DeepSeek 모델에 요청 보내기

Python으로 DeepSeek 활용하기

James Chapman

AI Curriculum Lead, DataCamp

복습

모델 및 데이터, 모델 파라미터를 포함한 Together.ai API로 요청을 보내는 컴퓨터.

요청 생성

from openai import OpenAI

# To send to DeepSeek API: base_url="https://api.deepseek.com"
client = OpenAI(api_key="<TogetherAI API Key>", base_url="https://api.together.xyz/v1")

openai 라이브러리로 요청 생성
OpenAI: AI 모델 및 앱 개발사 (예: ChatGPT)
base_url: 요청을 OpenAI에서 DeepSeek 모델 제공업체로 _전환_
api_key: API 인증 (제공업체 문서 참고)

¹ https://platform.deepseek.com/api_keys

요청 생성

from openai import OpenAI
# To send to DeepSeek API: base_url="https://api.deepseek.com"
client = OpenAI(api_key="<TogetherAI API Key>", base_url="https://api.together.xyz/v1")


response = client.chat.completions.create(

    model="deepseek-ai/DeepSeek-V4-Pro",

    messages=[{"role": "user",
               "content": "In one sentence, what is hallucination in AI?"}]

)


print(response)

응답

ChatCompletion(id='onVWeEx-gBAtS-a09121fcae54578c', choices=[Choice(finish_reason='stop', index=0,
logprobs=None, message=ChatCompletionMessage(content='Hallucination in AI is when a model confidently
generates information that sounds plausible but is factually incorrect, misleading, or entirely
fabricated.', refusal=None, role='assistant', annotations=None, audio=None, function_call=None,
tool_calls=[]), seed=None)], created=1781018557, model='deepseek-ai/DeepSeek-V4-Pro',
object='chat.completion', moderation=None, service_tier=None, system_fingerprint='default',
usage=CompletionUsage(completion_tokens=28, prompt_tokens=15, total_tokens=43,
completion_tokens_details=None, prompt_tokens_details=PromptTokensDetails(audio_tokens=None,
cached_tokens=0)), prompt=[])

응답

ChatCompletion(id='onVWeEx-gBAtS-a09121fcae54578c',
               choices=[Choice(finish_reason='stop', index=0, logprobs=None,
                               message=ChatCompletionMessage(content='Hallucination in AI refers...',
                               refusal=None, role='assistant', annotations=None, audio=None,
                               function_call=None, tool_calls=[]), seed=None)],
               created=1781018557,
               model='deepseek-ai/DeepSeek-V4-Pro',
               object='chat.completion',
               moderation=None,
               service_tier=None,
               system_fingerprint='default',
               usage=CompletionUsage(completion_tokens=28, prompt_tokens=15, total_tokens=43,
                                     completion_tokens_details=None,
                                     prompt_tokens_details=PromptTokensDetails(audio_tokens=None,
                                          cached_tokens=0)),
               prompt=[])

응답 해석

print(response.choices)

[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(
content='Hallucination in AI refers to the generation of false or nonsensical information
that is presented as factual, often due to limitations in training data, model biases, or
inference errors.', refusal=None, role='assistant', annotations=None, audio=None,
function_call=None, tool_calls=[]), seed=None)]

응답 해석

print(response.choices[0])

Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(
content='Hallucination in AI refers to the generation of false or nonsensical information
that is presented as factual, often due to limitations in training data, model biases, or
inference errors.', refusal=None, role='assistant', annotations=None, audio=None,
function_call=None, tool_calls=[]), seed=None)

응답 해석

print(response.choices[0].message)

ChatCompletionMessage(content='Hallucination in AI refers to the generation of false or
nonsensical information that is presented as factual, often due to limitations in training
data, model biases, or inference errors.', refusal=None, role='assistant', annotations=None,
audio=None, function_call=None, tool_calls=[])

print(response.choices[0].message.content)

Hallucination in AI refers to the generation of false or nonsensical information that is
presented as factual, often due to limitations in training data, model biases, or inference
errors.

API 사용 비용

DeepSeek의 경우:
- 제공업체 (예: together.ai)
- 모델
- 입출력 규모가 클수록 비용 증가

통행료 도로.

¹ https://api-docs.deepseek.com/quick_start/pricing

실습해 봅시다!

Python으로 DeepSeek 활용하기