DeepSeek+Cursor:AI代码CP出道,程序员集体“真香”了!

导语:
程序员的日常:写代码5分钟,debug两小时?
同事的代码像天书?自己写的代码隔天就看不懂?
别慌!今天揭秘两个让代码“活”起来的宝藏工具——DeepSeek(深度求索)和Cursor。

Cursor是AI代码编辑器,支持GPT等大模型对话编程,内置Deepseek中国大模型。提供Chat和Composer两种编程模式,Tab键AI补全功能强大,结合项目上下文理解代码逻辑。
一个懂你心思的AI代码助手,一个智能到离谱的编辑器,
双剑合璧,直接开启“代码躺赢模式”!

Part 1| 如何上车?

1️⃣ STEP 1:访问[cursor.com官网]注册,下载编辑器

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2️⃣ STEP 2:如何使用deepseek模型编程

之前Cursor只支持国外顶尖主流大模型GPT、Gemini、claude,由于DeepSeek全球范围的出圈以及超强的性能表现,Cursor在今年一月份更新版本,内置支持连接Deepseek-R1、DeepSeek V3大模型,用于AI辅助编程。

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在Cursor上使用DeepSeek编程的方式有两种

  • 是直接使用内置的deepseek-r1、deepseek v3模型,无需任何配置,下载安装好Cursor就可以使用,新用户有两周的试用时间,可以玩玩上面的各种模型,也是不错的体验。

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  • Cursor 中添加自定义deepseek-chat模型,将其集成到Cursor工作流程中,这需要一定的配置步骤,你需要在Cursor settings里配置相关模型,打开右上角的设置按钮,并点击models,就可以看到一堆模型。接下来点击add model按钮,新建deepseek-chat模型。

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配置API接口地址和APIKey,在OpenAI API Key窗口配置deepseek-chat模型信息,因为DeepSeek提供对 OpenAI API 格式的支持,可以直接填写deepseek-chat模型API接口地址,点击Verify按钮确认是否配置成功,没有报错即可。

有两种方式:

deepseek官网接口地址如下:

https://api.deepseek.com

APIkey:

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deepseek官网申请APIkey,但是由于太火爆总会出现卡顿的情况,官网也已经暂停了充值服务。

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其他体验方式

接口地址:https://api.moka-ai.com/v1(魔卡官网)

APIkey:赠送免费额度或https://shop.moka-ai.com/可购买

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配置好后,我们ctrl+i 打开AI聊天窗口,就可以和deepseek-chat模型对话来自动编程。

### DeepSeek Cursor Integration and Functionality in IT Context In the realm of information technology, integrating advanced tools like DeepSeek's cursor-based functionalities can significantly enhance data interaction processes. The primary purpose of incorporating a cursor mechanism within applications such as those provided by DeepSeek is to facilitate precise navigation through datasets during operations involving data discovery, cleaning, analysis, and visualization[^1]. The cursor serves multiple roles: - **Data Navigation**: A cursor allows users to traverse large volumes of data efficiently without loading entire datasets into memory at once. - **Real-Time Interaction**: With real-time updates enabled via cursors, changes made to underlying databases are immediately reflected in user interfaces. For implementing this feature effectively, developers often rely on server-side pagination techniques combined with client-side rendering optimizations. Here’s an example demonstrating how one might implement basic cursor functionality using Python alongside MongoDB for database management: ```python from pymongo import MongoClient def fetch_data_with_cursor(cursor_id=None): client = MongoClient('mongodb://localhost:27017/') db = client['example_db'] collection = db['data_collection'] if cursor_id: result = collection.find({'_id': {'$gt': cursor_id}}).limit(10) else: result = collection.find().sort('_id').limit(10) documents = list(result) next_cursor = str(documents[-1]['_id']) if documents else None return { 'documents': documents, 'next_cursor': next_cursor } ``` This code snippet illustrates fetching paginated results from a MongoDB collection based on a given cursor ID or starting fresh when no cursor is specified. This approach ensures efficient handling even with vast amounts of records while maintaining smooth performance characteristics suitable for interactive web applications. --related questions-- 1. How does implementing cursor-based pagination improve application efficiency? 2. What considerations should be taken into account when designing APIs supporting cursor-based interactions? 3. Can other NoSQL databases besides MongoDB support similar cursor mechanisms? If so, which ones? 4. Are there any potential drawbacks associated with utilizing cursors over traditional offset-based methods? 5. In what scenarios would it not make sense to use cursor-based pagination instead of standard approaches?
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