94 lines
2.6 KiB
TypeScript
94 lines
2.6 KiB
TypeScript
import endent from 'endent';
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import {
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createParser,
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ParsedEvent,
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ReconnectInterval,
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} from 'eventsource-parser';
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const createPrompt = (topic: string, words: string, essayType: string) => {
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const data = (topic: any, words: string, essayType: string) => {
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return endent`
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You are an expert formal essay writer and generator.
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You know very well all types of essays. Generate an formal ${essayType} essay about ${topic}, which has a number of maximum ${words} words.
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The generated content should NOT be longer than ${words} words.
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The essay must be in markdown format but not rendered, it must include all markdown characteristics. The title must be bold, and there should be a between every paragraph.
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Do not include informations about console logs or print messages.
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`;
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};
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if (essayType) {
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return data(topic, words, essayType);
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}
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};
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export const OpenAIStream = async (
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topic: string,
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essayType: string,
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words: string,
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model: string,
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key: string | undefined,
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) => {
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const prompt = createPrompt(topic, words, essayType);
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const system = { role: 'system', content: prompt };
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const res = await fetch(`https://api.openai.com/v1/chat/completions`, {
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headers: {
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'Content-Type': 'application/json',
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Authorization: `Bearer ${key || process.env.NEXT_PUBLIC_OPENAI_API_KEY}`,
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},
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method: 'POST',
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body: JSON.stringify({
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model,
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messages: [system],
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temperature: 0,
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stream: true,
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}),
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});
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const encoder = new TextEncoder();
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const decoder = new TextDecoder();
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if (res.status !== 200) {
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const statusText = res.statusText;
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const result = await res.body?.getReader().read();
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throw new Error(
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`OpenAI API returned an error: ${
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decoder.decode(result?.value) || statusText
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}`,
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);
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}
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const stream = new ReadableStream({
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async start(controller) {
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const onParse = (event: ParsedEvent | ReconnectInterval) => {
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if (event.type === 'event') {
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const data = event.data;
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if (data === '[DONE]') {
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controller.close();
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return;
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}
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try {
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const json = JSON.parse(data);
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const text = json.choices[0].delta.content;
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const queue = encoder.encode(text);
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controller.enqueue(queue);
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} catch (e) {
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controller.error(e);
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}
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}
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};
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const parser = createParser(onParse);
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for await (const chunk of res.body as any) {
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parser.feed(decoder.decode(chunk));
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}
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},
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});
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return stream;
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};
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