In-Depth Exploration: Creating a New Intelligent Development Experience with DeepSeek and Cursor

DeepSeek

<span>DeepSeek</span> is the latest star project, with Lei Jun personally recruiting key developers. The entire training process for <span>DeepSeek</span> V3 took less than 2.8 million <span>GPU</span> hours, and its performance is said to be close to that of <span>GPT-4o</span>. This project is very easy to use; you can register on your phone to receive 5 million tokens and a free credit of 10 yuan.

In-Depth Exploration: Creating a New Intelligent Development Experience with DeepSeek and Cursor

To test the performance of <span>DeepSeek</span>, install the Cline plugin in VS Code. Create an API key in DeepSeek.

In-Depth Exploration: Creating a New Intelligent Development Experience with DeepSeek and Cursor

Enter the API key information in Cline, and you can use DeepSeek in your VS Code chat.

In-Depth Exploration: Creating a New Intelligent Development Experience with DeepSeek and Cursor

Let’s write a small project to test it out. There is an open-source project called yl-dlp, which can download videos from YouTube but only works in the command line. Now let’s use DeepSeek to implement a graphical download operation.

In-Depth Exploration: Creating a New Intelligent Development Experience with DeepSeek and Cursor

In the CLINE chat window, state your requirements, and it will generate the necessary folders and files according to your request, granting permissions and automatically completing all operations. Start the project in the node environment.

In-Depth Exploration: Creating a New Intelligent Development Experience with DeepSeek and Cursor

Enter the corresponding URL in the address bar, and it will parse the videos and audio from the resources, allowing only single selection and correct downloads. Provide modification suggestions. After modifications, the effect is as shown in the figure:

In-Depth Exploration: Creating a New Intelligent Development Experience with DeepSeek and Cursor

Reaching this level is already impressive. Finally, the downloaded audio and video are both correct and can be played.

In-Depth Exploration: Creating a New Intelligent Development Experience with DeepSeek and Cursor

Writing this code used 400,000 tokens and cost a total of 0.8 yuan.

Below is part of the code for node’s express:

const express = require('express');
const { exec } = require('child_process');
const path = require('path');
const app = express();
const port = 3000;

app.use(express.json());
app.use(express.static(path.join(__dirname, '../public')));

// Get video information
app.post('/api/get-info', (req, res) => {
  const { url } = req.body;
  const command = `yt-dlp.exe -j ${url}`;

exec(command, (error, stdout, stderr) => {
    if (error) {
      return res.status(400).json({ error: 'Failed to get video info' });
    }

    try {
      const info = JSON.parse(stdout);
      const formats = info.formats.map(format => ({
        format_id: format.format_id,
        format: format.format,
        format_note: format.format_note,
        ext: format.ext,
        resolution: format.resolution,
        filesize: format.filesize,
        vcodec: format.vcodec,
        acodec: format.acodec,
        abr: format.abr,
        audio_channels: format.audio_channels
      }));

      res.json({
        title: info.title,
        thumbnail: info.thumbnail,
        duration: info.duration,
        uploader: info.uploader,
        formats: formats
      });
    } catch (parseError) {
      res.status(500).json({ error: 'Failed to parse video info' });
    }
  });
});

// Handle download request
app.post('/api/download', (req, res) => {
  const { url, videoFormat, audioFormat } = req.body;

if (!url || !videoFormat || !audioFormat) {
    return res.status(400).json({ error: 'Missing required parameters' });
  }

  const outputPath = path.join(__dirname, '../downloads/%(title)s.%(ext)s');
  const command = `yt-dlp.exe -f ${videoFormat}+${audioFormat} --merge-output-format mp4 -o \

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