DeepSeek API

Use the DeepSeek API via direct curl calls to access powerful AI language models for chat, reasoning, and code generation.

Official docs: https://api-docs.deepseek.com/

---

When to Use

Use this skill when you need to:

• Chat completions with DeepSeek-V3.2 model
• Deep reasoning tasks using the reasoning model
• Code generation and completion (FIM - Fill-in-the-Middle)
• OpenAI-compatible API as a cost-effective alternative

---

Prerequisites

1. Sign up at DeepSeek Platform and create an account
2. Go to API Keys and generate a new API key
3. Top up your balance (no free tier, but very affordable pricing)

export DEEPSEEK_API_KEY="your-api-key"

Pricing (per 1M tokens)

Type	Price
Input (cache hit)	$0.028
Input (cache miss)	$0.28
Output	$0.42

Rate Limits

DeepSeek does not enforce strict rate limits. They will try to serve every request. During high traffic, connections are maintained with keep-alive signals.

---

How to Use

All examples below assume you have DEEPSEEK_API_KEY set.

The base URL for the DeepSeek API is:

• https://api.deepseek.com (recommended)
• https://api.deepseek.com/v1 (OpenAI-compatible)

---

1. Basic Chat Completion

Send a simple chat message:

Write to /tmp/deepseek_request.json:

{
  "model": "deepseek-chat",
  "messages": [
    {
      "role": "system",
      "content": "You are a helpful assistant."
    },
    {
      "role": "user",
      "content": "Hello, who are you?"
    }
  ]
}

Then run:

curl -s "https://api.deepseek.com/chat/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json

Available models:

• deepseek-chat: DeepSeek-V3.2 non-thinking mode (128K context, 8K max output)
• deepseek-reasoner: DeepSeek-V3.2 thinking mode (128K context, 64K max output)

---

2. Chat with Temperature Control

Adjust creativity/randomness with temperature:

Write to /tmp/deepseek_request.json:

{
  "model": "deepseek-chat",
  "messages": [
    {
      "role": "user",
      "content": "Write a short poem about coding."
    }
  ],
  "temperature": 0.7,
  "max_tokens": 200
}

Then run:

curl -s "https://api.deepseek.com/chat/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json | jq -r '.choices[0].message.content'

Parameters:

• temperature (0-2, default 1): Higher = more creative, lower = more deterministic
• top_p (0-1, default 1): Nucleus sampling threshold
• max_tokens: Maximum tokens to generate

---

3. Streaming Response

Get real-time token-by-token output:

Write to /tmp/deepseek_request.json:

{
  "model": "deepseek-chat",
  "messages": [
    {
      "role": "user",
      "content": "Explain quantum computing in simple terms."
    }
  ],
  "stream": true
}

Then run:

curl -s "https://api.deepseek.com/chat/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json

Streaming returns Server-Sent Events (SSE) with delta chunks, ending with data: [DONE].

---

4. Deep Reasoning (Thinking Mode)

Use the reasoner model for complex reasoning tasks:

Write to /tmp/deepseek_request.json:

{
  "model": "deepseek-reasoner",
  "messages": [
    {
      "role": "user",
      "content": "What is 15 * 17? Show your work."
    }
  ]
}

Then run:

curl -s "https://api.deepseek.com/chat/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json | jq -r '.choices[0].message.content'

The reasoner model excels at math, logic, and multi-step problems.

---

5. JSON Output Mode

Force the model to return valid JSON:

Write to /tmp/deepseek_request.json:

{
  "model": "deepseek-chat",
  "messages": [
    {
      "role": "system",
      "content": "You are a JSON generator. Always respond with valid JSON."
    },
    {
      "role": "user",
      "content": "List 3 programming languages with their main use cases."
    }
  ],
  "response_format": {
    "type": "json_object"
  }
}

Then run:

curl -s "https://api.deepseek.com/chat/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json | jq -r '.choices[0].message.content'

---

6. Multi-turn Conversation

Continue a conversation with message history:

Write to /tmp/deepseek_request.json:

{
  "model": "deepseek-chat",
  "messages": [
    {
      "role": "user",
      "content": "My name is Alice."
    },
    {
      "role": "assistant",
      "content": "Nice to meet you, Alice."
    },
    {
      "role": "user",
      "content": "What is my name?"
    }
  ]
}

Then run:

curl -s "https://api.deepseek.com/chat/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json | jq -r '.choices[0].message.content'

---

7. Code Completion (FIM)

Use Fill-in-the-Middle for code completion (beta endpoint):

Write to /tmp/deepseek_request.json:

{
  "model": "deepseek-chat",
  "prompt": "def add(a, b):\n ",
  "max_tokens": 20
}

Then run:

curl -s "https://api.deepseek.com/beta/completions" -X POST -H "Content-Type: application/json" -H "Authorization: Bearer $DEEPSEEK_API_KEY" -d @/tmp/deepseek_request.json | jq -r '.choices[0].text'

FIM is useful for:

• Code completion in editors
• Filling gaps in documents
• Context-aware text generation

---

8. Function Calling (Tools)

Define functions the model can call:

Write to /tmp/deepseek_request.json:

{
  "model": "deepseek-chat",
  "messages": [
    {
      "role": "user",
      "content": "What is the weather in Tokyo?"
    }
  ],
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "get_weather",
        "description": "Get the current weather for a location",
        "parameters": {
          "type": "object",
          "properties": 
how to use deepseek
CursorClaude CodeClineCodexWindsurfGooseGitHub CopilotVS CodeGemini CLIKiloOpencodeKimi CLIRoo ClineAiderContinueZedBolt.newLovablev0Replit AgentSweepSmol DeveloperDevinCavemanAmpAntigravity
How to use deepseek on Cursor
AI-first code editor with Composer
1
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
›Cursor installed and configured on your development machine
›Node.js version 16.0+ with npm package manager (verify with node --version)
›Active project directory or workspace where you want to add deepseek
2
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
$npx skills add https://github.com/vm0-ai/vm0-skills --skill deepseekcopy
The skills CLI fetches deepseek from GitHub repository vm0-ai/vm0-skills and configures it for Cursor.
3
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ── always included ────
│   • Amp
│   • Antigravity
│   • Cline
│   • Codex
│ ●Cursor(selected)
│   • Cursor
│   • Windsurf
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/deepseek
Reload or restart Cursor to activate deepseek. Access the skill through slash commands (e.g., /deepseek) or your agent's skill management interface.
⚠
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
Additional Resources
›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?