utils/index.ts

import endent from 'endent';
import {
  createParser,
  ParsedEvent,
  ReconnectInterval,
} from 'eventsource-parser';

const createPrompt = (
  inputLanguage: string,
  outputLanguage: string,
  inputCode: string,
) => {
  if (inputLanguage === 'Natural Language') {
    return endent`
    You are an expert programmer in all programming languages. Translate the natural language to "${outputLanguage}" code. Do not include \`\`\`.

    Example translating from natural language to JavaScript:

    Natural language:
    Print the numbers 0 to 9.

    JavaScript code:
    for (let i = 0; i < 10; i++) {
      console.log(i);
    }

    Natural language:
    ${inputCode}

    ${outputLanguage} code (no \`\`\`):
    `;
  } else if (outputLanguage === 'Natural Language') {
    return endent`
      You are an expert programmer in all programming languages. Translate the "${inputLanguage}" code to natural language in plain English that the average adult could understand. Respond as bullet points starting with -.
  
      Example translating from JavaScript to natural language:
  
      JavaScript code:
      for (let i = 0; i < 10; i++) {
        console.log(i);
      }
  
      Natural language:
      Print the numbers 0 to 9.
      
      ${inputLanguage} code:
      ${inputCode}

      Natural language:
     `;
  } else {
    return endent`
      You are an expert programmer in all programming languages. Translate the "${inputLanguage}" code to "${outputLanguage}" code. Do not include \`\`\`.
  
      Example translating from JavaScript to Python:
  
      JavaScript code:
      for (let i = 0; i < 10; i++) {
        console.log(i);
      }
  
      Python code:
      for i in range(10):
        print(i)
      
      ${inputLanguage} code:
      ${inputCode}

      ${outputLanguage} code (no \`\`\`):
     `;
  }
};

export const OpenAIStream = async (
  inputLanguage: string,
  outputLanguage: string,
  inputCode: string,
  model: string,
  key: string,
) => {
  const prompt = createPrompt(inputLanguage, outputLanguage, inputCode);

  const system = { role: 'system', content: prompt };

  const res = await fetch(`https://api.openai.com/v1/chat/completions`, {
    headers: {
      'Content-Type': 'application/json',
      Authorization: `Bearer ${key || process.env.OPENAI_API_KEY}`,
    },
    method: 'POST',
    body: JSON.stringify({
      model,
      messages: [system],
      temperature: 0,
      stream: true,
    }),
  });

  const encoder = new TextEncoder();
  const decoder = new TextDecoder();

  if (res.status !== 200) {
    const statusText = res.statusText;
    const result = await res.body?.getReader().read();
    throw new Error(
      `OpenAI API returned an error: ${
        decoder.decode(result?.value) || statusText
      }`,
    );
  }

  const stream = new ReadableStream({
    async start(controller) {
      const onParse = (event: ParsedEvent | ReconnectInterval) => {
        if (event.type === 'event') {
          const data = event.data;

          if (data === '[DONE]') {
            controller.close();
            return;
          }

          try {
            const json = JSON.parse(data);
            const text = json.choices[0].delta.content;
            const queue = encoder.encode(text);
            controller.enqueue(queue);
          } catch (e) {
            controller.error(e);
          }
        }
      };

      const parser = createParser(onParse);

      for await (const chunk of res.body as any) {
        parser.feed(decoder.decode(chunk));
      }
    },
  });

  return stream;
};