ChatGPT Team VS Genmini Pro VS 文心一言3.5，ChatGPT到底有多强大？

作者：繁依Fanyi0 | 2024-07-01 02:42:28

踩

genmini pro

写在前面

本人只支持GPT-4.0，所以没管谷歌和百度的事（因为它们免费用户也能生成图片）

ChatGPT

键盘快捷键

询问版本号

生成图片

写代码


<dependencies>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-web</artifactId>
    </dependency>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-thymeleaf</artifactId>
    </dependency>
    <!-- 其他依赖 -->
</dependencies>
 
 
package com.example.shopping;
 
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
 
@SpringBootApplication
public class Application {
    public static void main(String[] args) {
        SpringApplication.run(Application.class, args);
    }
}
 
 
package com.example.shopping;
 
import org.springframework.stereotype.Controller;
import org.springframework.ui.Model;
import org.springframework.web.bind.annotation.GetMapping;
 
@Controller
public class ShoppingController {
 
    @GetMapping("/")
    public String homePage(Model model) {
        // 可以在这里添加模型属性，例如商品列表
        return "index"; // 返回index.html模板
    }
}
 
 
<!DOCTYPE html>
<html xmlns:th="http://www.thymeleaf.org">
<head>
    <title>购物网站</title>
    <meta charset="UTF-8">
    <!-- 引入CSS -->
</head>
<body>
    <h1>欢迎来到我的购物网站</h1>
    <!-- 内容和结构 -->
</body>
</html>
 
 
./mvnw spring-boot:run

写表格

导出Excel表格


import pandas as pd
 
# 创建数据
data = {
    "边数 (n)": list(range(3, 13)),
    "多边形名称": ["三角形", "四边形", "五边形", "六边形", "七边形", "八边形", "九边形", "十边形", "十一边形", "十二边形"],
    "内角和 (S)": [(n-2)*180 for n in range(3, 13)]
}
 
# 创建DataFrame
df = pd.DataFrame(data)
 
# 文件路径
file_path = '/mnt/data/polygon_angles.xlsx'
 
# 写入Excel文件
df.to_excel(file_path, index=False)
 
file_path

https://www.123pan.com/s/3fqmjv-2MK3v.html

代码分析

生成图表


# 数据（英文版）
countries_en = ['China', 'India', 'USA', 'Indonesia', 'Brazil', 'Others']
population = [1400, 1350, 330, 270, 210, 2940]
 
# 生成饼图（英文版）
plt.figure(figsize=(10, 7))
plt.pie(population, labels=countries_en, autopct='%1.1f%%', startangle=140)
plt.title('World Population Statistics Example Pie Chart')
plt.axis('equal')  # Ensure that pie is drawn as a circle.
plt.show()

导出Excel表格


# 将数据导出到Excel
data_en = {
    "Country": countries_en,
    "Population (millions)": population
}
 
# 创建DataFrame
df_en = pd.DataFrame(data_en)
 
# 指定导出的Excel文件路径
file_path_en = '/mnt/data/world_population_statistics.xlsx'
 
# 导出到Excel
df_en.to_excel(file_path_en, index=False)
 
file_path_en

https://www.123pan.com/s/3fqmjv-sMK3v.html

导出图表图片


# Re-generate the pie chart to save it as an image file
 
# Generate pie chart (English version) for saving
plt.figure(figsize=(10, 7))
plt.pie(population, labels=countries_en, autopct='%1.1f%%', startangle=140)
plt.title('World Population Statistics Example Pie Chart')
plt.axis('equal')  # Ensure that pie is drawn as a circle.
 
# File path for saving image
image_file_path = '/mnt/data/world_population_pie_chart.png'
 
# Save the figure
plt.savefig(image_file_path)
 
image_file_path