65 lines
1.7 KiB
TypeScript
65 lines
1.7 KiB
TypeScript
import { Message, OpenAIModel } from "@/types";
|
|
import { createParser, ParsedEvent, ReconnectInterval } from "eventsource-parser";
|
|
|
|
export const OpenAIStream = async (model: OpenAIModel, key: string, messages: Message[]) => {
|
|
const encoder = new TextEncoder();
|
|
const decoder = new TextDecoder();
|
|
|
|
const res = await fetch("https://api.openai.com/v1/chat/completions", {
|
|
headers: {
|
|
"Content-Type": "application/json",
|
|
Authorization: `Bearer ${key ? key : process.env.OPENAI_API_KEY}`
|
|
},
|
|
method: "POST",
|
|
body: JSON.stringify({
|
|
model,
|
|
messages: [
|
|
{
|
|
role: "system",
|
|
content: `You are ChatGPT, a large language model trained by OpenAI. Follow the user's instructions carefully. Respond using markdown format.`
|
|
},
|
|
...messages
|
|
],
|
|
max_tokens: 1000,
|
|
temperature: 0.0,
|
|
stream: true
|
|
})
|
|
});
|
|
|
|
if (res.status !== 200) {
|
|
throw new Error("OpenAI API returned an error");
|
|
}
|
|
|
|
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;
|
|
};
|