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78 lines
2.7 KiB
JavaScript
78 lines
2.7 KiB
JavaScript
import OpenAIApi from 'openai';
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import { getKey } from '../utils/keys.js';
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import { strictFormat } from '../utils/text.js';
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export class Qwen {
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constructor(model_name, url) {
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this.model_name = model_name;
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this.url = url;
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const config = {
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baseURL: this.url,
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apiKey: getKey('QWEN_API_KEY'),
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};
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this.openai = new OpenAIApi(config);
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this.apiKey = config.apiKey;
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}
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async sendRequest(turns, systemMessage, stop_seq = '***') {
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const messages = [{ role: 'system', content: systemMessage }, ...turns];
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const pack = {
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model: this.model_name || 'qwen-plus',
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messages: this.model_name.includes('o1') ? strictFormat(messages) : messages,
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stop: this.model_name.includes('o1') ? undefined : stop_seq,
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};
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try {
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console.log('Awaiting Qwen API response...');
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const completion = await this.openai.chat.completions.create(pack);
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const choice = completion.choices[0];
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if (choice.finish_reason === 'length') {
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console.log('Context length exceeded');
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return await this.sendRequest(turns.slice(1), systemMessage, stop_seq);
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}
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console.log('Received.');
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return choice.message.content;
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} catch (err) {
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console.error('Error occurred:', err);
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return 'My brain disconnected, try again.';
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}
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}
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async embed(text) {
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if (!text || typeof text !== 'string') {
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console.error('Invalid input for embedding: text must be a non-empty string.');
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return 'Invalid input for embedding: text must be a non-empty string.';
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}
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const headers = {
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'Authorization': `Bearer ${this.apiKey}`,
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'Content-Type': 'application/json'
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};
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const data = {
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model: 'text-embedding-v2',
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input: { texts: [text] },
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parameters: { text_type: 'query' }
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};
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try {
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const response = await fetch(this.url, {
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method: 'POST',
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headers: headers,
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body: JSON.stringify(data)
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});
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const responseData = await response.json();
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if (!responseData?.output?.embeddings) {
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console.error('Invalid response from embedding API');
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return 'An error occurred while processing your embedding request. Please try again.';
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}
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return responseData.output.embeddings[0].embedding;
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} catch (err) {
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console.error('Error occurred:', err);
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return 'An error occurred while processing your embedding request. Please try again.';
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}
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}
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}
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