beta/app/chat/route.ts

// app/api/chat/route.ts

import OpenAI from "openai";
import { OpenAIStream, StreamingTextResponse } from "ai";

// Optional, but recommended: run on the edge runtime.
// See https://vercel.com/docs/concepts/functions/edge-functions
export const runtime = "edge";

const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY!,
});

export async function POST(req: Request) {
  // Extract the `messages` from the body of the request
  const { messages, ...body } = await req.json();

  // console.log("BODY===>", body);

  const prompt = `You are a chatbot that helps users with questions specific to project tasks.
- Project Details:
    - Name: ${body.projectInfo.name}
    - Description: ${body.projectInfo.description}
    - Tech Stack: ${body.projectInfo.stack.join(", ")}

- Feature Context:
    - Name: ${body.featureInfo.name}
    - Description: ${body.featureInfo.description}

- Task Context:
    - Name: ${body.taskInfo.task_name}
    - Description: ${body.taskInfo.task_description}

OPERATION GUIDELINES:

1. Provide information and answer questions specifically related to the project, feature, or task context provided.
2. Do not give generic answers; tailor responses based on the given context.`;

  messages.unshift({ role: "system", content: prompt });
  console.log("MESSAGES ===>", messages);

  // Request the OpenAI API for the response based on the prompt
  const response = await openai.chat.completions.create({
    model: "gpt-3.5-turbo-16k",
    stream: true,
    messages: messages,
  });

  // Convert the response into a friendly text-stream
  const stream = OpenAIStream(response);

  // Respond with the stream
  return new StreamingTextResponse(stream);
}