Vercel AI SDK

import { aiUseChatAdapter } from "@upstash/rag-chat/nextjs";
import { ragChat } from "@/utils/rag-chat";

export async function POST(req: Request) {
  const { messages } = await req.json();
  const lastMessage = messages[messages.length - 1].content;

  const response = await ragChat.chat(lastMessage, { streaming: true });
  return aiUseChatAdapter(response);
}

"use client"

import { useChat } from "ai/react";

const ChatComponent = () => {
  const { messages, input, handleInputChange, handleSubmit } = useChat({
    api: "/api/chat",
    initialInput: "What year was the construction of the Eiffel Tower completed, and what is its height?",
  });

  return (
    <div>
      <ul>
        {messages.map((m) => (
          <li key={m.id}>{m.content}</li>
        ))}
      </ul>

      <form onSubmit={handleSubmit}>
        <input
          value={input}
          onChange={handleInputChange}
          placeholder="Ask a question..."
        />
        <button type="submit">Send</button>
      </form>
    </div>
  );
};

import { openai } from "@ai-sdk/openai";

const ragChat = new RAGChat({
  model: openai("gpt-3.5-turbo"),
  vector,
  redis: new Redis({
    token: process.env.UPSTASH_REDIS_REST_TOKEN!,
    url: process.env.UPSTASH_REDIS_REST_URL!,
  }),
  sessionId: "ai-sdk-session",
  namespace: "ai-sdk",
});