import { DEFAULT_SYSTEM_PROMPT, DEFAULT_TEMPERATURE } from '@/utils/app/const'; import { OpenAIError, OpenAIStream } from '@/utils/server'; import { ChatBody, Message } from '@/types/chat'; // @ts-expect-error import wasm from '../../node_modules/@dqbd/tiktoken/lite/tiktoken_bg.wasm?module'; import tiktokenModel from '@dqbd/tiktoken/encoders/cl100k_base.json'; import { Tiktoken, init } from '@dqbd/tiktoken/lite/init'; export const config = { runtime: 'edge', }; const handler = async (req: Request): Promise => { try { const chatBody = (await req.json()) as ChatBody; let prompt = chatBody?.prompt; let temperature = chatBody?.temperature; let messages = chatBody?.messages; let model = chatBody?.model; let key = chatBody?.key; await init((imports) => WebAssembly.instantiate(wasm, imports)); const encoding = new Tiktoken( tiktokenModel.bpe_ranks, tiktokenModel.special_tokens, tiktokenModel.pat_str, ); let promptToSend = prompt; if (!promptToSend) { promptToSend = DEFAULT_SYSTEM_PROMPT; } let temperatureToUse = temperature; if (temperatureToUse == null) { temperatureToUse = DEFAULT_TEMPERATURE; } const prompt_tokens = encoding.encode(promptToSend); let tokenCount = prompt_tokens.length; let messagesToSend: Message[] = []; for (let i = messages.length - 1; i >= 0; i--) { const message = messages[i]; const tokens = encoding.encode(message.content); if (tokenCount + tokens.length + 1000 > model.tokenLimit) { break; } tokenCount += tokens.length; messagesToSend = [message, ...messagesToSend]; } encoding.free(); const stream = await OpenAIStream(model, promptToSend, temperatureToUse, key, messagesToSend); return new Response(stream); } catch (error) { console.error(error); if (error instanceof OpenAIError) { return new Response('Error', { status: 500, statusText: error.message }); } else { return new Response('Error', { status: 500 }); } } }; export default handler;