We support ALL Deepseek models, just set deepseek/ as a prefix when sending completion requests
API Key
# env variable
os.environ['DEEPSEEK_API_KEY']
Sample Usage
from litellm import completion
import os
os.environ['DEEPSEEK_API_KEY']=""
response = completion(
model="deepseek/deepseek-chat",
messages=[
{"role":"user","content":"hello from litellm"}
],
)
print(response)
Sample Usage - Streaming
from litellm import completion
import os
os.environ['DEEPSEEK_API_KEY']=""
response = completion(
model="deepseek/deepseek-chat",
messages=[
{"role":"user","content":"hello from litellm"}
],
stream=True
)
for chunk in response:
print(chunk)
Supported Models - ALL Deepseek Models Supported!
We support ALL Deepseek models, just set deepseek/ as a prefix when sending completion requests
| Model Name | Function Call |
|---|---|
| deepseek-chat | completion(model="deepseek/deepseek-chat", messages) |
| deepseek-coder | completion(model="deepseek/deepseek-coder", messages) |
Reasoning Models
| Model Name | Function Call |
|---|---|
| deepseek-reasoner | completion(model="deepseek/deepseek-reasoner", messages) |
Thinking / Reasoning Mode
Enable thinking mode for DeepSeek reasoner models using thinking or reasoning_effort parameters:
- thinking param
- reasoning_effort param
from litellm import completion
import os
os.environ['DEEPSEEK_API_KEY']=""
resp = completion(
model="deepseek/deepseek-reasoner",
messages=[{"role":"user","content":"What is 2+2?"}],
thinking={"type":"enabled"},
)
print(resp.choices[0].message.reasoning_content)# Model's reasoning
print(resp.choices[0].message.content)# Final answer
from litellm import completion
import os
os.environ['DEEPSEEK_API_KEY']=""
resp = completion(
model="deepseek/deepseek-reasoner",
messages=[{"role":"user","content":"What is 2+2?"}],
reasoning_effort="medium",# low, medium, high all map to thinking enabled
)
print(resp.choices[0].message.reasoning_content)# Model's reasoning
print(resp.choices[0].message.content)# Final answer
note
DeepSeek only supports {"type": "enabled"} - unlike Anthropic, it doesn't support budget_tokens. Any reasoning_effort value other than "none" enables thinking mode.
Basic Usage
- SDK
- PROXY
from litellm import completion
import os
os.environ['DEEPSEEK_API_KEY']=""
resp = completion(
model="deepseek/deepseek-reasoner",
messages=[{"role":"user","content":"Tell me a joke."}],
)
print(
resp.choices[0].message.reasoning_content
)
- Setup config.yaml
model_list:
-model_name: deepseek-reasoner
litellm_params:
model: deepseek/deepseek-reasoner
api_key: os.environ/DEEPSEEK_API_KEY
- Run proxy
python litellm/proxy/main.py
- Test it!
curl -L -X POST 'http://0.0.0.0:4000/v1/chat/completions' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer sk-1234' \
-d '{
"model": "deepseek-reasoner",
"messages": [
{
"role": "user",
"content": [
{
"type": "text",
"text": "Hi, how are you ?"
}
]
}
]
}'