Claude Code Plugins

Community-maintained marketplace

Feedback

DeepSeek AI large language model API via curl. Use this skill for chat completions, reasoning, and code generation with OpenAI-compatible endpoints.

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name deepseek
description DeepSeek AI large language model API via curl. Use this skill for chat completions, reasoning, and code generation with OpenAI-compatible endpoints.
vm0_secrets DEEPSEEK_API_KEY

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.


Important: When using $VAR in a command that pipes to another command, wrap the command containing $VAR in bash -c '...'. Due to a Claude Code bug, environment variables are silently cleared when pipes are used directly.

bash -c 'curl -s "https://api.example.com" -H "Authorization: Bearer $API_KEY"' | jq .

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:

bash -c '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 .

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:

bash -c '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:

bash -c '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:

bash -c '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' | jq .

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:

bash -c '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:

bash -c '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": {
            "location": {
              "type": "string",
              "description": "The city name"
            }
          },
          "required": ["location"]
        }
      }
    }
  ]
}

Then run:

bash -c '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 .

The model will return a tool_calls array when it wants to use a function.


9. Check Token Usage

Extract usage information from response:

Write to /tmp/deepseek_request.json:

{
  "model": "deepseek-chat",
  "messages": [
    {
      "role": "user",
      "content": "Hello"
    }
  ]
}

Then run:

bash -c '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 '.usage'

Response includes:

  • prompt_tokens: Input token count
  • completion_tokens: Output token count
  • total_tokens: Sum of both

OpenAI SDK Compatibility

DeepSeek is fully compatible with OpenAI SDKs. Just change the base URL:

Python:

from openai import OpenAI
client = OpenAI(api_key="your-deepseek-key", base_url="https://api.deepseek.com")

Node.js:

import OpenAI from 'openai';
const client = new OpenAI({ apiKey: 'your-deepseek-key', baseURL: 'https://api.deepseek.com' });

Tips: Complex JSON Payloads

For complex requests with nested JSON (like function calling), use a temp file to avoid shell escaping issues:

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 current weather",
      "parameters": {
        "type": "object",
        "properties": {"location": {"type": "string"}},
        "required": ["location"]
      }
    }
  }]
}

Then run:

bash -c '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 .

Guidelines

  1. Choose the right model: Use deepseek-chat for general tasks, deepseek-reasoner for complex reasoning
  2. Use caching: Repeated prompts with same prefix benefit from cache pricing ($0.028 vs $0.28)
  3. Set max_tokens: Prevent runaway generation by setting appropriate limits
  4. Use streaming for long responses: Better UX for real-time applications
  5. JSON mode requires system prompt: When using response_format, include JSON instructions in system message
  6. FIM uses beta endpoint: Code completion endpoint is at api.deepseek.com/beta
  7. Complex JSON: Use temp files with -d @filename to avoid shell quoting issues