Deepseek

https://deepseek.com/

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

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

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?"}],
    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

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
)

PROXY

1. Setup config.yaml

model_list:
  - model_name: deepseek-reasoner
    litellm_params:
        model: deepseek/deepseek-reasoner
        api_key: os.environ/DEEPSEEK_API_KEY

2. Run proxy

python litellm/proxy/main.py

3. 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 ?"
          }
        ]
      }
    ]
}'