AI coding tools have been widely discussed in the community, but many conclusions need updating as versions evolve. This article provides a fresh look based on the latest releases.

Getting Started

Let's start by looking at the basic implementation:

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

export async function POST(req) {
  const { messages } = await req.json();
  const result = await streamText({
    model: openai("gpt-4o"),
    messages,
    system: "你是一个专业的前端开发助手。",
    maxTokens: 2000,
  });
  return result.toDataStreamResponse();
}

This snippet illustrates the fundamental usage. In real projects you'll also need to account for error handling and edge cases.

Source Code Analysis

Building on this foundation, we can further optimize:

"use client";
import { useChat } from "ai/react";

export function AIChat() {
  const { messages, input, handleInputChange, handleSubmit, isLoading } =
    useChat({
      api: "/api/chat",
    });
  return (
    <div className="chat-container">
      {messages.map((m) => (
        <div key={m.id} className={`message ${m.role}`}>
          <p>{m.content}</p>
        </div>
      ))}
      <form onSubmit={handleSubmit}>
        <input value={input} onChange={handleInputChange} />
        <button type="submit" disabled={isLoading}>
          发送
        </button>
      </form>
    </div>
  );
}

This pattern is very practical in large-scale projects and can significantly reduce maintenance costs.

Real-World Applications

In a real project, the usage gets a bit more complex:

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

export async function POST(req) {
  const { messages } = await req.json();
  const result = await streamText({
    model: openai("gpt-4o"),
    messages,
    system: "你是一个专业的前端开发助手。",
    maxTokens: 2000,
  });
  return result.toDataStreamResponse();
}

This approach improves both the testability and scalability of the code.

Optimization Tips

Here is a complete example:

"use client";
import { useChat } from "ai/react";

export function AIChat() {
  const { messages, input, handleInputChange, handleSubmit, isLoading } =
    useChat({
      api: "/api/chat",
    });
  return (
    <div className="chat-container">
      {messages.map((m) => (
        <div key={m.id} className={`message ${m.role}`}>
          <p>{m.content}</p>
        </div>
      ))}
      <form onSubmit={handleSubmit}>
        <input value={input} onChange={handleInputChange} />
        <button type="submit" disabled={isLoading}>
          发送
        </button>
      </form>
    </div>
  );
}

Pay attention to edge-case handling—this is crucial in production environments.

Summary

• Always verify compatibility before using in production
• In team collaboration, conventions and documentation matter more than the technology itself
• Stay up-to-date with community trends; technical solutions require continuous iteration