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:
```json
{
"model": "deepseek-chat",
"messages": [
{
"role": "system",
"content": "You are a helpful assistant."
},
{
"role": "user",
"content": "Hello, who are you?"
}
]
}
```
Then run:
```bash
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'
```
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:
```json
{
"model": "deepseek-chat",
"messages": [
{
"role": "user",
"content": "Write a short poem about coding."
}
],
"temperature": 0.7,
"max_tokens": 200
}
```
Then run:
```bash
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 deterministictop_p (0-1, default 1): Nucleus sampling thresholdmax_tokens: Maximum tokens to generate
---
3. Streaming Response
Get real-time token-by-token output:
Write to /tmp/deepseek_request.json:
```json
{
"model": "deepseek-chat",
"messages": [
{
"role": "user",
"content": "Explain quantum computing in simple terms."
}
],
"stream": true
}
```
Then run:
```bash
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'
```
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:
```json
{
"model": "deepseek-reasoner",
"messages": [
{
"role": "user",
"content": "What is 15 * 17? Show your work."
}
]
}
```
Then run:
```bash
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:
```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
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'
```
---
6. Multi-turn Conversation
Continue a conversation with message history:
Write to /tmp/deepseek_request.json:
```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
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:
```json
{
"model": "deepseek-chat",
"prompt": "def add(a, b):\n ",
"max_tokens": 20
}
```
Then run:
```bash
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:
```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
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'
```
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:
```json
{
"model": "deepseek-chat",
"messages": [
{
"role": "user",
"content": "Hello"
}
]
}
```
Then run:
```bash
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 countcompletion_tokens: Output token counttotal_tokens: Sum of both
---
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