Deepseek | liteLLM (original) (raw)

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:

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

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​

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
)