |
| import { TEXTGEN_TYPES } from '../constants.js'; |
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| export async function getVllmBatchVector(texts, apiUrl, model, directories) { |
| const url = new URL(apiUrl); |
| url.pathname = '/v1/embeddings'; |
|
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| const headers = {}; |
| setAdditionalHeadersByType(headers, TEXTGEN_TYPES.VLLM, apiUrl, directories); |
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| const response = await fetch(url, { |
| method: 'POST', |
| headers: { |
| 'Content-Type': 'application/json', |
| ...headers, |
| }, |
| body: JSON.stringify({ input: texts, model }), |
| }); |
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| if (!response.ok) { |
| const responseText = await response.text(); |
| throw new Error(`VLLM: Failed to get vector for text: ${response.statusText} ${responseText}`); |
| } |
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| const data = await response.json(); |
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| if (!Array.isArray(data?.data)) { |
| throw new Error('API response was not an array'); |
| } |
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| data.data.sort((a, b) => a.index - b.index); |
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| const vectors = data.data.map(x => x.embedding); |
| return vectors; |
| } |
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| export async function getVllmVector(text, apiUrl, model, directories) { |
| const vectors = await getVllmBatchVector([text], apiUrl, model, directories); |
| return vectors[0]; |
| } |
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